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Numerical Policy Error Bounds for $$\eta $$ η -Concave Stochastic Dynamic Programming with Non-interior Solutions

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  • Huiyu Li

Abstract

This paper derives explicit error bounds for numerical policies of $$\eta $$ η -concave stochastic dynamic programming problems, without assuming the optimal policy is interior. We demonstrate the usefulness of our error bound by using it to pinpoint the states at which the borrowing constraint binds in a widely used income fluctuation problem with standard calibrations and a firm production problem with financial constraints. Copyright Springer Science+Business Media New York 2015

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  • Huiyu Li, 2015. "Numerical Policy Error Bounds for $$\eta $$ η -Concave Stochastic Dynamic Programming with Non-interior Solutions," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 171-187, August.
    • Handle: RePEc:kap:compec:v:46:y:2015:i:2:p:171-187
    DOI: 10.1007/s10614-014-9460-9
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    1. Robert Kirkby, 2023. "Quantitative Macroeconomics: Lessons Learned from Fourteen Replications," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 875-896, February.

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    More about this item

    Keywords

    Accuracy test; Computable policy error bound; Noninterior solution; Euler equation error ; C63; E21;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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