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

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  • Pierre Lafourcade
  • Joris de Wind

Abstract

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.

Suggested Citation

  • Pierre Lafourcade & Joris de Wind, 2012. "Taking Trends Seriously in DSGE Models: An Application to the Dutch Economy," DNB Working Papers 345, Netherlands Central Bank, Research Department.
  • Handle: RePEc:dnb:dnbwpp:345
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    File URL: https://www.dnb.nl/binaries/Working%20Paper%20345_tcm46-275646.pdf
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    References listed on IDEAS

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    1. Ferroni Filippo, 2011. "Trend Agnostic One-Step Estimation of DSGE Models," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-36, July.
    2. Schmitt-Grohe, Stephanie & Uribe, Martin, 2003. "Closing small open economy models," Journal of International Economics, Elsevier, vol. 61(1), pages 163-185, October.
    3. 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, February.
    4. Iskrev, Nikolay, 2010. "Local identification in DSGE models," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 189-202, March.
    5. Alejandro Justiniano & Giorgio Primiceri & Andrea Tambalotti, 2011. "Investment Shocks and the Relative Price of Investment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 101-121, January.
    6. 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.
    7. Pablo Burriel & Jesús Fernández-Villaverde & Juan Rubio-Ramírez, 2010. "MEDEA: a DSGE model for the Spanish economy," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 1(1), pages 175-243, March.
    8. Whelan, Karl, 2003. " A Two-Sector Approach to Modeling U.S. NIPA Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(4), pages 627-656, August.
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    11. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2008. "Evaluating an estimated new Keynesian small open economy model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2690-2721, August.
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    Cited by:

    1. Kai Liu, 2014. "Public Finances, Business Cycles and Structural Fiscal Balances," Cambridge Working Papers in Economics 1411, Faculty of Economics, University of Cambridge.
    2. Tony Hall & Jan Jacobs & Adrian Pagan, "undated". "Macro-Econometric System Modelling @75," NCER Working Paper Series 95, National Centre for Econometric Research.
    3. Silvio Michael de Azevedo Costa, 2016. "Structural Trends and Cycles in a DSGE Model for Brazil," Working Papers Series 434, Central Bank of Brazil, Research Department.

    More about this item

    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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