Stochastic Policy Design in a Learning Environment with Rational Expectations

Hans Amman and David Kendrick

Journal of Optimization Theory and Applications, 2000, vol. 105, issue 3, No 3, 509-520

Abstract: Abstract In this paper, we present a method for using rational expectations in a stochastic linear-quadratic optimization framework in which the unknown parameters are updated through a learning scheme. We use the QZ decomposition as suggested by Sims (Ref. 1) to solve the rational expectations part of the model. The parameter updating is done with the Kalman filter and the optimal control is calculated using the covariance matrix of the uncertain parameter.

Keywords: macroeconomics; learning; rational expectations; stochastic optimization (search for similar items in EconPapers)
Date: 2000
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DOI: 10.1023/A:1004620021587

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