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Assessing DSGE model nonlinearities

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  • S. Boragan Aruoba
  • Luigi Bocola
  • Frank Schorfheide

Abstract

We develop a new class of nonlinear time-series models to identify nonlinearities in the data and to evaluate nonlinear DSGE models. U.S. output growth and the federal funds rate display nonlinear conditional mean dynamics, while inflation and nominal wage growth feature conditional heteroskedasticity. We estimate a DSGE model with asymmetric wage/price adjustment costs and use predictive checks to assess its ability to account for nonlinearities. While it is able to match the nonlinear inflation and wage dynamics, thanks to the estimated downward wage/price rigidities, these do not spill over to output growth or the interest rate.

Suggested Citation

  • S. Boragan Aruoba & Luigi Bocola & Frank Schorfheide, 2013. "Assessing DSGE model nonlinearities," Working Papers 13-47, Federal Reserve Bank of Philadelphia.
  • Handle: RePEc:fip:fedpwp:13-47
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    Cited by:

    1. Jean-François Rouillard, 2017. "Credit Crunch and Downward Nominal Wage Rigidities," Cahiers de recherche 17-05, Departement d'Economique de l'École de gestion à l'Université de Sherbrooke.
    2. Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2017. "Estimating the real effects of uncertainty shocks at the Zero Lower Bound," European Economic Review, Elsevier, vol. 100(C), pages 257-272.
    3. Caiani, Alessandro & Godin, Antoine & Caverzasi, Eugenio & Gallegati, Mauro & Kinsella, Stephen & Stiglitz, Joseph E., 2016. "Agent based-stock flow consistent macroeconomics: Towards a benchmark model," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 375-408.
    4. James Morley & Irina B Panovska, 2016. "Is Business Cycle Asymmetry Intrinsic in Industrialized Economies?," Discussion Papers 2016-12, School of Economics, The University of New South Wales.
    5. repec:eee:moneco:v:91:y:2017:i:c:p:52-68 is not listed on IDEAS
    6. Dongya Koh & Raül Santaeulàlia-Llopis, 2017. "Countercyclical Elasticity of Substitution," Working Papers 946, Barcelona Graduate School of Economics.
    7. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    8. S. Borağan Aruoba & Pablo Cuba-Borda & Frank Schorfheide, 2012. "Macroeconomic Dynamics Near the ZLB: A Tale of Two Countries," PIER Working Paper Archive 14-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 19 Jun 2014.
    9. Luigi Bocola, 2016. "The Pass-Through of Sovereign Risk," Journal of Political Economy, University of Chicago Press, vol. 124(4), pages 879-926.
    10. Gorodnichenko, Yuriy & Ng, Serena, 2017. "Level and volatility factors in macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 91(C), pages 52-68.
    11. Lind�, Jesper & Trabandt, Mathias, 2017. "Should We Use Linearized Models To Calculate Fiscal Multipliers?," CEPR Discussion Papers 12533, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Wages ; Prices ; Inflation (Finance) ; Nonlinear theories ; Time-series analysis;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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