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Merging Simulation and Projection Approaches to Solve High-Dimensional Problems

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  • Kenneth L. Judd
  • Lilia Maliar
  • Serguei Maliar

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 ε-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 one- and multicountry neoclassical growth models and a large-scale new Keynesian model with a zero lower bound on nominal interest rates.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18501.

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Date of creation: Nov 2012
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Handle: RePEc:nbr:nberwo:18501

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  1. Smets, Frank & Wouters, Raf, 2007. "Shocks and frictions in US business cycles: a Bayesian DSGE approach," Working Paper Series 0722, European Central Bank.
  2. Lawrence Christiano & Martin Eichenbaum & Sergio Rebelo, 2011. "When Is the Government Spending Multiplier Large?," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 78 - 121.
  3. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, 09.
  4. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
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Cited by:
  1. Nick Draper & André Nibbelink & Johannes Uhde, 2013. "An Assessment of Alternatives for the Dutch First Pension Pillar, The Design of Pension Schemes," CPB Discussion Paper 259, CPB Netherlands Bureau for Economic Policy Analysis.
  2. Maliar, Lilia & Maliar, Serguei, 2013. "Envelope condition method versus endogenous grid method for solving dynamic programming problems," Economics Letters, Elsevier, vol. 120(2), pages 262-266.
  3. Julien Albertini & Arthur Poirier, 2014. "Unemployment benefits extensions at the zero lower bound on nominal interest rate," SFB 649 Discussion Papers SFB649DP2014-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  4. Kenneth L. Judd & Lilia Maliar & Serguei Maliar & Rafael Valero, 2013. "Smolyak Method for Solving Dynamic Economic Models: Lagrange Interpolation, Anisotropic Grid and Adaptive Domain," NBER Working Papers 19326, National Bureau of Economic Research, Inc.
  5. Katrin Rabitsch & Serhiy Stepanchuk & Viktor Tsyrennikov, 2014. "International Portfolios: A Comparison of Solution Methods," Department of Economics Working Papers wuwp159, Vienna University of Economics, Department of Economics.

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