Operational monetary policy rules are characterized by a parsimonious specification and are therefore prone to specification error when estimated on real data. I devise a policy rule estimation procedure, which is robust to marginal misspecification, and study the effects of specification error in least squares. I find the robust evidence of upward bias in policy inertia in least squares applied to most commonly used Taylor type rule. In effect, least squares learning of a central bank can lead to increasing monetary policy inertia over time.
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Paper provided by The Center for Economic Research and Graduate Education - Economic Institute, Prague in its series CERGE-EI Working Papers with number
wp315.
Find related papers by JEL classification: E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
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