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Ensuring the Validity of the Micro Foundation in DSGE Models

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  • Martin Møller Andreasen

    ()
    (School of Economics and Management, University of Aarhus, Denmark and CREATES)

Abstract

The presence of i) stochastic trends, ii) deterministic trends, and/or iii) stochastic volatil- ity in DSGE models may imply that the agents' objective functions attain infinite values. We say that such models do not have a valid micro foundation. The paper derives sufficient condi- tions which ensure that the objective functions of the households and the firms are finite even when various trends and stochastic volatility are included in a standard DSGE model. Based on these conditions we test the validity of the micro foundation in six DSGE models from the literature. The models of Justiniano & Primiceri (American Economic Review, forth- coming) and Fernández-Villaverde & Rubio-Ramírez (Review of Economic Studies, 2007) do not satisfy these sufficient conditions, or any other known set of conditions ensuring finite values for the objective functions. Thus, the validity of the micro foundation in these models remains to be established.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2008-26.

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Length: 43
Date of creation: 26 May 2008
Date of revision:
Handle: RePEc:aah:create:2008-26

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Deterministic trends; DSGE models; Error distributions; Moment generating functions; Stochastic trends; Stochastic volatility; Unit-roots;

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References

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  1. Alejandro Justiniano & Giorgio E. Primiceri, 2006. "The Time Varying Volatility of Macroeconomic Fluctuations," NBER Working Papers 12022, National Bureau of Economic Research, Inc.
  2. Schmitt-Grohé, Stephanie & Uribe, Martín, 2001. "Optimal Fiscal and Monetary Policy Under Sticky Prices," CEPR Discussion Papers 2942, C.E.P.R. Discussion Papers.
  3. Gorodnichenko, Yuriy & Ng, Serena, 2010. "Estimation of DSGE models when the data are persistent," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 325-340, April.
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  7. Theodossiou, Panayiotis & McDonald, James B. & Hansen, Christian B., 2007. "Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models," Economics Discussion Papers 2007-13, Kiel Institute for the World Economy.
  8. Altig, David & Christiano, Lawrence & Eichenbaum, Martin & Lindé, Jesper, 2004. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Working Paper Series 176, Sveriges Riksbank (Central Bank of Sweden).
  9. Peter N. Ireland, 2004. "Technology Shocks in the New Keynesian Model," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 923-936, November.
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  11. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : II. New directions," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 309-341.
  12. Peter Ireland, 1999. "A Method for Taking Models to the Data," Computing in Economics and Finance 1999 1233, Society for Computational Economics.
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  14. Burnside, Craig, 1998. "Solving asset pricing models with Gaussian shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 22(3), pages 329-340, March.
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Citations

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Cited by:
  1. Martin Møller Andreasen, 2008. "Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter," CREATES Research Papers 2008-33, School of Economics and Management, University of Aarhus.
  2. Martin Møller Andreasen, 2008. "How to Maximize the Likelihood Function for a DSGE Model," CREATES Research Papers 2008-32, School of Economics and Management, University of Aarhus.
  3. Martin Møller Andreasen, 2008. "Explaining Macroeconomic and Term Structure Dynamics Jointly in a Non-linear DSGE Model," CREATES Research Papers 2008-43, School of Economics and Management, University of Aarhus.

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