首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Envelope condition method with an application to default risk models
Institution:1. Hoover Institution, 434 Galvez Mall, Stanford University, Stanford, CA 94305-6010, USA;2. Department of Economics, 579 Serra Mall, Stanford University, Stanford, CA 94305-6072, USA;3. Department of Fundamentos del Análisis Económico, University of Alicante, Campus de San Vicente, 03080 Alicante, Spain;4. Leavey School of Business, Lucas Hall 124, Santa Clara University, Santa Clara, CA, 95053, USA;1. Department of Economics, University of Maryland, College Park, MD 20742, United States of America;2. Division of International Finance, Federal Reserve Board, 20th Street & Constitution Ave., NW, Washington, DC 20551, United States of America;3. Department of Economics, University of Pennsylvania, 133 S. 36th Street, Philadelphia, PA 19104, United States of America;4. CEPR, United Kingdom;5. NBER, PIER, United States of America
Abstract:We develop an envelope condition method (ECM) for dynamic programming problems – a tractable alternative to expensive conventional value function iteration (VFI). ECM has two novel features: first, to reduce the cost of iteration on Bellman equation, ECM constructs policy functions using envelope conditions which are simpler to analyze numerically than first-order conditions. Second, to increase the accuracy of solutions, ECM solves for derivatives of value function jointly with value function itself. We complement ECM with other computational techniques that are suitable for high-dimensional problems, such as simulation-based grids, monomial integration rules and derivative-free solvers. The resulting value-iterative ECM method can accurately solve models with at least up to 20 state variables and can successfully compete in accuracy and speed with state-of-the-art Euler equation methods. We also use ECM to solve a challenging default risk model with a kink in value and policy functions.
Keywords:Dynamic programming  Bellman equation  Endogenous grid  Curse of dimensionality  Large scale  Default risk
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号