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Estimation and Evaluation of DSGE Models: Progress and Challenges

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  • Frank Schorfheide

Abstract

Estimated dynamic stochastic equilibrium (DSGE) models are now widely used for empirical research in macroeconomics as well as for quantitative policy analysis and forecasting at central banks around the world. This paper reviews recent advances in the estimation and evaluation of DSGE models, discusses current challenges, and provides avenues for future research.

Suggested Citation

  • Frank Schorfheide, 2011. "Estimation and Evaluation of DSGE Models: Progress and Challenges," NBER Working Papers 16781, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16781
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    References listed on IDEAS

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    1. José-Víctor Ríos-Rull & Frank Schorfheide & Cristina Fuentes-Albero & Raul Santaeulalia-Llopis & Maxym Kryshko, 2009. "Methods versus substance: measuring the effects of technology shocks on hours," Staff Report 433, Federal Reserve Bank of Minneapolis.
    2. Pablo Guerron-Quintana & Atsushi Inoue & Lutz Kilian, 2009. "Frequentist inference in weakly identified DSGE models," Working Papers 09-13, Federal Reserve Bank of Philadelphia.
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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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