Working Paper

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

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.

Keywords: General equilibrium models; Occasionally binding constraints; Computational methods; Time iteration; Policy function iteration; Endogenous grid;

JEL Classification: C6; C61; C63; C68;

https://doi.org/10.24149/gwp396

Bibliographic Information

Provider: Federal Reserve Bank of Dallas

Part of Series: Globalization Institute Working Papers

Publication Date: 2020-08-21

Number: 396