A Nonlinear Certainty Equivalent Approximation Method for Dynamic Stochastic Problems

Yongyang Cai, Kenneth Judd and Jevgenijs Steinbuks

No 21590, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper introduces a nonlinear certainty equivalent approximation method for dynamic stochastic problems. We first use a novel, stable and efficient method for computing the optimal policy functions for deterministic dynamic optimization problems, and then use them as certainty-equivalent approximations for the stochastic versions. Our examples demonstrate that it can be applied to solve high-dimensional problems with up to four hundred state variables with an acceptable accuracy. This method can also be applied to solve problems with inequality constraints that occasionally bind. These features make the nonlinear certainty equivalent approximation method suitable for solving complex economic problems, where other algorithms, such as log-linearization, fail or are far less tractable.

JEL-codes: C61 C63 C68 E31 E52 (search for similar items in EconPapers)
Date: 2015-09
New Economics Papers: this item is included in nep-cmp, nep-dge, nep-mac and nep-ore
Note: TWP
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Published as Yongyang Cai & Kenneth Judd & Jevgenijs Steinbuks, 2017. "A nonlinear certainty equivalent approximation method for dynamic stochastic problems," Quantitative Economics, vol 8(1), pages 117-147.

Downloads: (external link)
http://www.nber.org/papers/w21590.pdf (application/pdf)

Related works:
Journal Article: A nonlinear certainty equivalent approximation method for dynamic stochastic problems (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:21590

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w21590

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().