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Series Merging Simulation and Projection Approaches to Solve High-dimensional Problems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Maliar, Lilia Maliar, Serguei |
| Copyright Year | 2013 |
| Abstract | We introduce an algorithm for solving dynamic economic models that merges stochastic simulation and projection approaches: we use simulation to approximate the ergodic measure of the solution, we construct a fixed grid covering the support of the constructed ergodic measure, and we use projection techniques to accurately solve the model on that grid. The grid construction is the key novel piece of our analysis: we select an -distinguishable subset of simulated points that covers the support of the ergodic measure roughly uniformly. The proposed algorithm is tractable in problems with high dimensionality (hundreds of state variables) on a desktop computer. As an illustration, we solve oneand multicountry neoclassical growth models and a large-scale new Keynesian model with a zero lower bound on nominal interest rates. Kenneth L. Judd Hoover Institution Stanford University Stanford, CA 94305-6010 and NBER kennethjudd@mac.com Lilia Maliar Office T-24 Hoover Institution Stanford University CA 94305-6010, USA maliarl@stanford.edu Serguei Maliar Office T-24 Hoover Institution Stanford University CA 94305-6010, USA maliars@stanford.edu |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://bfi.uchicago.edu/sites/default/files/research/Judd_Maliar___Maliar__2012_.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
