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Generalized Method of Moments and Inverse Control

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  • Gregory Erin Givens
  • Michael K. Salemi

Abstract

This paper presents a Generalized Method of Moments algorithm for estimating the structural parameters of a macroeconomic model subject to the restriction that the coefficients of the monetary policy rule minimize the central bank's expected loss function. The algorithm combines least-squares normal equations with moment restrictions derived from the first-order necessary conditions of the auxiliary optimization. We assess the performance of the algorithm with Monte Carlo simulations using three increasingly complex models. We find that imposing the optimizing restrictions when they are true improves estimation accuracy and that imposing those restrictions when they are false biases estimates of some of the structural parameters but not of the policy rule coefficients.

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Bibliographic Info

Paper provided by Middle Tennessee State University, Department of Economics and Finance in its series Working Papers with number 200603.

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Date of creation: Jun 2006
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Handle: RePEc:mts:wpaper:200603

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Web page: http://www.mtsu.edu/~berc/working/Economics_Working_Papers.html
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Keywords: GMM; optimal monetary policy; simple rules; policy objectives;

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Cited by:
  1. Givens, Gregory & Salemi, Michael, 2012. "Inferring monetary policy objectives with a partially observed state," MPRA Paper 39353, University Library of Munich, Germany.
  2. Gregory E. Givens, 2012. "Estimating Central Bank Preferences under Commitment and Discretion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(6), pages 1033-1061, 09.

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