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A NONLINEAR PROGRAMMING METHOD FOR DYNAMIC PROGRAMMING

  • Yongyang Cai (a1), Kenneth L. Judd (a2), Thomas S. Lontzek (a3), Valentina Michelangeli (a4) and Che-Lin Su (a5)...
Abstract

A nonlinear programming formulation is introduced to solve infinite-horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to approximate value functions. Our numerical results show that this nonlinear programming is efficient and accurate, and avoids inefficient discretization.

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Address correspondence to: Yongyang Cai, Hoover Institution, Stanford, CA 94305, USA; e-mail: yycai@stanford.edu.
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Cai, Judd, Lontzek, and Michelangeli note with great sadness the passing of Che-Lin Su this past July. We thank him for his contributions. We are grateful to the editors and anonymous reviewers for their insightful comments and suggestions. We particularly thank Philipp Renner for his many helpful comments. Cai and Judd gratefully acknowledge NSF support (SES-0951576). The views expressed herein are those of the authors and do not necessarily reflect the views of the Bank of Italy.
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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

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Macroeconomic Dynamics
  • ISSN: 1365-1005
  • EISSN: 1469-8056
  • URL: /core/journals/macroeconomic-dynamics
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