The effects of gun control on crimes: a spatial interactive fixed effects approach

Abstract

This paper examines the effect of right-to-carry laws on crimes. We relax the assumption that unobserved time effects have homogeneous impacts on states; therefore, states with right-to-carry laws may follow different time trends which might be stronger or weaker than those of other states including states with no right-to-carry laws. The heterogeneous time trends are modeled by a factor structure where time factors represent time-varying unobservables, and factor loadings account for their heterogeneous impacts across states. No assumption is imposed on the shape of the time trend. Crime statistics exhibit spatial dependence, and a state’s adoption of right-to-carry law may have external effects on its neighboring states. Using a dynamic spatial panel model with interactive effects, we find positive spatial spillovers in crime rates. Depending on a crime category, an average \(1\%\) reduction in crime rates in neighboring states can decrease crime rates by 0.069–0.287%, with property crimes exhibiting higher degrees of spatial dependence than violent crimes. We find that although the passage of right-to-carry laws has no significant effects on the overall violent or property crime rates, they lead to short-term increases in robbery and medium-term decreases in murder rates. The results are robust to the number of factors, a different sample ending point, and some alternative spatial weights matrices and model specifications.

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Notes

  1. 1.

    Besides the adoption of right-to-carry laws, another important legislation is the Brady Bill which mandates background checks on firearm purchases and was implemented in 1994.

  2. 2.

    Colorado 2003, Iowa 2011, Kansas 2006, Michigan 2001, Minnesota 2003, Missouri 2003, Nebraska 2006, New Mexico 2003, Ohio 2004 and Wisconsin 2011. See http://www.gun-nuttery.com/rtc.php and the cited sources therein.

  3. 3.

    The definition of rape was revised in 2011. In this paper, statistics on rape are under the old definition (“forcible rape”).

  4. 4.

    For example, \(\tilde{\gamma }_{i}'\tilde{f}_{t}=\gamma _{i}+f_{t}\) if \(\tilde{\gamma }_{i}=\begin{pmatrix}\gamma _{1}&1\end{pmatrix}'\) and \(\tilde{f}_{t}=\begin{pmatrix}1&f_{t}\end{pmatrix}'.\)

  5. 5.

    We appreciate a referee’s suggestion on performing such a test for our model.

  6. 6.

    With a rotation, the loadings of treated units may be inside the convex hull of those of control units.

  7. 7.

    The conclusions for other types of crimes are similar, and the results are available upon request.

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Correspondence to Lung-fei Lee.

Additional information

This project was supported by the Fundamental Research Funds for the Central Universities (Project No. 17JNQN009). We would like to thank the editor Badi Baltagi, an anonymous referee, Paul Elhorst, and participants of the XI World Conference of the Spatial Econometrics Association at the Singapore Management University, and seminars at Jinan University for helpful comments. The usual disclaimers apply.

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Shi, W., Lee, L. The effects of gun control on crimes: a spatial interactive fixed effects approach. Empir Econ 55, 233–263 (2018). https://doi.org/10.1007/s00181-017-1415-2

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Keywords

  • Spatial panel data
  • Cross-sectional and spatial dependence
  • Interactive fixed effects
  • Crime