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Title: Three Essays on Crime Policy and the Bayesian Bootstrap

Citation Type: Dissertation/Thesis

Publication Year: 2021

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Abstract: This dissertation consists of three chapters. In the first chapter, I analyze credible intervals for quantiles constructed using Bayesian bootstrap techniques and show that credible intervals constructed using the “continuity-corrected” Bayesian bootstrap (Banks, 1988) have frequentist coverage probability error of only O(n −1 ). In addition, I show that these “continuity-corrected” Bayesian bootstrap credible intervals achieve the same frequentist coverage probability as the frequentist confidence intervals of Goldman and Kaplan (2017), up to some error term of magnitude O(n −1 ). Furthermore, I demonstrate that credible intervals constructed using the “continuitycorrected” Bayesian bootstrap have less frequentist coverage probability error than those constructed using the Bayesian bootstrap (Rubin, 1981). In the second chapter, I investigate three strikes laws, which mandate sharply increased sentences for criminals who commit a specific number of felonies. Specifically, I analyze the effect of these laws on violent crime rates using municipal-level data from the FBI. I compare violent crime rates of border municipalities in states with differing treatment statuses using a difference-in-differences specification with a sample matched on pre-treatment outcomes. I find no statistical evidence that three strikes laws reduce violent crime rates. I rule out reductions in violent crime rates greater than 1.3% and reject the hypothesis that three strikes laws reduce violent crime rates at the 5% significance level. Additional analyses and robustness checks support my main findings. vii

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Authors: Hoffman, Lonnie

Institution: University of Missouri

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Pages: 1-106

Data Collections: IPUMS USA

Topics: Crime and Deviance

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