Nonlinear Programming Method for Dynamic Programming
A nonlinear programming formulation is introduced to solve infinite horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to avoid inefficient discretization. Our numerical results show that this nonlinear programming method is efficient and accurate.
Cai and Judd gratefully acknowledge NSF support (SES-0951576). Michelangeli acknowledges the funding of the Bank of Italy research fellowship. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research or the Bank of Italy.
Cai, Yongyang & Judd, Kenneth L. & Lontzek, Thomas S. & Michelangeli, Valentina & Su, Che-Lin, 2017. "A Nonlinear Programming Method For Dynamic Programming," Macroeconomic Dynamics, Cambridge University Press, vol. 21(02), pages 336-361, March. citation courtesy of