Semiparametric Causality Tests Using the Policy Propensity Score
AbstractTime series data are widely used to explore causal relationships, typically in a regression framework with lagged dependent variables. Regression-based causality tests rely on an array of functional form and distributional assumptions for valid causal inference. This paper develops a semi-parametric test for causality in models linking a binary treatment or policy variable with unobserved potential outcomes. The procedure is semiparametric in the sense that we model the process determining treatment -- the policy propensity score -- but leave the model for outcomes unspecified. This general approach is motivated by the notion that we typically have better prior information about the policy determination process than about the macro-economy. A conceptual innovation is that we adapt the cross-sectional potential outcomes framework to a time series setting. This leads to a generalized definition of Sims (1980) causality. We also develop a test for full conditional independence, in contrast with the usual focus on mean independence. Our approach is illustrated using data from the Romer and Romer (1989) study of the relationship between the Federal reserve's monetary policy and output.
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Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 10975.
Date of creation: Dec 2004
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Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-12-20 (All new papers)
- NEP-ECM-2004-12-20 (Econometrics)
- NEP-ETS-2004-12-20 (Econometric Time Series)
- NEP-MAC-2004-12-20 (Macroeconomics)
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- Romer, Christina D. & Romer, David H., 1997. "Identification and the narrative approach: A reply to Leeper," Journal of Monetary Economics, Elsevier, vol. 40(3), pages 659-665, December.
- Sokbae Lee & Yoon-Jae Whang, 2009.
"Nonparametric Tests of Conditional Treatment Effects,"
Cowles Foundation Discussion Papers
1740, Cowles Foundation for Research in Economics, Yale University.
- Sokbae 'Simon' Lee & Yoon-Jae Whang, 2009. "Nonparametric tests of conditional treatment effects," CeMMAP working papers CWP36/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Song, Kyungchul, 2010. "Testing semiparametric conditional moment restrictions using conditional martingale transforms," Journal of Econometrics, Elsevier, vol. 154(1), pages 74-84, January.
- Joshua D. Angrist & Jörn-Steffen Pischke, 2010.
"The Credibility Revolution in Empirical Economics: How Better Research Design is taking the Con out of Econometrics,"
CEP Discussion Papers
dp0976, Centre for Economic Performance, LSE.
- Joshua D. Angrist & J�rn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
- Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design is Taking the Con out of Econometrics," Working Paper Series of the German Council for Social and Economic Data 142, German Council for Social and Economic Data (RatSWD).
- Joshua Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design is Taking the Con out of Econometrics," NBER Working Papers 15794, National Bureau of Economic Research, Inc.
- Angrist, Joshua & Pischke, Jörn-Steffen, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," IZA Discussion Papers 4800, Institute for the Study of Labor (IZA).
- Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The credibility revolution in empirical economics: how better research design is taking the con out of econometrics," LSE Research Online Documents on Economics 48898, London School of Economics and Political Science, LSE Library.
- Kyungchul Song, 2007. "Testing Conditional Independence via Rosenblatt Transforms," PIER Working Paper Archive 07-026, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Joeri Smits & Jeffrey S. Racine, 2013. "Testing Exclusion Restrictions in Nonseparable Triangular Models," Department of Economics Working Papers 2013-02, McMaster University.
- Joshua D. Angrist & Òscar Jordà & Guido Kuersteiner, 2013.
"Semiparametric Estimates of Monetary Policy Effects: String Theory Revisited,"
NBER Working Papers
19355, National Bureau of Economic Research, Inc.
- Joshua D. Angrist & Òscar Jordà & Guido M. Kuersteiner, 2013. "Semiparametric estimates of monetary policy effects: string theory revisited," Working Paper Series 2013-24, Federal Reserve Bank of San Francisco.
- Michael Lechner, 2006. "The Relation of Different Concepts of Causality in Econometrics," University of St. Gallen Department of Economics working paper series 2006 2006-15, Department of Economics, University of St. Gallen.
- White, Halbert, 2006. "Time-series estimation of the effects of natural experiments," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 527-566.
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