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Crime and punishment: evidence from dynamic panel data model for North Carolina (2003-2012)

机译:犯罪与惩罚:北卡罗来纳州动态面板数据模型的证据(2003-2012年)

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摘要

This paper exploits a dynamic panel data model to analyze the endogeneity of certain deterrent covariates, measurement errors in crime and inertial features of crime, and to check for unobserved heterogeneity in order to extract more precise and reliable estimates of the deterrent effect of law enforcement in North Carolina. It uses panel data on 90 counties of North Carolina over the period 2003-2012. After checking various socioeconomic covariates, among the deterrent variables, likelihood of arrest and conviction always showed deterrent effects on criminal behavior for different kinds of violent and property crimes. Since property crimes have relatively higher inertia than violent crimes, their associated long-run elasticities with respect to significant deterrence variables are greater, which implies that allocating more resources to increasing the likelihood of arrest for property crimes can effectively decrease them in the long run.
机译:本文利用动态面板数据模型来分析某些威慑协变量的内生性,犯罪中的测量误差和犯罪的惯性特征,并检查未观察到的异质性,以便提取出更精确,更可靠的执法威慑作用估计。北卡罗来纳。它使用2003-2012年期间北卡罗来纳州90个县的面板数据。在检查了各种社会经济协变量之后,在威慑变量中,逮捕和定罪的可能性始终显示出对各种暴力和财产犯罪的犯罪行为的威慑作用。由于财产犯罪的惯性要比暴力犯罪要高,因此它们在重大威慑变量方面的长期弹性更大,这意味着从长远来看,分配更多的资源以增加逮捕财产犯罪的可能性可以有效地减少犯罪。

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