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Gun Prevalence, Homicide Rates and Causality: A GMM Approach to Endogeneity Bias

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  • Kleck, Gary
  • Kovandzic, Tomislav
  • Schaffer, Mark E

Abstract

The positive correlation between gun prevalence and homicide rates has been widely documented. But does this correlation reflect a causal relationship? This study seeks to answer the question of whether more guns cause more crime, and unlike nearly all previous such studies, we properly account for the endogeneity of gun ownership levels. We discuss the three main sources of endogeneity bias - reverse causality (higher crime rates lead people to acquire guns for self-protection), mismeasurement of gun levels, and omitted/confounding variables - and show how the Generalized Method of Moments (GMM) can provide an empirical researcher with both a clear modeling framework and a set of estimation and specification testing procedures that can address these problems. A county level cross-sectional analysis was performed using data on every US county with a population of at least 25,000 in 1990; the sample covers over 90% of the US population in that year. Gun ownership levels were measured using the percent of suicides committed with guns, which recent research indicates is the best measure of gun levels for cross-sectional research. We apply our procedures to these data, and find strong evidence of the existence of endogeneity problems. When the problem is ignored, gun levels are associated with higher rates of gun homicide; when the problem is addressed, this association disappears or reverses. Our results indicate that gun prevalence has no significant net positive effect on homicide rates: ceteris paribus, more guns do not mean more crime.

Suggested Citation

  • Kleck, Gary & Kovandzic, Tomislav & Schaffer, Mark E, 2005. "Gun Prevalence, Homicide Rates and Causality: A GMM Approach to Endogeneity Bias," CEPR Discussion Papers 5357, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:5357
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    References listed on IDEAS

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    1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Jean-Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 767-808, November.
    4. Moody, Carlisle E, 2001. "Testing for the Effects of Concealed Weapons Laws: Specification Errors and Robustness," Journal of Law and Economics, University of Chicago Press, vol. 44(2), pages 799-813, October.
    5. Alastair R. Hall & Fernanda P. M. Peixe, 2003. "A Consistent Method for the Selection of Relevant Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 22(3), pages 269-287, January.
    6. Zivot, Eric & Startz, Richard & Nelson, Charles R, 1998. "Valid Confidence Intervals and Inference in the Presence of Weak Instruments," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1119-1146, November.
    7. Jeffrey M. Wooldridge, 2003. "Cluster-Sample Methods in Applied Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 133-138, May.
    8. Jinyong Hahn & Jerry Hausman, 2003. "Weak Instruments: Diagnosis and Cures in Empirical Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 118-125, May.
    9. Ruddell, Rick & Mays, G. Larry, 2005. "State background checks and firearms homicides," Journal of Criminal Justice, Elsevier, vol. 33(2), pages 127-136.
    10. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
    11. Bice, Douglas C & Hemley, David D, 2002. "The Market for New Handguns: An Empirical Investigation," Journal of Law and Economics, University of Chicago Press, vol. 45(1), pages 251-265, April.
    12. Mark Duggan, 2001. "More Guns, More Crime," Journal of Political Economy, University of Chicago Press, vol. 109(5), pages 1086-1114, October.
    13. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    14. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    15. Adrian R Pagan & Anthony D Hall, 1983. "Diagnostic tests as residual analysis," Published Paper Series 1983-1, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    16. Cragg, John G, 1983. "More Efficient Estimation in the Presence of Heteroscedasticity of Unknown Form," Econometrica, Econometric Society, vol. 51(3), pages 751-763, May.
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    Cited by:

    1. Kovandzic, Tomislav & Schaffer, Mark E & Kleck, Gary, 2008. "Estimating the Causal Effect of Gun Prevalence on Homicide Rates: A Local Average Treatment Effect Approach," IZA Discussion Papers 3589, Institute of Labor Economics (IZA).
    2. Carlisle E. Moody, 2010. "Firearms and Homicide," Chapters,in: Handbook on the Economics of Crime, chapter 17 Edward Elgar Publishing.

    More about this item

    Keywords

    counties; crime; endogeneity; GMM; gun levels; homicide;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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