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Tractable Likelihood-Based Estimation of Non-Linear DSGE Models Using Higher-Order Approximations

Listed author(s):
  • Robert Kollmann

This paper discusses a tractable approach for computing the likelihood function of non-linear Dynamic Stochastic General Equilibrium (DSGE) models that are solved using second- and third order accurate approximations. By contrast to particle filters, no stochastic simulations are needed for the method here. The method here is, hence, much faster and it is thus suitable for the estimation of medium-scale models. The method assumes that the number of exogenous innovations equals the number of observables. Given an assumed vector of initial states, the exogenous innovations can thus recursively be inferred from the observables. This easily allows to compute the likelihood function. Initial states and model parameters are estimated by maximizing the likelihood function. Numerical examples suggest that the method provides reliable estimates of model parameters and of latent state variables, even for highly non-linear economies with big shocks.

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File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/228887/3/2016-15-KOLLMANN-tractable.pdf
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Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number ECARES 2016-15.

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Length: 15 p.
Date of creation: Mar 2016
Publication status: Published by:
Handle: RePEc:eca:wpaper:2013/228887
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  1. Sergey Ivashchenko, 2014. "DSGE Model Estimation on the Basis of Second-Order Approximation," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 71-82, January.
  2. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models—Rejoinder," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 211-219.
  3. Robert Kollmann, 2015. "Tractable Latent State Filtering for Non-Linear DSGE Models Using a Second-Order Approximation and Pruning," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 239-260, February.
  4. Kollmann, Robert, 2012. "Global Banks, Fiscal Policy and International Business Cycles," MPRA Paper 69887, University Library of Munich, Germany.
  5. Jesus Fernandez-Villaverde & Pablo Guerron-Quintana & Juan F. Rubio-Ramirez & Martin Uribe, 2011. "Risk Matters: The Real Effects of Volatility Shocks," American Economic Review, American Economic Association, vol. 101(6), pages 2530-2561, October.
  6. Otrok, Christopher, 2001. "On measuring the welfare cost of business cycles," Journal of Monetary Economics, Elsevier, vol. 47(1), pages 61-92, February.
  7. Robert Kollmann, 2013. "Global Banks, Financial Shocks, and International Business Cycles: Evidence from an Estimated Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(s2), pages 159-195, December.
  8. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
  9. Benjamin Born & Johannes Pfeifer, 2014. "Risk Matters: The Real Effects of Volatility Shocks: Comment," American Economic Review, American Economic Association, vol. 104(12), pages 4231-4239, December.
  10. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
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