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Taking Trends Seriously in DSGE Models: An Application to the Dutch Economy

  • Pierre Lafourcade
  • Joris de Wind
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    We construct a new-Keynesian DSGE model tailored to the Netherlands and interpret it as a multivariate unobserved components model. We identify three major stochastic trends in the data—trends in general-purpose technology, investment-specific technology, and labor supply—and model them formally in our theoretical set-up. Our trend-cycle decomposition captures the data's co-integrating properties without which long-run analysis—whether scenario analysis or forecasting—would likely be misspecified. In particular, this approach appears to produce better-behaved posteriors for parameters along decision margins where traditional modeling imposes highly persistent but temporary shocks. The existence of permanent and temporary disturbances along the same margin broadens the scope for counterfactuals. Specifically, differences in short-run responses to the two types of shocks reflect smoothing motives and discounted valuation effects reminiscent of the Permanent Income Hypothesis.

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    File URL: http://www.dnb.nl/binaries/Working%20Paper%20345_tcm46-275646.pdf
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    Paper provided by Netherlands Central Bank, Research Department in its series DNB Working Papers with number 345.

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    Date of creation: Jul 2012
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    Handle: RePEc:dnb:dnbwpp:345
    Contact details of provider: Postal: Postbus 98, 1000 AB Amsterdam
    Web page: http://www.dnb.nl/en/

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    1. Cristiano Cantore & Miguel León-Ledesma & Peter McAdam & Alpo Willman, 2014. "Shocking Stuff: Technology, Hours, And Factor Substitution," Journal of the European Economic Association, European Economic Association, vol. 12(1), pages 108-128, 02.
    2. Schmitt-Grohé, Stephanie & Uribe, Martín, 2002. "Closing Small Open Economy Models," CEPR Discussion Papers 3096, C.E.P.R. Discussion Papers.
    3. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2007. "Evaluating An Estimated New Keynesian Small Open Economy Model," Working Paper Series 203, Sveriges Riksbank (Central Bank of Sweden).
    4. Giorgio E. Primiceri & Andrea Tambalotti & Alejandro Justiniano, 2009. "Investment Shocks and the Relative Price of Investment," 2009 Meeting Papers 686, Society for Economic Dynamics.
    5. Yongsung Chang & Taeyoung Doh & Frank Schorfheide, 2006. "Non-stationary hours in a DSGE model," Working Papers 06-3, Federal Reserve Bank of Philadelphia.
    6. Pablo Burriel & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2009. "MEDEA: A DSGE Model for the Spanish Economy," Working Papers 2009-17, FEDEA.
    7. Ferroni, Filippo, 2009. "Trend agnostic one step estimation of DSGE models," MPRA Paper 14550, University Library of Munich, Germany.
    8. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    9. Karl Whelan, 2001. "A two-sector approach to modeling U.S. NIPA data," Finance and Economics Discussion Series 2001-04, Board of Governors of the Federal Reserve System (U.S.).
    10. Kevin D. Hoover & Soren Johansen & Katarina Juselius, 2008. "Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression," American Economic Review, American Economic Association, vol. 98(2), pages 251-55, May.
    11. Iskrev, Nikolay, 2010. "Local identification in DSGE models," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 189-202, March.
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