Trends in American Gun Ownership (Criminal Justice: Recent Scholarship)

Criminal Justice Recent Scholarship

Edited by Marilyn McShane and Frank P. Williams III

A Series from LFB Scholarly

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Trends in American Gun Ownership

Richard L. Legault

LFB Scholarly Publishing LLC New York 2008

Copyright © 2008 by LFB Scholarly Publishing LLC All rights reserved. Library of Congress Cataloging-in-Publication Data Legault, Richard L., 1971Trends in American gun ownership / Richard L. Legault. p. cm. -- (Criminal justice : recent scholarship) Includes bibliographical references and index. ISBN 978-1-59332-267-0 (alk. paper) 1. Firearms ownership--United States. I. Title. HV8059.L43 2008 363.33--dc22 2008015989

ISBN 978-1-59332-267-0 Printed on acid-free 250-year-life paper. Manufactured in the United States of America.

Table of Contents

1.

Who Owns Guns in America _______________________1

2.

A History of American Gun Ownership ______________11

3.

Scientific Polling________________________________39

4.

Explaining Trends in Gun Ownership________________61

5.

The General Social Surveys _______________________71

6.

Modeling Repeated Survey Data ___________________81

7.

Simple Trends in Gun Ownership___________________95

8.

Who Reports Gun Ownership? ____________________ 105

9.

Understanding HGO ____________________________ 129 Bibliography __________________________________ 141 Appendix A – Survey Questions___________________ 151 Appendix B – Rejected Models ___________________ 159 Subject Index _________________________________ 167

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Acknowledgements

This research was supported in part by an appointment to the U.S. Department of Homeland Security Research Opportunity Program administered by the Oak Ridge Institute for Science and Education (ORISE) through a cooperative agreement between the U.S. Department of Energy and the U.S. Department of Homeland Security. ORISE is managed by Oak Ridge Associated Universities (ORAU) under the DOE contract number DE-AC05-06OR23100. All opinions expressed in this paper are the author’s and do not necessarily reflect the policies and views of DHS, DOE, or ORAU/ORISE. I consider myself exceptionally fortunate to have enjoyed the assistance, insight, and considerable talent of those who have reviewed this work. I would particularly like to express my deepest gratitude to Alan Lizotte, David McDowall, Graeme Newman, Steven Messner, and Piyusha Singh. Each has provided invaluable advice and suggestions on previous editions of this work. I also extend my thanks to Bob Vasquez for his comments on Chapter 6, Katherine Worboys for her advice on the historical review in Chapter 2, and the members of the START Center for their encouragement. I must also mention the accommodation and consideration provided to me by my colleagues at the Sourcebook of Criminal Justice Statistics. Your assistance, cooperation, and collaboration were among the most important influences on my ability to complete this work. Finally, I would like to dedicate this work to my wife, Suzanne, for her understanding and support. Rik Legault, 25 October, 2007

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CHAPTER 1

Who Owns Guns in America (and Why We Should Care)

INTRODUCTION There is a wealth of scientific literature regarding gun ownership and use in the United States. The details of this work would fill volumes, and cover such diverse topics as private gun ownership, legal firearm usage, illegal firearm usage, social harm and benefits of firearms, international comparisons of firearms usage and laws, the efficacy of various gun control laws and policies, homicide, suicide, history, etc. Likewise, a diverse group of academic fields, including sociology, criminology, economics, public health, and psychology, have studied firearms as an area of basic research over the last 80 years or so. While early surveys in the 1930’s asked only public opinion questions about firearms, there was a veritable explosion of social scientific research in the area following the growth of violent crime rates in the late 1960’s. Since that time there has been a steady growth in our scientific knowledge of the intersection of guns and human behavior. In spite of this attention, there has been little assessment of the trends in American gun ownership over time or the data from which we draw our knowledge. This book aims to do both. While it is not possible to know exactly why there has been so little attention paid to the data used to develop our knowledge of firearms in the U.S., it is probably due to two main reasons. First, only in recent years have sufficient amounts of detailed time series data been available to researchers. This means that, until recently, only very short-term trends were available for scientific study, and making generalizations from short-term trends is dangerous at best. Secondly, 1

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Trends in American Gun Ownership

recent developments in statistical methodology have provided researchers with the tools to carefully examine a number of research questions that were previously relegated to the realm of speculation. The dual advantages of available trend data and applicable methodology have now placed researchers in a position where examining data quality and understanding trends in the data are not only possible but a necessary and responsible next step in continuing this line of research. Household gun ownership (hereafter, HGO) in the U.S. has been reported at a rate of 46% as late as 1989. Nine years later in 1998, the same survey reported that household gun ownership rates had precipitously fallen to 38% (Smith; 1999, 30). Similarly, in the General Social Survey (GSS), HGO is reported at a rate of 46% in 1989, but only 32% in 2000. These severe declines could be indicative of either a pronounced change in U.S. gun ownership, a prominent change in reporting behavior on surveys that ask questions about gun culture and gun ownership, or random variation in reporting levels. This type of prominent change is worth studying for a number of reasons. First, it is interesting because it appears to have been a large change in such a short period of time, and second, because the U.S. has had such a high prevalence of civilian gun ownership for so many years. The history of American gun ownership is unlike any other developed, western nation, and it is important to understand this past as a point of reference for gun ownership today. Indeed, the United States has had very high levels of gun ownership for many years. Historical evidence and research in this area is discussed in Chapter 2. There are also a number of ways to directly measure the prevalence of present day HGO in the U.S. On the one hand, the most common measures in use today come from a wide variety of social science surveys, some of which are of a general nature and intended to collect a variety of demographic, social, public health, or public opinion data. On the other hand, there are also a number of surveys specifically designed to measure firearms ownership and the characteristics and behaviors of the gun-owning public. These sources of modern, scientific information are discussed in Chapter 3. There is also a periphery indicator of gun ownership in estimates of the total number of working firearms owned by private citizens in the U.S., usually referred to as the “civilian gun stock.” Recent estimates of the gun stock range from at least 192 million firearms in private hands (Cook & Ludwig, 1997:1) to 240 million (Kleck,

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3

1997:96-97) with between 3 and 6 million added every year.1 These additions are not, for the most part, replacements for lost, broken, or worn-out guns. Guns are durable goods that, with a modicum of care, can remain serviceable for many generations.2 When estimating the rate of available guns in the U.S. gun stock per 1,000 in the population, Kleck notes an increase from 678.5 to 905 available guns per 1,000 Hence, U.S. residents between 1976 and 1994 (1997:96-97).3 reconciling these estimates with the decreasing reports of HGO on social surveys has proven problematic. It is possible that this increasing stock of firearms is concentrated in fewer homes, and each home has many more guns in it, representing a massive shift in ownership in a very short period of time. While there has been some discussion of the relationship between these two readily accessible and seemingly contradictory pieces of information, little study has been dedicated to empirically describing, explaining, or understanding possible shifts in gun ownership over time in the United States. Understanding the dynamics of these changes over time is of vital importance for a number of practical reasons. Much of what is understood regarding crime, injuries, accidents, and suicide with firearms is based on the concepts of risk and exposure to firearms in the general population. Also, a number of scholarly studies attempting to discern the potential benefits of private gun ownership to society are based on these same concepts. These ideas are two sides of the same coin, and rely heavily on survey measurement of HGO for base rates of exposure, risk and availability. Little attention, however, has been paid to the possibilities of systematic, measurable error present in the survey estimates or demographic changes the in gun owning group itself. If this error does exist, it would adversely effect the conclusions drawn from these types of data. If it does not exist, an important question will be answered that would allow much greater confidence in the findings of previous scientific studies. In sum, much of what we know about

1

If one were to accept the median for the 1997 estimates and expected growth in the

civilian gunstock we could expect about 260 million firearms in civilian hands in 2007. 2

For a more detailed discussion of the service life of firearms in estimates of America’s

gun stock, see Wright, Rossi & Daly (1983), Ch2. 3

Although these estimates can be called into question as they do not limit population

estimates to residents over the age of 18, thereby not considering changes in the age demographic, they do provide at lease a rough estimate of firearm availability.

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Trends in American Gun Ownership

firearms, those who legally own them, how many there are in the U.S., what they are used for, etc. hinges on this one vital measure. Understanding the prevalence and characteristics of private gun ownership would allow policy makers to make more informed decisions concerning the difficult and controversial subject of gun control and would give scientists much more confidence in their findings. Little attention has been given to the assessment of reliability and validity of gun ownership data; however, the value of these data and the importance of assessing them are beginning to be recognized. The National Academies of Science has recently reported on gun ownership and violence in the U.S. In the report they listed 35 data sources pertaining to firearms in some way, but only three of these specifically addressed ownership (National Research Council, 2005:22-31). Data that can provide a detailed understanding of ownership are considered by those authors to be the most important data for understanding the various roles that guns are thought to play in crime and violence in the U.S. Nonetheless, the first major conclusion of this scientific body is that little or no effort has been made to assess the reliability and validity of these data, specifically data detailing gun ownership in the GSS (National Research Council, 2005:3, 4). The accompanying research recommendations of the committee state that future research on existing national gun ownership surveys should work toward establishing clear definitions and a better understanding of exactly what is being measured, including an understanding of inaccurate responses in national gun surveys and the application of current methods to reduce reporting errors. Understanding trends and response accuracy in a national gun survey is precisely the intent of this study. The explicit purpose of this work is twofold. The primary purpose is to explore, evaluate, and describe possible error in the measurement of HGO in the GSS over a period of 16 years. The secondary purpose is to offer some description of demographic trends in firearms reporting that will be indicative of actual changes in ownership when reporting error is taken into consideration. The presence and character of error certainly have implications for the various assumptions that are made about declining gun ownership and its relationship with attitudes concerning gun policies. However, it is also important to understand that this is not a study that is concerned with gun control per se.

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The Drop in HGO In all generally accepted survey measures, there appears to have been a precipitous drop in the level of HGO in the U.S. over the last 20 or so years (Legault, 2004; Davis & Smith, 2003; Smith, 1999). A few researchers have addressed this phenomenon and offered some explanation for it, but there has been very little in the way of empirical testing of these hypotheses. As early as 1959, household gun ownership was measured at about 50% in the United States (Gallup, 1972), and researchers began to note the stability of this figure beginning with Erskine (1972). This figure remained stable for about 40 years before its decline began in the mid 1980’s. For instance, reported HGO in the National Gun Policy Survey (NGPS) in 1980 was 48%, and in 1998, 38% (Smith, 1998:30). Among the hypotheses offered to explain this attrition are the reduction of the size of households in the U.S. (Smith, 1999:9) and the urbanization of America (Cook & Ludwig, 1997:11), although neither has been tested empirically. There are two notable weaknesses shared by these explanations. First, they fail to address the idea that the drop in reported HGO may be an artifact. It is unlikely that there could be such a precipitous change in any stable social statistic over such a short period of time. Secondly, while differences in reporting HGO based on gender have been described, there has been no attempt to explain such differences. The question that should be addressed by social scientists, then, concerns the events that could precipitate a 30% reduction (10 survey percentage points) in a previously stable statistic during this short time period. Citing urbanization in America as an explanation for reduced household firearms ownership seems intuitive (Cook & Ludwig, 1997:11). One might imagine that as more and more Americans move to cities there would be less motivation to own firearms for hunting or sporting purposes due to a lack of contact with the sporting subculture (Lizotte & Bordua, 1980:231). Unfortunately, Cook and Ludwig (1997) offer no test of this hypothesis. A similar explanation offered for the reduction in HGO is a reduction in household size in the U.S. (Smith, 1998:9; Smith, 1999:13). In this case, Smith (1998; 1999) hypothesizes that because homes in the U.S. are less likely to house multiple generations, the likelihood of a house containing a firearm is lessened. Like other

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Trends in American Gun Ownership

potential explanations offered for the drop in reporting HGO, however, Smith’s hypothesis has not been tested empirically. Finally, some researchers point to the disparity between men and women when reporting HGO on three different surveys, finding that husbands report a 9% higher rate of HGO, on average, than wives in face-to-face surveys such as the GSS and that this disparity has grown over time (Kleck, 1997:67; Ludwig, Cook, & Smith, 1998:1717). Of course, this should not be. That is, husbands and wives should be reporting at the same levels unless there is some systematic difference in the married households of those responding to this question. This, however, should not be the case as the household samples in any GSS sample after 1975 are self-weighting. Each household has an “equal probability of inclusion in the sample.” (Davis & Smith, 1992:42). Furthermore, these analyses give no indication of whether the disparity is related to race, parenthood, or other demographic factors commonly thought to be related to HGO. If a difference in the rates of reporting HGO by gender has developed and grown over time, then it is easy to imagine a growing gap in reporting HGO between married men and women. This also could explain decreases in the statistic over the last 20 years. If this is the case, HGO levels could be smaller, greater, or they may have had no appreciable reduction in ownership levels at all. If actual HGO levels have not changed, or are only marginally reduced, current speculations about Americans’ attitudes concerning firearms may be quite different than those reported on recent surveys. This does not explain, however, why there would be any difference in reporting HGO by gender for married couples. It is possible that men own relic or heirloom firearms of which their wives have no knowledge or do not consider “real” firearms or that there are simply firearms about which women are unaware in the home. While these scenarios certainly must be true in some cases, it is unlikely that they would explain of the large disparity in reporting among married couples in its entirety not would it offer a reason for the increase in the disparity of reporting over time. Another possible explanation for the gender-based HGO reporting difference is mentioned by Ludwig et al. when they posit that the social undesirability of being a gun owner could cause women to report a gun in the house less often than men (Ludwig et al., 1998:1715). Although there is no literature that examines the assumption that being a gun owner carries a stigma, one might assume that the negative portrayal of

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gun ownership in modern media could produce this effect. In fact, the bias of this negative portrayal of guns in the media is lamented by a number of critics (Dickens, 2000; Jacoby, 2000; Lott, 2003). In addition, Ludwig et al. add that women tend to be “more likely to be anti-gun than men” (1998:1715), and, of course, women underreport HGO compared to men. A comprehensive description of exactly who might be misreporting is unavailable, however, because the issue of gender discrepancies in reporting is only examined in simple percentages (Ludwig et al., 1998:1716). This method does not allow for the evaluation of demographic characteristics that could better specify and explain the reporting gap. Finally, there is one additional explanation of the reduction in HGO that would offer some illumination to the matter, but not necessarily as a function of misreporting or underreporting. This is not an explanation that has been offered in other sources, but is exclusive to this study.4 The increase in female-headed households with children has more than doubled over the past 30 years in the U.S. (Bryson & Casper, 1998:5). This would also explain both a decrease in HGO and a stable rate of personal gun ownership reports as the increase in total numbers of female-headed households would reduce the number of likely gun-owning households but not the number of individual gun owners. An additional limitation of most current interpretations explaining the reduction of reported HGO is that they ignore the strength of America’s “gun culture” (Wright, 1995:64). If firearms are much less prevalent in American households than in the past, and Americans who own a firearm are less likely to support increased gun control (Brennan, Lizotte, & McDowall, 1993; Smith, 1999:6-7) one would expect more consensus on gun control issues. However, this is certainly not the case (Smith, 1999). Each of these aforementioned hypotheses is discussed in detail in Chapter 4.

4

This hypothesis is also attributable to Phillip Cook as part of personal correspondence

with the committee in the National Research Council’s Firearms and Violence: A Critical Review (2005:58). This hypothesis had been discussed as an original idea with the reviewers overseeing a previous version of this book prior to the publication of the National Research Council’s work in May of 2005. It appears that this explanation was arrived at simultaneously but separately.

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Trends in American Gun Ownership

As previously mentioned, understanding trends, evaluating the quality of the available data, and testing these hypotheses requires detailed, repeated measures of data and an appropriate statistical methodology. These data and method, as well as the outcomes of the tests are described in Chapters 5 through 8. The intention of this coverage is not to confuse the reader or unnecessarily obfuscate the issue, but to communicate the process through which the hypotheses are tested in a clear and concise manner. In short, they are intended to be accessible. Accessibility and transparency are important in and of themselves, and have been my constant goal throughout this book. In the scientific study of a topic as potentially controversial as private firearms ownership it is extremely important that the use and construction of data, the analyses of these data, the hypotheses tested, and the interpretation of statistical tests be conducted with the utmost care, precision, and lucidity. Only then can we benefit from processes of scientific inquiry. In sum, HGO is an important measure in social science, public health, and policy research. Much of the analyses concerning the risks or benefits of gun ownership rely heavily on this measure, particularly the measure provided by the General Social Surveys. There appears to have been a large drop in the reported HGO over the last 20 years, and three major explanations have been offered by various researchers. By using multiple years of the GSS, tests of the gender gap/social undesirability bias, reduction in household size, urbanization of America, and increase in female-headed households hypotheses are possible, and each will be addressed and tested in due course. These tests, in turn, will provide valuable information and add to the current scientific knowledge regarding HGO and the data from which measures of HGO are derived. Whether or not each or any of these hypotheses will bear intellectual fruit in the form of evidence supporting measurement error, explanations of a reduction in HGO, falsification of the theories, or some combination of these possible outcomes, our knowledge will be broadened and future research can proceed better informed. Finally, it is important to remember that these data are difficult to work with for a variety of reasons. This probably explains the lack of rigorous testing in the past better than any other possible reason. Until recently, there were probably not enough years of detailed, repeated data to test many of these hypotheses. Also, because of the way in

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which gun ownership questions are distributed in surveys (Do you own a gun yes or no?) and the necessity of understanding these complex data in a trend or time series context, recent advances in statistical methodology and computing capacities have made more thorough examinations of this topic possible.

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CHAPTER 2

A History of American Gun Ownership

INTRODUCTION The private ownership of firearms in the United States is prolific when compared to most other western, industrialized countries (Kopel, 1992:13-15; Wright, 1995:63). There is a wealth of literature that attempts to explain the causes of this phenomenon and there is even more research describing variations if gun ownership within the United States. Historical impetus, the transmission of a “gun culture” through social institutions, and the social and economic costs and benefits of firearm ownership are just a few of the individual explanations that have been discussed by scholars in this specialized area of academic study. To date, however, there has not been any single review that examines the convergence or divergence of all the information presented in various studies regarding who owns guns in America and why they own them. This being said, there has been very little work toward understanding what “gun culture” really is. Generally, social scientists have used survey data to detail the demographic patterns of gun ownership in the U.S. without addressing the properties of culture. While informative, these analyses are seldom able to really describe gun culture. Recently, however, some work in this area has examined a small subset of gun owners though an ethnographic description of firearms enthusiasts in the American West (Kohn, 2004). More work of this type is needed to inform future data collection and analysis. In general terms, we currently define gun culture not in terms that would be accepted in the traditional social scientific sense of culture, but instead by the demographic characteristics of those who self-report 11

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gun ownership on surveys. According to most descriptive accounts of gun owners in the U.S., we know that current members of the gun culture tend to be white, male, rural, Protestant, and middle class (Bordua & Lizotte, 1979:171; Wright et al., 1983:122; Kleck, 1997:70). In addition, gun ownership tends to be more heavily concentrated in the South and South-Western regions of the country (Wright et al., 1983:122; Kleck, 1997:70), and gun owners were often socialized to become part of the gun culture by their parents who owned guns (Lizotte & Bordua, 1980:236-239; Lizotte, Bordua & White, 1981 502; Wright et al., 1983:122). The inception of scientific polling in the mid 1900’s allows us to discuss the characteristics of gun ownership in modern America with some known level of confidence. Unfortunately, there is little in the way of modern scientific evidence to give us a precise picture of the levels of gun ownership during these periods. Of course, the historical impetus provided by a long tradition of private gun ownership that influences the American self-image is highly influential to both social reality and the internalization of cultural values shared by gun owners. The characteristics of firearms ownership, and the culture surrounding it, have gone through a number of incarnations throughout American history. In order to understand these influences we can study descriptions of the culture and history of gun ownership as it passes through periods of prominence and change. Historians, social scientists, and legal scholars have tended to focus on three major historical periods pertaining to firearms ownership and use in the U.S. First, an understanding of the role of firearms in colonial America lends insight into the earliest formation of the American gun culture. During this period, the private ownership of firearms was viewed as absolutely necessary to the survival of European settlers in the Americas, and therefore almost every community was inundated with firearms (Kennett & Anderson, 1975:35; Kopel, 1992:309; Halbrook, 1994:56-57; Malcolm, 2001:546). Next, the antebellum and post-bellum periods were characterized by technological advances and widespread use of firearms due to the demands of the Civil War and the creation of a new frontier fostering further westward expansion (Kennett & Anderson 1975:115-118; Kopel, 1992:323-327). Finally, the taming of the frontier, growth of U.S. metropolitan areas, industrialization, and the rise of modern law enforcement characterizes the early 20th century, and also led to the first gun control laws in the U.S. (Kennett & Anderson, 1975:165-69; Vizzard, 2000:87-90).

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THE HISTORY OF PRIVATE GUN OWNERSHIP IN THE U.S. The birth of American gun culture is traced by most historians to the earliest European settlers to the New World5 (Kennett & Anderson, 1975:3-33; Halbrook, 1994: 37-38). Although most historians are in general agreement regarding the prevalence and necessity of firearms in America’s past interpretations of how this might relate to modern gun ownership varies widely (Tonso, 1982, 3-5; Hofstafter, 2001:32-33). The cultural influence of firearms in America has become pervasive in speech, attitudes, and rites of passage into manhood indicating an historical influence (Kennett & Anderson, 1975:250). This generally refers to an historical sense of self-reliance typified by a sporting gun culture; however, there are also historical references to the rights of Americans to use firearms for self-defense (Halbrook, 1994:58). In both of these cases our own past has created a strong social symbol and perception of social and political value in the firearm that stays with many Americans today (Tonso, 1982:10). Colonial America It is obvious that there are vast differences between American and European models of gun ownership. Most European countries exhibit very low rates of personal gun ownership compared to very high levels of gun ownership in the U.S. (Tonso, 1982). However, this gulf was also apparent during the earliest colonization of what would become the United States (Kennett & Anderson, 1975:44-46). In a very short period of time, the colonials had made a distinct cultural shift culminating in active resistance. There were new problems encountered in the New World, as the settlers would soon learn. The places that they had left behind in Europe had allowed them to exist in a world in which there were established justice systems, a sense of community, and a traditional hierarchy that reduced the need for self-reliance in the face of violence (Lane, 1997:34-35). The unmistakable reason for this phenomenon, pertaining specifically to

5

There are a number of works that discuss the historical and modern patterns of gun

ownership in Europe, Asia, and North-American countries; however, they are not the topic of discussion here.

For a complete discussion addressing the difficulties of

comparative gun study see, Tonso, 1982 and Kopel, 1992.

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personal ownership of firearms, regardless of class, is discussed by historians Kennett and Anderson: With firearms becoming a necessity for survival in the early colonies, local colonial governments became involved in the legal regulation of arms. The European idea that only gentlemen had the privilege to bear arms had been brought to America, but of necessity, this philosophy changed rapidly. In the first company to Virginia, 54 of 105 adventurers were labeled as gentlemen with the right to possess firearms. (1975:44) With only one-half of the settlers authorized to possess firearms, the harsh environment of the New World soon proved too difficult with which to cope. Firearms were used not only for defense in a harsh, primitive environment but for hunting as well. It became apparent to these pioneers that their very survival depended upon all of the men in their party to be well armed, “Thus was born the new concept of civic responsibility” (Kennett & Anderson, 1975:45). This concept soon led to the formation of militia societies throughout the colonies as well as legislation requiring those eligible for duty6 to have varying types and amounts of arms, gunpowder, and shot available at all times (Kennett & Anderson, 1975:45-57). Through legislation, attempts were made by the English monarchy to reconcile these differences as early as 1671 when the colonial government of Charles II in Virginia passed a law making possession of more than one firearm and more than 10 shots worth of gun powder and bullets illegal for certain colonists in an attempt to prevent arms trading with local American Indians (Halbrook, 1994:55-57). Violation of this law was punishable by not only death, but forfeiture of estate (Halbrook, 1994:56). However, these attempts to disarm the average colonist were often met with forceful and open resistance as in the circumstances of Bacon’s Rebellion (Halbrook, 1994:57). In this case, Bacon’s armed insurrection against the appointed governor of the

6

While only whites were usually allowed to possess firearms, gun ownership and militia

membership requirements were not restricted to landowners. Indentured servants and convicts, for instance, were also required to be armed as part of the militia. This civic responsibility and right, however, did not extend to American Indians, slaves or women (Kennett & Anderson, 1975:50).

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Jamestown Colony, William Berkeley, was at least partially motivated by orders to disarm some of the English colonists who supported Bacon on issues of taxation and relations with indigenous American Indians. This is not to say that universal firearms ownership was the norm, however, at least not as we might consider it today. There were still a number of limitations on who was allowed to possess firearms, usually based on race or social status (Cottrol & Diamond, 1995:130-132). As we shall see, the limitations on ownership throughout the history of America often depended on the particular ethnocentric attitudes common of struggles for political power (Kennett & Anderson, 1975:50-51, 153-155; Halbrook, 1994:57, 147-53; Cottrol & Diamond, 1995:145-146; Kleck, 2001:77). Historiography, for which information is garnered in three main indicators of gun ownership, provides the best indication of the numbers of firearms in the hands of private citizens in the colonies. First is discussion concerning the need for and import of firearms in the New World, second is a review of the laws requiring private citizens to maintain firearms, and third is the apparent growth of gun production as a skilled industry in the Americas, and the technological advances thereof, as compared to European firearm production. The need for firearms in Colonial America is a strong indicator of firearms ownership levels as a simple matter of logic. If one accepts that there was a strong perceived need for guns as a tool of colonization, then they must have existed for the colonization to be successful. Additionally, while exact numbers are not readily available, we can gain a rough estimate of gun prevalence based on the number of firearms that were imported to the colonies. Next, the legal requirements of the day provide us with yet more information concerning the levels of private firearms ownership. If most of the colonies enacted similar laws to aid the processes of colonization and trade, and these laws reflect the necessity of the time we can have more confidence in the conclusions that can be drawn from this information. Finally, we can examine early gun production in the U.S. to understand the relative importance of firearms as tools of colonization. There are many references to the importation of massive quantities of firearms to North America from Europe. While these seldom include exact numbers of guns, and many seem to be commentaries that mention firearms as an afterthought, they do give us insight to the general tenor of firearm importation in the colonies. For instance, France exported over 200,000 muskets exclusively for trade with

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Trends in American Gun Ownership

American Indians between 1663 and 1763 (Kennett & Anderson, 1975:54; Kopel, 1992:308). Another, more general observation is made by Kennett and Anderson, “James I of England thought nothing of dispatching boatloads of arms to America, while preventing citizens of the British Isles from having them” (Rutman, “Militant New World”; Peterson “Arms and Armor in Colonial America” as cited in Kennett & Anderson, 1975:45). One must assume that arming the indigenous population in this fashion must have required stronger armament of the colonists of the same period. Even were the natives not well armed, they posed more than a sufficient perceived threat to cause the formation of the militias throughout all of the colonies, with the exception of Pennsylvania.7 The colonial militias were formed by laws designating all ablebodied freemen as members to preclude their governments’ the expense of keeping a standing army to protect the citizens (Kennett & Anderson, 1975:45; Kopel, 1992:311-312; Halbrook, 1994:56-61). For instance, in Virginia, English colonists were required by order of the governor to be armed while traveling to court or church in response to threat of American Indian attack (Halbrook, 1994:56). Both Virginia and Massachusetts enrolled all freemen, 16 to 50, and all white indentured servants into the militia. All members were required to provide their own weapons, powder and shot (Kennett & Anderson, 1975:46). Some laws even encouraged hunting with the intention that militia members would participate in target practice without incurring government expense for powder and ball (Kennett & Anderson, 1975:46). The last significant indication of the importance and prevalence of private firearms ownership in colonial America is the apparent technological advances made in firearms in the colonies, and the social status of those who built and maintained the firearms. The colonies saw the functional improvement of the Germanic rifle in Pennsylvania

7

Although the pacifist nature of the founding Quakers prevented them from requiring

members of the colony to be armed as members of a militia, this is not to say that they were not armed and familiar with the use of firearms. In 1763 many of the Quakers took up a call to arms to defend themselves against violent raids into Philadelphia (Boornstin, “The Americans: The Colonial Experience”; Hindle, “The March of the Paxton Boys”; Rutman, “Militant New World”; Peterson “Arms and Armor in Colonial America” as cited in Kennett & Anderson, 1975:46-47).

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17

by skilled, Teutonic, immigrant craftsman (Kennett & Anderson, 1975:40; Tonso, 1982:224). The need for skilled craftsman to create and maintain muskets and rifles8 was not, however, limited to Pennsylvania. These craftsmen were among the most skilled technicians available to work in wood, brass, steel, and machinery. Gunsmiths were to be found in every colony in the New World, and these men were so respected in their communities that they were often elected to political office (Kennett & Anderson, 1975:40-41; Tonso: 224, 227). It is unlikely that sparse firearms ownership in such an isolated and demanding environment as the American colonies would drive a need for such skilled craftsmen throughout the colonies; supporting assertions that the ownership of firearms was nearly universal during this time. Nonetheless, considering the limitations on private gun ownership during the early colonial period within their own historical context, we can see that ownership among those parts of the population that enjoyed full rights of citizenship was universally considered necessary and was pervasive in everyday life. Antebellum & Postbellum America The Antebellum period, from 1780’s through the 1860’s, appears on its face to be markedly different from the colonial period, prior to the adoption of the U.S. Constitution. There was no longer a colonial power exerting control over the new country. The great, modern experiment in democracy had begun. The country slowly developed from a frontier territory in its entirety, to a settled land interspersed with large cities and a frontier that was continually moving westward. While the economy was still mostly agrarian, industry had begun to grow, usually in northern cities, and with it, crime and violence that was heretofore unknown among urban dwellers (Lane, 1997:135-141). Although these changes and developments seem only to distinguish the two eras, there are a number of themes that they share, particularly with regard to firearm use and ownership. Westward expansion during this period created new frontiers, challenges, and opportunities similar to those of the colonial period. Also akin to the colonial period, endeavors on the frontier usually 8

For a complete discussion of the terminology concerning early firearms and the

practical meaning of the evolution of the firearm, see Tonso, 1982, ch.2 and Greener, 2002.

18

Trends in American Gun Ownership

required a firearm of some kind to successfully negotiate the needs of hunting to supplement one’s diet and of self-defense against both common criminals and American Indians. The American proclivity for making impressive technological advances in firearms design and production did not end with the colonial era’s Pennsylvania Rifle, but flourished, influencing the growth of other industries and supplying arms to most of Europe’s armies (Kennett & Anderson, 1975:85, 8992). Finally, the antebellum era was also marked by war and conflict with the natives of the new country, foreign powers, and eventually between the states themselves, all of which required ready access to firearms. The New Frontier The American frontier continued westward as the burgeoning country expanded its borders throughout this period starting with the Louisiana Purchase in 1803 and ending with the completion of the Central and Union Pacific Railroads in 1869. According to Tonso, those who moved west were in need of firearms for defense because American Indians were regularly provoked into hostile behavior toward the settlers, and were well able to defend themselves against white expansion. This was especially true at the fringes of the frontier (1982:170). This threat was actually much greater than was posed by American Indians in the eastern portions of the country, and would not subside until the very end of the 19th century (Kennett & Anderson, 1975:114; Tonso, 1982:171). During the latter half of the century, Kennett and Anderson make note of the American Indians’ intense resistance to western movement by whites: After the Civil war, the settlers and cavalry fought Indians in almost every western state and territory until the 1890s. Though the eventual subjugation of the American Indians seems now to have been a foregone conclusion, the yearly struggles with the Sioux, Cheyenne, Apache, Commanche, and a host of smaller tribes kept the decision hanging in the balance for many years. (1975:115) Many of the American Indians west of the Mississippi River were well-armed with working firearms during this period. A number of private companies continued to use firearms as barter in the fur trade

A History of American Gun Ownership

19

and some companies were established to produce guns specifically for trade with the American Indians, as allowed for by the Indian Intercourse Act of 1834. This law provided authority to legally supply American Indians with firearms, and was often used as an incentive or inducement to convince them to move west of the Mississippi River (Kennett & Anderson, 1975:116). In some cases, the U.S. government even provided gunsmiths to maintain the Indians’ weapons as part of the agreement (Kennett & Anderson, 1975:116). This practice was certainly not uncommon as more than 60,000 American Indians had been removed from the eastern U.S. by 1840, and over 30,000 had received rifles from the government (Kennett & Anderson, 1975:116). As this expansion and conflict was a constant part of frontier life until the 1890’s, so was a perceived need for firearms in the everyday life of many Americans. Out of the same perception as the original colonists of the 17th and 18th centuries, pioneers moving westward would have to be armed (Kennett & Anderson, 1975:105; Tonso, 1982:171). Kennett and Anderson even go so far as to refer to the 19th century as the “age of the firearm” in the U.S., outstripping the nearly universal ownership of the colonial era when the whole of North America was a frontier (1975:110). The firearm was apparently believed to be so essential to those who would move west that the federal government deemed it necessary to provide free arms to pioneers who were planning to go to Oregon, California, or New Mexico, were they unable to afford guns themselves9 (Kennett & Anderson, 1975:114). The great value of firearms is also evidenced by the cost of purchasing a gun in these remote frontier areas. For instance, Kennett and Anderson note that, a .44 caliber Colt Hartford Dragoon pistol that sold for $25 in the east sold for $300 in the California gold fields (1975:112). The importance of firearms to these frontier areas was not simply a result of the danger posed to settlers by indigenous peoples, however. Nor was the need for firearms merely a consequence of the need to hunt, whether for subsistence or as a profession (Kennett & Anderson, 1975:118-120;

9

Many of the pioneers who moved westward during this period were new to the

Americas, and had little previous exposure to firearms in their home countries. It would therefore stand to reason that they would be unaware of a need for firearms in their endeavors even though travel pamphlets of the time usually had guns at the top of the list of necessary equipment for moving west (Kennett & Anderson, 1975:114).

20

Trends in American Gun Ownership

Kopel, 1992:309). Throughout much of the western territories there was also a desperate need to defend oneself against other white settlers who made their living through law breaking and violence (Kennett & Anderson, 1975:121, 124-125; Tonso, 1980:174-178; Kopel, 1992:323328). The armed citizenry of the American West was the primary method of dealing with this criminal threat of violence (McGrath, 1989: 129). Unlike frontiers in other countries, the American frontier was characterized by settlements that almost always preceded any system of established law and order (Tonso, 1982:175; Kopel, 1992:328-329). This model was in keeping with American tendencies toward individualism and responsibility for personal defense and contributed to the wide proliferation of personal firearms ownership10 (Tonso, 1982:178-179; Kopel, 1992:326). This tradition also served to save both federal and local governments the financial burden of protecting the populace and administering justice (Kennett & Anderson, 1975:134-35; Tonso, 1982:176-177). It was not, however, new to the American system of government. It was the same system that was used throughout early colonial history and directly led to the formation of militias, and continued in the eastern portion of the country as well. There may have been little threat of Indian attack, outlaw raid, or starvation in the East during this time, but an armed population still thrived, even in the most populous cities (Kennett & Anderson, 1975:134). “Civilized” America: Eastern Cities Westward expansion and the appearance of new frontiers provides us with a simple explanation for the proliferation of firearms ownership in these unsettled areas, however, it does not provide us with much insight regarding patterns of firearms ownership in already settled areas. These areas were very different from the frontiers as there was little or no threat of attack by indigenous populations, food was usually provided by commercial hunters, and a legal system to enforce civil 10

For instance, other countries that had originally been settled by Britain, such as

Australia and Canada tended to settle new territory by establishing outposts under the control of the Crown and negotiating treaties with aboriginal peoples prior to settlement. This is in stark contrast to the American model of individual settlement with only peripheral government control (Kopel, 1992; Tonso, 1982:325).

A History of American Gun Ownership

21

and criminal law was well established. Tonso provides us with one main reason for gun ownership to remain common in such an environment, when he asserts that, “As America developed into a largely rural-agricultural society behind the frontier and then transformed it into a largely urban-industrial society, human threats to individual and group security did not automatically fade away” (1982, 185). Conflicts, major wars, civil disorder, feuds, crime, heterogeneous immigration, huge population growth and an industrial base that grew at a much faster rate than those in similar countries all contributed to a less stable society and conflict, thus increasing rates of gun ownership for personal and communal defense (Lane, 1997:104-107, 110-111; Monkkonen, 2001:2137-39). While this was true throughout the country, the southern U.S seemed to exemplify these ideals. The custom of whites being armed was almost universal in the South. This was probably less due to any failing of the courts or law enforcement, but more out of a strong martial tradition and a fear of potential slave uprisings (Kennett & Anderson, 1975:151; Cottrol & Diamond, 1995:136). Much as firearms would later be employed to quell labor uprisings in the 19th century’s industrialized North, they were used in the South with great effectiveness against unarmed, indentured populations (Tonso, 1982:192-193; Cottrol & Diamond, 1995:138-139). “Vigilance committees” were formed to meet the potential threat of slave revolt, and remained heavily armed in the South prior to the Civil War. In addition to their role of reacting to slave uprisings, they used firearms to pursue and apprehend runaway slaves (Kennett & Anderson, 1975:153; Kopel, 1992:332; Cottrol & Diamond, 1995:137). These groups are considered the social ancestor of the later Ku Klux Klan, and were often met with armed resistance by abolitionist groups (also made up of private, armed citizens referring to themselves as vigilance committees) when attempting to enforce the Fugitive Slave Act of 1850 (Kopel, 1992:332). This is not to say that free Blacks had much better access to arms in the northern states during the same time period, as they were usually barred from membership in the militia (Cottrol & Diamond, 1995:138). Ownership of firearms by all Blacks was often curtailed, as were other civil liberties, for their own “protection,” often leaving Black populations at the mercy of white rioters or criminal groups (Cottrol & Diamond, 1995:139, 140). During this same period the South was also preparing for secession. Authors who visited southern cities in the decades prior to

22

Trends in American Gun Ownership

the Civil War often described them as resembling an “armed military camp” (Kennett & Anderson, 1975:151). One may conclude that, while easily quantifiable estimates of firearms ownership for this time are unavailable, firearms ownership among white males11 must have been widespread, to say the least. Some of the western states along the North-South delineation saw citizens using privately owned firearms for combat well before the official start of the Civil War (Kopel, 1992:332). The South did not have a monopoly on social injustice, unrest, or firearms ownership in the U.S. Nor were rural areas, economically and geographically similar to the South, the only areas to experience widespread firearms use and ownership. Those residing in the metropolitan areas apparently also found personal firearms useful for a variety of tasks. Throughout the urban expansion of the 19th century there were a number of widely publicized riots in the streets of American cities. Many of these involved firearms. Cincinnati in 1841, Philadelphia in 1844, St. Louis in 1854, New York in 1863, and Pittsburgh and Chicago in 1877 all experienced major rioting involving firearm use by both rioters and those disposed to public order (Kennett & Anderson, 1975:145-147; Kopel, 1992:341). Major newspapers of the time made mention that private citizens were disregarding local laws that forbade concealed carry of firearms in the interest of personal security (Kennett & Anderson, 1975:147). Additionally, during the NYC anti-draft riots, smaller, African-American newspapers encouraged their readership to arm themselves in 1865: The colored men who had manhood in them armed themselves, and threw out their pickets every day and night, determined to die defending their homes… Most of the colored men in Brooklyn who remained in the city were armed daily for self-defense. (Joel P. Bishop as cited in Halbrook, 1994:105) Finally, while these riots seemed to be relatively common in major cities, the specific reasons for the riots were not. Almost all the riots found their origins in some type of social reform movement or protest,

11

This tradition continued well after the Civil War and many would say continues today.

For a more complete discussion of the “social function” of firearms, courts, and lawenforcement as tools of shifting power groups see, Tonso (1982: pp. 193-198).

A History of American Gun Ownership

23

such as racial equality, abolition of slavery, immigrants’ rights, organized labor demands, or some combination of these social issues (Kennett & Anderson, 1975:145-146; Tonso, 1982:193-195; Kopel, 1992:339, 341-342). Whether the use of force or firearms in any of these situations was or was not justified by the circumstances may be disputable, but they were certainly not the only violent uses of guns in urban areas during this period. No exact figures are available to detail the prevalence of firearm crime in cities during this period; however, Kennett & Anderson note that the advent of the small, inexpensive revolver seems to coincide with newspaper accounts of firearms use by both criminal gangs and private citizens in metropolitan areas (1975:148). The presence of established court systems and law enforcement may not have had the effect on firearm use that one might expect (Kennett & Anderson, 1975:148; Tonso, 1982:195-196, 200; Lane, 1997:111). Also, these reports of firearms use in urban areas were unusually high considering the availability of conventional courts of law in the eastern portions of the U.S. Nonetheless, while the courts were more developed and accessible in settled areas when compared to the frontier, law enforcement usually was not. Historians even go so far as to state that unarmed, urban police forces depended on assistance from citizens to the point that police officers were often considered secondary participants in any altercation with criminals (Kennett & Anderson, 1975:151; Lane, 1997:109-111). Therefore, private citizens in urban areas, very much like their contemporaries in the west, usually found themselves responsible for their own safety, well-being, and personal protection (Kennett & Anderson, 1975:147; Tonso, 1982:190-192; Kopel, 1995:341). It seems that the “differences” between the frontier and the more urban areas of the U.S. were less evident than one might intuitively expect. Even as the need to supplement diets through hunting and the fear of attack by Indians diminished to near nonexistence in settled areas, the risk or fear of harm from riot or crime rose exponentially (Kopel, 1992: 341; Lane, 1997:107-112). In a society which valued independence, individuality, and personal responsibility for selfdefense it is not surprising that many citizens felt it their right or duty to defend themselves with force. So esteemed were these principles that the reading of philosophers’ works supporting these tenets was common in grammar schools and high schools during this time period,

24

Trends in American Gun Ownership

thus possibly impressing itself on the American identity12 (McClurg, Kopel, & Denning, 2002). Although firearms had been common throughout most of America prior to this time, it was perhaps the earliest time that firearms became the weapon of choice for personal protection or crime in metropolitan areas (Kennett & Anderson, 1975:148). It is difficult to imagine that rifles and muskets were regularly carried by anyone in their daily life in a major metropolitan area, even in the reportedly martial atmosphere of the South. Technological advances in firearms in the mid 19th century allowed, for the first time, widespread access to affordable, small, relatively powerful, reliable, safe, repeating handguns in the form of the pocket revolver (Kopel, 1992:341). In more general terms, technological advances in firearms continued in the antebellum period as they had in the colonial period, only more so. This spirit of invention and innovation would lead to the development of a reputation for the U.S. as firearms manufacturers to the world. These various technological advances also provide some indication of the prevalence and importance of firearms in antebellum society. For instance, one would question the assumption of widespread firearms ownership throughout the U.S. if firearm manufacturers were unable to produce their wares in sufficient quantities and with sufficient utility to be available and desirable to a population where experience with guns was common. Also, the later growth of the American gun industry as a world leader in the design and manufacture of military arms would not have been possible without the innovation in firearm design and function predicated by the demand of the American private gun owner. The Firearms Industry The 19th century witnessed some of the greatest advances in the firearms industry to date. It is true that firearms today are often constructed from exotic metal alloys and synthetic materials that were unheard of a century ago, but most of the basic operating designs used in modern guns were originally developed in the late 1800’s. The American technological advances in firearms from the flintlock of the Revolution and early 19th century to the self loading, fully automatic 12

For instance, students were often required to read translations of Cicero’s defense of

Milo in which the right to defend one’s self with violence when threatened is highlighted.

A History of American Gun Ownership

25

firearms that were developed by 1900 were influential throughout the world.13 However, the evolution of the gun is not the only event that may point toward high frequency of firearms ownership in this period. During the same time the American gun industry grew to become world leaders in the manufacture of firearms. Understanding both the development of the firearm and the firearms industry in the U.S. will support the assertion that such advances are indicative of widespread personal gun ownership to such a degree that the demand for firearms would help to fuel the industrial revolution in America. Prior to adopting new gun technologies at the beginning of the Civil War, the U.S. military had a policy against paying any royalties for patent firearms, and still used muzzle loading, single shot pistols and muskets (Kennett & Anderson, 1975:91). The first large foreign use of American arms didn’t occur until the Crimean War (1854-1856), but Colt’s first widely used revolver was invented in 1832 and began production in 1836 (Kennett & Anderson, 1975:89). The demands of military powers, foreign or domestic, could not have driven the innovation of the American gun industry. The innovations came well before the military demand. Although a tenuous connection, civilian demand for personal weapons seems the only logical solution for the initial growth of the firearms industry in the early 1800’s. By the end of the 19th century, the growth rate of American industries and cities far outstripped that of British cities (Kopel, 1992:341). Many of the practical advances in machining, mass production, and interchangeability that allowed America to be on the forefront of the industrial revolution were actually a result of advanced manufacturing techniques from within the firearms industry (Kennett & Anderson, 1975:89). Some examples of the industries that were made possible by engineers from the firearms industry include early tabulating machines, clock-making, sewing machines, typewriters, and the internal combustion engine (Kennett & Anderson, 1975:89). It is doubtful the gun industry could have made these innovative advances without a steady market for their products, and without the product demand to drive development. Without the type of production data that is available today, it is difficult to ascertain exactly how much of this

13

For a more complete discussion and description of the technological development of

firearms from their earliest uses through today, see Greener, 2002 and Tonso, 1982: Ch. 4.

26

Trends in American Gun Ownership

market was private and how much was public, but we do know that firearms manufacturers depended heavily on the civilian market to survive between large military contracts (Kennett & Anderson, 1975:101-102). Due to the advanced systems of firearms production that were pioneered during this era, small arms produced in the Northeastern U.S. were not only to be found in the hands of Americans or the U.S. military, but most of the major military powers of the day. Verification of the skill of producers like Colt, Winchester, Smith & Wesson, and Remington could be found in the arsenals of almost every European country. During the Crimean War, Colt revolvers were used by British, Turkish, and Russian armies alike (Kennett & Anderson, 1975:90). France equipped its army with American arms during the FrancoPrussian War (Kennett & Anderson, 1975:93). The British and Russian Armies contracted with Americans to develop their first breech-loading rifle in the 1870’s, and other American arms were purchased by the governments of Egypt, Japan, and Mexico (Kennett & Anderson, 1975:94). Kennett and Anderson go on to note that by 1882, that, with the single exception of the needlegun, (the weapon of the Prussian Army), every gun with a breech loading system used in Europe was of American origin in its design and application; a large portion being of American manufacture (1975:95). Of course, military arms sales, whether foreign or domestic could explain the growth of the arms industry in the latter part of the 19th century, but they do not necessarily correlate to private gun ownership in the U.S. The advances in firearms technology was obviously the driving force behind the interest of foreign governments adopting American firearms, but these sales could not sustain the industry by themselves, nor could they account for the initial progress in the development of American arms (Kennett & Anderson, 1975:95). In addition to the advances in production technology that benefited the burgeoning industrial complex of the U.S., there were also huge leaps forward in the development of firearms themselves (Tonso, 1982: 67-69). At the very beginning of the 19th century the form and function of personal firearms had changed little from their earliest inception.14

14

While the exact date and place of the first use of firearms is unknown, there are

historical records of guns in Europe as early as 1247 (Greener, 2002:18). While some forms of modern firearms were originally conceived well before the 19th century, they

A History of American Gun Ownership

27

These guns generally loaded a powder charge and projectile from the muzzle and were fired by igniting the gun powder through some type of opening in the back of the barrel as exemplified by the matchlock, wheel-lock, flintlock, and the percussion-lock (Tonso, 1982:61-63; Greener, 2002:64-68, 117). These firearms were cumbersome, difficult to load, and highly susceptible to adverse environmental conditions, making them utterly unreliable by modern standards (Tonso, 1982:6263). By the end of the 19th century, however, firearms, as we know them today, had been invented. The metallic cartridge, smokeless gun powder, revolvers, repeating rifles, and semi-automatic and fully automatic pistols and rifles were all invented and in production before 1900.15 Technology that was unchanged for six centuries reached its acme within a 75 year period in America, and has remained unchanged in its basic function and design over the last 100 years of invention, progress, and technology. The technological advances offered by the gun industry not only guaranteed a prosperous future to the American gun manufacturers of antebellum America, but assured the prospects of all manufacturing industries. One must assume that the original technological advances were supported by the market demands of a nation of private firearms users, because the innovative designs and advances in gun production preceded both the American Civil War and major contracts to supply guns to foreign militaries. Within the early American military complex, advanced technologies such as breech loading rifles, metallic cartridges and revolvers were not adopted until 1861, long after they were actually developed (Kennett & Anderson, 1975:91). The United States witnessed a great episode of change in the antebellum period. America was transformed from an agrarian, subsistence based society made up almost entirely of frontier territories

were not able to be produced or used in any practical way until the 1800’s. For instance, revolvers were developed as early as the 15th century, but were never manufactured in any functional form until the early 1800’s (Greener, 2002:524). 15

For explanations regarding the terminology of modern firearms, the evolution of

firearms through the 19th century and the exact, scientific and engineering explanations of the inner working of firearms and ammunition, see The Gun and its Development, 9th ed. by W. W. Greener (2002). This work was originally published in 1910, and offers the reader detailed information concerning firearms of all types from the 1200’s through the early 20th century.

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Trends in American Gun Ownership

to a mostly settled country reaching across an entire continent. By the end of the 19th century, America was an industrial nation with large metropolitan areas and almost no frontiers. As evidenced by the use of firearms in both the cities and frontiers of the era, and the progression and development of the firearms industry, private ownership did not cease to be a reality in the lives of everyday Americans. The militia system, the market-driven innovation in the gun industry, and the use of guns for self-defense and in crime by private citizens both on the frontier and in the cities all support this assertion. Obviously, one would expect that firearms use in the 20th century would not be much different; however, we shall see that the development of more effective law enforcement systems and a growing movement toward progressive social ideals would cause America to question its reliance on the gun as a necessary tool for survival and a symbol of national identity. The Early 20th Century The 20th century brings to a close any major discussion of firearms use in frontier environment. The westward expansion of the U.S. through land or gold rushes in the 19th century was largely over. The country had developed, for the most part, well established, organized, professional law enforcement agencies (Kennett & Anderson, 1975:166). Technological advances such as the telegraph and the transcontinental rail road system further rendered much of the isolation and self-reliance of the 1800’s pioneer unnecessary and obsolete. The new century also ushered in the first national gun control laws, the first laws to restrict ownership of guns and the first laws to make particular types of firearms illegal. These concepts were heretofore largely foreign to the citizens of the U.S., and are indicative of shifting gun ownership patterns and values regarding guns as the entire country became settled. The change in attitudes and subsequent changes in law were not limited to firearms, however. This period in U.S. history was, more generally, an era of progressive politics, government redress of social ills, and social conscience in journalism that inspired the new American tradition of using legislation as the main weapon of social justice and social control (Kennett & Anderson, 1975:165-166; Tonso, 1982:257; Vizzard, 2000:87-88). Many of the efforts to encourage a just society through government intervention resulted in laws and programs that are universally accepted today, such as child labor laws. However, not all of the reformers’ efforts were so successful (Kennett & Anderson,

A History of American Gun Ownership

29

1975:166). Many of the experimental reforms of the progressive era hint at the potential difficulty and complexity of social problems and types of reforms intended to address them in the modern, industrialized U.S. The Volstead Act, for instance, is widely accepted as a failed experiment (Kopel, 1995:389) that caused national discontent and the growth of organized crime in the earliest part of the 20th century. Finding a “cure” for crime was indeed one of the chief goals of these social reformers, and few ideas were beyond consideration.16 Among these attempts to provide social order and social justice to a growing nation were the earliest attempts to restrict firearms ownership and use. As we shall see, the first places to attempt restrictions on firearms were large cities, which could be an indication or an eventual cause of the changing demographic of firearm ownership in the U.S., and the growing dichotomy of attitudes concerning guns. In the late 1800’s, most firearm control laws were local in nature. State or local ordinances dealing solely with the restriction of concealed weapons were the norm throughout America, rather than the restriction of any types of firearms or general ownership, with the exception of certain racial or ethnic groups17 (Kennett & Anderson, 1975:163; Halbrook, 1994:93-96; Cottrol & Diamond, 1995:142-143; Vizzard, 2000:87). This pattern, however, was soon to change. Perhaps the earliest success in the general restriction of firearms was the Sullivan Act in New York City. Gun Control Laws While a history of gun control laws do not offer a direct measure of gun ownership patterns, most of the available information from scholarly sources focus on these laws.18 The value of understanding the tenor and 16

At about the same time that the earliest gun control laws were considered in New York

City there were laws passed in Colorado outlawing cigarettes, a law in New Jersey enacted to sterilize criminals in hopes that it would render the “hopelessly defective criminal classes” unable to procreate, and a bill introduced in Massachusetts to prohibit women from wearing short skirts (Kennett & Anderson, 1975:177). 17

Many early gun control laws did in fact restrict ownership, but these were generally

designed to prevent firearm possession by Blacks and American Indians (Cotroll & Diamond, 1995; Halbrook, 1994; Vizzard, 2000:88). 18

Most of the historical literature describing guns and their roles in America from

colonial through post-bellum eras detail technology and function of firearms. Most

30

Trends in American Gun Ownership

development of gun laws during this period lies in the insight it can provide into public opinion and political force surrounding firearms, in turn allowing us to arrive at some conclusions about the prevalence of gun ownership and use. The progenitor of nearly all early attempts at gun control was the Sullivan Law. Enacted in New York City in 1911, the Sullivan Law was the first instance of a legal requirement to register guns and restrict firearms possession in the U.S. by requiring a license to purchase or possess a handgun19 (Kennett & Anderson, 1975:175; Vizzard, 2000:87-88). There are a variety of explanations that are offered for the popularity of this law, and a variety of interpretations of its implicit purposes. None offer a complete explanation of the possible expectations of those who drafted the law, or the motivations behind the introduction of the law; however, these various interpretations are precursors to the general debate over firearms today. Kennett and Anderson cite the handgun wounding of New York City mayor William J. Gaynor, and the subsequent press coverage that laid the blame for most criminal activity and violence in the city on the apparently large numbers of guns that were owned and carried there, to be among the motivating factors for the law (1975:176). There were also vocal supporters of restricting possession of firearms in political office, as well as among those who influenced the politics of the time (Kennett & Anderson, 1975:176). This formidable political support combined with the new, cosmopolitan sensibilities of the Progressive Era in a city that was growing faster than any other in the world, to enormous effect. In the new urban environment there was less socialization to firearms than in rural areas (Vizzard, 2000:88). While there appeared to be little popular opposition to the passage of such a law, this could be because dissenters’ discordant voices were squelched by the press due to the unilateral support for firearms restriction articulated by the stories and editorials of the city’s newspapers (Kennett and Anderson, 1975:171,178). Those who were able to

reviews of the 20th century, however, focus almost exclusively on gun control laws. (e.g. Kennett & Anderson, 1975: ch.7,8; Kopel, 1995:387-393; Vizzard, 2000: ch. 6) 19

In addition to restricting the carry and ownership of firearms, the Sullivan Law also

increased the penalties for possessing other weapons which were already illegal under an 1866 law forbidding “Sling shot, billy, sand-club or metal knuckles and any dirk or dagger, or sword cane or air gun” (Kennett & Anderson, 1975:169).

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express opinions that were unsupportive of firearm restrictions offered arguments that still echo in public and academic literature to this day.20 There is also some evidence that firearms use and ownership was widespread in New York City prior to the Sullivan Law. In 1903 the New York Tribune published reported police estimates of gun carrying in the city. The New York Police Department estimated that at least 20,000 citizens carried a handgun regularly, only about 600 of those with the required police permit to carry a concealed weapon even though there were not yet any legal restrictions on the simple possession of a handgun (Kennett & Anderson, 1975:179). Yet another possible motivation of those who supported the Sullivan Law is offered by Kennett & Anderson (1975), Tonso (1982), and Kopel (1992). This argument deals with power relationships between classes of people, and is also offered as an example of gun control laws’ implicit ability to limit ownership by race (Halbrook, 1994; Cottroll & Diamond, 1995). This explanation describes the Sullivan Law as a discriminatory reaction to the large influx of Eastern European immigrants, and with them elements of anarchism, socialism, and labor unrest (Kennett & Anderson, 1975:173-174, 178; Kopel, 1992:341-344). In this case, gun control was only intended to disarm minority groups consisting of blacks, immigrants, or other “undesirable” classes such as the Irish, Italians, or Jews by the discretionary nature of the issuance of police permits for the possession and concealed carry of firearms (Tonso, 1982:256-257; Kopel, 1992:342-343). In these accounts, social stratification is the central theme of gun ownership in a society that was experiencing the social upheaval of early industrial America. The Sullivan Law appears to have had little immediate effect on the social value of gun ownership in New York as there was little apparent reduction in the ownership or use of guns in any quarter of the population. There was perhaps even less impact on crime rates (Kennett & Anderson, 1975:184-185). Although there is no way to

20

Letters to the New York Tribune criticized the Sullivan Law by making statements

such as, “Even if he [Mayor Gaynor’s would be assassin] obeyed the law, which is unlikely, he could still choose an ice pick, a reaping hook, or a butcher’s cleaver” and that earlier laws would have been sufficient if properly enforced (Kennett & Anderson, 1974:178). These observations in 1911 are similar to arguments offered against gun control a century later.

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ascertain exactly how many firearms are owned in violation of the Sullivan Law today in New York City, some estimate there are as many as 2 million (Tonso, 1982:258). As for the immediate impact of the Sullivan Law on crime in New York City, those who opposed the law were quick to decry its ineffectiveness when homicide rates rose the year after its enactment (Kennett & Anderson, 1975:185). In essence, this was the beginning of the visceral, bitter debate that still surrounds gun policies today, the argument that is perpetuated by the inherent differences in social and political philosophy between a more modern, urban model of communitarianism, and the traditional, rural model of individualism and a focus on individual rights. The next major phase in gun control did not occur until the 1920’s. Although a number of states used the Sullivan Law as a basis for their own laws between 1911 and 1927, these tended to be dead letters even though firearms were generally described by social reformers, newspapers, and progressive politicians as a national disease (Kennett & Anderson, 1975:187). Most of the states who passed strict legislation of this type simply did not enforce their laws (Vizzard, 2000:88). The onset of World War I, further reinforced the general apathy for the enforcement of restrictive gun control laws, and perhaps even made some of these policies seem hypocritical. For a short time gun ownership, and skilled gun use, were again seen as national virtues rather than a national disease. After this brief hiatus, however, the eyes of the nation would once again turn to legislation, this time at the federal level, as an answer to the American gun “problem.” The first legislation attempting to address firearm crime at the national level was passed into law in 1927. This law did nothing to restrict the possession of firearms, as the Sullivan Law had. Instead, it only banned the mail order sale of small caliber handguns to individuals21 (Vizzard, 2000:89-90). Largely due to the perceived ineffectiveness of this law, debate for more meaningful gun control legislation began in 1934 (Vizzard, 2000:89).

21

The Miller Act of 1927 was an obvious attempt to address a crime problem through

firearm control. For the most part, however, this law did little to restrict access to guns by anyone. While it outlawed cheap, small caliber handgun sales through the mail, it did not restrict common carriers from delivering these same guns rendering the law ineffectual at best. Addressing such shortcomings led to the National Firearms Act of 1934 and the Federal Firearms Act of 1938 (Vizzard, 2000:90).

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The years following the First World War saw large upturns in crime rates before the Stock Market Crash of 1929. The crime problem was so dire in some places that rural areas formed armed citizens’ organizations to defend their banks from robbery. Philadelphia issued pistols to their firemen, and New York City eased enforcement of the Sullivan Law as women began buying pistols for personal protection, armed guards were hired to protect fine money collected in city courts, and Wall Street businessmen began to carry handguns in public (Kennett & Anderson, 1975:195). The economic problems that followed 1929 coupled with the common use of sawed-off shotguns and fully automatic rifles by criminals only served to worsen the problem (Kennett & Anderson, 1975:202-204). A combination of increasingly powerful criminal organizations built around an illegal alcohol trade, bank robbery and other street crime increases, the dire financial hardships of the Great Depression, and readily available, powerful firearms was indeed potent. It was argued by both gun control advocates and detractors that their policy was the answer to controlling crime in America; however, it seemed that neither an armed citizenry nor armed law enforcement agencies would stem the crime wave (Kennett & Anderson, 1975:203). In order to address the concerns of a country gripped by depression, unemployment, and a violent crime wave, Congress reacted by passing the National Firearms Act of 1934 (NFA). Just as the Sullivan Law in New York was the first local statute to place limits on possession of firearms, the NFA was the first federal legislation to limit the sale and ownership of certain classes of firearms by requiring licenses and implementing taxes for possession of automatic weapons, sawed-off shotguns, and other “destructive devises” (Vizzard, 2000:89-90). The initial crime control bill also would have banned interstate transfer of concealable firearms, which would effectively eliminate handguns (Kennett & Anderson, 1975:204; Vizzard, 2000:89). Such a measure was not to be, however, as organized, grassroots resistance to the law by the National Rifle Association (NRA) and other populist organizations weakened many of its original provisions (Kennett & Anderson, 1975:205-211; Vizzard, 2000:89-90). It was during this time that the NRA ceased to be simply an organization to promote marksmanship and distribute surplus military arms, and initiated their role as a grass-roots political action organization (Kennett & Anderson, 1975:205). In the early 1930’s the NRA began to actively recruit sportsmen into their ranks, increasing

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their membership from about 3,500 individuals to an organization with affiliates in over 2,000 shooting and sportsmen’s clubs (Kennett & Anderson, 1975:205). By the time hearings commenced in the Senate and House of Representatives in 1934 the NRA had organized a letter writing campaign that provided them a stalwart voice in Congress (Kennett & Anderson, 1975:206). When sponsors of these bills appealed to their sympathetic constituents in an attempt to mobilize a counter-balance to the power wielded by the NRA, they were generally unsuccessful in their efforts (Kennett & Anderson, 1975:211). The modern gun control debate, as we know it today, had taken form in just a few short years. Early gun control legislation can inform those who wish to study and understand the patterns of legal gun ownership in the U.S. today. Kennett and Anderson discuss a cultural division in America in which a divergence of values can explain the deep division that is experienced between “shirtsleeve” America embodying traditions of self-reliance and individualism, and “cosmopolitan” America, representing modern, progressive ideals of communitarianism (1975:254). The relative differences of these groups’ worldviews are thrown into sharp relief by the gun control debate. Although this view offers an overly simplistic and polarizing view of gun ownership it may offer a lens through which we can examine some of the traits associated with ownership in their most basic forms. In so much as we can understand the characteristics of “shirtsleeve” America, we can understand some of the perceived characteristics of gun ownership, and the sometimes derisive differences that surround this visceral issue (Tonso, 1983:330-331). Shirtsleeve Americans are described by B. Bruce-Biggs as inarticulate and independent traditionalists who model themselves after frontier pioneers (2001:57). He also offers his interpretation of Kennett and Anderson’s cosmopolitan American as those who prefer a more communitarian, European model of society in which they can lead an equitable, democratic life under the watchful eye of good government (Bruce-Biggs, 2001:57). Judging from these descriptions, insulting and crude though they may be, and the political force initiated by members of the NRA, conflict was inevitable given that gun ownership in the early 20th century must have been quite common. Understanding the political might that was mobilized to thwart gun control at the national level provides us the best indication of gun ownership during this period. The NFA and the later Federal Firearms Act of 1938 were originally intended to place strong restrictions on the

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private ownership of handguns and ammunition and force those who did own guns privately to register them (Kennett & Anderson, 1975:206, 211-212). These laws, like the Sullivan Law before them, had a great deal of support among the “cosmopolitan” portion of the population, however they were weakened to the point of derision by the organized political efforts of the “shirtsleeve” part of America. This in itself indicates that a very large part of the population felt sufficiently threatened by the potential of these laws to engage in strong, active political behaviors. They must have felt that they had something tangible at stake. These dissenters would most likely have been gun owners, just as so many Americans before them. THE VALUE OF HISTORY In any case, one should assume that there are some lessons to be learned from America’s unique history of widespread gun ownership. In the early periods of American colonization the immediate needs of European newcomers would have dictated firearms ownership as a perceived necessity for survival in a hostile land. As the nation was freed from its colonial obligations and gained sovereignty, it did so largely through the military force of an armed citizenry coupled with westward expansion that was characterized by notions of mandatory gun ownership. While guns were desired and used in settled areas for different reasons, the tradition of personal armament, the civic responsibility of defending oneself, and the massive technological advances of the firearms industry in the United States did more than keep gun ownership alive, it became an active part of the national identity at least until the early 20th century. Furthermore, the technological innovation that enabled the U.S. to move to the forefront of the industrial revolution was fueled, in large part, by the demand of private gun owners. A history as strong as the tradition of gun ownership in the United States would lead us to expect continued high levels of legal firearms possession. This debate is almost certainly one that occurs at a variety of levels in the U.S. The abovementioned chasm between those who support restrictive gun control and those who do not was never as simple as Bruce-Biggs (2001) would lead us to believe. Kennett and Anderson conclude their work with an observation on the complexity of American values concerning guns and the ensuing cultural conflict:

36

Trends in American Gun Ownership Sophisticated America and shirtsleeve America war in all of us. We abhor the gun in the hands of the assassin but find it a comfort in our bureau drawer. A majority of Americans, the polls tell us, would subject their right to bear arms to police control and a majority of Americans would not hesitate to use those arms if threatened by urban rioters. In the face of certain crises old attitudes will re-emerge with great force. (1975:255)

Even without the information that scientific polling in the late 20th century has given us, greater insight into patterns of legal gun ownership in the U.S., and the attitudes that accompany them in history, provide us with a framework for the discussion of gun ownership that is rich in detail. We have only been able to describe legal gun owners and legal guns in America the more explicit means of survey data since 1959 (Erskine, 1972:455). Nonetheless, to interpret the wealth of information offered by such polls without being informed by the cultural and historical dimension of gun ownership in America would provide us with a narrow understanding indeed. CONCLUSION The prevalence of private firearms ownership in the United States is extremely high, especially when compared to most other western, industrialized countries (Kopel, 1992:13-15; Wright, 1995:63). Literature that attempts to explain this phenomenon, and that which describes gun ownership in the United States, is often limited to one viewpoint on the topic. Although there is a wealth of information available, many studies ignore the historical impetus and the transmission of a “gun culture” through social institutions, the social and economic costs and benefits of firearms ownership, or modern scientific knowledge in this specialized area of academic study, much to their detriment. Without this multifaceted approach many authors may miss valuable information that would inform their work and broaden theories and explanations regarding this important area of research. The characteristics of firearms ownership, and the culture surrounding it, have gone through a number of incarnations throughout American history. Although the history of gun ownership has passed through periods of prominence and change it seems quite clear that it had always held a place of prevalence and importance in American

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culture. Each of the major periods of history of guns in America inform us that private gun ownership remained prominent in the United States well into the turn of the last century, and there appears to be agreement on this assumption throughout most credible historical literature on the topic. It is abundantly clear from this evidence that private gun ownership driven by of need for firearms has been one of the most important defining characteristics of American culture. This need can be interpreted as a real, functional need or a perceived need, and the exact needs seem to change over time. It does seem, though, that the pervasive roles of private firearms, whether in rebellion, hunting, or self-defense, indicate very high rates of private gun ownership historically.

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CHAPTER 3

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INTRODUCTION The private ownership of firearms in the United States today is indeed common (Kopel, 1992:13-15; Wright, 1995:63; Hemenway, 2004). Although we’ve already discussed evidence from historical literature, modern work based on survey measurement of firearms ownership will provide us with a much more detailed picture of individual gun owners in the latter part of the 20th century. Working toward understanding the levels of disparity or consensus in previous research, a discussion of the traditional predictors of gun ownership in the U.S., and cultural and demographic predictors of gun ownership, will arm us with the insight necessary to design analyses that address each of these considerations. This will also provide a rich and informative springboard from which to draw informed conclusions regarding the analyses. Some estimate that almost half of the households in the U.S. have at least one legally owned firearm (Wright, 1995:63), with between 100 (Wright, Rossi & Daly, 1983:43) and 240 million guns in private hands (Cook & Ludwig, 2000:11, Kleck, 1997:67). If one accepts these estimates of gun ownership in the U.S., it is easy to understand how there could truly still be a “gun culture.” As social scientists, we understand culture as manifesting itself through shared beliefs, values, goals, and symbols that are usually driven by complex historical and societal influences (Seidman, 1994:105-107). Accepting this functional definition of culture, we can begin to define and understand the American gun culture, how it has been influenced, how it operates within the larger structure of modern American society, and what impact it has on members of the culture. A deeper understanding of American gun culture would truly be significant because the more we understand about the profusion of private gun ownership in the U.S. 39

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population, the more we realize that this behavior cannot be dismissed as deviant (Wright, 1995:64). To the contrary, legal gun ownership in the U.S. exemplifies the very definition of normative behavior. In general terms, we currently define gun culture by the demographic characteristics of its members. According to most descriptive accounts of gun owners in the U.S., we know that members of the gun culture tend to be white, male, rural, Protestant, and middle class (Bordua & Lizotte, 1979:171; Wright et al., 1983:122; Kleck, 1997:70). In addition, gun ownership tends to be more heavily concentrated in the South and South-Western regions of the country (Wright et al., 1983:122; Kleck, 1997:70). Gun owners were often socialized to become part of the gun culture by their parents who owned guns (Lizotte & Bordua, 1980:236-239; Lizotte et al., 1981 502; Wright et al., 1983:122). Of course, the historical impetus provided by a long tradition of private gun ownership that influences the American self-image is highly influential to both social reality and the internalization of cultural values shared by gun owners. We have already seen that the characteristics of firearms ownership, and the culture surrounding it, have gone through a number of incarnations throughout American history. In addition to the description of the culture and history of gun ownership we can look to social scientific literature to provide a more complete picture of this phenomenon. While there is no way to assess modern scientific evidence to give us a precise picture of the levels of gun ownership prior to the 1950’s, scientific polling offers rich data that has examined the characteristics of gun ownership in modern America with great detail over the last 50 years or so. These data come from a variety of sources and were collected for both general purposes or, sometimes, specifically to study gun ownership. As early as 1938, the Gallup Poll began asking questions concerning Americans’ opinions on gun control (Erskine, 1972:455). Only a few years later, in 1959, the same polling agency began trying to measure the frequency and distribution of gun ownership in the U.S. (Erskine, 1972:456; Young, Hemenway, Blendon & Benson, 1996:635; Kleck, 1997:64). Through national surveys such as Gallup, the General Social Surveys (GSS), the National Gun Policy Surveys (NGPS), and the National Study of the Private Ownership of Firearms (NSPOF) we have garnered knowledge about legal gun owners today. These surveys use a number of different methods and modes to conduct interviews across a national sample, and they allow us to understand the

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characteristics of modern gun owners with a scope of knowledge that was simply not available prior to their inception. While they do not always completely agree in some specific details concerning gun owners (Wyant & Taylor, 2007), and they sometimes are not as accurate as we would like them to be, (Kleck, 1997:65; Ludwig et al., 1998:1717) we can often overcome, or at least understand, their shortcomings through replication and testing. There are also a number of targeted surveys or other research models that attempt to examine the gun culture directly, either by surveying gun owners exclusively, or by attempting to isolate different facets of the gun culture. These research designs serve a number of purposes, but the major questions they hope to answer concern reasons for gun ownership and if divergence in the values or characteristics within the gun culture exist. Later, truly unique surveys attempted to collect data on individuals in order to describe differences between these two gun ownership cohorts (Cao, Cullen, & Link, 1997). Additionally, surveys have sampled only gun owners to facilitate questions relating to political action and public opinion (Weil & Hemenway, 1993). Finally, the most recent surveys that attempt to measure the prevalence and characteristics of gun ownership find their inception in the fields of medicine and public health, the most prominent of these being the Behavioral Risk Factor Surveillance System (BRFSS) of the Centers for Disease Control and Prevention (CDC) (CDC, 2005). Before discussing the specific literature, though, the casual reader should be forewarned and forearmed. When one enters into any discussion pertaining to a controversial topic, readers must be aware of the distinct possibility of bias (Tonso, 1983:340). Even with the relatively recent advances in social science and quantitative analysis, hotly contested topics, such as firearms ownership, require the reader to examine the relevant literature with objective, critical evaluation. According to Tonso (1983:330), the debate over gun control and private firearms ownership in the U.S. is merely a manifestation of larger conflict in cultural values between communitarian minded urbanites and individualistic rural-dwellers (Kennett & Anderson, 1975:254-256; Bruce-Biggs, 2001:73). This cultural conflict has led to problems ranging from irreconcilable differences in basic assumptions (i.e. whether guns are basically good or evil), to questionable ethical practices and scholarship on both sides of the debate (c.f. Malcolm, 2003:26-27; Morin, 2003:C01). In short, the reader must always be

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cognizant of the potential influences of bias in scholarship concerning firearms Thus it is with great care and attention that we shall examine and discuss this literature. MODERN PATTERNS OF LEGAL GUN OWNERSHIP Today, gun culture in America usually refers to an amalgam of demographic characteristics that provide us with a picture of the average legal firearms owner. The earliest study of this type dates to 1959 by the Gallup poll (1972:626). In this poll, respondents were asked whether or not they had a gun in their home, and what type of gun it was.22 These data were then classified by region and community size (Gallup, 1972:1626-1627). Although there were survey data on gun related topics as early as 1935, there were no specific data concerning legal gun ownership in the United States, only questions attempting to measure public opinion on gun control issues (Erskine, 1972:456). Later studies, such as the General Social Surveys (GSS), National Gun Policy Surveys (NGPS), and National Survey on Private Ownership of Firearms (NSPOF), have provided more detailed information about gun ownership. These studies supply us with a wealth of descriptive information about private gun owners. It is also important to note that while there are differences in the design, purpose, and execution of these surveys, they generally reach a consensus in their findings. The information collected by these studies has provided us with a strongly supported demographic picture of gun owners based on characteristics such as income, family status, race, religion, and gender, among others. This is certainly a great advance over the earliest Gallup Poll, which only describes the respondents in terms of region and size of place. Describing the gun culture, however, is not simply a matter of naming a litany of demographic characteristics to describe gun owners. For instance, one of the earliest works in this area describes and compares two major groups of gun owners, those who own guns for sport and those who own guns for protection (Lizotte & Bordua, 22

The respondents were asked, “Do you have a gun in your home?” and “What type of

gun?” respectively (Gallup 1972: 1626).

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1980:229; Lizotte et al., 1981:502). It is only by combining the findings of such research with our understanding of the historical perspective of gun ownership and use that we can engage in an informed dialogue concerning American gun culture. Modern discussion of American gun culture is, nonetheless, dominated by a series of demographic characteristics that are commonly accepted to describe legal gun ownership and gun culture. We know that members of the gun culture (i.e. gun owners) tend to be white, male, rural, Protestant, and middle class (Bordua & Lizotte, 1979:171; Wright et al., 1983:122; Kleck, 1997:70). Additionally, gun ownership tends to be more heavily concentrated in the South and South-Western regions of the country (Dixon & Lizotte, 1987:398-400; Wright et al., 1983:122; Kleck, 1997:70), and gun owners are often socialized into the gun culture by gun owning parents (Lizotte & Bordua, 1980:236-239; Lizotte et al., 1981:502; Wright et al., 1983:122). These demographic variables should be discussed individually as they effect rates of household ownership and its relation to individual gun ownership according to their place in modern polling. Even though the methods of historical research and scientific polling stand in stark contrast, many of the modern descriptions of gun ownership are quite similar to historical descriptions. These very different methods not only corroborate one another, allowing us to understand the background of gun culture in America, but provide us the opportunity to better ascertain the roles and importance of personally owned firearms in American culture and the characteristics of those who own them. Region and Gun Ownership The demographic that is perhaps most closely associated with gun ownership is region, more particularly the South. The South refers, generally, to areas of the Southeastern United States, and has received a great deal of attention in scholarly research as an area with high levels both of gun ownership and violence (see Hackney, 1969; Gastil, 1971; Reed, 1986). However, later endeavors to test hypotheses linking gun ownership and violent subculture with a common cause have typically met with little success (see Loftin & Hill, 1974; O’Conner & Lizotte, 1978; Dixon & Lizotte, 1987; Nisbet & Cohen, 1996). Nonetheless, it

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is true that most surveys and polls place the South at the forefront of private gun ownership over a long period of time.23 Prevalence of Gun Ownership in the South Throughout all of the years and surveys, and throughout all of the differing types of survey methodology, sampling techniques, and question wording and placement, the overwhelming concurrence of findings is extraordinary. Among all of the regions reported in these various surveys the South, more particularly the Southeastern United States,24 displays particularly high levels of gun ownership consistently over time. Although the argument that a higher density of gun ownership is indicative of the strength and prevalence of gun culture is somewhat tautological, we must accept that there is some social or ecological factor that maintains high levels of gun ownership, even if this does not fully support the concept of gun culture per se. As early as 1959, the Gallup Poll began asking questions about private gun ownership in the U.S., including demographic data to determine prevalence of gun ownership by region and community size (Gallup, 1972:1626). In this early survey, researchers found that respondents in the South reported household gun ownership at a rate of 67%, a full 14 percentage points above the next highest region. This is in agreement with the 1968 results of a Harris survey in which Southerners report household gun ownership at a rate of 59%, at 8 percentage points above the next highest region (Erskine, 1972:457,458). Although these early surveys had slightly different question wording, and sampling procedures have changed throughout

23

As early as 1959, the Gallup Poll has asked its respondents questions regarding

household gun ownership (HGO), and has found that HGO is most prevalent in the South-Eastern U.S. (Gallup, 1972). This finding is in agreement with all other studies meant to describe gun ownership demographically (see Cook & Ludwig, 1997; Davis & Smith, 2001; Smith, 1999; Smith & Martos, 1999; Smith, 2001). 24

Although Gastil (1971) and Hackney (1969) used complex and somewhat arbitrary

definitions of “South” most modern work in the area has settled on defining “South” in the same terms of the U.S. Census. The states included in each census region are as follows: South = DE, MD, WV, VA NC, SC, GA, FL, KY, TN, AL, MS, AR, OK, LA, TX; West = MT, ID, WY, NV, UT, CO, AZ, NM; Midwest = WI, IL, IN, MI, OH, MN, IA, MO, ND, NB, KS; Northeast = ME, VT, NH, MA, CT, RI, NY, NJ, PA.

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the years, the proportion of gun ownership differences between the South and other regions of the U.S. have changed little. Beginning in 1972, the National Opinion Research Center (NORC) began to ask respondents questions concerning gun ownership in the General Social Surveys (GSS) (Davis & Smith, 2003). In these face-toface surveys, the results agree with the findings of Gallup and Harris in that southern respondents reported HGO at a rate of 11 percentage points higher than the next highest region in 1972 (Pastore & Maguire, 2001:148). Throughout the lifespan of the GSS, there does appear to be some reduction in the singularity of the southern HGO reporting. For instance, in recent years the gap between the South and the Midwest has narrowed with no difference in reporting in 2000, and only 7 percentage points in 2002 (Pastore & Maguire, 2001:148; Davis & Smith, 2003). This could be due to either a pronounced reduction in the Southern gun ownership, an increase in the Midwest, or some combination of these changes. Although this trend in region of ownership shows a reduction in the gap between the South and other regions of the United States, Gallup polls still show a difference of 8 percentage points as late as 2001 (Pastore & Maguire, 2002:150). When one considers that these surveys have shown an overall drop in HGO (Pastore & Maguire, 2001:148) there is very little drop in the proportional difference in ownership between the South and other regions. Finally, although the large gap in levels of gun ownership between the South and other parts of the U.S. may appear to be narrowing in recent years, its value as a standard by which other areas may be compared and assessed remains. The perceived difference between the South and the rest of the U.S. is perhaps most evident in the body of literature attempting to draw a connection between firearms ownership, Southern subculture, and violent behavior. Southern Subculture of Violence A short review of the literature addressing the connection between guns, the South, and violence, tenuous though it may be, is certainly informative. This examination provides further insight into the status of this region as a progenitor and current leader of gun ownership and gun culture in the U.S. One of the earliest attempts to offer a theory of a Southern subculture and its relation to violence (and, indirectly, gun ownership) was offered by Hackney (1969) from an historical

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perspective. Hackney (1969) provides a hypothesis explaining high rates of homicide in the southern U.S as an inherent part of its culture by comparing the ratio of suicides to homicides, and regressing dummy variables measuring “southerness” and a few structural variables such as percent urban, urbanization rate, and poverty on suicide rates, homicide rates, and the ratio of suicides to homicides (Hackney, 1969:911-12, 914). His findings note an effect of structural variables on these rates, but also significant effects for region when controlling for these structural variables, leading him to conclude that high rates of homicide in southern states are due to some function of Southern subculture and cultural transmission of violence. When ascribing explanations for increased rates of violence to those who may have been raised in the violent subculture of the South, Hackney raises a point that has led to a strong interrelationship between this line of research and that of private gun ownership in the U.S. Hackney raised the question of whether or not ready access to firearms through increased rates of legal ownership make murder more likely in the South than in other parts of the country, and found such a connection (1969:919). Since this observation, research has often focused on the possible connection between violence, “southerness”, and firearms ownership. Gastil (1971) offered a similar test of the Southern subculture of violence with comparable results. In this case, Gastil performs a test very similar to Hackney’s, but adds a few additional structural variables to control for access to healthcare, while assigning numerical values to individual states to give each a categorical score for “southerness” (Gastil, 1971:419). Again, the results are similar to Hackney’s, and the author concludes that, with a lack of explanatory power on the part of the structural variables, some type of unobserved cultural effect specific to the South must be the cause of increased homicide rates. Finally, and also quite like Hackney, Gastil mentions the possibility of exposure to firearms and its potential relationship to homicide rates, but does not allow for this potentially confounding variable in his subsequent analyses (Gastil, 1971:418). The next major contribution in this area was made by Loftin and Hill (1974), in which they replicate tests for both the Gastil and Hackney hypotheses finding that, with more accurate measures of the same structural variables, the cultural explanation for increased violence becomes statistically insignificant (Loftin & Hill, 1974:722). Furthermore, they point out the conceptualization of culture by both

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Gastil and Hackney is tautological in nature. That is, one cannot measure the prospect of cultural differences by region simply by including a measure of the region itself. In short, state borders are not sufficient measures of culture, and imprecise theoretical construction and conceptualization will always yield untestable hypotheses (Loftin & Hill, 1974:722, 723). This early work prompted a number of studies attempting to describe the relationship between Southern subculture of violence (if it actually exists), firearm ownership, and interpersonal violence. O’Conner and Lizotte (1978) were the first to attempt this by testing the relationship between Southern subculture and gun ownership; specifically, the indirect effect of Southern subculture on violence mediated by personal handgun ownership. Using 1973 and 1974 GSS data, the authors estimated logistic regressions on handgun ownership finding that there was no effect of handgun ownership and socialization in southern states (O’Conner & Lizotte, 1978:426-427). There are, however, significant effects of socialization in rural areas and income on handgun ownership (O’Conner & Lizotte, 1978:427). Nonetheless, this does not address the quandary of gun ownership in general and it’s potential relationship with the South nor does it disentangle the possible connections to a Southern subcultural influence. Some support was given to the hypothesis of a cultural influence on gun ownership by Young (1986). In this study, subsamples of the 1983 GSS were used to estimate the effect of cultural influence on white, female gun ownership, and the difference in this influence between female and male gun owners. Young posits that women in the South will be motivated by cultural influences to become gun owners, and women not in the South will be motivated mainly by fear of crime to become gun owners (Young, 1986:173). The author finds that women in the South are relatively unaffected by situational factors that predict gun ownership while women in the non-South tend to be motivated by extreme fear of crime (Young, 1986: 177-178). There are a number of difficulties with the test of this hypothesis, however. Perhaps the foremost limitation is a methodological impediment concerning the interpretation of the two subsamples used for comparison. Young compares two subsamples; one for women that were not socialized in the South and one for women that were raised in the South (1986:177). The support for his hypothesis rests on the comparison of separate logistic regression equations estimated for each of the sub-sets. Unfortunately, he does not offer the necessary test to

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determine if the coefficients from each of the equations are significantly different from one another (Cohen, 1983). Dixon and Lizotte (1987) provide the next test of the southern subculture hypothesis that includes a test for direct and indirect effects of gun ownership and Southern culture on violence. Perhaps more importantly, this is the first test of these hypotheses that includes a rational conceptualization of violent subculture (Dixon & Lizotte, 1987:388-389). By using GSS questions regarding approval of the use of violence, the authors were able to construct factors representing approval for both aggressive and defensive violence (Dixon & Lizotte, 1987: 391, 392-393). By using these factors there was a separation of region and subcultural violence, by which the relationship between the two could be tested. In their analysis, although there is an effect of region on ownership, there is no direct or indirect effect of aggressive violence on gun ownership (Dixon & Lizotte, 1987: 399). There is, nonetheless, some effect of approval of defensive violence mitigating the direct influence of region on gun ownership. This theme was used by Ellison (1991) to further explore the relationship between subcultural violence, region, and gun ownership. In this case, Ellison (1991) argues that overzealous approval of defensive violence separates the South from other regions of the U.S., and that this difference is indicative of a culture of violence (268). In an attempt to explain high levels of Southern firearm ownership Ellison (1991) also explores four dimensions of southern subculture: subculture of violence, racial prejudice, ideological conservatism, and sporting gun subculture (268-270). As do many of his predecessors, Ellison utilizes the GSS data from the 1984, 1987, and 1999 surveys (Ellison, 1991:271). While the author sufficiently tests each of these hypotheses, treating the data as if they were cross-sectional, he finds little evidence predicting gun ownership by region. While defensive violence is related to the South, it is a poor predictor of both overall firearms ownership and handgun ownership (Ellison, 1991: 279). Similarly, prejudice on the part of white Southerners was a predictor of increased gun ownership, but this relationship was significantly weakened when controlling for sporting subculture (Ellison, 1991: 279). Political ideology (conservatism) is positively related to gun ownership, but not related to region (Ellison, 1991: 280). Finally, sporting subculture and firearms ownership are strongly related, as one would expect, but neither is related to region at all (Ellison, 1991: 281). The strongest predictors of gun ownership found in these equations are

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rural socialization and religion, far outstripping other estimates (Ellison, 1991:276-277). Setting aside the argument that voicing approval of defensive violence on a survey is indicative of a subculture of violence, the author finds little support for any of the hypotheses posed in this study, however, the relationship he finds between political conservatism and gun ownership has implications for later work. Testing relationships between region of socialization and political opinions pertaining to issues of gun control constitutes the most recent direct contribution to this literature.25 Brennan, Lizotte, and McDowall (1993) studied the effect of region on attitudes regarding gun control legislation. Using data from a 1975 Decision Making Information, Inc. (DMI) survey commissioned by the National Rifle Association 26 (NRA), they test the proposition that Southerners will be more resistant to restrictive gun control (294295). In this study, Southern socialization and prevalence of shotgun ownership are taken into consideration to explain many of the respondents’ attitudes. While there is much less overall support for the most restrictive types of gun control (i.e. a ban on all handguns), the South and West are far less likely than the North and Midwest to support such a ban, and there is no regional difference in support for registration of all firearms (Brennan et al., 1993: 302-303). Overall, however, Southerners were more likely to be opposed to all types of restrictive gun control than respondents in other regions, and Southern shotgun 27 owners were more likely to oppose registration (Brennan et al., 1993:303). Finally, as one might expect, one of the strongest predictors of opposition for all types of restrictive gun ownership is rural residence (Brennan et al., 1993:304).

25

There have been other, more recent tests concerning subcultural violence in the South;

however these tend not to focus on the relationship between firearm ownership and region (see Nisbett and Cohen, 1996). 26

While questions have been raised regarding the reliability of data associated with the

NRA, the authors explain that the data converge with similar survey data commissioned by both neutral and antigun organizations, and that the particular data used in this study are valid and reliable (Brennan et al. 1993:295). 27

This is of particular interest because shotguns are a type of firearm that are likely to be

owned in the Southern U.S., highly related to sporting use, and seem to be related to some part of a cultural identity in this particular region (Brennan et al., 1993:292-293).

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Trends in American Gun Ownership

In sum, there seems to be a strong relationship between region of socialization, current region of residence, and legal firearm ownership. Much of this is due to the socialization of children into a sporting gun culture in the South, although some small part may be due to a subculture that encourages and approves of both firearms ownership and defensive violence among its members that may be due to the rural nature of much of the South. While there is little difference in the proportion of ownership that can be attributed to each region, there does appear to be some narrowing of the gap between the South, West, and Midwest as part of an overall reduction in household gun ownership in the U.S. and possibly considerable reductions in southern HGO. The convergence of these varied assessments of the relationships between region, socialization, and gun ownership are valuable. Predictions involving region, particularly the South or West, can be made with relative confidence when designing and interpreting models to test trends in gun ownership, especially where these trends may be tempered or exacerbated by regional considerations. Demographic Predictors of Ownership While it is necessary to treat the body of research concerning region in the U.S. as a separate topic due to the relatively complex explanations that have been offered for the prevalence of gun ownership in the South, most other strongly related demographic characteristics of gun owners are almost simplistic in their parsimony and convergence between numerous studies. Most social scientists fully accept, for instance, that the average gun owners are white, Protestant, middle class males who were socialized in rural areas (Newton & Zimring, 1969; Bordua & Lizotte, 1979:171; Lizotte & Bordua, 1980:236-239; Lizotte et al, 1981:502; Wright et al., 1983:122; Young, Loftin & McDowall, 1987:55; Kleck, 1997:70). Interestingly, these relationships also tend to hold true even when types of guns are taken into account or certain demographics are focused upon as a subsample (Kleck, 1979:902; Williams & McGrath, 1978:56). Moreover, most of these surveys, studies and reports center around the abovementioned characteristics, but with different sampling and survey design. Although these different research designs often yield similar information, each warrants some discussion.

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Gallup and Harris Polls The earliest surveys to determine the characteristics of gun owners were the Gallup Poll and the Harris Poll (Erskine, 1972). These polls reveal the basis for most current estimation of gun owner characteristics. The 1959 Gallup Poll was the first to ask any questions concerning household gun ownership (HGO), followed by the Harris Poll in 1968 (Erskine, 1972:457). Despite different question wording,28 both polls included questions regarding ownership, type of gun owned, region, and size of community, and both surveys had very similar findings. For example, as mentioned earlier, the South had by far the highest levels of household gun ownership (Gallup, 1972:1626-1627). In addition to the preponderance of HGO in the South, these surveys also noted that non-metropolitan areas had by far the highest percentage of respondents reporting HGO (Erskine, 1972:457). For instance, Gallup Poll respondents in the South reported 67% HGO with the next highest reporting area at 53%, but respondents reported 81% HGO on farms, 68% in town under 2,500, and 52% in towns from 2,500 to 49,999 (Erskine, 1972:457; Gallup, 1972:1627). While these reports were bivariate in nature, they did provide the first scientific examination of HGO in America. Both the Gallup and Harris Polls also have nearly identical sampling techniques and designs. In their inceptions both of these surveys relied upon multistage cluster sampling to choose households. This selection process led to face-to-face interviews in each respondent’s home, with the interviewee chosen through a variety of random selections methods intended to provide the agencies with nationally representative samples (Newport, Saad & Moore, 1997; Pastore & Maguire, 2002:571). Both Harris and Gallup surveys, however changed to the more cost effective method of random digit

28

Gallup seemed to be more concerned with HGO asking, “Do you have a gun in your

home?” on early surveys and, “Do you happen to have in your home any guns or revolvers?” Harris, however asked, “Do you own a firearm?” which could intonate personal as opposed to household gun ownership (Erskine, 1972:456,457).

Many

questions concerning gun ownership are also confusing to gun owners. For instance, the second Gallup question asks about guns and revolvers as if they are two different things when in fact revolvers are always guns, but guns are not always revolvers. For a more complete review of these issues, see Tonso, 1983.

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Trends in American Gun Ownership

dialing for telephonic interviews in 1978 and 1986, respectively (Newport et al, 1997; Pastore & Maguire, 2002:571). Gallup and Harris both continue to collect detailed data on HGO and the characteristics of gun owners. Most recent polls continue to show comparable patterns of ownership. For example, 2001 Gallup and Harris data reveal that most gun owners are still male, white, rural, Southern, politically conservative, and have an income over $30,000 per year 29 (Pastore & Maguire, 2002: 147,149). Both of these surveys have increased the number and type of questions that they ask about gun ownership and both surveys report very similar findings.30 General Social Surveys Perhaps the most prolific and informative effort to address social issues, demography, and public opinion that has thus far been undertaken is the General Social Survey (GSS) as administered by the National Opinion Research Center (NORC). Started in 1972, the GSS has been administered on more than 24 occasions with well over 40,000 completed interviews (Davis & Smith, 2003). Each of these interviews has included a number of questions regarding gun ownership, public opinion regarding guns and gun control issues, as well as a wealth of demographic data for each of the respondents. In these surveys, there has been a general trend over time toward less household gun ownership in the U.S. Whereas in 1973, 47% of households reported HGO on the survey this rate has fallen to as low as 32% in 2000 (author’s calculation of GSS data). Although, these assessments are, like any survey, subject to a variety of reporting errors, GSS estimates have consistently fallen 3 to 6 percentage points under other surveys administered in the same time period, a difference too large to be entirely due to random error (Kleck, 1997:65). Additionally, there also appears to be underreporting by women as 29

Interestingly, these characteristics, as a proportion of total gun owners, have remained

remarkably unchanged since the earliest surveys. For detailed information for previous years of Gallup data see http://www.gallup.com or previous editions of the Sourcebook of Criminal Justice Statistics. 30

In fact, where the categories defined by the polling agencies overlap, every category of

gun owners in the 2001 reports for these agencies are within random sampling error of one another. For data, sample size, and sampling error size, see Pastore and Maguire, 2002: 147,149,571.

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evidenced by a gender gap in reporting HGO by married women as high as 9% below the reporting rates of married men (Kleck, 1997:100; Ludwig et al., 1998; Legault, forthcoming). Nonetheless, the GSS was and continues to be the richest source for data addressing gun owners and HGO. Measures of HGO reported by the GSS are, at least proportionately, also very similar to those reported by polls such as Gallup and Harris, even if they are usually lower. Over time, the general characteristics of respondents reporting a gun in their household have remained stable. Throughout any of the years that the survey has been conducted gun owners remain chiefly rural, Southern, Protestant, Republican, middle-aged, white, and male (Pastore & Maguire, 2001:148). This observation lends credence to the necessity of the replication of the survey over time as no other source can provide us with both these types of observations and the confidence that the survey questions, sampling methods, and availability of data remain unchanged and can therefore be compared over time. Herein lays the primary strength of design and benefit of the GSS. The GSS has also been the data source for a number of the aforementioned studies on region and ownership (O’Conner & Lizotte, 1978; Young, 1986; Dixon & Lizotte, 1987; Ellison, 1991). In addition to supplying information regarding a potential subculture of violence, each of these studies also confirm the primary predictors of gun ownership using more complex analysis for a variety of time periods (O’Conner & Lizotte, 1978; Young, 1986; Dixon & Lizotte, 1987; Ellison, 1991). More recently, the GSS data have been utilized to test the hypothesis that there has been a sharp increase in personal gun ownership by women in the U.S. (Smith & Smith, 1995). In this study the authors examine a variety of sources that indicate a substantial increase of gun ownership among women, and compare the findings of these sources to GSS data from 1980 through 1994. In this analysis, they determine that there has been no increase in female gun ownership overall, and no increase in proportion to male ownership (Smith & Smith, 1995:143,147). This study, perhaps better than most, illustrates the strength of valid and reliable replication over time that best characterizes the GSS. Similarly, two studies have used the GSS to illustrate the gender disparity between men and women when reporting HGO by pointing out that husbands report, on average, a 9% higher rate of HGO than wives on face-to-face surveys (Kleck, 1997:100; Ludwig et al, 1998:

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Trends in American Gun Ownership

1717). Of course, this is not possible. That is, husbands and wives should report at the same levels due to the nature of the survey. Furthermore, these analyses give no indication of whether the disparity is related to race, parenthood, region, or other demographic factors commonly thought to be related to HGO. Of course, this could also be due to some systematic difference in the selection of the household or the respondent in the household. Fortunately, the design of the GSS precludes this type of error. Households are chosen with random selection and the individual respondents are chosen from a complete list of all persons who live in that household (Davis & Smith, 1992:42). Although these studies rely on simpler, bivariate analysis they have opened yet another area for further research through the inherent usefulness of the GSS. GSS data are collected through a multistage, stratified probability sampling technique to acquire subjects (Davis & Smith, 1992:31). Initially, a modified probability design was used, but additional funding allowed NORC to switch to a full probability design starting in 1975 (Davis & Smith, 1992:32). In order to test the potential effects of this new design, the 1975 and 1976 surveys incorporated a transitional design, in which half of the respondents were chosen using the new sampling technique, and half using the old technique. Thus, researchers are able to effectively test findings from earlier and later samples and assign differences over time to either empirical shifts in survey response or changes in sampling methods (Davis & Smith, 1992:32). The GSS also enjoys an additional advantage of its sampling design when household level variables are being studied.31 The full probability design of the sample started in 1975 gives each household an equal chance of being included in the study (Davis & Smith, 1992:42). Therefore, for any household level variable being studied the design of the GSS is “self-weighting,” that is to say that there will be no difference between the statistical confidence one may place in findings from the GSS and a simple random sample (Davis & Smith;

31

In this case, household level variable refers to any question that asks respondents to

answer based on information concerning their entire household and not the individual respondent interviewed.

Some examples of household level variables are home

ownership, household income, or household gun ownership (HGO).

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1992:43). Thus, it is an excellent source for data concerning household firearm ownership in the U.S., and has been used often.32 The benefit of replication both in sampling design and question construction, coupled with the sheer volume of associated data that are available for analysis, imbues the GSS with many advantages over its counterparts. The reports of the survey, however, are still similar to those of other surveys giving us further confidence in our understanding of gun owners’ demographic characteristics at a national level. Recent Surveys Recently, there have been three major national surveys that have collected information focused narrowly on issues surrounding firearms ownership, safety, storage, and public opinion regarding guns and gun control. The National Gun Policy Surveys (NGPS) have been conducted 5 times between 1996 and 2001 through a collaboration of Johns Hopkins School of Public Health and NORC (Smith, 2001). The second survey, the National Survey on Private Ownership and Use of Firearms (NSPOF), was conducted by Cook & Ludwig under the auspices of the Police Foundation (Cook & Ludwig, 1997). Also, the Survey of Gun Owners in the United States, (SGOUS) designed and led by Hemenway & Azrael (2000) examined very similar issues with a very similar sample. Finally, the Behavioral Risk Factor Surveillance System (BRFSS) is a state-based telephone survey conducted by the CDC and is intended to monitor risk factors for a number of health related matters that could result in disease or injury (CDC, 2005) Each of the NGPS’ have reported similar findings concerning who owns guns in America, and these figures are, again, similar to other reports of personal and household gun ownership. For the 2001 NGPS reports that gun ownership is most common among respondents who are male, live in rural areas, married, middle-aged, conservative, and white (Smith, 2001:6). Also, gun ownership tends to increase with increases in income up to $80,000 per year and does not seem to be related to education (Smith, 2001:6). The NSPOF and SGOUS, while each conducted on one occasion, also yield similar results. Cook and Ludwig (1997) report that gun 32

e.g. O’Conner & Lizotte, 1978; Wright et al., 1983; Young, 1986; Dixon & Lizotte,

1987; Ellison, 1991; Kleck, 1997.

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Trends in American Gun Ownership

ownership, “was highest among middle-aged, college-educated people of rural small-town America. Whites were substantially more likely to own guns than blacks, and blacks more likely than Hispanics.” (2). It is also important to note also that the strongest predictor of ownership was whether or not the respondent’s parent(s) owned guns; that is, socialization into gun culture during youth (Cook & Ludwig, 1997:2). Similarly, Hemenway and Azrael’s survey sampled over 1900 respondents and found again similar demographic results (2000). Each of these surveys employed random digit dialing telephone interviews consisting of a probability sample of adults in the continental U.S. with telephones (Cook & Ludwig, 1997:4; Hemenway & Azrael, 2000; Smith, 2001:2). There are, nonetheless, differences between the surveys that require mention. First, the NSPOF and SGOUS data are from samples of more than 1,900 respondents (Cook & Ludwig, 1997; Hemenway & Azrael, 2000). This is much larger than of any of the 5 NGPS’, each of which calculated their findings from a sample of approximately 1,200 (Smith, 2001:2). This increase in size, in random samples should reduce sampling error by about 1% (Newport et al., 1997). In a sample of this size, and with such a prevalent behavior being measured, this difference matters little. The second issue, however, has implications for research. One of the most important benefits of the NGP survey is replication. While the NSPOF and SGOUS have trivially less error, the NGPS data can be considered in context, and where trends can be observed and tested, much like the GSS. In any case, each of these surveys yield strikingly similar results. Furthermore, these results mirror those of each of the other surveys discussed earlier. The BRFSS is perhaps the most recent scientific survey to provide information regarding gun ownership and the behavior of gun owners. The survey has been conducted yearly in all 54 states and territories of the U.S. by their respective state departments of health since 1984. However, questions regarding gun ownership have not been in every survey (CDC, 2002). Perhaps the greatest advantage of this survey is its sheer size. This survey has not been used extensively to study specific socio-demographic characteristics of owners but it was not designed to be used in such a manner. Even in the most recent literature discussing the public health perspective of gun use and gun ownership in the U.S., studies such as the GSS, NGPS and NSPOF are cited as authoritative sources for detailed social information in regard to gun ownership (Hemenway, 2004:6). In any case, the BRFSS, and

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other public health surveys that include some questions about gun ownership could become a valuable resource in the future due to their advanced research designs and large sample size. Specialized Studies Addressing Firearms Ownership There are three additional studies that specifically address legal firearms ownership and require mention primarily because they were the first to address this issue from an academic standpoint. Also, they were the first to bring the sophistication and weight of multivariate, quantitative study to bear on the issue. While there were a number of surveys that acquired information prior to these studies, there were no attempts to document and understand the topic based on social theory and using modern scientific techniques to explain firearms ownership in the U.S. Wright and Marston (1975) were among the earliest to bring the power of the GSS data to bear on defining gun owners demographically. Their study used many of the same variables used in this work from one year of the GSS. They were perhaps the first to see the wealth of information available in these data to understand HGO and personal gun ownership. While most of the information they report are merely correlations, one must keep in mind that it was among the first studies of is kind and helped to define the demographic characteristics that are still associated with gun ownership 30 years later. Bordua and Lizotte (1979) used county level data from Illinois to construct a path analysis model explaining legal firearm ownership (155). In this case, the authors were able to use the proportion of county residents who possessed Illinois Firearm Owner Identification Cards (FOIC)33 with demographic data for each county including population ages, racial makeup of the county, female-headed households, population density, number of woodland acres in the county, crimes rates, etc. (Bordua & Lizotte, 1979:156). This model and these data allowed the authors to estimate direct and indirect effects for each of the demographic variables on gun ownership. 33

These cards were used as a proxy for rates of firearms ownership as they are necessary

to legally acquire or possess a firearm in Illinois. While these cards indicate firearms ownership, they do not give any information on the quantity or type of firearms owned (Bordua & Lizotte, 1979:155).

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Trends in American Gun Ownership

The initial important finding of this study is a strong negative correlation between legal firearms ownership for males and minors and crime (Bordua & Lizotte, 1979:159). Female ownership, however, showed a non-linear relationship with crime in that very low levels of crime predict high levels of ownership; however above a certain level of increase in county crime rates, women’s ownership rates have a strong positive relationship with crime (Bordua & Lizotte, 1979:160,163). The authors interpret this relationship as a defensive reaction to crime by women. In the end, though, the vast majority of social determinants of gun ownership were reflections of earlier studies. Counties with high rates of gun ownership were rural, with a high population of hunters who were socialized into the gun/sporting culture at a young age (Bordua & Lizotte, 1979:171-172). The two major findings that would drive later research in this area were the negative relationship between crime and gun ownership and the curvilinear relationship between crime and female gun ownership. The next study to address these issues was also conducted by Lizotte & Bordua (1980). In this case, the authors used data collected in a telephone survey of Illinois residents specifically designed to address legal firearms ownership to build on their earlier work by attempting to separate and describe the subcultural contexts of ownership for sport or protection (Lizotte & Bordua, 1980:230-233). In this case, sport ownership culture refers to those who were socialized into firearms ownership at an early age through parental influence and engagement in sporting activities with firearms34 (Lizotte & Bordua, 1980:232). The authors also describe another subculture within gun ownership, that of owning guns for protection which could be related to subcultures of violence, trust in the criminal justice system, local crime rates, or a host of other cultural or situational factors (Lizotte & Bordua, 1980:233). In their final analysis, though, the authors found that there were some similarities between each typology of gun ownership (Lizotte & Bordua, 1980:241-242; Lizotte et al, 1981:502). In both cases, respondents experienced socialization into a sporting gun culture, even when they reported protection as the primary reason for owning a gun

34

Sporting use of firearms varies; therefore, a variety of activities that provide contact

and interaction of its members may be included in this category such as hunting, membership in shooting clubs, target shooting, etc.

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(Lizotte et al, 1981:502). As in their earlier work, though, the authors found that most of the traditional predictors of gun culture held true with the exception of women who are more likely to own guns for protection than for sport (Lizotte & Bordua, 1980:241). Summary With the exception of some disagreement on the matters of region, female ownership, and trends in HGO rates, modern information regarding legal gun ownership in the U.S. is relatively tedious in its agreement. Through a variety of samples, research designs, and methodologies, from simple to complex, there is a resounding consensus in scientific literature on the topic. Although the conformity of most of the research may seem uneventful in its predictability it is nonetheless invaluable to our understanding of gun ownership patterns in America. Because of the attention given to this topic we can, with a level of confidence that is impressive for most social science, say that gun ownership is widespread in the U.S. with gun owners tending to be male, rural, white, married, and Protestant with higher than average income. Education levels make little difference in determining gun ownership, whereas residence, defined in terms of current region or size of place, has less of an effect on ownership than the area of socialization. Finally, while there is little evidence of the existence of a subculture of violence and even less evidence of a direct or exclusive association with the Southeastern U.S., there does appear to be a higher rate of HGO in the South. As for the question of a reporting gap in HGO between women and men, current research only informs us of its existence. As yet, there is little scientific evidence to support any explanation that has thus far been offered concerning the gap other than its possible growth over time (Kleck, 1997:100; Ludwig et al, 1998). Similarly, evidence of a vast reduction of HGO in the U.S. has not yet been systematically evaluated in terms of potential causes or explanations. Nor has the validity of this drop in ownership levels been examined in any exhaustive way. However, with the existence of a gender gap in reporting, the steady growth of the nation’s gun stock in excess of population growth, and a steady rate of personal gun ownership over time, this topic certainly calls for further examination (Wright et al., 1983; Kleck, 1997).

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CONCLUSION The profusion of private firearms ownership in the United States is unique in the world (Kopel, 1992:13-15; Wright, 1995:63; Hemenway, 2004:5). Although there is a wealth of information available, many studies lack a multifaceted approach. Additionally, many authors miss valuable information that would inform their work and broaden the theories and explanations regarding this important area of research. In general terms, we still define gun culture by the demographic characteristics of its members, and perhaps for good reason. According to most descriptive accounts of gun owners in the U.S., we know that members of the gun culture tend to follow very specific demographic trends (Bordua & Lizotte, 1979:171; Wright et al., 1983:122; Kleck, 1997:70). Gun ownership tends to be more heavily concentrated in the South and South-Western regions of the country (Wright et al., 1983:122; Kleck, 1997:70), and gun owners were often socialized to become part of the gun culture by their parents who owned guns (Lizotte & Bordua, 1980:236-239; Lizotte et al, 1981:502; Wright et al., 1983:122). Although national surveys such as Gallup, the General Social Surveys (GSS), the National Gun Policy Surveys (NGPS), and the National Study of the Private Ownership of Firearms (NSPOF) have provided much of our knowledge about legal gun owners today, comparing them to early accounts of gun ownership it is similar to viewing two sides of the same coin. Gun ownership in the past and present tends to uncannily similar. It seems rather apparent that private gun ownership is now and has been one of the most important defining characteristics of American culture, differentiating us from most of the rest of the developed world. Understanding these connections has the added benefit of providing a roadmap for researchers to follow when attempting to build on past scientific research and endeavor to employ new techniques to better explain these relationships or better understand precise interrelations between predictors and reporting behavior. More specifically, a comprehensive understanding of how these demographic characteristics operate to predict gun ownership will help to guide this research in its attempt to test a variety of theories explaining a reduction in HGO.

CHAPTER 4

Explaining Trends in Gun Ownership

THEORY There are four major theoretical explanations for the apparent reduction of HGO in recent years that will be addressed here in some detail. Additionally, there is a fifth explanation that is often overlooked; the passage of time could provide evidence to support an actual reduction in household ownership among the demographic that has traditionally been referred to as the “gun culture.” Although each of these explanations is relatively simple, as mentioned earlier, they are as yet untested. When considering the gender gap in reporting, the reduction of household size, the increase in the percentage of female-headed households, and the urbanization of America as individual explanations, it is important to remember that any combination of these hypotheses or any of the hypotheses individually have the potential to describe the recent reduction in HGO. As each of these hypotheses is discussed, the past work in these areas as well as the necessary theoretical underpinnings will be described in greater detail. The Gender Gap The gender gap in reporting HGO, serving as an explanation for underreporting of gun ownership, was first noted by Kleck (1997:67). This analysis provides some initial support for the assertion that HGO misreporting has somehow grown since 1987, and poses the possibility that there has been some change in gun owners’ feelings of legitimacy (Kleck, 1997:67). This point is illustrated by calculating and comparing reported HGO percentages for married men and women 61

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Trends in American Gun Ownership

from the 1973-1993 GSS (Kleck, 1997:100). In this relatively simple comparison Kleck notes a two to three percentage point gap in HGO reporting between married men and women prior to 1988 and an increase to an average 7 percentage points thereafter (1997:67). The author goes on to hypothesize that the increased discussions of highly restrictive federal gun control legislation in the U.S. during this period would function as a motivation for private citizens to consider gun ownership as less legitimate, thereby motivating such citizens to conceal their own private gun ownership (Kleck, 1997:67). Similar logic was applied one year later by Ludwig and his colleagues to explain the same findings (Ludwig et al., 1998). Additionally, women may underreport because they are not the actual owner of the firearm and they no not feel it within their purview to “inform” on the gun owner in the house who is more likely the male of the household (Kleck, 1997:67). If this is the case, one should expect that, unlike the social undesirability hypothesis, reporting discrepancies would be higher among respondents who are from typical areas where gun ownership is normative. As such, it is not the social undesirability associated with gun ownership, but a protective mechanism in which one is acting to protect an approved, socially acceptable behavior. The work by Ludwig et al. (1998) pursues a line of logic similar to Kleck’s, and tests the relationship between the gender gap in reporting HGO in a similar fashion. Further, they make similar observations regarding the factors inherent to the design of the survey that could be relevant to a reporting gap between men and women. The authors hypothesize that due to the nature of social undesirability bias, false positives in reporting HGO should be extremely rare in relation to false negatives; therefore, the larger of the estimates for each comparison between married men and women should be the most accurate (Ludwig et al., 1998:1715). This allows us to predict a direction in the gender disparity in HGO reporting. When controlling for appropriate demographic variables, one should expect that the higher of the two reporting estimates between married men and women should be accurate. Therefore, if the simple percentages of reporting by gender provided by Ludwig et al. (1998) are any indication, the level of HGO reported by married males is more representative of the actual HGO in married households than those reported by married women or a combination of all married respondents.

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Ludwig et al. also provide an explanation for the difference in reporting HGO between married men and women. Similar to Kleck (1997), although somewhat more complete in their proposition, they offer the hypothesis that underreporting of HGO by married women is a function of social undesirability bias (Ludwig et al., 1998:1717). This also speaks to Kleck’s observation that public awareness of problems associated with gun ownership could reduce the feelings of legitimacy of private gun ownership (1997:67). Therefore, the concept of social undesirability bias deserves some examination to understand how it might operate in regard to reporting HGO, and why it might be more pronounced for women than men. Most recently, the gender gap in reporting gun ownership was examined by Wyant & Taylor (2007). In this case, the authors analyzed cross-sectional data from both the NSPOF and the SGOUS, comparing the gender gap among a number of other research questions with the gender gap in gun reporting. In this particular case the authors report gaps in reporting firearm collection size by gender when data subsamples were selected for only households that report gun ownership.35 Social Undesirability Bias When asking a respondent to self-report socially undesirable behavior, face-to-face interviews such as the GSS tend to have less success at getting to the truth than self-administered questionnaires (SAQ) (Aquilino, 1994). Additionally, the problem of getting to the truth of socially sensitive topics may be especially acute for socially marginalized36 respondents (Aquilino, 1994:234). Further, women, 35

These gender gaps appeared in opposite directions in each of the two surveys and are

specific to the number of guns in the household. The authors split the data by using a zero-inflated negative binomial model. This provides separate results for the no-gun (zero) group and the group that reported owning one or more guns. Unfortunately, the household sample was not censored for married respondents only therefore limiting conclusions that could be drawn regarding misreporting. 36

There is some controversy regarding the findings of studies attempting to test social

undesirability bias. These studies are all concerned with illegal behavior (drug use), and none examine legal behavior (i.e. gun ownership). Additionally, comprehensive reviews of this literature find it lacking in support (Harrison & Hughes, 1997; National Research Council, 2001; 2003). Nonetheless, this hypothesis has enjoyed some popularity in

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rather than just racial or ethnic minorities, may very well fall into this category (Stewart & McDermott, 2004:528, 529). The differences in surveys concerning guns in this regard are noted by Kleck: “[T]he General Social Surveys… are among the few national surveys done face to face in the respondents’ homes, a format where R’s necessarily are identifiable. Since 1990, the GSS has yielded gun prevalence estimates three to 6 percentage points lower than other surveys conduced at the same time, a difference that cannot be entirely attributed to sampling error.” (Kleck, 1997:65) For differences in attitudes about firearms by gender, one may also look to the results of the 1997-98 National Gun Policy Survey (NGPS), where 10% of households reporting gun ownership also report “a time in your household when there was a disagreement about guns in the house.” (Smith, 1999:18). Of these disputes, 92% were reports of women who were opposed to having the gun in the house or women who wanted greater safety taken with the gun in the house (Smith, 1999:18). Perhaps, then, men tell their spouses that they have disposed of the firearm when actually they have not. The 1998 NGPS study provides similar information in that a large majority of women categorically support restriction of gun ownership (Smith & Martos, 1999:53-56). Nevertheless, these studies report examination of attitudes by neither race, political orientation, nor by other predictors of gun ownership or gun culture. Gender may be one of the most important demographic variables influencing reported gun ownership. Measuring the HGO reporting error for married women under the assumption that social desirability motivations will have a more pronounced effect on misreporting HGO seems justified. One might also expect that the error of reporting HGO will also be higher between females and males due to the differential and negative effects of survey communication on marginalized subgroups such as minorities or women (Aquilino, 1994:211-212). Sensitivity to perceived expectations of the interviewer or society in general could therefore influence the response of the interviewee.

literature examining survey response.

This popularity, combined with the lack of

empirical attention and the ability to test the hypothesis, is why it is included and tested here.

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65

Context Effects There may also be an influence on the interviewee response due to context effects yielded by question placement on the survey. For instance, gun ownership questions immediately follow questions concerning, “fear of walking alone at night” on the 2000 GSS questionnaire (NORC, 2000:31-32). This question placement could exert a biasing influence on the respondent (Rockwood & Sangster, 1997:119, 127). While this could have a bias on overall survey reporting, unless there were some differences in how respondents reacted to the question order by gender it should not have any influence on reporting differences between respondents in the survey because they are all asked the same questions in the same order.37 One could imagine that this might be true. However, this is not tested here in great part due to the lack of comparison samples that would be necessary to determine the influence context effects might have. Although there are a number of reasons mentioned by these authors for women to underreport gun ownership, it is equally likely that men could be overreporting household gun ownership. However, because one can expect patterns of reporting or not reporting HGO to vary based on the strength of the “gun culture” geographically and demographically, these patterns may offer some indication as to which gender is misreporting HGO. In this case, if women are underreporting, one would expect to find that there is less of a reporting discrepancy where gun culture is strongest, such as rural areas and southern states, conversely, if men are over reporting there would be higher discrepancies in these areas. Summary There are a number of potential reasons for women to underreport HGO on surveys. First, women may not know that there is a gun in the house, or may not consider some firearms as “real” guns. Second, women may have been lied to about the disposal of a gun by their husbands. Third, women may not report HGO because they feel it to be socially illegitimate due to social undesirability bias or they may not want to “inform” on the individual gun owner in the house. Fourth,

37

For more on known difficulties with survey estimates of guns and ownership, see

Kleck, 1991: Appendix 2 and Kleck, 1997:65.

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Trends in American Gun Ownership

groups who may fear or mistrust the government may be unwilling to report HGO. Lastly, these possibilities may be mitigated by membership in, or the influence of, a strong “gun culture,” such as those that exist in rural areas or the Southeast. Consequently, one should anticipate patterns of reporting HGO based on the strength of the “gun culture” geographically and demographically. We should expect to find that there is less of a reporting discrepancy between married men and women places where the gun culture is strongest, such as rural areas and southern states if women are underreporting (Bordua & Lizotte, 1979:171-72; Lizotte & Bordua, 1980:232; Dixon & Lizotte, 1987; Smith & Martos, 1999:7-9; Wright et al, 1983:104-06). The Urbanization of America The second potential explanation for the reduction of reported HGO on surveys in the U.S. implies that the population shift away from rural areas to urban areas accounts for the overall reduction of reported HGO in the U.S. (Cook & Ludwig, 1997:11). Essentially, this hypothesis relies on the seemingly reasonable argument that a demographic shift from areas with strong sporting gun cultures to areas without a modern tradition of legitimate gun ownership or use will account for the overall reporting change. On its face, the simple logic of this argument is appealing; however, when examined in detail it seems highly improbable. Although the increase of the urban population and the decrease of the rural population in the U. S. in recent years is somewhat axiomatic, it is interesting to note the magnitude of this population shift. According to the most recent census, there has been a steady shift in the U.S. population toward urban areas since the founding of the republic (U.S. Census, 2004:30). Of course, the early population shifts are due to a number of factors that may or may not have any relevance to the most recent years. Over the last 50 years of decennial census data urban populations in the U.S. have grown from 64% to 79% of the total U.S. population. Conversely, rural populations have decreased from 36% to 21% of the total U.S. population (U.S. Census, 2004a:30). Considering the scale of these population shifts, the urbanization hypothesis seems yet more appealing. If one were to consider only the household-level reports of gun ownership, and the associated reductions in reporting over the last 20 years, the urbanization hypothesis appears to be both attractive and

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67

parsimonious. However, when one considers that individual-level reports of gun ownership have remained mostly unchanged throughout this entire period, serious doubt is cast on this hypothesis. If urbanization in America were the explanation for reduced levels of gun ownership it should be reflected in individual reports of gun ownership, but individual reports of gun ownership have remained stable at about 29% (Kleck, 1997:98-99; Smith, 1998:9). A reduction in the proportion of rural population, HGO reporting, and equal reductions in individual gun ownership would point to the need for further evaluation of this hypothesis, yet these conditions do not exist. It is much more likely that explanations that are unrelated to individual ownership, such as household size or systematic reporting error, explain changes in reporting over time. Reduction in Household Size This hypothesis supposes that a reduction in the population of American households explains a reduction in HGO (Smith, 1998:9; Smith, 1999:13). This is a relatively simple, reasonable and logical hypothesis that relies on two different types of change in American household demographics to explain shifts in HGO trends. First, a reduction in the average household population would necessarily reduce the total number of persons that could own a gun and therefore the odds of HGO for that household. Likewise, a decrease in the number of generations living in the household could have the same dissipating effect on reporting HGO. The U.S. Census reports a steady reduction in persons per household from about 3.3 in the mid-1960’s to about 2.6 today (2004b). Similarly, a change in the number of generations currently living in the household could have some effect on reporting HGO. One expects that if grandparents, or any other adults, were living in the household in addition to a parent or parents, the odds of individual gun ownership and therefore HGO would increase. Conversely, if there are fewer adults in the household the likelihood of HGO would decrease. This would not only encompass multi-generational or extended households per se, but also single parent households as well. This premise is elegant in its simplicity and relatively easy to test because surveys such as the GSS report detailed household enumeration data that allows testing of the hypothesis with a measure of total household population in the sample. Therefore, changes in reporting levels that do not vary

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Trends in American Gun Ownership

between the years of the survey, combined with a singular effect of household populations in the survey overall, would indicate a real decrease in HGO. Increase in Female-Headed Households The final testable explanation that could be offered to explain some part of the reduction in HGO takes the increase in female-headed households into account. Similar to the reduction in household population hypothesis, it is easily testable with GSS data due to the inclusion of detailed household enumeration data. It is also simple in its attempt to explain reductions of HGO, although it does not imply reporting error. Instead it is a possible explanation that attempts to reconcile the reduction in HGO and the stability of personal gun ownership (PGO) in the GSS sample. It is easy to imagine that, since the percentage of female-headed households has more than doubled between 1970 and 199738 and women are less likely to be gun owners than men, this could explain an actual reduction in HGO and still account for the status quo of PGO. In any case, this is easily testable and is therefore included in the analyses. CONCLUSION Although there are five major theoretical explanations for the apparent reduction of HGO reporting, only four of them provide logical implications for an explanation of this reporting change. Although each of these explanations is relatively simple, they are as yet untested or at least not tested with sufficient rigor. The gender gap in reporting, denoting reporting error, as well as a reduction of household size or increase in female-headed households, as actual reductions of HGO over time, certainly warrant further examination. Also, there remains a possibility that HGO reporting has decreased within the demographics that have traditionally been considered parts of the “gun culture.” Testing these hypotheses, then, is both possible and necessary to understand the issue more completely while remembering that combinations of these hypotheses potentially explain recent reductions in HGO reporting. It is much less likely, though, that the urbanization of America could be responsible for any part of this trend as it appears

38

From 10% to 23% in 27 years (Bryson & Casper, 1998:5).

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to be logically inconsistent when one regards known survey measures of individual gun ownership. As we shall see, the data and methodologies for modeling and testing these hypotheses are available.

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CHAPTER 5

The General Social Surveys

INTRODUCTION TO THE DATA The GSS is a personal interview survey that has been conducted by the National Opinion Research Center (NORC) almost yearly since 1972. As stated by the principle investigators, “The mission of the GSS is to make timely, high quality, scientifically relevant data available to the social science research community.” (Davis & Smith, 1992:1). To date more than 43,000 individual survey interviews have been conducted in pursuit of this mission (Davis & Smith, 2003). The immense undertaking of numerous surveys conducted over so many years hints at the main strength of the GSS, replication. This characteristic alone makes the GSS particularly well suited to analysis of potential changes in HGO over time. In this particular case it will allow analysis of over 18,000 respondents who were asked questions regarding Household Gun Ownership from 1976 through 2000. Data for this study were drawn from 16 years of the 1976-2000 General Social Surveys (GSS).39 These years were chosen to eliminate survey years in which detailed household enumeration data were not available (pre-1976) and years in which questions on gun ownership were not asked (1978, 1983, & 1986). Also conspicuous in their absence are the 2002 and later survey data. These GSS years have been eliminated for two specific reasons. Firstly, the survey changed the method in which it assesses the respondent’s race from all earlier surveys in 2002. Secondly, there had been a change in interview mode.

39

Specifically, the survey years 1976, 77, 80, 82, 84, 85, 87, 88, 89, 90, 91, 93, 94, 96,

98, and 2000 are used. These years were chosen for the availability of rotating questions regarding gun ownership and precise household enumeration data.

71

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Trends in American Gun Ownership

The GSS began using computer aided survey technology in 2002, a change from all earlier face-to-face interviews (Davis & Smith, 2003). Because no methodological reports are yet available to determine what effect these changes may have on the validity of the survey when conducting time series analysis, it is wise to forego one additional year of data in the interest of the known benefits of replication and validity available in the earlier surveys. Table 1. Coding, Means, and Standard Deviations for Dependent Variables. Selected years 1976-2000 GSS Variable† HGO

Coding of Variable Does the R have a gun in the home? 0=No 1=Yes

Mean

Std Dev.

n

0.43

0.495

23,587

Pistol

Is it a handgun? 0=No 1=Yes

0.22

0.416

23,551

Rifle

Is it a rifle? 0=No 1=Yes

0.25

0.435

23,553

Shotgun

Is it a shotgun? 0=No 1=Yes

0.26

0.438

23,552

0.27

0.443

20,467

0.36

0.480

15,371

PGO Dwelown

Guns belong to R? 0=No 1=Yes Does R own or rent home? 0=Rent 1=Own

† Weighted by GSS weights for over-sample of African-Americans

The Variables40 Table 1 presents the coding of dependent variables used in this study; while Table 2 presents independent variables. These variables are from the 1976-2000 GSS and have been coded to represent typical measures

40

The variables in the equations are estimated without individual survey weights. With

the exception of weighting for minority over-samples, weighting is not necessary to reduce the possibility of errors due to design effects of the GSS. In this case, the variables of interest are household level variables, for which the GSS is “self-weighting” (Davis & Smith; 1992, 40-43). That is to say, there will be no difference between the statistical confidence one may place in findings from the GSS and a simple random sample (Davis & Smith; 1992, 43).

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of HGO and theoretical explanations of change in HGO reporting levels. This will provide a baseline for the comparison of differences between groups. Specific questions as used by the GSS for each variable and the response frequencies are reported in Appendix A. The reported n’s for these variables in Table 1 reflect the total number of respondents for these questions minus missing cases. Many of the equations will not benefit from the apparent size of the data set as reported in Table 1, however. Case deletion, due to the “split-ballot” design of the GSS, will significantly reduce the total sample used in many of the equations. In later years of the GSS, the sample is randomly split into thirds with some questions asked only on two of the three ballot questionnaires (Davis & Smith, 1992:22). Fortunately, this does not pose a problem in attaining accurate estimates because the subsamples receiving different ballots are randomly selected (Davis & Smith, 1992:20). The main dependent variable in the study, OWNGUN, was coded from the GSS so that the numeric values for “no gun in the household / gun in household” are 0 and 1 respectively.41 We can see in Table 1 that reported HGO is 43% for all years of the survey. Other dependent variables include PISTOL, RIFLE, and SHOTGUN. These variables provide detail regarding the type of firearm that is referred to in the OWNGUN question, and is only asked of respondents who report HGO. These are included to provide additional detail regarding the types of firearms, and whether these appear to make any difference in reporting behavior. The final variable detailing gun ownership is ROWNGUN and will be discussed as PGO. This question asks those respondents reporting HGO whether or not the firearm that they are reporting in the home belongs to them personally. This has been recoded to reflect personal gun owners as members of the entire survey and not only as members of the HGO group. This is the only dependent variable in the study that is an individual, as opposed to household, level question. Respondents who report that they personally own a gun are coded as 1 and those who report that they do not, or reported no HGO are coded as 0, and about 27% of GSS respondents report personal gun ownership. Finally, this also differs

41

Respondents who refused to answer, did not answer, or did not know were coded as

missing.

This represents about 1% of the sample and should be considered

inconsequential.

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Trends in American Gun Ownership

from the HGO variable in that it is only available after 1980 when it was added to the survey. The last variable reported in Table 1 is DWELOWN. This represents whether the respondents rent or own their home and is included as a confirmatory variable. By performing analyses similar to those estimated on the main dependent variables, we will be able to observe whether the misreporting among married couples on household-level variables is common among innocuous questions or not. If such an unobtrusive question produces a reporting discrepancy between men and women this would refute the social undesirability bias hypothesis and indicate that there may be an overall reporting difference between men and women on any survey question. If, however, no reporting difference between married men and women is detected here this would offer some limited support to the gender gap hypothesis because it would indicate that the difference is not due to gender alone. This variable is only available from 1985 onward. The independent variables are presented in Table 2. The first of these allows for the examination of only those respondents who are married or living as married and cohabitating at the time of the interview. Past studies have relied on the GSS variable denoting marital status for this information (Kleck, 1997; Ludwig et al, 1998); however this is not the best choice in this particular case. The GSS variable MARITAL does not specifically ask the respondent whether or not they are currently living with their spouse, nor does it include those respondents who are living as married couples but are not actually married at the time of the interview. Although it does allow a respondent to report his or her marital status as “separated” this does not include any form of specification and could be construed as a legal status that may or may not indicate cohabitation. This results in the loss of pertinent data and the introduction of possibly misleading information. For these reasons I have constructed the variable ALLCOHAB to reflect the actual living status of the respondent at the time of the interview. This variable includes married couples and those couples who are living as married, but only those who are cohabitating at the time of the GSS interview. ALLCOHAB is calculated from the Household Enumeration Variables in the GSS (Davis & Smith, 2003:1225-1274). These variables provide detailed information on up to 14 persons currently living in or visiting the respondent’s household including the exact relationships of these persons to the respondent. A condensed

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version of these variables (HHTYPE1) is provided by the GSS for most, but not all years, therefore this variable was manually recoded for the 2000 GSS data (Davis & Smith, 2003:1260). Syntax commands for performing these recodes in the SPSS computer program are provided in GSS Methodological Report Number 73, but required some alteration to work properly (Smith, 1992).42 Unfortunately, the Household Enumeration Variables are also not recoded into HHTYPE1 for GSS years prior to 1976, and there are insufficient data to calculate them manually. Consequently, these data have been censored from the analysis in the interest of the accuracy and detail afforded by the cohabitation variable. Only two categories are reflected by ALLCOHAB: 0=cohabitating as a couple and 1=not cohabitating as a couple. The presence of a current spouse or partner, or not, is of vital importance because of the potential differences between reporting behavior of spouses / partners. All possible detail regarding these potential differences are necessary to test the Gender Gap hypothesis. Additionally, these observations may lead to logical conclusions concerning reporting error and gender that further address this hypothesis. In any event, this variable is crucial in detecting the presence of misreporting between cohabitating couples who are married or living as married, and will be used to censor samples of GSS data to examine the members of this group separately from the rest of the sample. The subsequent variables have no substantive change in coding from the GSS. GENDER43 is coded so that the values in the variable are 0 = male and 1 = female, and will provide information to compare the reporting behavior of each gender. This is necessary for the assessment of disparity among the cohabitating sample.

42

A complete discussion of this procedure, the SPSS commands used, and the alterations

made to construct these data are available by contacting the author. 43

In the table, it is worth noting that approximately 43% of the respondents were male

and 57% female. This indicates that women are somewhat over-sampled, even if only by a few percentage points. Therefore, if women really do underreport HGO this could artificially lower the estimates of HGO even further. For more information on the selection of respondents, and sample distribution by gender see (Davis & Smith; 1992, 34, 37).

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Trends in American Gun Ownership

Table 2. Coding, Means, and Standard Deviations for Independent Variables. Selected years 1976-2000 GSS Mean

Std Dev.

n

Married and couples currently cohabitating 0=No 1=Yes

0.59

0.491

29,344

Gender

0=Male 1=Female

0.57

0.496

30,241

Hompop

Total number of household members.

2.65

1.481

30,238

Female HHH

Female Headed Household 0=No 1=Yes

0.35

0.476

20,062

Education

In Years

12.72

3.108

30,142

45.42

17.57 0

30,144

0.16

0.367

30,241

13.18

4.658

27,230

0.22

0.414

28,680

0.34

0.473

28,680

0.30

0.458

28,680

0.14

0.351

28,680

0.28

0.449

30,166

0.31

0.465

30,166

0.25

0.436

30,166

0.15

0.356

30,166

0.38

0.489

30,063

4.12

1.353

28,759

Variable†

Coding of Variable

Allcohab

Age

In Years

Race

0=White 1=Non-White

Income

In constant 1986 U.S. dollars / year:

0=1-999; 1 = 1k-1,999; 2 = 2k-2,999; 3 = 3k-3,999; 4 = 4k-4,999; 5 = 5k-5,999; 6 = 6k-6,999; 7 = 7k-7,999; 8 = 8k-8,999; 9 = 9k-9,999; 10=10k-10,999; 11=11k-11,999; 12=12k-14,999; 13=15k-19,999; 14=20k-24,999; 15=25k-29,999; 16=30k-39,999; 17=40k-49,999; 18=50k-74,999; 19=75k-99,999; 20=100,000+ NorthDid R live in the Northeast at the age of 16? East16 0=No 1=Yes Did R live in the South at the age of 16? South16 0=No 1=Yes MidDid R live in the Midwest at the age of 16? West16 0=No 1=Yes Did R live in the West at the age of 16? 0=No West16 1=Yes Did R live in a rural area at the age of 16? Rural 16* 0=No 1=Yes Small-town Did R live in a small town at the age of 16? 16** 0=No 1=Yes Suburb Did R live in a suburban area at the age of 16? 16*** 0=No 1=Yes Urban Did R live in an urban area at the age of 16? 16**** 0=No 1=Yes Are Children currently living in the Children household? 0=No 1=Yes Extremely Liberal=1, Liberal=2, Slightly Liberal=3, Moderate=4, Slightly Political Views Conservative=5, Conservative=6, Extremely Conservative=7 † Weighted by GSS weights for over-sample of African-Americans * Rural defined as open country but not a farm or on a farm. ** Smalltown defined as small town or city (under 50k population).

*** Suburb defined as in a medium size city (50k-250k population) or in a suburb of a large city. **** Urban defined as large city (over 250k population).

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HOMPOP is the GSS measure of total household population. This variable will be a key variable of interest when testing the household size hypothesis. By interacting this variable with the GSS years we will be able to inspect the results for trends in reporting HGO as they relate to changes in household size. Female HHH is a dichotomous variable denoting female-headed households. This variable has been created from the GSS variable RPLACE, which asks the respondent what their relationship is with the head of household. The GSS code signifying that the respondent is the head of household is 1. Consequently, coding all values other than 1 as missing and then multiplying this new variable by GENDER produces a variable with the value of 1 for female-headed households and 0 for male-headed households where the respondent is the head of household. EDUC measures the respondent’s number of years of education (Davis & Smith, 2003:56, 59). AGE reflects the age of the respondent in years; all respondents are 18 or older (Davis & Smith, 2003:55). The variable RACE reflects the reported race of the respondent. Race has been coded to reflect non-white and white respondents. There is arguably some level of social marginalization imposed upon all nonwhites in the U.S., and reporting of legal gun ownership on the GSS would probably vary based on this difference as opposed to any other racial categorization. INCOME represents a categorical scale of the respondents’ reported total household income in constant 1986 U.S dollars as reported in the GSS variable REALINC. It is coded by the GSS to represent 21 categories (Davis & Smith, 2003:1265; see also Ligon, 1994). These categories are detailed in Table 2. The next variables, NORTH-EAST16, SOUTH16, MWEST16, and WEST16, represent the region of the U.S. in which the respondent was living at the age of 16.44 This was chosen over information on the

44

The region categories were constructed in the same manner as Wright, Rossi & Daly

(1983). North East consists of the GSS categories New England and Middle Atlantic (ME, VT, NH, MA, CT, & RI); South is South Atlantic, East South Central, and West South Central (DE, MD, WV, VA, NC, SC, GA, FL, DC, KY, TN, AL, MS, AR, OK, LA, & TX); Midwest is East North Central and West North Central (WI, IL, IN, MI, OH, MN, IA, MO, ND, SD, NE, & KS); and West consists of the Mountain and Pacific regions (MT, ID, WY, NV, UT, CO, AZ, NM, WA, OR, CA, AK, & HI).

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Trends in American Gun Ownership

area of the country where the respondent currently resides because it yields information about the level of gun culture a respondent may have been exposed to in their youth. Respondents who were socialized in the South are expected to have much higher rates of gun ownership than other areas, whereas the Northeast (the excluded category in this case) should be lowest45 (Bordua & Lizotte, 1979:166; Brennan et al., 1993:300-04; Dixon & Lizotte, 1987:391; Lizotte & Bordua, 1980:23642; Lizotte et al., 1981; O’Conner & Lizotte, 1978:422; Wright et al., 1983:106-07). This variable was coded from the original 10 categories of the GSS to reflect four traditional regions in the U.S. (Wright et al, 1983:106). In addition, respondents that reported “foreign” were removed from the sample due to a lack of meaning in the concept being measured.46 NORTH-EAST16 will be excluded from analyses to avoid perfect collinearity. Similarly, RURAL16, SMALLTOWN16, SUBURB16 and URBAN16 describe the type of area in which the respondent resided at the age of 16: rural, smalltown, suburban, or urban (the excluded category in this case) (Dixon & Lizotte, 1987:396; O’Conner & Lizotte, 1978:422). While similar in name to definitions of size of place defined by agencies such as the census, these variables were constructed to differ from other definitions in order to more accurately portray gun culture. The GSS categories that make up the RURAL16 variable include “Open country but not on a farm” and “On a farm.” The small town variable is defined by the GSS category, “In a small city or town (under 50,000)” (Davis & Smith, 2001:60). These categories reflect areas that would be most closely associated with modern gun culture in the U.S. Although towns with populations approaching 50,000 may at first seem too large to include in this category, this includes small cities with easy access to rural areas such as Altoona, PA (pop. 49,741); Valdosta, GA (pop. 45,721); Salina, KS (pop. 46,146); and Roswell, NM (pop. 46,190) (U.S. Department of Justice, 2002). This category also represents a large number of towns

45

Subcultural socialization and its effects on gun ownership are well documented. For a

more complete discussion on these effects, see O’Conner & Lizotte, 1978; Dixon & Lizotte, 1987. 46

Respondents in this category represent only about 4.9% of the total sample in the GSS.

Without knowing the respondents’ nations of origin, it would be impossible to attempt to determine the nature of, or lack of, gun culture to which they were exposed.

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with populations well under the 50,000 limit. According to the census information used in the FBI’s Uniform Crime Reports, there are 4,943 towns with a population under 10,000 and 2,195 towns with populations between 10,000 and 50,000 (U.S. Department of Justice, 2002). These are areas in which the one would expect high levels of participation in gun culture activities in addition to easy access to areas appropriate to the sporting use of firearms. Finally, these areas do not include towns or cities that are actual suburbs of large cities. The SUBURB16 variable includes the GSS categories of “medium-size city (50,000-250,000)” and “In a suburb of a large city” (Davis & Smith, 2001:60). These categories should effectively eliminate the inclusion of traditional suburban areas with populations under 50,000 into the small town category. URBAN16 is made up of only one GSS category, “In a large city (over 250,000)” (Davis & Smith, 2001:60). Using these dummy variables, I expect that gun culture and gun ownership would be reported more often by respondents raised in rural areas or small towns (Bordua & Lizotte, 1979:166; Lizotte & Bordua, 1980:236-42; Lizotte et al., 1981; Wright et al., 1983:106-07). URBAN16 will be excluded from analyses to avoid perfect collinearity. The variable CHILDREN is coded as: 0=no children currently residing in the household, and 1=yes, children are currently residing in the household. This variable allows me to determine whether families with children eschew guns.47 This type of variable is not often included in analyses of firearms ownership and exposure, but should reveal valuable information regarding the presence of children as a determinate of HGO. Lastly, POLITICAL VIEWS are measured with a seven-point scale provided directly from the 2000 GSS. This is an additional delineation in groups who are likely to own or report gun ownership, i.e., more conservative people are more likely to belong to the gun culture. The respondents were asked: We hear a lot of talk these days about liberals and conservatives. I’m going to show you a seven-point scale on

47

Created from three GSS questions that ask about the number of members of a

household by age: first, number of household members under 6 years old (BABIES); second, number of household members from 6-12 years old (PRETEEN); and third, the number of household members from 13-17 years old (TEENS) (Davis & Smith, 2001:6667).

80

Trends in American Gun Ownership which the political views that people might hold are arranged from extremely liberal—point 1—to extremely conservative— point 7. Where would you place yourself on this scale? (Davis & Smith, 2001:96)

This set of variables, ranging in years from 1976 to 2000, will allow the estimation of a variety of equations designed to test the gender gap / social undesirability bias and household size hypotheses, while at the same time controlling for all of the major predictors of gun ownership in the U.S. To date, there has been no research that attempts to examine these hypotheses explaining the reduction of HGO with the same level of rigor or completeness. This set of variables will allow for such tests. Further, this current investigation into the nature of HGO does not appear very different from the scientific studies mentioned in chapters one and three, with one major exception, all of the past research has been cross-sectional. While there have been discussions of trends in gun ownership, few studies approach the topic with anything resembling ample data or analysis. The data presented here will allow for trends to be studied while holding constant other major indicators of gun ownership. Because the GSS is a personal interview survey conducted by NORC since 1972 it is appropriate for the study of gun ownership over time. In addition to the 43,000 individual survey interviews that have been conducted, replication allows us to examine some aspect of data quality as well as test hypotheses that depend on time series techniques. In this case analysis of over 18,000 respondents who were asked questions regarding Household Gun Ownership from 1976 through 2000 will provide new and valuable information on the topic. In sum, the appropriate methods and data for investigating changes in HGO over time are those that are designed and intended for time series analysis. The difficulties that arise when one considers the logistic distribution of gun ownership reports must be dealt with by using specific statistical techniques. Fortunately, there are methods that are suitable for this type of analysis, although they have only recently begun to be used in social science with any level of frequency. These multi-level models, commonly referred to as Fixed Effects and Changing Parameters models, are discussed in detail in the following chapters.

CHAPTER 6

Modeling Repeated Survey Data

METHODOLOGY The statistical methods that must be employed to understand trends in American gun ownership are necessarily complex. In order to include the background necessary to understand these methods the first few sections of this chapter inform the casual reader or those without formal training in quantitative social science. For those readers who are trained in statistics, and interested in the precise methodology employed in later chapters, the sections that follow the Logistic Regression subheading will provide exact details on the analyses that follow. In order to take full advantage of the basic strength of the GSS data, replication, it is necessary to estimate some form of time series analysis. This analysis must also fully address the research questions regarding HGO changes in reporting patterns (and misreporting patterns) over time. Unfortunately, most time series models that are commonly used in criminological research rely on some form of the classic linear model and assume a Normally distributed, continuous dependent variable (Greene, 1997:225; see also McDowall, McCleary, Meidinger, & Hay, 1980:15). This necessity eliminates, for practical purposes, our ability to use these estimators for studying the changes in HGO over time because the binary, “yes / no” nature of the HGO survey questions violates this assumption. This requirement may indicate why no one has attempted this analysis in the past. Modeling Cause Before discussing the details of these particular analyses, it is important to introduce some basic information regarding statistics and statistical analysis as well as how these tools apply to social science research. 81

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Trends in American Gun Ownership

While this discussion will be considered unnecessary, redundant, or rudimentary by some, I hope that it will allow readers without formal training in quantitative social science to better understand the analyses presented in the next few chapters. It is important for the casual reader to understand only a few fundamental concepts, each of which is essential to an informed understanding of cause48 and effect. Therefore, a brief discussion of the separate, but equally important, roles of time order, correlation, and the elimination of extraneous causal factors will precede discussion of the models that are used to understand HGO trends. Time order is a relatively simple idea when discussing criteria for establishing cause or causal relationships. It merely states that the cause must precede the effect in time. One may assert, for example, that gender has an effect on survey reporting behavior because the sex of a respondent almost certainly precedes answering questions on a survey. Therefore, this statement can be made with a great deal of time order confidence. If, however, one is interested in the effect of region on survey response this relationship is much less clear. Questions regarding the current residence of a survey respondent versus regional effects that may carry over from an earlier, different region of residence may go unanswered. This in turn could create problems in our ability to establish time order. Correlation or covariance must also be present to imply cause between two variables. Correlation suggests that these two variables share variation; in other words, when the value of one variable changes the other will also change in a predictable manner. To continue with the previous example, let us assume that we are interested in the relationship between gender and survey response. If the respondents were all males or all females, gender would cease to be a variable and would instead be defined as a constant. It cannot, then, be correlated with anything because it does not vary. If one has a representative sample, though, this proposition can be tested easily. When the correlation is calculated between two variables it is possible that there could be no relationship, a positive relationship, or a negative relationship. In the example of gender and survey response, the two variables could be completely independent of one another so that

48

To be complete in the discussion without belaboring the subject the reader should be

aware that this refers to the viewpoints of logical positivism in the ontology of science.

Modeling Repeated Survey Data

83

changes in one variable’s value have no observable correlation or interpretable meaning. If this is the case there would be a zero correlation, or no linear relationship, between gender and survey response. It is also possible that a positive relationship (where one observes variables that increase or decrease together) or a negative relationship (where one variable increases when the other decreases) might be observed. The important concept, though, is that two ideas, concepts, or variables must be related for one to cause the other. The elimination of extraneous causal factors is perhaps the most difficult of these three requirements to successfully resolve, and is best illustrated by example. In the case of gun ownership, for instance, there is a strong correlation between gun ownership and race when they are tested alone (this indicates that minority respondents are less likely to be gun owners). However, when one adds additional explanatory variables such as income this relationship could disappear. In this example it is important to understand that income is positively related to gun ownership (as income increases so does the likelihood of gun ownership). Income is also negatively related to minority status. Therefore, in this illustration, the argument that minorities are less likely to be firearms owners seems logical for a number of reasons, but it is actually the relationship between income and firearms ownership that explains the original relationship. In order to illustrate the interrelationship between time order, correlation, and the elimination of extraneous causes in social science, it is first useful to understand the strongest type of design that addresses these considerations. Once this ideal is understood we can then move on to an understanding of the designs that are employed here, and how they attempt to establish cause. The best, some would argue only, way to genuinely assess causation is through a randomized experiment. Experiments are characterized by the number of ways in which the experimenter or researcher exercises control over the variables of interest in a study to establish cause. While there are no experiments in this book, developing a basic understanding of this process will highlight the shortcomings of other research designs that attempt to establish cause while also illustrating the need for additional types of research designs. Examining these shortcomings, and illustrating how cause is established in a more general sense, will inform our understanding of the difficulties posed by other types of data, such as the GSS, in establishing and measuring causal relationships.

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The classic experimental design requires at least two groups to be randomly assigned: treatment and control groups. The treatment group is the group that receives an intervention from the researcher, and the control group is the group that does not receive any intervention from the researcher. By randomizing the groups that will either receive or not receive an intervention, the researcher hopes to minimize systematic error and control for all other extraneous causal factors that might influence the outcomes of the study. The next step in this design is to control the intervention received by the subjects and record the outcomes. If there is a difference between the treatment group and control group, then it is assumed that the observed difference was caused by the intervention. Thanks to randomization, the possibility that an observed change was caused by the influence of another variable is minimized. In other words, by performing these steps a researcher is able to actively regulate and influence time order and extraneous causal variables by manipulating the group assignments. She can then manage the implementation of a potentially causal variable and measure its impact Unfortunately for most social science, it is neither practical nor ethical to attempt to randomly assign individuals to groups, develop an intervention and record the outcomes. For instance, assigning subjects to gun owning and non-gun owning groups, forcing them to either own or not own a firearm, and then later measuring their reporting behavior would violate a number of ethical considerations.49 There are, nonetheless, other methods to deal with this limitation in social research. These methods, while not as robust as an experiment, provide us with the best possible approximation of ensuring that time order, correlation, and the elimination of extraneous causal variables, are well established. Regression Modern, quantitative social scientists have a battery of methodological and statistical tools at their disposal that allow us to adapt to a lack of experimental data. While not principally ideal, they do allow us to 49

This is obviously also true of a number of demographic and social characteristics. It is

certainly not possible to alter an individual’s education, income, household population, and so on, only to then record the effect that these have on his or her survey reporting behavior.

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85

overcome many of the shortcomings present in the measurement and collection of these data. In this case, determining whether variables are correlated, or covary, is particularly easy to measure mathematically. Data that are conceptually clear or collected over time may enable us to ensure that we are observing variables in the correct time order. Eliminating additional causal factors is a bit more challenging, though. For this we must be able to appraise, or estimate, the relationships between many variables simultaneously in order to determine which of them best explains variation in the outcome. There are many techniques for modeling50 these types of data to include many variables. They all fall under the general heading of multivariate analysis. Essentially, some type of outcome, usually referred to as a Dependent Variable, is measured to determine how it is affected by a series of Independent Variables that portend to explain that outcome. Mathematically, this tool is often expressed as:

Y = a + b1( x) + b2 ( x) + ...bi ( x) + e

(1)

where Y is the dependent variable, or outcome; a is the intercept, or value of Y if all other values were zero; b(x) is the slope for each independent variable included in the equation, or measure of the impact for that variable; and e is an error term, or unexplained variation. These measures of impact for the independent variables are important because they allow for the impacts of all the other variables in the equation simultaneously. This means that a researcher can include multiple variables that are expected to correlate with the dependent variable to determine what effect they have individually while allowing for the effects of all of the other variables. While we may not know whether or not there are additional variables that could be affecting the outcome (this additional variation is included in the error term), it does allow a researcher to include known variables that affect the outcome. A series of tests can also be performed that indicate whether the observed outcomes from a sample are likely to also exist in a population of interest within a predetermined margin of error. For instance, the GSS uses a probability sampling scheme to choose survey subjects. This increases our ability to make generalizations about the 50

The term modeling is widely used to describe mathematical equations that attempt to estimate a parameter (a population value) from a statistic (a sample value) by using various estimators (mathematical formulas) based on probability mathematics.

86

Trends in American Gun Ownership

U.S. population while using GSS data, but additional tests can provide an indication of the likelihood that our regression findings are also true in the population. These are usually referred to as tests of statistical significance. If a regression coefficient is statistically significant we usually interpret this to mean that it did not occur by chance in our sample, and is therefore representative of a relationship that also exists in the population from which the sample was drawn. This method, while imperfect, gives the researcher some control over the elimination of extraneous casual factors. This is especially true when those casual factors are part of a well thought out theoretical explanation of the relationship. This mathematical method of assessing multiple effects simultaneously is generally referred to as multivariate regression. A brief review of regression and its limitations is also necessary to fully understand how to model cause mathematically and how to model repeated survey data. First, there are many classifications of regression. This particular type of regression assumes that the relationship between the variables is linear and attempts to fit a line to the data. It is therefore categorized as linear regression. This type of equation also assumes that the dependent variable being studied is Normally distributed.51 If these assumptions are not met, the capacity for this equation to accurately explain the relationships between variables suffers. In particular, any tests that are performed to determine whether the findings in the equation are statistically significant become unreliable. This means that, while we might observe effects that are large in magnitude, we would not know if these relationships appear by chance or indicate a strong relationship in the population in which we are interested. Since none of the dependant variables presented here meet the assumptions of Normality or linearity a different type of regression is necessary to understand their relationships. Logistic regression meets these requirements. At this point we depart from our description of the basic scientific and statistical background of the book. From here, we can move onto a more detailed discussion of exactly how these data must be treated based on their observed and expected distributions. This is also the point of the chapter at which the casual reader may find 51

There are a number of other assumptions that must be met in order to use linear regression, and there are a number of different types of linear regression. For a comprehensive treatment of these methods it is best to refer to an instructional manual for multivariate statistics or econometrics such as Greene (1997).

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87

the discussion less valuable to their substantive understanding of the book, and readers with a formal understanding of quantitative social science will find detailed justification for the analyses. Logistic Regression These outcomes, then, must be estimated as a series of logistic regressions. Using this method allows a more comprehensive depiction of the outcomes while other relevant variables are held constant. Logistic regression allows us to interpret the resulting coefficients as odds statements, and does not assume a linear functional form (Aldrich & Nelson, 1984). Using this method I will be able to determine the odds of reporting HGO for different demographic groupings (Long, 1997:81). Another of the advantages of using Logistic regression, aside from its desirable properties when estimating limited dependent variables, is the ease with which one may interpret the outcomes of the equations. While I will report the simple odds for each of the coefficients in the equations, I will also discuss percent changes in odds.52 Logistic regression in itself is not sufficient to examine these data, however. Because of the unique nature of these data and the need to study change two specific methods are used both of which rely on Logistic regression equations, yet also allow the study of change over time. First, Fixed Effects models are estimated to allow time effects to be fixed, in turn allowing individual variable effects to be viewed independent of time effects (Greene, 1997:621). Second, Changing Parameter models are estimated to study trends and changes for specific variables of interest as they interact with time (Firebaugh, 1997). The statistical methods, their benefits, and their limitations are each discussed in detail. Also, specific models and equations that are used to examine HGO reporting are outlined in detail. There are two main models that are appropriate for estimating changes in HGO reporting behavior over time, each are specialized cases of logistic regression. As mentioned earlier, it has been difficult 52

When the coefficients of a logistic regression are expoentiated and transformed through

a simple formula, we may interpret the result as a percent change in odds of the dependent variable for a one unit change on the independent variable while holding all other variables constant. The transformation formula used here is: Percent change in the β Odds Ratio = (e − 1)*100 .

88

Trends in American Gun Ownership

in the past to evaluate survey data such as the GSS due to the nature of its distribution. Logistic regression allows for proper estimation using these data as it does not assume a linear functional form. In addition to the desirable properties of this method when estimating limited dependent variables, parameter estimates can be interpreted as odds statements (Aldrich & Nelson, 1984). Therefore, using this method we are able to determine the odds of reporting HGO for different demographic groupings and sub-groupings (Long, 1997:81). While the resulting simple odds from logistic regression can be reported for each of the coefficients in the equations, I also discuss percent changes in odds. These results alone however are not sufficient in addressing the questions at hand or fully utilizing these data, as they encompass 16 years of GSS data. Simply estimating logistic regression equations on the data would not provide any information regarding the element of time. In order to address this shortcoming, two specialized cases of logistic regression are required, the fixed effects model and the changing parameters model. Prior to discussing these models in detail and prior to presenting these models’ analyses, each of the dependent variables are subjected to a series of preliminary evaluations in order to determine whether additional analyses are justified. Although I have been somewhat critical of previous studies that have relied heavily on reporting only the proportions of men and women reporting HGO or the proportion of total respondents who report HGO, there is certainly a place for this type of analysis. Strong and detailed conclusions cannot be drawn from these analyses, but they do provide useful baselines from which to make assessments of the efficacy of further analyses. A series of contingency tables for each of the dependant variables precede the regression analyses and also serve to inform them. The Fixed Effects Model The logistic fixed effects model is most often cited as an appropriate model for the study of logistically distributed dependent variables across time in panel data (Green, 1997:896-899; Wooldridge, 2002:491-492). However, it is also acceptable for estimating trends in repeated cross-sectional survey data such as the GSS (Firebaugh, 1997: 43). These models allow for the examination of these data over time, while fixing and separating the effects of time from all of the household

Modeling Repeated Survey Data

89

and individual level effects in the model.53 The model itself is relatively simple to estimate by converting the year variable of the GSS into individual dummy variables where a value of 1 is assigned to the year in question a value of zero is assigned to all other years, then including these dummies, minus one excluded reference year, to the pooled logit model. This model can also be expressed as:

Ln ( PY ) = α + γ i D ti + X β 1 + ... X β n + e

(2)

where D is a dummy variable for each time period covered in the data and γ denotes the fixed term in the equation. This model is similar in its execution to Least Squares with Dummy Variables (LSDV) models, but without the more restrictive assumptions of least squares estimators.54 Estimating these models with any level of confidence in the results depends heavily on one assumption, aside from the usual considerations that apply to logistic regression. Due to the nature of the logit model, large numbers of cases and observation years are necessary to produce findings that are asymptotically consistent and efficient (Green, 1997:898-99). With 16 time periods and an n over 23,000 for the main dependent variable, this requirement is met. This model will allow for estimation of each of the parameters that are associated with reporting HGO independent of any time effects. Additionally, the effects of time will be separately observable as a measure of the difference in any given year from the excluded year in the equation, in this case the first year of data. These will be important in determining whether or not there is any actual trend in overall HGO reporting as well as which of the possible explanatory variables’ effects remain while holding the time change constant. The Changing Parameters Model For further explanation, a specialized case of the logistic fixed effects model is useful. The changing parameters model allows for the study 53

In this case, the fixed effects model will yield results that can be interpreted much like

a Hierarchical Linear Model (HLM) would be, without having to meet the restrictive assumptions of such a model. For a complete discussion, see Firebaugh, 1997, p.63. 54

These assumptions include Normally distributed variables and a linear relationship

between the variables.

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Trends in American Gun Ownership

of trends in individual and household level effects over time, while controlling for the effects of other explanatory variables and the general time trend. This is accomplished by including an interaction term consisting of the variable in question and the time dummies. In other words, the model is designed to study the change in β, the changing effects of X’s over time (Firebaugh, 1997:42). The model can also be expressed as:

Ln( PY ) = α + γ i Dti + Xβ1 + ...Xβ n + ( X ti Dti ) + e

(3)

where (XtiDti) is an expression of the interaction between some variable of interest and the time dummies. This equation is a specialized case of equation (2), created by adding a series of interaction terms. As such, this equation will allow for both the assessment of the change in a specific variable, and the assessment of whether or not the “changing parameter” (the entire set of interaction terms) is significant. Statistical significance of individual interaction coefficients can be determined with standard t tests, and Bayesian Information Criterion (BIC) will determine significance for the interactions jointly (Long, 1997:110-112). This criterion simply assesses whether a model fits the data well enough to justify the number of parameter estimates that are included. This test is especially useful in assessing nested models as it penalizes a model for having more parameters. Many other tests for assessing the fit of two different equations lack this feature and therefore favor models with more parameters. For Maximum Likelihood Estimators, the criterion appears as:

BICk = D( M k ) − df k ln N

(4)

where D(M) is the model deviance, comparing the model under observation with the saturated model with degrees of freedom equal to the sample size minus the number of parameters in the current model. In this case, the model with the smaller BIC is the model that best fits the data. The larger the difference the more confidence one has in the outcome of the test (Long, 1997:112). In sum, the changing parameter model promises the ability to further understand any time component in these equations by interacting the potential time effects with any variable of interest to distinguish the change in that variable over time. At the same time, one

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does not have to assume that this model fits the data better than the fixed effects model simply because more parameter estimates are imposed on the data. THE ERRORS Perhaps the greatest threat to the parameter estimates in any of the models presented in this study is the presence of autocorrelation. Because the main interest in the analysis addresses change over time, autocorrelation in the error term poses the threat of biasing the standard errors (although not the slopes) in the equation downward, thereby rendering the t (Wald) tests unreliable and increasing the chance of Type 1 error (Greene, 1997). That is, one would be more likely to find a result significant when it actually is not. Traditional methods of correcting autocorrelation, however, are impracticable in this analysis. Because the GSS is not performed in temporally equidistant periods, and all of the questions necessary to this analysis do not appear in each consecutive GSS, the autocorrelation function would be difficult if not impossible to estimate. In its stead the analysis uses robust standard errors55 to calculate the significance tests in the equations. These standard errors allow for the presence of autocorrelative error, and provide greater confidence in the significance tests of the findings (Wooldridge, 2002:56-58). Model Specification & Design A number of models must be estimated in order to test the various theories that offer explanations for reductions in reporting HGO. Each provides its own information in these tests, but each of the nested models is also compared to each other in order to determine whether adding additional parameter estimates actually adds to the ability of the model to fit the data and advance our understanding of HGO reporting. The following chapters provide the exact results of applying these statistical models to the GSS data. However, it is not only important to understand the mathematics and the interpretation of the statistical models. It is also important to comprehend the research design and the way in which each of the models is specified. That is, the logic for including each of the models, the decision for inclusion of each of the

55

For full details of this process, see Wooldridge, 2002:265-78, see also Kim, 2004.

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Trends in American Gun Ownership

variables in the models, and what their actual meanings are all of the utmost importance. In other words, these data and models will provide us with specific information necessary to address each of the research questions and hypotheses being tested. It is in this interest that each of the models is discussed. Reviewing Patterns of Reporting The task of describing a baseline for these analyses and discerning possible associations between trends and reporting or, in some cases, differences in reporting by gender are initially addressed through a series of models that detail contingency tables. By calculating a series of contingency tables for each of the dependent variables in Table 1 and Gender for each year of available data, patterns of association or non-association emerge indicating whether further analyses are justified or not and provides focus for more complex analyses. The results of these contingency tables on overall HGO, PGO, reported ownership of rifles, shotguns, and pistols, and home ownership provide baselines for each of the dependent variables. Furthermore, these contingency tables detail reporting levels for male and female respondents separately. If strong trends are noted in the tables examining the overall GSS reporting behavior, further analysis is warranted to discern detail in the trends. Additionally, if tables limited to married respondents show similar trends, as well as trends in the difference in reporting between men and women, then further investigation into the gender gap hypothesis is warranted. Finally, a series of contingency tables for married respondents’ reports of home ownership presents information allowing for comparisons of men and women’s reporting behavior on a more commonplace variable. Evaluation of whether or not a gender gap exists on an innocuous variable helps us to determine the effects of gender alone on reporting compared to the separate effects of gun ownership. The results of these tables indicate which relationships merit further investigation by determining which of these relationships appear to be trending and which do not. Testing the Theories The decision to include fixed effects models is decided, in part, by the results of the contingency tables. For instance, if there are trends in HGO reporting, but no difference between married men and women

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reporting HGO, delving deeper into this area would not be justified. However, accepting the reports of earlier analyses focusing on HGO reporting and gender (Kleck, 1997; Ludwig et al., 1998) predictions regarding the form and function of these models can be made as they relate to each of the theories being tested. The first models provide a multivariate baseline by regressing all independent variables on HGO and PGO, respectively. This allows examination of the data and comparison of these findings with earlier work in the field to ensure that these data are representative of the level of convergence in others’ discussed in earlier chapters. These models also allow for initial assessment of the household population hypothesis. The next models are used to investigate the efficacy of the gender gap theoretical explanation. The fixed effects models regress HGO, Rifle, Shotgun, and Pistol on all independent variables, with the exclusion of female-headed households, censored for married couples only. If Gender exhibits a significant, non-trivial effect in these equations further examination must include changing parameter models to determine if this effect has grown over time. Additionally, it must allow for comparison to the fixed effects models to determine whether this effect exists throughout the sample or is limited to some demographic subset of the sample. Included in these analyses, a report of the BIC’s for each of the models determines which of the models best fit the data, essentially whether the changing parameter models add any additional, useful information to the analysis. If these more complex models do not add any unique, useful information they are included in Appendix B, but not discussed in detail. Similarly, if household population indicates a significant effect on HGO, Rifle, Shotgun, or Pistol reporting for all respondents it is included in changing parameter models to determine whether trends in U.S. household populations explain reductions in HGO overall or by type of firearm reported. Each models’ BIC is reported to determine best fit. Models which do meet the best fit criterion are also included in Appendix B. Finally, fixed effects models are reported where HGO, Rifle, Shotgun and Pistol are regressed on female-headed households substituted for the Gender variable. If the female-headed household variable exhibits a significant, non-trivial effect in these equations further examination includes changing parameter models to determine if this effect has grown over time. Best fit is determined as in the other

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equations. As in each of the previous tests, models that do not further our understanding of the data are included in Appendix B. CONCLUSION Using the GSS data from 1976 through 2000 takes advantage of the highly relevant high quality data provided in the GSS and, further, makes the most of all available years of data. Indeed, the research design and the methodology are used intentionally to take advantage of the main strength of the GSS, replication. In this case using the GSS data allows for the analysis of more than 18,000 respondents who were asked questions regarding Household Gun Ownership on 16 surveys over a 25 year period. Although one might question the absence of the 2002 and later survey data, the noteworthy changes in the survey’s methodology regarding race and the change in interview mode justifies the exclusion. This is especially true when one considers that no methodological reports are yet available to determine what effect these changes may have when comparing the new data to earlier surveys. By using fixed effects and changing parameter models, research questions can be addressed while allowing for the non-Normal nature of the GSS data, but still taking advantage of the strengths of the GSS. These models also allow for the consideration of changes over time throughout the investigation and a more comprehensive understanding of the outcomes while other relevant variables are held constant. Finally, statistical tests allow for a better understanding of the outcomes of the analyses by determining whether or not the findings in the various models add new, unique information or simply add superfluous parameter estimates without advancing our understanding of HGO reporting.

CHAPTER 7

Simple Trends in Gun Ownership

BIVARIATE TRENDS The results of the initial 16 contingency tables detailing HGO reporting on the GSS are presented in Table 3. In this table, and each of the subsequent reports of contingency tables, total percent reporting HGO, males and females reporting HGO, the percent difference between men and women’s reporting, and whether that difference is statistically significant are in the columns, respectively. These details provide basic information on the reporting trends and a baseline for future analyses. It is also worthwhile to note that these analyses are not particularly new analyses or outcomes. They closely follow earlier analyses by Kleck (1997) and Ludwig et. al (1998). Nonetheless, the value of determining baselines and justification for the more complex analyses to follow outweighs the redundancy of the technique. Although this analysis does not lend any substantive information regarding factors that might underlie HGO reporting, the results do point toward a need for more detailed examination of the topic. One is immediately struck by the difference of 14 percentage points between HGO reporting levels in the 1970’s and the turn of the century. Upon closer examination, however, it appears as if this steep reduction in reporting might be a relatively recent phenomenon due to the comparative stability until 1989. The difference between male and female reporting is also expected; although this does not yet indicate reporting error, it does indicate that men are much more likely to be gun owners than women.

95

96

Trends in American Gun Ownership Table 3 – Percent of GSS respondents reporting HGO By gender, 1976 - 2000 Percent reporting HGO Year

Total

Male

1976

47.2%

52.2%

1977

50.8

55.3

1980

47.8

1982

46.5

1984

Female

χ2

p

43.2%

n 1476

% Δ 9.0*

11.8

<.001

47.0

1519

8.3*

10.4

.001

55.9

41.4

1455

14.5*

29.9

<.001

55.0

40.2

1828

14.8*

39.4

<.001

45.4

53.6

39.8

1457

13.8*

27.1

<.001

1985

44.6

54.7

36.4

1520

18.3*

50.8

<.001

1987

46.1

51.0

42.4

1806

8.6*

13.4

<.001

1988

40.5

50.5

33.6

960

16.9*

27.7

<.001

1989

46.1

54.9

39.4

1030

15.5*

24.6

<.001

1990

42.7

53.2

34.6

907

18.6*

31.5

<.001

1991

40.3

50.9

32.1

976

18.8*

35.5

<.001

1993

42.4

52.8

34.5

1066

18.3*

35.8

<.001

1994

41.1

50.9

33.5

1970

17.4*

60.9

<.001

1996

40.3

47.5

34.6

1914

12.9*

32.7

<.001

1998

35.0

42.7

29.3

1869

13.4*

36.1

<.001

2000

32.9

42.4

25.4

1834

17.0*

59.4

<.001

* p<.05

In order to better observe the differences between gun reporting and personal gun ownership between men and women, Table 4 presents the percent of respondents who report personal gun ownership on the GSS. This is markedly different than reports of HGO. Here, we observe individuals reporting that they personally own a firearm. This measure does not rely on a respondent’s knowledge of what another person in the household may or may not own. It is an individual level measure of gun ownership. While the patterns of PGO appear similar to the patterns of HGO, there appears to be much greater stability in this measure. Again, we note that men are much more likely to be gun owners. There is only about a 6 percentage point difference in reporting between the 1980 and 2000 GSS. Furthermore, this level of difference does not appear until the last two years of the survey. PGO immediately appears to be a better, more stable measure of gun ownership.

Simple Trends in Gun Ownership

97

Table 4 – Percent of total GSS respondents reporting PGO By gender, 1980 - 2000 Percent reporting PGO Year

Total

Male

1980

29.0%

51.8%

1982

29.4

48.7

1984

25.8

1985

Female

χ2

p

11.3%

n 1422

% Δ 40.5*

279.1

<.001

15.1

1785

33.6*

237.3

<.001

46.6

11.5

1455

35.1*

226.8

<.001

29.2

50.7

11.8

1517

38.9*

275.0

<.001

1987

28.3

47.4

13.6

1795

33.8*

247.9

<.001

1988

24.9

44.9

11.0

956

33.9*

142.2

<.001

1989

27.9

50.0

11.0

1025

39.0*

190.1

<.001

1990

28.2

50.9

10.6

905

40.3*

178.6

<.001

1991

26.2

47.7

9.6

971

38.1*

179.3

<.001

1993

29.0

48.9

14.0

1064

34.9*

154.0

<.001

1994

28.2

47.5

13.2

1968

34.3*

281.6

<.001

1996

26.8

44.3

12.9

1908

31.4*

236.9

<.001

1998

22.9

39.5

10.8

1864

28.7*

212.0

<.001

2000

22.7

39.1

9.8

1834

29.3*

220.5

<.001

* p<.05

Table 5 begins examining the potential for actual reporting error in HGO reporting. Here, only respondents that were married and cohabitating or cohabitating as married couples are examined, with percentages reporting HGO split by gender. The drop in reporting is less pronounced than in the total sample. There is a reduction of only about 6 percentage points over the 16 years presented. This differs from Tables 3 and 4 in that one should not expect any significant difference between cohabitating men and women when they are reporting on household level variables. This, of course, is indicative of either men over reporting HGO, women underreporting, or both. Whatever the case, there are statistically significant and non-trivial differences between men and women on HGO reports for 8 of the 16 years analyzed. With so many of the years displaying this type of result it is highly unlikely that these findings could be due to chance. While this is not different than the results of earlier reports of a gender gap in reporting HGO (Kleck, 1997; Ludwig et al., 1998) it provides valuable replication with these data and reinforces strong motivation for further study.

98

Trends in American Gun Ownership Table 5 – Percent of marrieda GSS respondents reporting HGO By gender, 1976 - 2000 Percent reporting HGO % Δ 2.4

χ2

p

3.0

0.324

1,048

4.7

4.2

0.069

55.9

935

5.4

8.2

0.053

58.1

53.9

1,154

4.2

3.2

0.083

55.6

54.8

897

0.8

60.0

0.430

55.6

60.2

51.2

942

9.0*

57.7

0.003

1987

57.1

57.3

56.8

1,078

0.5

30.0

0.459

1988

52.6

57.1

48.7

572

8.4*

80.4

0.026

1989

56.4

61.0

52.4

638

8.6*

28.4

0.017

1990

53.8

57.8

49.6

541

8.2*

6.3

0.035

1991

53.6

58.0

49.7

563

8.3*

29.3

0.029

1993

52.0

56.1

48.1

627

8.0*

79.3

0.028

1994

51.9

55.9

48.0

1,156

7.9*

51.7

0.004

1996

50.6

52.5

48.8

1,019

3.7

63.1

0.135

1998

43.9

45.9

42.2

985

3.7

33.1

0.138

2000

42.4

46.1

38.9

968

7.2*

90.5

0.014

Year

Total

Male

Female

1976

57.2%

58.5%

56.1%

1977

58.9

61.3

56.6

1980

58.5

61.3

1982

55.9

1984

55.2

1985

n 500

* p<.05 a

Includes respondents cohabitating as married

In order to determine whether these differences in reporting are aggravated or mitigated by the type of firearm that one reports in the home, Tables 6, 7, and 8 further examine the difference in HGO reporting by focusing on whether the respondent reports a rifle, shotgun or pistol in the home after they have responded to the HGO questions affirmatively. Again, as these data include only those respondents who are either both married and cohabitating with their spouse or cohabitating with someone in a spouse-like relationship are included, there should be no difference between the reporting rates of men and women.

Simple Trends in Gun Ownership

99

Table 6 – Percent of marrieda GSS respondents reporting HGO - rifle By gender, 1976 - 2000 Percent reporting HH rifle % Δ

χ2

499

3.2

0.54

.260

34.2

1,048

4.7

2.49

.065

35.3

932

4.3

1.83

.100

39.9

35.3

1,154

4.6

2.60

.060

33.7

34.6

33.1

898

1.5

0.23

.341

37.0

40.7

33.5

942

7.2*

5.25

.013

1987

37.4

40.4

34.7

1,078

5.7*

3.80

.030

1988

35.1

41.0

30.1

572

10.9*

7.43

.004

1989

35.0

39.8

30.8

637

9.0*

5.89

.011

Year

Total

Male

Female

n

1976

36.3%

38.0%

34.8%

1977

36.5

38.9

1980

37.3

39.6

1982

37.4

1984 1985

p

1990

34.9

41.2

28.4

541

12.8*

9.66

.001

1991

34.6

39.6

30.2

563

9.4*

5.46

.012

1993

30.8

34.3

27.5

627

6.8*

3.45

.038

1994

34.2

40.4

28.3

1,156

12.1*

18.79

<.001

1996

31.4

34.5

28.4

1,020

6.1*

4.35

.022

1998

28.2

28.9

27.7

982

1.2

0.17

.365

2000

27.8

30.9

24.9

961

6.0*

4.29

.023

* p<.05 a

Includes respondents cohabitating as married

Table 6 reports on those respondents reporting a rifle in their home. Firstly, a pattern of reduced reporting over time is noted, as there is a drop of about 9 percentage points over the 16 years detailed. Next, one sees that there are ten years in which significant differences exist between the reporting rates of men and women, and that these differences are often of a greater magnitude than the differences of HGO reporting in general. In addition, when examining these differences it appears that there may be a pattern of growth over time because they appear in only the later years of the survey. Not only do the reporting differences appear in later years, but they also seem to grow over the reporting period. This could point to a growth in reporting error over time based on type of firearm because it is certainly more pronounced than the reports of overall HGO that are not limited by type of firearm.

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Trends in American Gun Ownership

Similarly, Table 7 details levels of reporting and gender differences for those respondents who report a shotgun in their home. It appears that there is an even greater drop in reporting a shotgun than a rifle in the home over time with a total reduction in reporting of about 11 percentage points between the 1976 and 2000 surveys. Additionally, shotgun reporting differs from total HGO and rifle reporting in so much as that there does not seem to be a pattern of disagreement. In this case, the differences in reporting are large and appear throughout almost all of the 16 years presented. Table 7 – Percent of marrieda GSS respondents reporting HGO - shotgun By gender, 1976 - 2000 Percent reporting HH shotgun Year

Total

Male

Female

n

% Δ

χ2

p

1976

36.5%

37.1%

35.9%

499

1.2

0.08

.427

1977

38.2

42.3

34.4

1,048

7.9*

6.90

.005

1980

37.8

43.2

32.9

932

10.3*

10.60

.001

1982

37.2

42.7

32.3

1,153

10.4*

13.27

<.001

1984

35.9

37.1

34.9

898

2.2

0.48

.267

1985

36.7

42.0

31.6

942

10.4*

10.94

.001

1987

37.8

41.8

34.3

1,078

7.5*

6.40

.007

1988

32.2

36.8

28.1

572

8.7*

4.98

.016

1989

35.9

42.1

30.5

637

11.6*

9.38

.001

1990

35.3

41.5

28.8

541

12.7*

9.59

.001

1991

36.7

40.4

33.3

561

7.1*

3.05

.049

1993

34.3

39.6

29.3

627

10.3*

7.35

.004

1994

32.6

38.2

27.2

1,156

11.0*

15.87

<.001

1996

33.3

38.7

28.2

1,020

10.5*

12.56

<.001

1998

28.0

31.8

24.9

982

6.9*

5.76

.010

2000

25.2

29.2

21.4

962

7.8*

7.59

.004

* p<.05 a

Includes respondents cohabitating as married

The final type of firearm reported by the survey is presented in Table 8. Again, there are obvious differences between reports of a pistol in the household and HGO, as well as apparent differences between rifle and shotgun reporting. First, there appears to be no reduction in levels of reporting household pistols over these 16 years,

Simple Trends in Gun Ownership

101

although there appears to have been an increase in the mid 1980’s. Also, somewhat surprisingly, there appears to be a pattern of differences in reporting that is unlike total HGO, rifles or shotguns. In this case there appears to be a reduction of misreporting over the time examined. That is, there were fairly large differences in reporting a pistol in the household in the early survey years, but these differences almost completely disappear after 1989. Table 8 – Percent of marrieda GSS respondents reporting HGO - pistol By gender, 1976 - 2000 Percent reporting HH pistol % Δ

χ2

p

9.3*

5.78

.011

2.2

0.69

.224

932

8.1*

7.48

.004

1,153

4.6*

3.22

.042

898

7.5*

6.37

.007

25.1

942

7.0*

5.77

.010

33.6

28.1

1,078

5.5*

3.75

.031

28.7

30.8

26.8

572

4.0

1.13

.166

30.3

37.8

23.7

637

14.1*

14.99

<.001

1990

28.5

31.4

25.4

541

6.0

2.41

.072

1991

26.7

29.6

24.1

561

5.5

2.11

.087

1993

29.5

31.0

28.1

627

2.9

0.65

.236

1994

29.9

35.4

24.7

1,156

10.7*

15.75

<.001

1996

27.3

29.5

25.1

1,020

4.4

2.39

.070

1998

24.2

26.4

22.4

982

4.0

2.09

.085

2000

24.3

25.9

22.9

961

3.0

1.19

.155

Year

Total

Male

Female

1976

24.2%

29.3%

20.0%

1977

23.5

24.6

22.4

1980

28.1

32.4

24.3

1982

25.4

27.8

23.2

1984

25.9

30.1

22.6

1985

28.6

32.1

1987

30.7

1988 1989

n 499 1,048

* p<.05 a

Includes respondents cohabitating as married

With three different patterns of reporting, it appears as if the relationship between total HGO and type of firearms owned may be more complex than earlier work in this area has reported. In any case, the reporting of each of these types of firearms demands additional analysis, and each will be treated separately with more complex models to determine what characteristics of gun ownership and gun reporting can lend to the development of a more complete model.

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Trends in American Gun Ownership

Home Ownership The final set of contingency analyses consists of the test of an innocuous variable at the household level in order to determine whether the differences in HGO reporting between men and women might be due to general differences in reporting behaviors based on the gender of the respondent. In order to provide this information, a series of contingency tables were calculated for the GSS question asking the respondents whether they own or rent their home. This was further detailed by limiting the sample to married respondents by gender for the GSS years from 1985 – 2000. The results are reported in Table 9. In this case, one can see that there are no differences between the reporting behaviors. There is one year in which the difference in reporting is significant at .049; however, this is most likely due to chance and can be ignored. Table 9 – Percent of marrieda GSS respondents reporting home ownership By gender, 1985 - 2000 Percent reporting home ownership % Δ

χ2

930

3.0

1.15

.159

79.7

1,057

1.5

0.37

.298

75.9

554

0.9

0.05

.448

76.1

80.4

594

-4.3

1.61

.121

74.7

77.1

519

-2.4

0.40

.299

77.0

78.3

75.9

557

2.4

0.44

.287

1993

80.7

81.1

80.4

649

0.7

0.06

.441

1994

76.2

73.7

78.1

1,082

-4.4

2.86

.053

1996

77.4

78.5

76.3

1,001

2.2

0.70

.223

1998

79.4

76.9

81.4

979

-4.5

3.01*

.049

2000

75.1

73.1

76.8

930

-3.7

1.66

.113

Year

Total

Male

Female

n

1985

75.8%

77.3%

74.3%

1987

80.4

81.2

1988

76.4

76.8

1989

78.3

1990

75.9

1991

* p<.05 a

Includes respondents cohabitating as married

p

Simple Trends in Gun Ownership

103

CONCLUSION Although these results are preliminary, they do shed some light on how HGO reporting has changed over time. For instance, we can now say that there is a pronounced decrease in HGO reporting over time. Also, it appears that the discrepancy between married respondents, and those living as married couples, may have grown over time. PGO levels, however, do not demonstrate the same type of steady reduction in reporting seen in HGO. Instead, they show a sharp decline only in the last two years of the survey. Finally, reductions in reporting HGO differ depending on the type of firearm that the respondents report. Rifle and shotgun ownership exhibit a strong, steady decline over the time period in question while pistol ownership actually appears to increase over this time in married households. This is not the only difference. Surprisingly, the difference between men and women reporting pistols in married households appears to have decreased over these years of the survey. The home ownership results for married respondents offer some support to the idea that the differences in reporting HGO by gender is most likely not due to any inherent differences in reporting behavior based purely on gender. Instead, we can proceed with some confidence that these differences are more than likely due to something specifically about reporting gun ownership. Further evidence to support this notion appears in the direction of the differences between men and women. There is not even a constant direction in the non-significant differences between the sexes. Due to these findings, further analysis on this particular variable will not be warranted. While certainly not conclusive, these results are valuable for four reasons. First, they point to a need for further analyses to determine the nature of the trends in American HGO reports. Secondly, although many of these analyses are replications of others’ prior work, they offer a better measure of marriage by including cohabitating couples to confirm earlier analyses. Third, new analyses indicate a more complex relationship in HGO reporting than previously understood. The idea that HGO reporting differs based on the type of firearm in the household is a new one and deserves attention. Finally, a better understanding of whether the gender gap in HGO reporting is due to a fundamental difference in reporting behavior based on gender or something specific to firearms is important. Treating an innocuous measure like home ownership to the same type of analyses as HGO and

104

Trends in American Gun Ownership

finding that there are no differences in the reporting behavior of married women and men supports the idea that the gender gap in HGO reporting is a phenomenon somehow specific to gun reporting. Of course, further research into this question is necessary as it would be useful to see if there are differences in reporting other household level behaviors that are not mundane to find out if they, too, indicate different reporting behaviors. In any case, the results thus far indicate a need for further examination of each of the hypotheses. Bivariate relationships tell us very little about the complex relationships between gun ownership, reporting, and time. In order to test these complex relationships and understand why these differences and inconsistencies appear in HGO reporting, the next step is to calculate multivariate, fixed effects models that include additional indicators that predict gun ownership in the U.S.

CHAPTER 8

Who Reports Gun Ownership?

INTRODUCTION While the information presented in Chapter 7 is informative and interesting it does little to help one understand who is reporting gun ownership (and who is not), why they are reporting gun ownership, and whether or not these trends differ based on predictors of gun ownership. However, by applying the more advanced models discussed in Chapter 6, the effect that these traditional predictors have on reporting HGO can be estimated. In other words, while these models are more complex, they offer the distinct advantage of being able to include all of the information necessary to understand which of the variables typically associated with HGO predict changes in trends. Perhaps most importantly, they provide us the explanatory power to test the theories described in Chapter 4. BASELINE MODELS OF GUN OWNERSHIP Tables 10 and 11 detail the baseline regression models in which all of the variables predicting gun ownership are regressed on HGO and PGO respectively. All regression models in this analysis and all analyses presented here are calculated with Robust Standard Errors.56 Additionally, all models were diagnosed for multicollinearity by estimating Weighted Least Squares (WLS) equations and calculating Variable Inflation Factors (VIF).57 These models allow the effects of 56

See p. 89 for discussion of Robust Standard Errors.

57

No VIF’s in any model exceeded a value of 4. This is well within commonly accepted

limits; therefore, it is safe to assume that collinearity is not a problem in any of these equations.

105

106

Trends in American Gun Ownership

household level variables to be observed with time fixed, therefore providing information on overall trends and effects. The results of Table 10 are unremarkable in their agreement with earlier analyses. Two results that are of interest however, household population (HOMPOP) and children in the household. Household population has not often been included in analyses of HGO. In this equation, the HOMPOP parameter estimate indicates that each additional member of the household increases the odds of reporting HGO by about 20%. This indicates that a changing parameter model should be calculated to determine whether or not this effect exhibits a trend over time in the GSS, and how much of the overall decrease in HGO reporting can be attributed to this trend. Yet another estimate that is seldom included in analyses explaining HGO is the presence of children in the home. In this case, the estimate for Children indicates that the presence of household members under the age of 18 reduces the odds of reporting a gun in the household by about 15%. This contradicts other studies that report “Gun ownership does not vary with the presence of children” (Smith, 1999:25). Smith’s conclusion was drawn from a bivariate analysis of the NORC NGPS, absent controls.58 Another informative result worth discussion is the significance of the year variables. Table 10 shows that, when controlling for all of the usual predictors of HGO, only the year 2000 is significantly different than the 1976 value of HGO. This indicates first, that the overall trend in reduced HGO may not be as pronounced as it appears in the raw data, and second, that the other predictor variables should explain the trend when included in a changing parameter model. Essentially, there is little substantive difference or disagreement between these findings and those of numerous past studies predicting HGO. Therefore, we can proceed with further analyses of these data with the confidence that, while the analytical means and methods might differ, the nature of the data do not fundamentally contradict previous findings. Table 11 includes all of the same dependent variables predicting PGO for the entire GSS sample. These findings differ from the results of Table 10 in two important ways. First, the direction of the effects of

58

Although not presented here, the equation was also estimated with ALLCOHAB added

as a control variable, and the parameter estimate for Children becomes insignificant, agreeing with Smith’s bivariate analysis.

Who Reports Gun Ownership?

107

Table 10. Logistic Fixed Effects Model on HGO for all GSS respondents Selected years, 1976 – 2000; n = 19,371 Exp. β Variable Gender

Exp. β

(SE)

Fixed effect dummy

0.588**

1977

(.019) Hompop

1.197** 0.927**

1980

0.489**

1982

1.004**

1984

1.114**

1985

2.703**

1987

1.814**

1988

1.903**

1989

3.010**

1990

1.828**

1991

1.266**

1993

0.847**

1994

1.119**

0.992 (.084)

1996

(.043) Political Views

0.983 (.095)

(.071) Children

0.957 (.095)

(.098) Suburb16

1.038 (.104)

(.167) Smalltown16

1.138 (.112)

(.104) Rural16

0.978 (.099)

(.083) West16

1.127 (.099)

(.127) Mid-West16

1.078 (.095)

(.005) South16

1.146 (.102)

(.001) Income

1.174 (.103)

(.026) Age

1.091 (.096)

(.006) Race

1.183 (.106)

(.021) Education

(SE)

1.000 (.086)

1998

(.014)

0.811 (.071)

2000

0.728** (.064)

**p<.001

G² 2493.82

*p<.05 Pseudo R² .125

(sig.) <.001 BIC 23,643

108

Trends in American Gun Ownership

household population and having children in the household operate in exactly the opposite direction than in the equation predicting HGO. In this case, an increase of one person in the household population reduces the odds of reporting personal gun ownership by about 6%, while the presence of children in the household increases the odds of reporting PGO by about 31%. The relationship between household population and PGO can be explained simply. As the total population in the house increases, any single individual in the household is less likely to be the one gun owner in that household. For instance, if there were only two people in a given household containing a firearm, each member would have a 50% chance of being the individual owner of that gun, all other things being equal. If, however, that household population were increased twofold, each member of the household would only have a 25% chance of being the individual gun owner. Thus, as household population increases, the odds of the respondent being the individual gun owner decrease, in this case by 15%. The presence of children in the household may at first seem unlikely to increase the odds of PGO reporting by 31%. However, being married usually doubles the odds of HGO (Smith, 1999; Legault, 2002; 2004), and because married households are also much more likely to have children in the residence, the parents of these children may be reporting legal ownership of a child’s firearm.59 It is purely a legal distinction, but adults would likely report personal ownership of firearms that were procured for the use of older children. Since it is illegal for persons under the age of 18 to personally own a firearm, their parents or guardians would have to be the legal owner of that firearm thereby explaining the positive effect of children on PGO. The time component in personal gun ownership is similar to that of the HGO equation in Table 10. When controlling for all of the common predictors of PGO, only the years 1998 and 2000 are significantly different than the 1976 value of PGO. Therefore, this supports the argument that there is little change in the overall trend of PGO, and that the other predictor variables may explain any real trend when included in a changing parameter model. The findings in the PGO equation could be explained by the difference in the level of analysis. However, these findings could also

59

This equation was also calculated controlling for ALLCOHAB, and the coefficient

grows in magnitude to 1.352.

Who Reports Gun Ownership?

109

be explained by household level variables. There is little substantive difference or disagreement between the findings of either of these models and those of numerous past studies predicting individual gun ownership. To proceed with further analyses of these data is therefore both justified and necessary in order to determine whether trends are operating, to test each of the theories offered to explain changes in HGO, and to develop an understanding of these data as they pertain to HGO and PGO specifically over the 16 years of survey response data that are available. Table 11. Logistic Fixed Effects Model on PGO for all GSS respondents Selected years, 1980 – 2000; n = 16,783 Exp. β Exp. β (SE) Fixed effect dummy (SE) Variable Gender 1982 0.134** 1.112 (.006) (.111) Hompop 1984 0.941* 0.927 (.020) (.092) 1985 Education 1.036 0.943** (.101) (.007) Race 1987 0.594** 0.990 (.039) (.097) 1988 Age 0.954 1.014** (.108) (.001) Income 1989 1.079** 1.029 (.006) (.112) 1990 South16 1.045 2.725** (.118) (.163) Mid-West16 1991 1.702** 0.936 (.100) (.104) 1993 West16 1.027 2.056** (.113) (.144) Rural16 1994 2.634** 1.058 (.186) (.100) 1996 Smalltown16 1.024 1.590** (.098) (.110) Suburb16 1998 1.185* 0.797* (.086) (.078) Children 2000 1.311** 0.780* (.078) (.081) Political Views 1.105** (.016) **p<.001 *p<.05 Pseudo R² .207

G² 2851.97 (sig.) <.001 BIC 16,229

110

Trends in American Gun Ownership

THE GENDER GAP IN REPORTING HGO Evaluating the effects of the gender gap on reporting HGO involves three main strategies: fixed effect models, changing parameter models, and comparison of fixed effects models. The data are limited to only those respondents that are married and cohabitating or cohabitating as if they were married. This allows for comparisons of the respondents’ reporting behavior by gender, and for comparisons of various groups. More importantly, this method allows for these comparisons to be made in a number of different types of analyses that better explain and detail this gap than simple, bivariate analyses such as those reported in the previous section and those reported in previous research (Kleck, 1997:100; Ludwig et al., 1998:1716). The fixed effects models will be estimated on all of the same variables that were used to assess reporting behavior in the previous models, but without the full sample. These models will be assessed for all HGO, household rifle ownership, household shotgun ownership, and household pistol ownership. These models will reveal general trends, and whether or not a respondents’ gender equates to differences in reporting. If these differences are noted, the models will be further examined for detailed trends in step two, the changing parameter model. Estimating the changing parameter model allows for the assessment of specific trends that are untapped in the fixed effects model. The fixed effects model provides general information regarding trends in reporting, but the changing parameter model allows for more direct measurement of trends in specific reporting behaviors. For instance, if the fixed effects model shows a trend in HGO and a difference in reporting by gender, then we can include interaction terms that are products of gender and years in order to determine whether a growing trend in misreporting by gender could explain part of an overall reduction in HGO reporting. If, however, the changing parameter model does not exhibit findings that support a trend or if the model does not fit the data as well as the more parsimonious fixed effects model it can be discounted, along with support for a hypothesis that depends on the specific trend to explain reductions in HGO. Finally, if a gender gap is found in the fixed effects model, or both the fixed effects and changing parameter models, examination of the data to test the social undesirability bias explanation of the gender gap can be performed. The model that best explains the data can be further

Who Reports Gun Ownership?

111

split to examine subsets of the data by gender, race, and “type of place” in order to pinpoint the reporting discrepancies and to further describe trends. For instance, if a series of equations, sub-divided by the ‘type of place’ the respondent lived in at age 16, were computed and the coefficients were compared using cross-coefficient tests to show that reporting differences by gender exist only if the respondent was raised in areas of higher population density (and low gun culture), this might support the social undesirability bias hypothesis. Conversely, if the differences in reporting for men and women were not effected by any of these predictors, one might be more inclined to dismiss this explanation. The detail provided by the available GSS data combined with the rigor of these models should provide a much clearer picture to test of the gender gap hypothesis than any previous study has yet attempted. Married HGO Reporting The first step in the evaluation of the gender gap in reporting HGO is reported in Table 12. This equation limits the GSS sample by predicting HGO only for married couples. In this equation, the parameter estimate for Gender should be insignificant, indicating that there is no difference in reporting between married male and female respondents on this household level variable. This, evidently, is not the case with married women having a 15% reduced odds of reporting HGO compared to married men. The inconsistency represents perhaps the widest gap in reporting HGO thus far noted in any research findings (Kleck, 1997:100; Ludwig et al., 1998:1716). Logically, if women and men who are married are reporting different rates, misreporting must be present. Either married men are over reporting HGO, women are underreporting, or both. Viable explanations for the disparity in reporting should, obviously, tend toward the second explanation (Ludwig et al., 1998:1715). There is no theoretical reason for men to report HGO when it is untrue, but there are a variety of reasons for women to report lower rates, as previously mentioned. Marriage should effectively double the number of people who should report HGO through the inclusion of wives in the household (or vice versa). That is, there should now be two respondents who would report household gun ownership. Males might be more likely to be personal gun owners, but the ownership is now part of a two-adult household. It

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follows, then, that married men and married women should have exactly the same odds of reporting HGO. Additionally, the household population variable is no longer significant indicating that it has no bearing on HGO in married households. Of course, this is likely because most of the variation in this variable is removed. That is, they generally have a higher population than households without a couple cohabitating in residence. Race remains a significant predictor of HGO, as those in the nonwhite category have a 52% reduced odds of reporting. Education also remains significant. As one might expect, each additional year of education reduces the odds of reporting HGO by about 6.6%. Age, is significant, but as in the first equation, the effect is very small. One would expect that, over all, the respondents in the marriage category would be older than those who are not married. This lends support to the argument that as one ages there is a higher likelihood of accumulating wealth and durable goods such as firearms. The income variable remains significant, increasing the odds of HGO reporting by 8%, only slightly less than for all respondents. The “region at age 16” variables maintain a recognizable pattern in this equation. For married respondents we can observe an increase in odds from Midwest (91%) to West (109%) to South (169%) in comparison to the Northeast, replicating traditional findings and generally agreeing with the coefficients in the first equation. The “type of place” variables also display a recognizable pattern. There is a steady increase in the odds of reporting HGO when each of the areas is compared to respondents who reported living in an urban area at age 16. Living in the suburbs at 16, living in a small town at 16, and living in a rural area at 16 consecutively increase the odds of reporting HGO. Being from a rural area is the strongest predictor of HGO for married respondents, raising the odds more than twofold. The presence of children in the household also has no effect on whether married respondents report HGO. This differs from the model predicting HGO for all respondents but not if one controls for marital status. This provides further support for the finding that the effect of children on HGO is spurious when one controls for marital status. Finally, political views’ effect on reported HGO changes little from the first equation. In this case, an increase in self-reported, politically conservative beliefs increases the odds of HGO by about 11%. Finally, an overall reduction in HGO reporting is significant for only the last two years.

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Table 12. Logistic Fixed Effects Model on HGO for marriedª GSS respondents Selected years, 1976 – 2000; n = 11,181 Exp. β Variable

(SE)

Gender

0.850**

Exp. β Fixed effect dummy 1977

(.035) Hompop

1.040

1980

(.023) Education

0.934**

1982

(.008) Race

0.478**

1984

(.034) Age

1.006**

1985

(.002) Income

1.080**

1987

(.007) South16

2.686**

1988

(.157) Mid-West16

1.911**

1989

(.108) West16

2.092**

1990

(.142) Rural16

3.148**

1991

(.224) Smalltown16

1.892**

1993

(.128) Suburb16

1.260*

1994

(.088) Children

0.987

1996

(.061) Political Views

1.110**

1998

(.017)

2000 **p<.001

G² 1101.79

*p<.05

(sig.) <.001

Pseudo R² .088 a

BIC 14,244

Includes respondents cohabitating as married

(SE) 1.138 (.151) 1.125 (.151) 1.108 (.148) 1.087 (.146) 1.070 (.143) 1.138 (.154) 1.093 (.163) 1.140 (.165) 1.062 (.157) 0.990 (.145) 0.895 (.129) 0.979 (.129) 0.959 (.129) 0.744* (.100) 0.695* (.094)

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The next step is to determine whether this disparity in gender reporting has changed in its magnitude or intensity over time by interacting the Gender variable with the year dummy variables. The results of this analysis60 indicate that while the difference in reporting by gender is significant and non-trivial, it has not changed over the 16 years of the survey. Goodness of fit is assessed between the two models by differencing their BIC’s. The restricted model in Table 12 fits the data better by an absolute difference of 148.61 Types of Firearms The next three models present similar equations limited by the type of firearms that the married respondent reported as the household guns: Rifle, Shotgun, and Pistol. Tables 13, 14, and 15 report the findings of each of these equations. These tables will provide further insight into patterns of misreporting by gender, and provide some more general insight into potential differences in reporting for married respondents. Differences by type of firearm may also offer support of refutation of some of the theoretical premises that surround the Gender Gap explanations of reduced gun ownership over time. These analyses are presented separately because there are appreciable differences in their findings. Table 13 introduces the parameter estimates for household rifle reporting for married respondents. First, Gender predicts almost a 20% reduction in odds for women reporting a rifle in the household than men. Secondly, unlike the full HGO model in Table 12, an increase in the household population raises the odds of having a rifle in the home by about 7%. Race is an even stronger predictor of rifle ownership, reducing the odds of reporting by over two-thirds for married, nonwhite respondents. Most of the other variables maintain values similar to the overall HGO model with two exceptions. The “type of place” variables are even more pronounced with “rural at 16” increasing in magnitude even more than in the other equations, while still maintaining its place as the strongest predictor of ownership reporting. Also, being from the West and Midwest both increase the odds of reporting gun ownership. These 60

See Appendix B, Table B1 for the results.

61

An absolute difference of 2 to 6 is considered “positive” evidence, 6 to 10 is considered

“strong,” and >10 “very strong” (Long, 1997:112).

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findings are expected, and agree with earlier research as rifles are more strongly associated with membership in the gun sporting culture and are more useful for hunting in these areas. Lastly, there does not appear to be any significance in the time component in this equation. Table 13. Logistic Fixed Effects Model on HGO for marriedª GSS respondents - Rifle Selected years, 1976 – 2000; n = 11,166 Variable Gender Hompop Education Race Age Income South16 Mid-West16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

Exp. β (SE) 0.805** (.034) 1.072* (.025) 0.954** (.008) 0.290** (.025) 1.001 (.002) 1.068** (.007) 1.811** (.112) 1.541** (.093) 1.912** (.137) 3.364** (.264) 2.012** (.155) 1.372** (.111) 0.960 (.062) 1.098** (.018)

Fixed effect dummy 1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

**p<.001

G² 928.82

*p<.05

(sig.) <.001

Pseudo R² .074 a

BIC 13,823

Includes respondents cohabitating as married

Exp. β (SE) 1.119 (.150) 1.168 (.158) 1.281 (.174) 1.105 (.152) 1.237 (.167) 1.319* (.182) 1.293 (.196) 1.215 (.179) 1.257 (.191) 1.186 (.177) 0.899 (.135) 1.189 (.160) 1.036 (.143) 0.970 (.136) 0.927 (.130)

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Trends in American Gun Ownership Table 14. Logistic Fixed Effects Model on HGO for marriedª GSS respondents - Shotgun Selected years, 1976 – 2000; n = 11,164 Variable Gender Hompop Education Race Age Income South16 Mid-West16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

Exp. β

Exp. β

(SE) 0.697** (.030) 1.051* (.025) 0.939** (.008) 0.374** (.031) 1.003 (.002) 1.067** (.007) 2.494** (.156) 2.035** (.124) 1.310** (.099) 3.258** (.256) 1.957** (.151) 1.233* (.101) 0.939 (.061) 1.086** (.018)

(SE) 1.132 (.152) 1.162 (.158) 1.253 (.170) 1.161 (.160) 1.248 (.168) 1.317* (.180) 1.129 (.173) 1.245 (.184) 1.257 (.191) 1.305 (.196) 1.103 (.163) 1.118 (.151) 1.168 (.160) 0.955 (.133) 0.798 (.113)

Fixed effect dummy 1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

**p<.001

G² 1087.91

*p<.05

(sig.) <.001

Pseudo R² .090 a

BIC 13,630

Includes respondents cohabitating as married

The effects of HGO predictors on reporting shotgun ownership are reported in Table 14. Among the three types of firearms reported here, Gender has the most pronounced effect on reporting household shotgun ownership. Compared to married men, Married women have a 30% reduced odds of reporting a shotgun in the household, offering yet more evidence of the gender gap in reporting, despite not being in the form

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of a trend. “Type of place” and regional variables return to values quite similar to the overall HGO model. They are less pronounced than in the rifle reporting model with the exception of those respondents who lived in the West at 16. This does not differ from previous findings as shotguns are not as well suited to the geographic terrain in western states and are therefore less popular in that area (Dixon & Lizotte, 1987; Brennan et al., 1993). Finally, the time component in the shotgun equation shows no variation, indicating that there are no apparent trends or changes in shotgun reporting behavior over time. This is similar to the overall married HGO equation, but different from the rifle reports and, as we shall see, pistols as well. Table 15 details the equation predicting household pistol ownership reporting. Although one might expect pistol ownership to produce the highest levels of misreporting between male and female respondents for a variety of reasons, it does not. Even though handguns are smaller, easier to hide, most often used in crime, and perhaps carry the most stigma and contention of all types of firearms, married female respondents exhibit only about a 22% reduction in odds of reporting a pistol in the household compared to married males. While this is higher than overall HGO and rifle reporting it is also lower than household shotgun reporting. Most of the other predictors present values that are remarkably similar to overall HGO, rifle, and shotgun reporting. There are, however, two other notable differences. First, “suburb at 16” reverses direction and becomes insignificant indicating that household handgun reporting for respondents who live in suburbs at the age of 16 is not different than for respondents who lived in urban areas at 16. However, some difference should be expected because the suburb variable predicts higher ownership reporting in every other equation. The change could be due to a number of factors. First, handgun ownership could be concentrated among respondents from small towns and rural areas, therefore eliminating most handgun ownership in both suburban and urban areas. However, this is unlikely since most firearms owned for protection are handguns, and these are often found in areas of higher population concentration such as urban and suburban areas (Bordua & Lizotte, 1979; Lizotte & Bordua, 1980; McDowall & Loftin, 1983; Kleck, 1997). It is also possible that this change is part of the reason for the slight reduction in the reporting gender gap when compared to shotgun reporting. It could be that the social stigma

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attached to handguns causes greater reporting differences between rural / small town respondents and suburban / urban respondents. In these cases the gender difference would be slightly diffused by the overall reporting difference between respondents raised in areas with stronger ties to the gun culture and those who were not. Further analysis concentrating on the areas of respondent socialization will be needed to specify these possible relationships. Table 15. Logistic Fixed Effects Model on HGO for marriedª GSS respondents - Pistol Selected years, 1976 – 2000; n = 11,164 Exp. β Variable Gender Hompop Education Race Age Income South16 Mid-West16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

(SE) 0.777** (.034) 0.990 (.024) 0.970** (.008) 0.657** (.051) 1.007** (.002) 1.098** (.008) 2.814** (.186) 1.472** (.098) 2.189** (.167) 1.371** (.107) 1.317** (.100) 0.970 (.078) 0.962 (.064) 1.082** (.018)

Exp. β Fixed effect dummy 1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

**p<.001

G² 624.28

*p<.05

(sig.) <.001

Pseudo R² .053 a

BIC 13,001

Includes respondents cohabitating as married

(SE) 0.926 (.133) 1.197 (.170) 1.057 (.153) 1.126 (.163) 1.218 (.175) 1.393* (.199) 1.376* (.216) 1.365* (.209) 1.244 (.198) 1.066 (.170) 1.197 (.183) 1.309 (.183) 1.226 (.177) 0.997 (.146) 1.020 (.150)

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The final major difference between the handgun ownership equation and the others concerns the time component. Unlike any of the other equations there appears to be an actual rise in reporting of household handgun ownership in the mid 80’s. Although it is purely speculation, one might attribute this increase, at least in part, to an overall increase in the total number of handguns added to the U.S. gunstock in the years immediately preceding these surveys.62 This however is a somewhat difficult argument to make as the numbers of privately owned handguns have continued to rise steadily since that time as has the rate of available handguns (Kleck, 1997:96-97). The gender gap appears to operate in each of these equations regardless of the type of firearm reported. Even though there was no apparent trend in the gender gap in the changing parameter model for overall HGO, when the models for each type of firearm are compared, Gender seems to exert an even stronger influence than in the total HGO equation. In order to determine whether trends are operating in each of these equations separately, changing parameter models were calculated with interactions similar to those in the HGO model. The BIC’s for the rifle, shotgun and pistol changing parameter models are 13,945; 13,759; and 13,126 where the absolute differences are 122, 129, and 125 respectively. These differences all favor the fixed effect model as the best fit. Thus the changing parameter models offer no additional information. Nonetheless, the results are reported in Appendix B. Subgroup Analysis: Testing for Social Undesirability Bias Although no trends were evident in the analyses of gun reporting over time, the question of the reasons behind the gender gap remains unanswered. In order to test the possible explanation of social undesirability bias as a motivating factor for women or minority groups to underreport, two sets of fixed effects models are calculated and compared. If general differences in reporting exist on variables that are specifically meant to assess the level of gun culture, interpretation of these differences may lead to support for the social undesirability explanation. On the one hand, if no significant differences are noted between men and women reporting gun ownership who were living in rural areas or in the South at age 16, but differences are noted for those who were raised in suburban areas or the Northeast, this might support 62

For details on yearly additions to the U.S. gunstock see Kleck, 1997:96-97, Table 3.1.

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the social undesirability bias because the gap only exists in areas that are not traditionally part of the gun culture. This would indicate that external social forces are operating on those respondents from areas where gun ownership might be perceived as deviant. On the other hand, if respondents from these different areas with different patterns of gun ownership, cultural traditions, and perceptions about guns were to exhibit similar reporting discrepancies there would be little support for this explanation. Table 16 presents the first subgroup analysis. In this analysis the data for married or cohabitating respondents are split into four subgroups by censoring the data by gender and race. In the interest of readability, the only fixed effects, year variables presented are those that are statistically significant for one or more of the groups. The third and sixth columns in the table provide the z statistic for the crosscoefficient tests and significance levels. If the z score is significant, it indicates that the coefficients in the two separate equations are actually different from one another. In this case, household reporting for white men and women differs only on education and income. Moreover, these differences only indicate small changes in the magnitude of the effects for variables that have only marginal effects in the first place. There is no change in the direction of the effect, and there are no differences in the effects of any of the variables that would indicate the effect of socialization in a traditional gun culture. Therefore, this analysis does not support the social undesirability hypothesis. The equations presented in the fourth and fifth columns compare the same analyses for married men and women in the non-white category. These equations also offer little or no support for the social undesirability hypothesis. There are only three variables between the two equations with appreciable differences, and, in each of these cases, nonwhite women report HGO at higher rates than do nonwhite men. This might indicate that the men in this category are effected by the social undesirability bias, but women certainly are not. Neither of the models presented in Table 16 provide support for the social undesirability bias explanation of the gender gap in reporting. Further, these models do not motivate additional investigation of the type of place or region of socialization subgroups as none of these variables show difference in reporting by gender in the white subgroup and those that do have appreciable differences in the non-white subgroup deliver parameter estimates that differ in a direction that vigorously refutes the hypothesis.

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Table 16. Logistic Fixed Effects Model on HGO for marriedª GSS respondents Selected years, 1976 – 2000†; Subsamples split by gender and race; cross-coefficient ttests Exp β White Male (SE) Variable

Hompop

1.062 (.040) Education 0.914** (.011) Age 1.005* (.002) Income 1.096** (.012) South16 2.938** (.265) Mid-West16 1.910** (.157) West16 2.207** (.230) Rural 16 3.714** (.408) Smalltown16 2.002** (.207) Suburb16 1.274* (.138) Children 0.937 (.090) Political 1.102** Views (.026) 1984 1.098 (.226) 1998 0.802 (.163) 2000 0.839 (.173)

Test for Exp β Difference of Exp White β Female WM / WF (SE) z (Sig.)

1.051 (.078) 0.991 (.035) 1.019* (.007) 1.090** (.025) 5.138** (.835) 3.298* (.296) 2.987* (.235) 1.587* (.419) 0.784 (.206) 0.763 (.193) 0.877 (.210) 1.082 (.064) 0.782 (.704) 0.447 (.396) 0.285 (.262)

n=4,831 n=5,011

n=632

n=707

G² test

524.95

67.44

82.62

(sig.)

(<.001) (<.001)

(<.001)

(<.001)

Pseudo R²

.098

.092

.113

*P <.10

a †

0.699 (.242) -1.669* (.048) -0.430 (.334) 1.792* (.037) 1.113 (.133) 0.083 (.476) 0.385 (.350) 1.170 (.121) -0.431 (.333) -0.488 (.313) -0.703 (.241) -1.270 (.102) -0.493 (.311) 0.059 (.476) 0.787 (.216)

Test for difference of Exp Exp β Nonwhite β NWM / NWF Female z (SE) (Sig.)

1.106 (.078) 1.022 (.036) 1.023* (.007) 1.014 (.026) 1.305 (.390) 1.758 (.558) 0.952 (.372) 2.973** (.850) 1.469 (.406) 1.547 (.413) 0.704 (.171) 1.015 (.057) 0.135* (.128) 0.101* (.097) 0.112* (.106)

**P<.05

1.025 (.035) 0.943** (.013) 1.006* (.002) 1.067** (.010) 2.561** (.216) 1.892** (.154) 2.090** (.201) 3.104** (.332) 2.131** (.215) 1.371* (.144) 1.029 (.095) 1.151** (.028) 1.261 (.241) 0.789 (.152) 0.671* (.131)

Exp β Nonwhite Male (SE)

422.65 .071

0.491 (.312) 0.627 (.265) 0.393 (.347) -2.118* (.017) -2.942* (.002) -1.246 (.106) -2.011* (.022) 1.612 (.053) 1.648* (.049) 1.920* (.027) -0.646 (.259) -0.785 (.216) -1.345 (.089) -1.141 (.127) -0.705 (.240)

Includes respondents cohabitating as married Fixed effects (Years) presented only where one or more coefficients are statistically

significant

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Finally, further comparisons could be made between men and women by race, but such comparisons will not be made here. No logical test could be performed regarding a comparison of these groups and what the relationship of their respective response rates should be. Comparing them would render no useful information, confuse the issue of the gender gap in reporting, and be essentially inappropriate to this analysis. Summary As noted by other scholars (Kleck, 1997:100; Ludwig et al, 1998:1716), there is a gender gap in reporting HGO. Although none have estimated more than bivariate tests to assess the phenomenon, the preceding analyses offer strong verification that this gap exists. The evidence presented here cannot, however, confirm assertions that women are necessarily under reporting and that men are not over reporting except to say that the discrepancies appear most often among respondents who were not socialized in areas that are traditionally associated with gun ownership. Those who have noted the gap have also hypothesized that it might explain some part of the steep reduction in HGO reporting over the last few years of the GSS (Kleck, 1997:96; Ludwig et al, 1998:1715). This assertion is not empirically supported by these findings. None of the changing parameter models denote trends in the gender gap even though it is present in each of the fixed effect models. Ultimately, neither the hypothesis that a growing gender gap explains any part of the reduction of HGO, nor the hypothesis that the gender gap can be explained by purposefully incorrect survey responses by women due to social undesirability bias are in any way substantiated by this analysis. Reduction in Household Population This hypothesis supposes that a reduction in the population of American households explains a reduction in HGO (Smith, 1998:9; Smith, 1999:13). This is a relatively simple, reasonable, and logical hypothesis that is also easily tested using the GSS data. A reduction in the average household population would necessarily reduce the total number of persons that could own a gun and therefore the odds of HGO for that household. This is supported by the baseline model presented in Table 10 (p.73 herein). However, the second part of this hypothesis is not tested by this model.

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This hypothesis asserts that, first; there has been a reduction in the average population of households in the United States. This is supported by U.S. Census reports detailing a steady reduction in persons per household from about 3.3 in the mid-1960’s to about 2.6 today (2004b). Second, it should be correlated in some way with levels of HGO. It follows, then, that this change over time could account for some, or all, of the decline in reported HGO. In order to test this hypothesis, a changing parameter model was estimated with interactions calculated as the product term of the variable Hompop and the year dummies.63 The BIC for this model was calculated and compared to the BIC of the equation presented in Table 10. In a result similar to the gender gap trend analysis, the changing parameter model is not favored over the fixed effects model.64 In any case, the interactions’ parameter estimates, meant to describe a trend, are all statistically insignificant, indicating an actual drop in HGO over time. The model is presented in Appendix B (Table B5). These equations, and the comparison between the two, provide the necessary empirical test to support the theory that a change in household population has caused a reduction in reporting HGO. In the first test a correlation between HGO and household population indicates that household population does have an effect on HGO. In the second model the main effect remains while there is no apparent trend connecting the two over time. This indicates that the magnitude of the effect is unchanged over time; therefore, the known reduction in household population in the U.S. must correspond to a similar and related drop in HGO. Female-Headed Households The models necessary to test this theoretical explanation for reductions in HGO reporting are slightly different than those presented previously. These models do not include the Gender variable of the other models, because it is not necessary to test the theory. Additionally, the variable

63

As noted earlier all interactions were calculated with variables that were grand-mean

centered to avoid the ill effects of multicollinearity. 64

The difference in the BIC’s favoring the more general model found in Table 10 is 120.

A value of 10 or more is “very strong” evidence to reject the saturated model (Long, 1997).

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for female-headed households is highly collinear with the gender variable. The percentage of female-headed households has more than doubled between 1970 and 1997 (Bryson & Kasper, 1998:5), and women are less likely to be gun owners than men. Therefore, the increase in female-headed households could explain an actual reduction in HGO and still allow for the stability of PGO. Table 17 presents a fixed effects model including all GSS respondents predicting HGO and replacing the Gender with Female HHH. There is very little in this equation that is substantively different than the baseline model presented in Table 10. All of the predictors of HGO are significant with very similar magnitude and direction of the effects of place, region, income, education, household population, race, and political views. There is one conspicuous exception, however. Whereas the presence of children reduced the odds of HGO (when not controlling for marital status) in the baseline model, it has no effect whatsoever in this model. Additionally, there is the main variable of interest that is not included in the baseline model, Female HHH. In this case, female-headed household have 69% lower odds of reporting HGO than male-headed households. This is an enormous difference, and fulfills the first part of testing this theory. There is a strong correlation between female-headed households and reporting HGO. As in the previous test, the next step is to compute a changing parameter model to assess the relationship over time. Consequently, a changing parameter model is estimated with interactions calculated as the product term of the variable Female HHH and the year dummies.65 The BIC for this model was calculated and compared to the BIC of the equation presented in Table 10. In a result similar to the trend analyses for gender gap and household population, the changing parameter model is not favored over the fixed effects model.66 Also, the interactions’ parameter estimates, meant to describe a trend, are all statistically insignificant except for the last year in the analysis. The model is presented in Appendix B (Table B6).

65

All interactions were again calculated with variables that were grand-mean centered to

avoid the effects of multicollinearity. 66

The difference in the BIC’s favoring the more general model found in Table 17 is 111.

A value of 10 or more is “very strong” evidence to reject the saturated model (Long, 1997).

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Table 17. Logistic Fixed Effects Model on HGO for all GSS respondents including female heads of household Selected years, 1976 – 2000; n = 12,935 Exp. β Variable Female HHH Hompop Education Race Age Income South16 Mid-West16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

(SE) 0.313** (.016) 1.112** (.025) 0.931** (.007) 0.532** (.035) 1.006** (.001) 1.094** (.006) 2.758** (.164) 1.792** (.103) 1.852** (.129) 2.975** (.205) 1.758** (.117) 1.276** (.089) 0.968 (.065) 1.098** (.016)

Exp. β Fixed dummy 1977

effect

1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

**p<.001

G² 1947.88

*p<.05

(sig.) <.001

Pseudo R² .153

(SE) 1.179 (.139) 1.132 (.129) 1.215 (.139) 1.153 (.134) 1.168 (.133) 1.139 (.130) 1.010 (.130) 1.316 (.167) 1.234 (.159) 1.044 (.132) 1.162 (.145) 1.088 (.120) 1.113 (.124) 0.907 (.101) 0.836 (.101)

BIC 15,284

These equations, and the comparison between the two, provide the necessary empirical test to support the theory that a change in the proportion of female-headed households in the United States has caused a reduction in reporting HGO. While the first hypothesis, a correlation between HGO and female-headed households, is supported there is no apparent trend denoting a change in the reporting behavior of female-headed households over time. This, combined with the

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knowledge that the proportion of female-headed households has doubled over the last 20 years, provides evidence in support of the hypothesis that an increase in female-headed households accounts for a large amount of the overall decrease in HGO reporting. CONCLUSION Although none of the theoretical assertions regarding measurement error in the recent reduction in HGO were supported in these analyses, valuable information and insight into the nature of the GSS data and HGO reporting have been brought to light. Both the female-headed household and household population hypotheses were supported and appear to explain much of the drop in HGO reporting. In addition, the multivariate analysis of HGO reporting over 16 years has shown that the downward trend in reporting may not be as severe as one would infer from simply observing the percentage of reports from each year. Furthermore, the difference between HGO and PGO reporting where children are concerned is somewhat unexpected and quite interesting. Finally, future research should be positively informed by the results of these findings as each of the major theoretical explanations for reductions in HGO reporting, as well as at least one additional option, have been explored, tested, and, in some cases, refuted. In reviewing the results of Table 3 in the last chapter, one is initially struck by the obvious reduction in HGO reporting throughout the 16 years used in this study. However, when reviewing the model in Table 10 that uses well accepted predictors of gun ownership, this reduction is much less obvious. In fact only the year 2000 data shows a downward trend at all. None of the other years included in this model are significantly different than the HGO levels reported in 1976. This indicates that while the numbers of respondents who are associated with a combination of demographic variables may have shifted, these demographic predictors explain much more of the decline than the passage of time in the fixed effects models.67 Future research should continue to test these models with subsequent years of the GSS once 67

In order to explore the possibility that shifts in the demographic control variables might

offer some empirical explanation for reduced HGO; they were included in a variety of changing parameter models. These exploratory analyses lacked theoretical motivation and are not reported in this study. No combination of traditional demographic predictors and HGO produced a trend with any explanatory value.

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the necessary methodological reports comparing the new definitions of race and findings of computer aided survey techniques to older versions of the survey are published. One of the most interesting findings reported here is the counterintuitive relationship between PGO and children in the household, reported in Table 11. The possibility that the presence of children in the household could increase the odds of an adult responding as a personal gun owner is unexpected and surprising to say the least. This finding has prima fasciae value, but demands future development and study. Although outside the scope and purpose of this particular study, future research should use the original GSS variables of BABIES, PRETEENS, and TEENS to determine whether this effect is concentrated by age group. One should expect that children in the TEENS category would have the greatest effect on adult respondents reporting personal gun ownership in such a situation. Finally, the results from each of the theory tests rejected the explanations for a reduction in HGO due to measurement error, but did not reject those hypotheses that rely on changes in household demographics to explain the decreases in reporting HGO. The gender gap in HGO reporting was confirmed, but there is no trend to explain a gender-based reduction of HGO reporting over time. Likewise, the most common explanation for systematic underreporting of HGO, social undesirability bias, found equally little support. More innocuous explanations, such as women not considering an antique firearm or heirloom to be a firearm and so not reporting it as such, and women being unaware of a firearm in their own home as potential remain possible explanations for the gender gap. While these analyses point to the need for further assessment of these explanations, neither is testable with the current GSS data. This is indeed unfortunate. Conversely, hypotheses that link reduced HGO reports to decreases in household population and increases in female-headed households were equally supported by these analyses. As in the case of the gender gap theory, both were found to be strong predictors and were heavily correlated with HGO. However, in contrast to the gender gap hypothesis, both of these variables explain changes in reporting over time. While some of these promising theories have been rejected, the potential value of these tests to those interested in better understanding firearm ownership in the U.S. remains high. With the exception of the female-headed household theory, each was touted in recent scientific

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literature as the most likely explanation for a reduction in HGO reporting. Testing these theories is the first step toward a better assessment and understanding of these data and patterns of change in American gun ownership over time.

CHAPTER 9

Understanding HGO

CONCLUSION & DISCUSSION The primary purpose of this work has been to explore, evaluate, and describe possible errors in the measurement of household gun ownership in the GSS over a period of 16 years. The secondary purpose is to offer some description of demographic trends in firearms reporting that are indicative of actual trends in ownership. This is especially difficult when reporting error is taken into consideration. The presence and character of error certainly have implications for the various assumptions that are made about declining gun ownership and its relationship with attitudes concerning gun policies. While there is almost certainly measurement error present in the GSS, such as reports of household gun ownership based on the gender gap, the quantity and character of this error does not appear to have changed in the 16 years of the survey that were analyzed here. Understanding the dynamics of changes in HGO over time is of vital importance. Much of what is understood regarding crime, injuries, accidents, suicide, and the potential benefits of firearms is based on the concepts of risk, exposure, and prevalence of firearms in the general population. These arguments rely heavily on survey measurement of HGO for base rates of exposure, risk and availability. It is surprising, then, that so little attention has been paid to the possibility that there may be systematic, measurable error present in the survey estimates that would adversely effect the conclusions drawn from these types of data before now. Although utilized, and generally revered, for some time almost no consideration has been paid to the validity or reliability of these data. These deficiencies have been most recently noted by the Committee on Law and Justice of the National Research Council who stated: 129

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Trends in American Gun Ownership The committee is not aware of any research assessing the magnitude or impact of response errors in surveys of firearms ownership and use.” [And] “Concerns about response errors in self-reported surveys of firearms possession and use require much more systematic research before surveys can be judged to provide accurate data to address critical issues in the study of firearms and violence…Without systematic research on these specific matters, scientists can only speculate. (2005:36, 37)

In sum, much of what we know about firearms, who legally owns them, how many there are in the U.S., how they are used, etc. hinges on this one vital measure. Before now, much of our insight has consisted of conjecture and speculation. This book begins to address this shortcoming, but it is only a beginning. Because understanding HGO is important in social science, public health, and policy research, the attention of each of these fields should be brought to bear on the topic. Most of the analyses concerning the risks or benefits of gun ownership rely heavily on this measure, particularly the measure provided by the General Social Surveys. While these data should be examined first, continued inquiry and examination should progressively focus on all of the available data in this area by building on the research detailed here. Little attention has been given to historical and cultural influences on gun ownership and reporting. A better understanding of the role that firearms have historically played in the U.S. informs our expectations of current and future patterns of ownership. Many of the historical investigations that examine gun ownership explicitly imply that the prevalence of guns can be ascribed to a need for guns either real or perceived. This is probably not much different from today, and may be one of the underlying reasons that some geographic areas in the U.S. are typically associated with higher levels of gun ownership than others. The perception of need is a concept that, while difficult to measure well, deserves better treatment and scientific investigation. It is almost certainly a better explanation than those that focus purely on subcultural violence. This concept also has the added benefit of bridging the observed and theoretical gap between legal and illegal firearms possession and use. The strength of a perception of need and the cultural influences that drive this perception for both law-abiding citizens and criminals deserves much more attention from researchers.

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This is especially true of scientists who try to assess the efficacy of modern violence reduction programs focusing on firearms criminals. Historiography has also provided some relatively new conclusions that necessitate further investigation. For instance, the observation that private demand for technologically superior firearms drove development in the American gun industry, thereby influencing the industrial revolution and foreign military demand, is an interesting assertion and one that deserves more than cavalier treatment. Technological efficacy is not a novel idea when attempting to explain individual motivation for firearms ownership and use, and this finding supports that proposition. While interesting, this statement requires further investigation before we assume its veracity. In any case, the importance of historical reference in understanding gun ownership should not be carelessly rejected. The characteristics of firearms ownership, and the culture surrounding it, have gone through a number of incarnations throughout American history. It seems clear that private gun ownership maintained its prevalence and importance in American culture throughout each of these historical periods. It also seems that the pervasive roles of private firearms, whether in rebellion, hunting, or self-defense, indicate very high rates of private gun ownership historically. Modern, scientific research into the contemporary nature of HGO supports similar conclusions. In general terms, we still define “gun culture” by the demographic characteristics of its members, and perhaps for good reason. According to most descriptive accounts of gun owners in the U.S., we know that members of the gun culture tend to be white, male, rural, Protestant, and middle class (Bordua & Lizotte, 1979:171; Wright et al., 1983:122; Kleck, 1997:70). Gun ownership is more heavily concentrated in the South and Southeastern regions of the country (Wright et al., 1983:122; Kleck, 1997:70), where gun owners are often socialized to become part of the gun culture by their parents who owned guns (Lizotte & Bordua, 1980:236-239; Lizotte et al., 1981:502; Wright et al., 1983:122). National surveys such as Gallup, the General Social Surveys (GSS), the National Gun Policy Surveys (NGPS), and the National Study of the Private Ownership of Firearms (NSPOF) have provided much of our knowledge about legal gun owners today. Comparing their findings to early accounts of gun ownership is as if viewing two sides of the same coin. Gun ownership in the past and present tends to be uncannily similar. Understanding these connections has allowed us

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to build on past historical and scientific research to employ new techniques that better explain these relationships and their impact on reporting behavior. More specifically, a comprehensive understanding of how these demographic characteristics operate to predict gun ownership has guided this research in its attempt to test a variety of theories explaining a reduction in HGO. Armed with this knowledge, we have tested several hypotheses. Nonetheless, even with the analyses performed here, little is known regarding other threats to the validity HGO measures. We do know, however, that the initial analyses produce no support for any of the explanations that rely on changes in measurement error to explain declining levels of HGO. It appears that the large drop in the reported HGO over the last 20 years may not be nearly as pronounced as originally considered. It is also not likely that there has been any significant reduction in HGO reporting by those members of the population that have been identified as part of the “gun culture.” While household demographics may be changing in the U.S., the demographics of household gun owners are not. Even though the General Social Surveys (GSS) reported HGO at a rate of at least 46% until 1989, but only 32% in 2000, we have seen that the only years that show significant declines are 1998 and 2000 when controlling for the traditional correlates of HGO. This certainly indicates that we should continue to watch this trend closely, but it does not point to a severe downward trend signifying the end of gun owning households in the U.S. This is because shifts in ownership levels can be ascribed to changing demographics in the U.S. over the same time period. Assessment of subsequent survey years will be crucial in monitoring these trends. These findings also agree with periphery indicators of gun ownership, such as estimates of the “civilian gun stock.” Because approximation of the gun stock ranges from at 230 to 280 million firearms in private hands, it is difficult to imagine that the only explanation for this increasing stock of firearms is that more guns are concentrated in fewer homes (Cook & Ludwig, 1997:1; Kleck, 1997:96-97). Analysing the Drop in HGO As previously established, there appears to have been a precipitous drop in the level of HGO in the U.S. over the last 20 or so years

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(Legault, 2004; Davis & Smith, 2003; Smith, 1999). In these data, HGO reporting decreased by about 14% for all respondents and 15% for married respondents between 1976 and 2000. A few researchers have addressed this phenomenon and have offered some explanation for it. And yet, until now, there has been very little in the way of empirical testing of the hypotheses that might explain the change. When we do conduct analyses controlling for the demographic predictors of HGO, the 2000 GSS is the only year that is significantly different than 1976 for all respondents. Furthermore, only 1998 and 2000 are significantly different from the 1976 data for the married respondents. This indicates that the reduction may not be so prominent when the correlates of HGO are included in the equation. Understanding past research and establishing baselines from which we can further our understanding of these reporting behaviors is important. However, in order to conduct this type of analysis, it is important that we move beyond our current understanding and crucial that we use the types of data and methodologies that will facilitate new discoveries. The Right Data The GSS is eminently appropriate for the study of gun ownership across time. In addition to the large sample size yielded by the more than 43,000 individual survey interviews that have been conducted, replication allows us to examine aspects of data quality as well as test hypotheses that depend on time series techniques. For instance, in this case, the analysis of over 18,000 respondents who were asked questions regarding Household Gun Ownership from 1976 through 2000 has provided new and valuable information on the topic. The appropriate methods and data for investigating changes in HGO over time are those that are designed and intended for time series analysis. Difficulties that arise when one considers the non-Normal distribution of gun ownership reports must be dealt with by using specific statistical techniques. Fortunately, methods that are suitable for this type of analysis have recently become available in social science. These multi-level models, commonly referred to as fixed effects and changing parameters models, have been exceptionally appropriate for this inquiry. Additionally, we should expect that they will also be used for other, analogous research questions with increasing frequency.

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The Right Methods Using the GSS data has taken advantage of data that are, indeed, wellsuited for understanding HGO. However, data alone are not sufficient in developing a deeper understanding of trends in American gun ownership. It is equally critical that quantitative methods, that demonstrate the ability cope with the unique nature of these data while taking advantage of its inimitable strengths, are applied. The use of fixed effects and changing parameter models has addressed the non-Normal nature of the GSS data, while still taking advantage of the information available throughout the multiple years of the GSS. These models have also allowed for a more comprehensive understanding of the outcomes while other relevant variables are held constant. Finally, statistical tests associated with these models allow for a clearer, more detailed understanding of the outcomes. By determining whether or not the findings in the various analyses add new, unique information or simply add superfluous parameter estimates without advancing our understanding of HGO reporting, some of the possible confounding factors of time have been eliminated. Thus, the methods have afforded the opportunity to add a genuinely new understanding of trends in American gun ownership. Trends in American Gun Ownership The hypotheses offered to explain the attrition of HGO are the reduction in the size of household populations in the U.S., an increasing gender gap (including social undesirability bias), an increase in femaleheaded households, and the urbanization of America (Smith, 1999:9; Cook & Ludwig, 1997:11). Although the latter has not been tested empirically due to logical inconsistency, each of the others has. An association between HGO and household population over time is supported. The attempt to discern a trend through the use of the changing parameter model failed to detect any correlation over time. Because there is no change over time, the main effect of household population has not changed. This information, combined with the knowledge that there have been measurable decreases in U.S. household populations over the time in question, offers strong substantiation for this explanation in the GSS data. In other words, a decrease in household populations in the U.S. partially explains a reduction in HGO.

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Some researchers have also pointed to the disparity between men and women when reporting HGO on three different surveys, finding that husbands report a 9% higher rate of HGO than wives on face-toface surveys such as the GSS, on average, and that this disparity has grown over time (Kleck, 1997:67; Ludwig et al., 1998:1717). Of course, husbands and wives do not report at the same levels and there appears to be some systematic difference in their reporting. Despite the fact that this should not be the case, married women do appear to underreport as compared to men. This continues to be true even when including additional corollary explanations that predict HGO. Again, as in the case of the household population hypothesis, there is no indication that underreporting by women has changed at all in the 16 years of the GSS data that are examined here. The absence of a trend in this case, however, does not explain a reduction in reporting HGO because there is no external evidence of changing trends in the numbers of women in married households. This does not explain, however, why there would be any difference in reporting HGO by gender for married couples; while there is no apparent trend, the difference is quite pronounced. It is possible that men own relic or heirloom firearms of which their wives have no knowledge or do not consider them to be “real” firearms. It is equally possible that there are working firearms in the home of which women are simply unaware. While these scenarios certainly must be true in some cases, it is still unlikely that it would explain the large disparity in reporting among married couples in its entirety. It is unfortunate that these scenarios are not discernable for any other form of misreporting in the GSS data or any current measure of HGO. Another possible explanation for the gender-based HGO reporting disparity mentioned by Ludwig et al. is that the social undesirability of being a gun owner could cause women to report a gun in the house less frequently than men (Ludwig et al., 1998:1715). Although there is no literature that examines the assumption that being a gun owner carries a stigma, one might assume that the negative portrayal of gun ownership in modern media could produce this effect. In addition, Ludwig et al. add that women tend to be “more likely to be anti-gun than men” (1998:1715), and, of course, women underreport HGO as compared to men. This is a difficult hypothesis to test, and the situation of underreporting HGO is quite unique to other studies assessing social undesirability bias. Even though there has been some past substantiation examining limited time periods of GSS data (Legault,

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Forthcoming), there is no confirmation in these analyses that this bias has an effect on the reporting behavior of married women regarding HGO. The final explanation tested further illuminates our understanding of the matter. It appears that an increase in female-headed households has caused a decrease in HGO. Similar to the household population hypothesis, this is not a function of misreporting or underreporting, but rather a change in demographics that explains the decrease in HGO while allowing for the relative stability of PGO. The fact that the proportion of female-headed households with children has more than doubled over the past 30 years in the U.S. lends additional credibility to this explanation. As in the other propositions that have been tested here there is a strong association between female-headed households and a reduction in the odds of reporting HGO, and this relationship has not changed over time. Indeed this adds to the overall evidence that changes in U.S. household demographics explain a large part of the observed reduction in HGO reporting. Overall, this evidence strongly suggests that a decrease in household populations and an increase in the proportion of femaleheaded households have both contributed to a reduction in HGO in the U.S. Also, a gender gap in reporting is due to reporting error, but this gap has been constant over the years of the GSS that are examined here and does not explain a drop in HGO reporting. Further, social undesirability does not appear to explain the gender gap in reporting. All of these observations also lend themselves to the conclusion that there has been little or no change in the traditional demographic of gun owning households. PROPOSITIONS FOR FUTURE RESEARCH These tests have served to improve our scientific understanding of household gun ownership in the U.S. and HGO reporting behavior. Nonetheless, this should only be the beginning of continuing research in this area. There are additional hypotheses that should be addressed by historians regarding the role and prevalence of firearms in American history. Also, future years of the GSS should be included in these statistical models to lend strength to these findings, other trends that explain HGO and reporting should be explored to include issues of mobility and current residence, the perception of a need for firearms,

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and the interaction of gender on these factors. Additional specification of these models by type of firearm reported should also continue. Historical research should investigate hypotheses of the influence of private firearm ownership and demand on the technological development of firearms as well as their potential influence on American industrial development in general. More rigorous examination of these assertions demands primary source research that can support or refute observations positing that private demand for technologically superior firearms fuelled development that allowed U.S. firearms to be in such high demand throughout the world at the end of the 19th century. Including all available years of the GSS in this study is impractical due to a change in survey mode and a drastic change in the reporting method of race. However, as soon as methodological reports become available to inform researchers of the effects of these changes, these years should be included in these models. This would provide additional indications of trends that might begin later in the data. At the very least it will provide additional statistical power when testing complex models. To truly understand the gender gap in reporting would require modules to be added to the GSS in the future. These additions would need to ask detailed questions designed to disentangle the relationship between ownership, reporting, and gender. Perhaps the simplest method of discovering where these differences are actually occurring and why would be to include these questions in the verification phase of the GSS. In the verification phase, called “Reinterviews,” interviewers conduct a second interview of the original GSS respondent from a selected household. This, in effect, creates panel data and allows for methodological studies of reliability, cognition, question wording and evaluation of context effects (Davis & Smith, 1992:25). In this case, when interviewers question selected households that have already completed the GSS questionnaire; they could include questions about gun ownership to adults other than the initial respondent in married households. When misreporting is discovered reasons for the discrepancy should then determined.

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Examining the data for additional trends that explain changes in HGO is extremely important.68 Including changes in mobility and the effects that this might have on those who were raised in areas with high levels of gun ownership and later moved to areas of low gun ownership and vice-versa could increase our understanding of this phenomenon. Although this would probably not explain reductions in HGO it could possibly lead to a better understanding of the gender gap hypothesis if social undesirability bias were operating. As unlikely as this hypothesis might be, it should not be dismissed out of hand with only one test. Allowing for demographic mobility and attempting to use this to explain the gender gap would provide an additional test and provide greater confidence in these findings if further rejected. Finally, research should continue to examine HGO by type of firearm. As we have seen here, there are differences in reporting patterns based on the type of gun being reported. Giving attention to this type of fine detail could provide insight into HGO reporting that has previously been overlooked. Therefore, any study including each of the two aforementioned suggestions should include examination by type of firearm separately. SUMMATION HGO is an important measure in sociology, criminology, public health, policy, and economic research. Much of the analyses concerning the risks or benefits of gun ownership rely heavily on this measure, particularly the measure provided by the General Social Surveys. There appears to have been a large drop in the reported HGO over the last 20 years. By using multiple years of the GSS, tests of the gender gap/social undesirability bias, reduction in household size, and the increase in female-headed households hypotheses were performed. These tests have provided valuable information and add to the current scientific knowledge regarding HGO as well as the data from which the measures of HGO are derived. We now know that although measurement error is present it is constant over time and likely not producing a change in HGO. Conversely, demographic changes in 68

Exploratory analyses were performed, including changing parameter models in an

attempt to find trends in the region and “type of place” variables. None challenged the fixed effects models and no trends were evident. Because of this, and because they were outside the stated scope of this work, they were not reported here.

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American households likely are producing measurable changes. This also indicates that there have not been any major shifts in gun ownership among the demographics that have always represented a majority of gun owners in the U.S. Evidence provided in this work fully supports the recommendations of the National Academies of Science (2005). Finally, there is a large degree of observable measurement error in the GSS data regarding HGO. In household where there are couples that are married or cohabitating as married there are large discrepancies in reporting between men and women. Researchers using this measure should allow for this discrepancy in their analyses as it would imbue a severe downward bias if it was uncorrected. Gun ownership and the reporting of gun ownership in surveys represent complex problems. Simple explanations seldom offer a great deal of enlightenment. Nevertheless, these types of tests are the first step in understanding the most important measure in the social-scientific study of firearms, gun violence, gun ownership, and gun policy.

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Tonso, William R. (1982). Gun and Society: The Social and Existential Roots of the American Attachment to Firearms. Lanham, MD: University Press of America. Tonso, William R. (1983). Social science and sagecraft in the debate over gun control. Law and Policy Quarterly, 5:325-43. U.S. Census Bureau (2004a). 2000 Census of Population and Housing, Population and Housing Unit Counts. PHC-3-1, United States Summary. Washington DC. U.S. Census Bureau (2004b). Annual Social and Economic Supplement: 2003 Current Population Survey, Current Population Reports, Series P20-553. America’s Families and Living Arrangements: 2003. Washington DC. U.S. Department of Justice, Federal Bureau of Investigation (2002) Crime in the United States online, 2002. Retrieved March 03, 2004 from: http://www.fbi.gov/ucr/02cius.htm. Vizzard, William J. (2000). Shots in the Dark: The Policy, Politics, and Symbolism of Gun Control. Lanham, MD: Rowman and Littlefield. Weil, Douglas S. and David Hemenway (1993). I am the NRA: An analysis of a national random sample of gun owners. Violence and Victims, 8:353-65. Williams, J. Sherwood and John H. McGrath III (1978) A Social Profile of Urban Gun Owners. In James A. Inciardi and Anne E. Pottinger (Eds.) Violent Crime Historical and Contemporary Issues (pp. 51-58) Sage publications. Wooldridge, Jeffery (2002). Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press. Wright, James D. and Linda L. Marston (1975). The ownership of the means of destruction: Weapons in the United States. Social Problems, 23:93-107.

150

Bibliography

Wright, James D., Peter H. Rossi, and Kathleen Daly (1983). Under the Gun: Weapons, Crime, and Violence in America. New York: Aldine. Wright, James D. (1995). Ten essential observations on guns in America. Society, 32:63-68. Wyant, Brian R. and Ralph B. Taylor (2007). Size of household firearm collections: Implications for subcultures and gender. Criminology, 45(3):519-46. Young, John T., David Hemenway, Robert J. Blendon, and John M. Benson (1996). The Polls – Trends: Guns. Public Opinion Quarterly, 60:634-49. Young, Robert L. (1986). Gender, region of socialization, and ownership of protective firearms. Rural Sociology, 51(2):16982. Young, Robert L. David McDowall, and Colin Loftin (1987) Collective security and the ownership of firearms for protection. Criminology, 25(1):47-62.

Appendix A

GSS QUESTIONS (Davis & Smith, 2003) This appendix lists frequencies for each of the variables used in the analysis. Where appropriate, corresponding interview questions are listed. GSS variables that are reported without asking questions (interviewer reported) are listed as such. Finally, all frequencies and categories reported in this appendix are calculated by the author from recoded data used for analysis. Therefore, these data may not match those reported in the GSS Codebook. Missing cases and categories are omitted, as they are omitted from the analysis. All reported question numbers and page numbers refer to the GSS Codebook (Davis & Smith, 2003).

151

152

Appendix A

Appendix A tables Q. 237 OWNGUN (p. 257) “Do you happen to have, in your home (IF HOUSE: or garage)

belong to you?”

69

any guns or revolvers?” No

69

Q. 237B ROWNGUN (p. 258) “Do any of these guns personally

HGO

No

Yes

1976

779

697

1976

n/a

1977

748

771

1977

n/a

n/a n/a

1980

760

695

1980

250

412

1982

1019

810

1982

261

509

1984

795

662

1984

285

375

1985

842

678

1985

232

443

1987

1032

770

1987

275

482

1988

571

389

1988

147

238

1989

555

475

1989

184

286

1990

520

387

1990

130

255

1991

583

393

1991

134

254

1993

614

452

1993

141

309

1994

1160

810

1994

253

555

1996

1142

772

1996

254

512

1998

1215

654

1998

222

427

2000

1231

603

2000

187

416

One of the complaints often voiced by critics of surveys on gun ownership concerns the

specific wording of gun-related questions.

For instance, this question may appear

confusing to some gun owners because it is redundant. A revolver is a gun, although a gun may not always be a revolver.

Appendix A

153

Q. 237A PISTOL – SHOTGUN – RIFLE (p. 257) IF YES: “Is it a pistol shotgun rifle or what?” CODE ALL THAT APPLY. no no no pistol pistol rifle rifle shotgun shotgun 1976

1151

321

1052

420

1054

418

1977

1204

313

1057

460

1042

475

1980

1113

338

1025

426

1019

432

1982

1434

394

1373

455

1340

488

1984

1144

314

1058

400

1051

407

1985

1170

350

1087

433

1102

418

1987

1371

431

1360

442

1328

474

1988

741

219

725

235

728

232

1989

768

261

746

283

743

286

1990

694

213

677

230

672

235

1991

774

199

730

245

722

251

1993

809

257

817

249

777

289

1994

1485

483

1485

483

1488

480

1996

1484

427

1464

447

1438

473

1998

1500

366

1476

390

1477

389

2000

1459

364

1459

364

1481

343

154

Appendix A

Q. 1188 DWELOWN (p. 1213) “(Do you/Does your family) own your (home/apartment), pay rent, or what?”

ALLCOHAB Author constructed from Household Enumeration Variables.

Own

Rent

1976

0

0

1976

236

508

1977

0

0

1977

469

1058

1980

0

0

1980

514

947

1982

0

0

1982

748

1107 910

Single

Cohab

1984

0

0

1984

562

1985

947

551

1985

580

949

1987

1102

667

1987

795

1009

1988

612

331

1988

602

874

1989

634

318

1989

582

943

1990

557

297

1990

553

814

1991

633

324

1991

626

885

1993

710

337

1993

630

974

1994

1222

673

1994

1247

1739

1996

1165

679

1996

1319

1559

1998

1159

666

1998

1322

1494

2000

1101

686

2000

1306

1486

Appendix A

155

Q. 23 SEX (p. 59) Interviewer coded 1976 1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

Male 669 693 641 779 598 688 778 638 660 604 636 685 1290 1285 1232 1229

Female 830 837 827 1081 875 846 1041 843 877 768 881 921 1702 1619 1600 1588

Q. 24 RACE (p. 60) Interviewer coded White 1976 1361 1977 1339 1980 1318 1982 1323 1984 1251 1985 1338 1987 1222 1988 1234 1989 1319 1990 1150 1991 1264 1993 1347 1994 2483 1996 2349 1998 2241 2000 2238

Non 138 191 150 537 222 196 597 247 218 222 253 259 509 555 591 579

156

Q. 34 HOMPOP (p. 66) Number of household members (total persons, recoded from Household Enumeration Variables) 1977

1980

1982

1984

1985

1987

1988

1989

1990

1991

1993

1994

1996

1998

2000

1

235

261

288

413

330

343

420

328

327

330

377

377

760

744

780

742

2

482

472

493

583

459

510

532

518

504

483

476

521

1001

988

937

929

3

257

286

259

351

278

269

340

250

269

221

275

295

527

454

483

459

4

237

257

248

268

219

230

293

232

259

203

241

267

447

453

394

433

5

171

138

107

149

121

120

144

100

106

89

98

107

170

152

145

160

6

60

72

38

54

47

35

59

37

35

28

29

31

55

71

62

64

7

24

19

22

18

11

13

16

10

21

14

14

5

25

29

16

15

8

17

12

6

15

3

7

6

3

8

4

2

1

6

8

9

2

9

7

9

1

3

2

3

4

3

5

0

2

2

1

4

4

8

10

2

2

6

3

3

4

5

0

3

0

2

0

0

1

2

5

11

1

2

0

1

0

0

0

0

0

0

0

0

0

0

0

0

12

1

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

13

3

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

Appendix A

1976

Family income on 1976 – 2000 surveys in constant dollars by category (Base = 1986). 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

1976

0

19

0

0

101

0

0

85

0

60

0

90

66

182

0

310

205

128

0

148

0

1977

16

0

0

53

0

0

79

0

53

0

60

0

137

114

158

130

217

173

170

0

38

1980

18

0

0

50

0

59

46

0

54

50

0

54

78

114

204

109

192

0

269

0

61

1982

31

0

59

0

83

71

64

63

0

54

95

0

150

252

84

199

230

0

161

83

0

1984

20

0

32

44

31

0

47

30

41

55

0

0

104

186

173

85

206

168

0

120

0

1985

10

0

31

46

48

44

60

33

0

61

0

87

92

141

168

0

251

185

0

162

0

1987

16

0

51

41

57

45

47

55

0

78

0

107

102

147

180

133

237

141

98

130

0

1988

20

25

0

23

40

42

35

42

54

0

83

0

81

124

139

116

212

124

77

120

0

1989

14

18

0

17

32

33

57

0

49

0

87

0

79

221

65

118

194

127

105

164

0

1990

6

13

0

53

29

30

27

43

0

73

0

0

115

135

147

110

194

82

0

172

0

1991

11

26

31

35

39

29

23

38

0

76

0

82

97

188

112

94

235

86

86

80

0

1993

17

20

25

34

34

53

0

39

69

0

77

0

122

139

98

225

133

114

108

0

160

1994

23

32

36

40

88

42

80

0

131

0

108

0

233

262

409

163

308

227

183

271

0

1996

26

35

18

74

42

31

77

0

119

124

0

104

82

407

218

185

490

200

0

329

0

1998

36

32

24

67

33

47

59

94

0

98

0

103

202

300

200

175

456

210

230

0

136

2000

30

32

45

29

73

74

0

103

0

104

108

0

178

272

346

221

222

216

229

0

174

157

0

Appendix A

Q. 1326 REALINC (p. 1265)

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Appendix B

EXCLUDED MODELS This appendix details the various changing parameter models that were excluded from the main chapters of the book. Although they were not included in the text they are important. For instance, the lack of significance of the models testing the female-headed household and household population hypotheses each tell use that these measures did not change their impact on HGO reporting over time. Because we know that their impact did not change, that their value in the U.S. population changed, and that they have main effects when holding time constant, we also know that they each explain a portion of the overall drop in HGO reporting over time. Readers that are interested in the mathematical specification of these models should refer to Chapter 6. Readers that are interested in the conceptual specification of these models and their interpretations can find these details in Chapter 8.

159

160

Appendix B

Table B1. Logistic Changing Parameter Model on HGO for marriedª GSS respondents Selected years, 1976 – 2000 with gender interaction; n = 11,181

Centered Variable Interaction† Gender Gender x 1977 Gender x 1980 Gender x 1982 Gender x 1984 Gender x 1985 Gender x 1987 Gender x 1988 Gender x 1989 Gender x 1990 Gender x 1991 Gender x 1993 Gender x 1994 Gender x 1996 Gender x 1998 Gender x 2000 **p<.001 *p<.05 Pseudo R² .089 a

Exp. β (SE) 0.835** (.035) 1.180 (.314) 1.064 (.286) 1.190 (.318) 1.311 (.352) 0.897 (.239) 1.274 (.344) 0.887 (.265) 0.876 (.254) 0.838 (.248) 0.930 (.272) 1.031 (.296) 1.015 (.266) 1.021 (.272) 1.139 (.304) 0.866 (.234)

Variable Hompop Education Race Age Income South16 Midwest16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

Exp. β (SE) 1.042 (.024) 0.934** (.008) 0.479** (.034) 1.006** (.002) 1.080** (.007) 2.689** (.158) 1.912** (.108) 2.089** (.142) 3.152** (.224) 1.898** (.128) 1.264* (.089) 0.982 (.061) 1.110** (.017)

Centered Year Dummies† 1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

Exp. β (SE) 1.138 (.151) 1.125 (.151) 1.109 (.148) 1.084 (.146) 1.069 (.143) 1.138 (.154) 1.099 (.165) 1.143 (.166) 1.060 (.157) 0.990 (.145) 0.895 (.129) 0.979 (.129) 0.960 (.129) 0.744* (.100) 0.694* (.094)

G² 1113.35 (sig.) <.001 BIC 14,372

Includes respondents cohabitating as married

† Gender and year dummies are grand-mean centered to reduce the effects of multicollinearity interactions calculated from centered variables

Appendix B

161

Table B2. Logistic Changing Parameter Model on HGO for marriedª GSS respondents – Rifle Selected years, 1976 – 2000 with gender interaction; n = 11,166

Centered Variable Interaction† Gender Gender x 1977 Gender x 1980 Gender x 1982 Gender x 1984 Gender x 1985 Gender x 1987 Gender x 1988 Gender x 1989 Gender x 1990 Gender x 1991 Gender x 1993 Gender x 1994 Gender x 1996 Gender x 1998 Gender x 2000

Exp. β (SE) 0.791** (.034) 1.236 (.331) 1.235 (.334) 1.201 (.324) 1.348 (.369) 1.016 (.274) 1.041 (.285) 0.825 (.250) 0.939 (.276) 0.680 (.207) 0.909 (.270) 1.154 (.344) 0.864 (.231) 1.044 (.285) 1.408 (.391) 0.950 (.266)

Variable Hompop Education Race Age Income South16 Midwest16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994

1998 2000 G² 950.72

*p<.05

(sig.) <.001

a

Centered Year Dummies†

1996

**p<.001 Pseudo R² .075

Exp. β (SE) 1.073* (.025) 0.953** (.008) 0.289** (.025) 1.001 (.002) 1.069** (.008) 1.814** (.112) 1.541** (.093) 1.911** (.137) 3.363** (.264) 2.014** (.155) 1.375** (.112) 0.956 (.062) 1.098** (.018)

Exp. β (SE) 1.126 (.151) 1.172 (.159) 1.286 (.174) 1.107 (.152) 1.237 (.168) 1.321 (.182) 1.293 (.197) 1.214 (.179) 1.236 (.189) 1.182 (.177) 0.903 (.135) 1.180 (.159) 1.038 (.143) 0.972 (.136) 0.925 (.131)

BIC 13,945

Includes respondents cohabitating as married

† Gender and year dummies are grand-mean centered to reduce the effects of multicollinearity interactions calculated from centered variables

162

Appendix B

Table B3. Logistic Changing Parameter Model on HGO for marriedª GSS respondents – Shotgun Selected years, 1976 – 2000 with gender interaction; n = 11,164

Centered Variable Interaction† Gender Gender x 1977 Gender x 1980 Gender x 1982 Gender x 1984 Gender x 1985 Gender x 1987 Gender x 1988 Gender x 1989 Gender x 1990 Gender x 1991 Gender x 1993 Gender x 1994 Gender x 1996 Gender x 1998 Gender x 2000 **p<.001 *p<.05 Pseudo R² .091 .

a

Exp. β (SE) 0.687** (.030) 1.044 (.280) 0.827 (.225) 0.848 (.229) 1.172 (.322) 0.773 (.208) 0.967 (.263) 0.883 (.270) 0.824 (.243) 0.654 (.199) 1.002 (.300) 0.882 (.260) 0.846 (.226) 0.765 (.208) 0.924 (.256) 0.782 (.221)

Variable Hompop Education Race Age Income South16 Midwest16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

Exp. β (SE) 1.053* (.025) 0.939** (.008) 0.375** (.031) 1.003 (.002) 1.067** (.007) 2.499** (.157) 2.034** (.124) 1.305** (.099) 3.273** (.258) 1.964** (.152) 1.239* (.102) 0.935 (.061) 1.086** (.018)

Centered Year Dummies† 1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

Exp. β (SE) 1.133 (.152) 1.155 (.157) 1.247 (.169) 1.157 (.159) 1.236 (.167) 1.313* (.180) 1.125 (.172) 1.238 (.184) 1.236 (.189) 1.305 (.196) 1.098 (.163) 1.111 (.150) 1.157 (.159) 0.952 (.133) 0.789 (.113)

G² 1096.05 (sig.) <.001 BIC 13,759

Includes respondents cohabitating as married

† Gender and year dummies are grand-mean centered to reduce the effects of multicollinearity interactions calculated from centered variables

Appendix B

163

Table B4. Logistic Changing Parameter Model on HGO for marriedª GSS respondents – Pistol Selected years, 1976 – 2000 with gender interaction; n = 11,164

Centered Variable Interaction† Gender Gender x 1977 Gender x 1980 Gender x 1982 Gender x 1984 Gender x 1985 Gender x 1987 Gender x 1988 Gender x 1989 Gender x 1990 Gender x 1991 Gender x 1993 Gender x 1994 Gender x 1996 Gender x 1998 Gender x 2000 **p<.001 *p<.05 Pseudo R² .054 a

Exp. β (SE) 0.781** (.035) 1.731 (.498) 1.290 (.370) 1.495 (.434) 1.186 (.346) 1.365 (.393) 1.360 (.390) 1.307 (.412) 0.921 (.285) 1.196 (.382) 1.306 (.418) 1.769 (.540) 1.088 (.305) 1.317 (.379) 1.523 (.445) 1.534 (.451)

Variable Hompop Education Race Age Income South16 Midwest16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

Exp. β (SE) 0.992 (.024) 0.969** (.008) 0.658** (.051) 1.007** (.002) 1.099** (.008) 2.814** (.186) 1.473** (.098) 2.192** (.168) 1.375** (.107) 1.317** (.100) 0.972 (.078) 0.958 (.064) 1.081** (.018)

Centered Year Dummies†

1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

Exp. β (SE)

0.952 (.137) 1.216 (.175) 1.080 (.158) 1.143 (.168) 1.241 (.180) 1.418* (.205) 1.400* (.222) 1.364* (.213) 1.261 (.203) 1.085 (.175) 1.231 (.189) 1.318 (.187) 1.248 (.181) 1.017 (.150) 1.044 (.155)

G² 640.05 (sig.) <.001 BIC 13,126

Includes respondents cohabitating as married

† Gender and year dummies are grand-mean centered to reduce the effects of multicollinearity interactions calculated from centered variables

164

Appendix B

Table B5. Logistic Changing Parameter Model on HGO for all GSS respondents Selected years, 1976 – 2000 with household population interaction; n = 19,371

Centered Variable Interaction† Hompop Hompop x 1977 Hompop x 1980 Hompop x 1982 Hompop x 1984 Hompop x 1985 Hompop x 1987 Hompop x 1988 Hompop x 1989 Hompop x 1990 Hompop x 1991 Hompop x 1993 Hompop x 1994 Hompop x 1996 Hompop x 1998 Hompop x 2000

Exp. β (SE) 1.190** (.021) 1.031 (.060) 1.037 (.061) 1.116 (.065) 1.008 (.059) 1.075 (.062) 1.098 (.065) 1.117 (.082) 0.919 (.057) 1.043 (.075) 1.014 (.067) 1.004 (.067) 1.043 (.059) 0.942 (.055) 0.976 (.057) 0.926 (.054)

Variable Gender Education Race Age Income South16 Midwest16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

Centered Year Dummies† 1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000

**p<.001

G² 2,493.80

*p<.05

(sig.) <.001

Pseudo R² .126

Exp. β (SE) 0.589** (.019) 0.926** (.006) 0.488* (.026) 1.004** (.001) 1.114** (.005) 2.706** (.127) 1.817** (.083) 1.911** (.105) 3.022** (.168) 1.830** (.098) 1.275** (.071) 0.847* (.043) 1.121** (.014)

Exp. β (SE) 1.191 (.108) 1.102 (.101) 1.238* (.113) 1.143 (.105) 1.109 (.101) 1.173 (.108) 1.031 (.112) 1.089 (.109) 1.056 (.116) 0.956 (.100) 0.975 (.101) 1.008 (.089) 0.950 (.086) 0.788* (.073) 0.682* (.064)

BIC 23,763

† Household population and year dummies are grand-mean centered to reduce the effects of multicollinearity interactions calculated from centered variables

Appendix B

165

Table B6. Logistic Changing Parameter Model on HGO for all GSS respondents Selected years, 1976 – 2000 with female heads of household interaction; n = 12,935

Centered Variable Interaction† Fem HH Fem HH x 1977 Fem HH x 1980 Fem HH x 1982 Fem HH x 1984 Fem HH x 1985 Fem HH x 1987 Fem HH x 1988 Fem HH x 1989 Fem HH x 1990 Fem HH x 1991 Fem HH x 1993 Fem HH x 1994 Fem HH x 1996 Fem HH x 1998 Fem HH x 2000

Exp. β (SE) 0.309** (.017) 1.465 (.467) 1.029 (.319) 1.092 (.333) 0.941 (.293) 0.913 (.286) 1.454 (.446) 0.691 (.240) 1.133 (.377) 1.246 (.409) 0.736 (.250) 1.367 (.438) 1.118 (.335) 1.497 (.445) 1.258 (.378) 0.309** (.017)

Variable Hompop Education Race Age Income South16 Midwest16 West16 Rural16 Smalltown16 Suburb16 Children Political Views

Centered Year Dummies†

0.931** (.007) 0.532** (.035) 1.006** (.001) 1.094** (.006) 2.765** (.165) 1.802** (.103) 1.860** (.130) 2.983** (.205) 1.759** (.117) 1.279** (.089) 0.968 (.065) 1.099** (.016)

1977 1980 1982 1984 1985 1987 1988 1989 1990 1991 1993 1994

1998 2000 G² 1960.19

*p<.05

(sig.) <.001

Exp. β (SE)

1.112** (.025)

1996

**p<.001 Pseudo R² .154

Exp. β (SE)

1.245 (.163) 1.157 (.148) 1.247 (.159) 1.177 (.153) 1.179 (.152) 1.189 (.151) 1.011 (.147) 1.353* (.189) 1.270 (.177) 1.046 (.149) 1.200 (.163) 1.118 (.138) 1.154 (.142) 0.936 (.117) 0.823 (.103)

BIC 15,395

† Female heads of household and year dummies are grand-mean centered to reduce the effects of multicollinearity interactions calculated from centered variables

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Subject Index A

D

American Indians, 14, 16, 18, 23, 29 Autocorrelation, 88, 89 Automatic Rifles, 33

Destructive Devices, 33

E Education, 54, 58, 74, 75, 105, 107, 110, 111, 113, 114, 116, 118, 119, 122, 123 Ethnography, 11

B Bayesian Information Criterion, 88, 91, 105, 107, 111, 112, 113, 114, 116, 117, 121, 122, 123 Behavioral Risk Factor Surveillance System, 40, 54, 55

F Federal Firearms Act, 32, 34 Female-Headed Households, 7, 8, 56, 60, 67, 74, 75, 91, 121, 122, 123, 125, 134, 136 Firearm Crime, 23, 32 Firearm Importation, 15 Fixed Effects Model, 78, 85, 86, 87, 88, 90, 91, 92, 102, 105, 107, 108, 111, 113, 114, 116, 117, 118, 119, 121, 122, 124, 131, 132, 135 Flintlock, 24, 27 Franco-Prussian War, 26 Frontier, 12, 17, 18, 19, 20, 21, 23, 27, 28, 34

C Centers for Disease Control, 40, 54, 55 Changing Parameter Model, 78, 85, 86, 87, 88, 91, 92, 104, 106, 108, 117, 120, 121, 122, 124, 131, 132, 135 Civil War, 12, 21, 22, 25, 27 Civilian Gun Stock, 2, 3, 58, 130 Colonial America, 12, 13, 14, 15, 16, 17, 19, 20, 24, 29, 35 Colt, 19, 25, 26 Concealed Carry, 22, 31 Context Effects, 64 Crimean War, 25, 26 Culture, 11, 12, 36, 38, 39, 40, 42, 43, 45, 47, 57, 58, 59, 64, 65, 76, 113, 118, 129

G Gallup Poll, 5, 39, 41, 43, 44, 50, 51, 52, 59, 129 Gender Gap, 8, 51, 58, 60, 61, 62, 67, 73, 78, 90, 91, 96, 101, 108, 109, 112, 114, 115, 117, 118, 120, 121, 122, 125, 135, 136

167

168

Subject Index

General Social Surveys, 2, 4, 6, 8, 39, 41, 44, 46, 47, 51, 52, 53, 54, 55, 56, 59, 61, 62, 63, 64, 66, 67, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 85, 86, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 104, 105, 107, 109, 111, 113, 114, 116, 119, 120, 122, 124, 125, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136 Great Depression, 33 Gun Control, 1, 4, 7, 12, 28, 29, 30, 31, 32, 33, 34, 35, 39, 40, 41, 48, 51, 54, 61 Gun Culture, 2, 7, 11, 12, 13, 36, 38, 39, 40, 41, 42, 43, 44, 49, 55, 57, 59, 60, 63, 64, 65, 67, 76, 77, 109, 116, 117, 118, 129 Gun Ownership, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 17, 20, 25, 26, 28, 29, 31, 32, 34, 35, 36, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 71, 75, 76, 77, 78, 90, 94, 99, 101, 102, 103, 104, 106, 107, 112, 117, 124, 125, 126, 127, 128, 129, 130, 131, 133, 135, 136 Gunsmith, 17, 19

H Harris survey, 43, 44, 50, 51, 52 Heirloom Firearm, 6, 133 Household Gun Ownership, 2, 3, 4, 5, 6, 7, 8, 43, 44, 49, 50, 51, 52, 53, 54, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 69, 70, 71, 73, 75, 77, 78, 79, 84, 85, 86, 87, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119,

120, 121, 122, 123, 124, 125, 127, 128, 130, 131, 132, 133, 134, 135, 136 Household Population, 60, 66, 67, 75, 90, 91, 104, 106, 110, 112, 120, 121, 122, 124, 125, 132, 133, 134 Hunting, 5, 14, 16, 18, 19, 23, 57, 113

I Indian Intercourse Act, 18 Industrialization, 12

L Law Enforcement, 12, 21, 23, 28, 33 Logistic Regression, 46, 78, 84, 85, 86, 87, 105, 107, 111, 113, 114, 116, 119, 122, 131

M Matchlock, 27 Maximum Likelihood Estimators, 88 Measurement Error, 3, 4, 8, 51, 53, 55, 63, 66, 67, 73, 88, 89, 93, 95, 97, 124, 125, 127 Media, 6, 133 Military Arms, 24, 26, 33 Militia, 14, 16, 20, 21, 28 Misreporting, 7, 60, 62, 63, 64, 72, 73, 79, 99, 108, 109, 112, 115, 133, 134, 135 Multicollinearity, 103, 121, 122 Musket, 15, 17, 24, 25

N National Academies of Science, 4, 7, 62, 127, 136 National Firearms Act, 32, 33, 34

Subject Index

169

National Gun Policy Survey, 5, 39, 41, 54, 55, 59, 63, 104, 129 National Opinion Research Center, 44, 51, 53, 54, 64, 69, 78, 104 National Rifle Association, 33, 34, 48 National Study of the Private Ownership of Firearms, 39, 41, 54, 55, 59, 62, 129 Needlegun, 26 New York Police Department, 31

O Overreporting, 64

P Panel Data, 86, 135 Pennsylvania Rifle, 18 Percussion-Lock, 27 Personal Gun Ownership, 67, 70, 71, 90, 94, 95, 101, 103, 104, 106, 107, 122, 124, 125, 130, 134 Pistol, 19, 25, 27, 33, 70, 90, 91, 96, 98, 99, 101, 108, 112, 115, 116, 117 Progressive Era, 28, 32, 34 Public Health, 1, 2, 8, 40, 55, 128, 136

R Remington, 26 Rifle, 16, 19, 24, 26, 27, 70, 90, 91, 96, 97, 98, 101, 108, 112, 113, 115, 117 Riots, 22 Robust Standard Errors, 89 Rural, 12, 21, 22, 30, 32, 33, 39, 40, 42, 46, 48, 49, 51, 52, 54, 55, 57, 58, 59, 64, 65, 66, 74, 76, 110, 112, 115, 117, 129

S Sawed-off Shotguns, 33 Self-Defense, 13, 18, 22, 23, 28 Shotgun, 48, 70, 90, 91, 96, 98, 101, 108, 112, 114, 115, 117 Smith & Wesson, 26 Social Justice, 28, 29 Social Undesirability, 6, 8, 61, 62, 64, 72, 78, 108, 117, 118, 120, 125, 133, 136 Southern Subculture, 44, 45, 46, 47 Sporting Gun Culture, 5, 13, 47, 48, 49, 57, 65, 77, 113 Stigma, 6, 115, 133 Suburban, 74, 76, 115, 117 Sullivan Law, 29, 30, 31, 32, 33, 34 Survey of Gun Owners in the United States, 54, 55, 62

T The National Gun Policy Surveys, 5, 39, 41, 54, 55, 59, 63, 104, 129 Time Series, 1, 8, 70, 78, 131

U Underreporting (see also misreporting), 7, 51, 60, 61, 62, 64, 73, 117, 125, 133, 134 Urban, 17, 21, 22, 23, 30, 32, 36, 45, 65, 74, 76, 110, 115 Urbanization, 5, 8, 45, 60, 65, 67, 132

V Variable Inflation Factors, 103 Volstead Act, 29

170

Subject Index

W War, 18, 21, 22, 35 Weighted Least Squares, 103

Weighting, 6, 53, 70 Wheel-Lock, 27 Winchester, 26 World War I, 32, 33