How Do Right-to-Carry Laws Affect Crime Rates? Coping with Ambiguity Using Bounded-Variation Assumptions

By Charles F. Manski, John V. Pepper. Review of Economics and Statistics, 2015

150 citations recorded by the source corpus.

Abstract Despite dozens of studies, research on crime has struggled to reach consensus about the impact of right-to-carry (RTC) gun laws. With this in mind, we formalize and apply a class of bounded-variation assumptions that flexibly restrict the degree to which outcomes may vary across time and space. Using these assumptions, we present empirical analysis of the effect of RTC laws on violent and property crimes in Virginia, Maryland, and Illinois. Imposing specific assumptions that we believe worthy of consideration, we find that RTC laws increase some crimes, decrease other crimes, and have effects that vary over time for others.

Subfields: Clinical Psychology, Health, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/2e0ea72c360c8cf185d5e96c4b86c3e1ddba3455

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Citations in the corpus

Inference on breakdown frontiers (2017, background): “Manski and Pepper (2018) also studied a model where relaxations of baseline assumptions are parameterized by a vector of numbers r. Unlike Imbens, however, they derive identified sets indexed by r.”
What’s trending in difference-in-differences? A synthesis of the recent econometrics literature (2022, unknown): “Rambachan and Roth (2022b) propose an approach for robust inference and sensitivity analysis when parallel trends may be violated, building on earlier work by Manski and Pepper (2018).”
How Much Should We Trust Staggered Difference-In-Differences Estimates? (2021, unknown): “Since at least Meyer (1995), it has been shown that including covariates in a linear fashion is inappropriate if the treatment has different effects across subgroups in the population.”
Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey (2021, background): “To do so, one may for instance implement the partial identiﬁcation approach in Manski and Pepper (2018) or Rambachan and Roth (2019).”