Macroeconomists have long been concerned with the causal e§ects of monetary policy. When the identiÖcation of causal e§ects is based on a selection-on-observables assumption, non-causality amounts to the conditional independence of outcomes and policy changes. This paper develops a semiparametric test for conditional independence in time series models linking a multinomial policy variable with unobserved potential outcomes. Our approach to conditional independence testing is motivated by earlier parametric tests, as in Romer and Romer (1989, 1994, 2004).
Causal Effects of Monetary Shocks: Semiparametric Conditional Independence Tests with a Multinomial Propensity ScoreJoshua Angrist and Guido Kuersteiner ,
3( 93 )
The Review of Economics and Statistics
Causal Effects of Monetary Shocks: Semiparametric Conditional Independence Tests with a Multinomial Propensity Score