TIME SERIES ANALYSIS OF DRUG USE AND CRIME IN NYC

这项研究将考察随着时间的推移，当地执法的影响 减少毒品使用和贩毒的努力：财产犯罪， 年暴力犯罪、当地海洛因和可卡因价格以及毒品使用指标 纽约市。我们的研究将是时间序列研究，每月检查一次 从1970年开始的观察。我们将检查变种-在警察 政策如：军官总人数、军官人数 专门分配给禁毒处等特种部队， 总体逮捕率，在毒品和非毒品之间的逮捕分配 重罪、毒品犯罪之间的分配逮捕毒品 分区与其他警察单位之间的毒品逮捕分配 重罪和轻罪，以及将毒品逮捕分配给 海洛因、可卡因和其他毒品。 我们采用动态时间序列的方法，并结合了最近的一些 研究这些相互关系的计量经济学文献的进展。 这种动态建模使我们不仅可以研究同时代的 变量之间的关系，但它也允许我们评估 变量之间相互反应的时间。我们将应用这些 技术与新构建的犯罪、逮捕、 警察人员、劳动力和贫困变量、人口变量、 药品价格，以及纽约市的各种药物使用指标 涵盖了从1970年开始的20年。

This study will examine the effects, over time, of local law enforcement efforts at reducing drug use and drug trafficking on: property crime, violent crime, local heroin and cocaine prices, and drug use indicators in New York City. Ours will be a time-series study, examining monthly observations, beginning in 1970. We will examine variations-in police policies such as: the total number of officers, the number of officers specifically assigned to the Narcotics Division and other special units, overall arrest rates, the allocation of arrests between drug and non-drug felony crimes, the allocation of drug arrests between the Narcotics Division versus other police units, the allocation of drug arrests between felony and misdemeanor offenses, and the allocation of drug arrests between heroin, cocaine, and other drugs. We employ a dynamic time series approach and incorporate some of the recent advances in the econometric literature to examine these interrelationships. This dynamic modelling allows us to examine not only the contemporaneous relationships between the variables, but it also allows us to assess the timing of the reactions of variables to each other. We will apply these techniques to a newly constructed time series of data on crime, arrests, police personnel, labor force and poverty variables, demographic variables, drug prices, and a variety of drug use indicators for New York City covering the two decades beginning in 1970.