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Estimating Central Bank Preferences under Commitment and Discretion Author info | Abstract | Publisher info | Download info | Related research | Statistics Gregory Erin Givens
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This paper explains US macroeconomic outcomes with an empirical new-Keynesian model in which monetary policy minimizes the central bank's loss function. The presence of expectations in the model forms a well-known distinction between two modes of optimization, termed commitment and discretion. I estimate the model separately under each policy using maximum likelihood over the Volcker-Greenspan-Bernanke period. Comparisons of fit reveal that the data favor the specification with discretionary policy. Estimates of the loss function weights point to an excessive concern for interest rate smoothing in the commitment model but a more balanced concern relative to inflation and output stability in the discretionary model.
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Paper provided by Middle Tennessee State University, Department of Economics and Finance in its series Working Papers with number
200905.
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Date of creation: Jun 2009Date of revision:
Handle: RePEc:mts:wpaper:200905Contact details of provider: Email: Web page: http://www.mtsu.edu/~berc/working/Economics_Working_Papers.html More information through EDIRC
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Keywords: Optimal Monetary Policy ; Commitment ; Discretion ; Policy Preferences ; Other versions of this item:
Find related papers by JEL classification: E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
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