Econometric Methods to Study the Effects of Public Interventions and Terrorism

摘要项目编号：0350645机构：NBERNSF项目：ECONOMICSPI: Abadie， alberto标题：研究公共干预与恐怖主义影响的计量经济学方法本研究由两个项目组成，将发展创新的计量经济学方法来研究公共政策干预的影响。第一个项目研究了治疗效果估计和缺失数据输入的简单匹配方法。研究平均处理效果的简单匹配估计分布的新分析技术为解决两个突出问题开辟了道路：(a)估计效果和其他处理效果的最流行匹配程序的性质-估计倾向得分的简单匹配估计-没有得到很好的理解。本项目将通过将最近的发展扩展到对估计协变量（如倾向得分）进行匹配的情况来填补文献中的这一空白。(b) CPS及其他大型调查采用一种称为“热甲板”的核对程序来推算缺失值。治疗效果的简单匹配估计值的大偏差表明热甲板估算程序将产生类似的偏差。本研究将研究一种改进的热甲板程序的性质，该程序不存在这些偏差。对政策干预效果的研究通常在总体水平上进行，并使用不受利益干预影响的经济体作为对照组。这种方法存在两个问题：(i)研究人员使用亲和度的主观测量来选择可能的控制，在如何选择对照组方面存在一些歧义。如果使用汇总数据进行分析，通常的横截面标准误差（仅衡量汇总变量的不确定性）就不适用。这些模型中的不确定性是关于控制组在没有干预的情况下重现受影响经济体行为的能力。本项目将研究数据驱动程序的特性，以构建适当的控制组。这一过程限制了选择对照组的自由裁量权，迫使实证研究人员利用观察到的可量化特征来证明受影响经济体和非受影响经济体之间的亲和力。此外，本项目将研究如何使用时间序列信息测量比较对照组质量的不确定性。倾向分数匹配估计量和基于“热甲板”数据的估计量的性质是经济学实证研究中的重要问题。此外，对这些性质的研究将需要在计量经济学中发展和应用新的分析方法。本研究中开发的方法也将用于编写STATA计量软件包的软件，以供更广泛的使用。该项目还将有助于有效地制定和执行公共政策。

ABSTRACTPROPOSAL NO: 0350645INSTITUTION: NBERNSF PROGRAM: ECONOMICSPI: Abadie, AlbertoTITLE: Econometric Methods to Study the Effects of Public Interventions and TerrorismThis research, consisting of two projects, will develop innovative econometric methods to study the effects of public policy interventions. The first project studies simple matching methods for treatment effects estimation and missing data imputation. New analytical techniques for the study of the distribution of simple matching estimators of average treatment effects have opened the way to solve two outstanding problems: (a) The properties of the most popular matching procedures to estimate the effects of and other treatment effects---simple matching estimators on the estimated propensity score---are not well understood. This project will fill this gap in the literature by extending recent development to the case when matching is done on estimated covariates (as the propensity score). (b) The CPS and other large surveys use a matching procedure known as 'hot deck' to impute missing values. Large biases in simple matching estimators of treatment effects indicate that hot deck imputation procedures will produce similar biases. This research will study the properties of an improved hot deck procedure that is free of these biases.Studies of the effects of policy interventions often take place at an aggregate level and use economies not exposed to the intervention of interest as a control group. This approach is subject to two problems: (i) there is some ambiguity about how to choose control groups with researchers using subjective measures of affinity to select between possible controls. (ii) If aggregate data are used for the analysis, the usual cross-section standard errors, which measure only uncertainty about aggregate variables, do not apply. Uncertainty in these models is about the ability of the control group to reproduce the behavior of the exposed economies in absence of the intervention. This project will study the properties of data-driven procedures to construct adequate control groups. This procedure limits the discretion in the choice of the control group, forcing the empirical researcher to demonstrate the affinities between the exposed and non-exposed economies using observed quantifiable characteristics. In addition, this project will study how to measure uncertainty about the quality of the comparison control groups using time series information. The properties of propensity score matching estimators and estimators based on data imputed by 'hot deck 'are important problems empirical research in economics. Moreover, the study of these properties will entail the development and application of new analytical methods in econometrics. The methods developed in this research will also be used to write software for the STATA econometric package for wider use. The project will also help in the efficient development and implementation of public policy.