A Generalized Time Iteration Method for Solving Dynamic Optimization Problems with Occasionally Binding Constraints

28 Pages Posted: 28 Aug 2020 Last revised: 11 Jan 2022

See all articles by Ayse Kabukcuoglu

Ayse Kabukcuoglu

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Enrique Martínez-García

Federal Reserve Bank of Dallas - Research Department

Date Written: August, 2020

Abstract

We study a generalized version of Coleman (1990)’s time iteration method (GTI) for solving dynamic optimization problems. Our benchmark framework is an irreversible investment model with labor-leisure choice. The GTI algorithm is simple to implement and provides advantages in terms of speed relative to Howard (1960)’s improvement algorithm. A second application on a heterogeneous-agents incomplete-markets model further explores the performance of GTI.

JEL Classification: C6, C61, C63, C68

Suggested Citation

Kabukcuoglu, Ayse and Martinez-Garcia, Enrique, A Generalized Time Iteration Method for Solving Dynamic Optimization Problems with Occasionally Binding Constraints (August, 2020). Globalization Institute Working Paper No. 396, Available at SSRN: https://ssrn.com/abstract=3682356 or http://dx.doi.org/10.24149/gwp396

Enrique Martinez-Garcia

Federal Reserve Bank of Dallas - Research Department ( email )

2200 North Pearl Street
PO Box 655906
Dallas, TX 75265-5906
United States
214-922-5262 (Phone)

HOME PAGE: http://sites.google.com/view/emgeconomics

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