Interest Rate Smoothing versus Serially Correlated Errors in Taylor Rules: Testing the Tests

This paper contributes to the recent debate about the estimated high partial adjustment coefficient in dynamic Taylor rules, commonly interpreted as deliberate interest rate smoothing on the part of the monetary authority. We argue that a high coefficient on the lagged interest rate term may be a consequence of an incorrectly specified central bank reaction function. Focusing on omitted variables, our Monte Carlo study first generates the well-known fact that all coefficients in the misspecified equation are biased in such cases. In particular, if relevant variables are left out from the estimated equation, a high partial adjustment coefficient is obtained even when it is in fact zero in the data generating process. Misspecification also leads to considerable size distortions in two tests that were recently proposed by English, Nelson, and Sack (2003) in order to distinguish between interest rate smoothing and serially correlated disturbances. Our results question the common interpretation of very slow partial adjustment as interest rate smoothing in estimated dynamic Taylor rules.