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Federal Reserve Bank of Chicago
Working Paper Series
Constrained Discretion and Central Bank Transparency
Francesco Bianchi
Leonardo Melosi

We develop and estimate a general equilibrium model in which monetary policy can deviate from active inflation stabilization and agents face uncertainty about the nature of these deviations. When observing a deviation, agents conduct Bayesian learning to infer its likely duration. Under constrained discretion, only short deviations occur: Agents are confident about a prompt return to the active regime, macroeconomic uncertainty is low, welfare is high. However, if a deviation persists, agents’ beliefs start drifting, uncertainty accelerates, and welfare declines. If the duration of the deviations is announced, uncertainty follows a reverse path. For the U.S. transparency lowers uncertainty and increases welfare.

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Francesco Bianchi & Leonardo Melosi, Constrained Discretion and Central Bank Transparency, Federal Reserve Bank of Chicago, Working Paper Series WP-2014-16, 01 Jul 2014.
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Keywords: Bayesian learning; reputation; uncertainty; expectations; Markov-switching models; impulse response
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