CAUSAL EFFECTS OF MONETARY SHOCKS: SEMIPARAMETRIC CONDITIONAL INDEPENDENCE TESTS WITH A MULTINOMIAL PROPENSITY SCORE

• 成果类型: Article
• 署名作者: Angrist, Joshua D.; Kuersteiner, Guido M.
• 署名单位: Massachusetts Institute of Technology (MIT); Georgetown University
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/REST_a_00109
• 发表日期: 2011-08
• 页码: 725-747
• 关键词: federal-funds rate; model checks; time-series; POLICY; inference; identification; regression; bootstrap; exposure; granger

摘要

We develop semiparametric tests for conditional independence in time series models of causal effects. Our approach is motivated by empirical studies of monetary policy effects and is semiparametric in the sense that we model the process determining the distribution of treatment-the policy propensity score-but leave the model for outcomes unspecified. A conceptual innovation is that we adapt the cross-sectional potential outcomes framework to a time series setting. We also develop root-T consistent distribution-free inference methods for full conditional independence testing, appropriate for dependent data and allowing for first-step estimation of the (multinomial) propensity score.