Accuracy estimates for a numerical approach to stochastic growth models

Manuel Santos and Jesus Vigo

No 107, Discussion Paper / Institute for Empirical Macroeconomics from Federal Reserve Bank of Minneapolis

Abstract: In this paper we develop a discretized version of the dynamic programming algorithm and derive error bounds for the approximate value and policy functions. We show that under the proposed scheme the computed value function converges quadratically to the true value function and the computed policy function converges linearly, as the mesh size of the discretization converges to zero. Moreover, the constants involved in these orders of convergence can be computed in terms of primitive data of the model. We also discuss several aspects of the implementation of our methods, and present numerical results for some commonly studied macroeconomic models.

Keywords: Economic; development (search for similar items in EconPapers)
Date: 1995
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Working Paper: Accuracy Estimates for a Numerical Approach to Stochastic Growth Models (1996)
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