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.
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Provider: Federal Reserve Bank of Dallas
Part of Series: Globalization Institute Working Papers
Publication Date: 2020-08-21