Utvidet returrett til 31. januar 2025

Bayesian Estimation of DSGE Models

Om Bayesian Estimation of DSGE Models

"This book depicts valuable and revealing methods for solving, estimating, and analyzing a class of dynamic equilibrium models of the macroeconomy. It describes formally tractable techniques for the study of macroeconomic models that feature transition mechanisms for a large number of underlying shocks. Both authors have played important roles in developing and applying these techniques. This is a terrific resource for how to use these methods in practice."--Lars Peter Hansen, David Rockefeller Distinguished Service Professor of Economics, University of Chicago, and recipient of the Nobel Prize in economics"This timely book collects in one place many of the key Markov chain Monte Carlo methods for numerical Bayesian inference along with many of their recent refinements. Written for applied users, it offers clear descriptions of each algorithm and illustrates how it can be used to estimate dynamic stochastic general equilibrium models in macroeconomics."--James D. Hamilton, Professor of Economics, University of California, San Diego"This is perhaps the most thorough book available on how to estimate DSGE models using sophisticated Bayesian computation tools. It is an excellent resource for professionals and advanced students of the topic."--Serena Ng, Professor of Economics, Columbia University

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  • Språk:
  • Engelsk
  • ISBN:
  • 9780691161082
  • Bindende:
  • Hardback
  • Sider:
  • 296
  • Utgitt:
  • 29. desember 2015
  • Dimensjoner:
  • 140x217x25 mm.
  • Vekt:
  • 480 g.
  • BLACK NOVEMBER
  På lager
Leveringstid: 4-7 virkedager
Forventet levering: 5. desember 2024

Beskrivelse av Bayesian Estimation of DSGE Models

"This book depicts valuable and revealing methods for solving, estimating, and analyzing a class of dynamic equilibrium models of the macroeconomy. It describes formally tractable techniques for the study of macroeconomic models that feature transition mechanisms for a large number of underlying shocks. Both authors have played important roles in developing and applying these techniques. This is a terrific resource for how to use these methods in practice."--Lars Peter Hansen, David Rockefeller Distinguished Service Professor of Economics, University of Chicago, and recipient of the Nobel Prize in economics"This timely book collects in one place many of the key Markov chain Monte Carlo methods for numerical Bayesian inference along with many of their recent refinements. Written for applied users, it offers clear descriptions of each algorithm and illustrates how it can be used to estimate dynamic stochastic general equilibrium models in macroeconomics."--James D. Hamilton, Professor of Economics, University of California, San Diego"This is perhaps the most thorough book available on how to estimate DSGE models using sophisticated Bayesian computation tools. It is an excellent resource for professionals and advanced students of the topic."--Serena Ng, Professor of Economics, Columbia University

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