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General Equilibrium Restrictions for Dynamic Factor Models

Author

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  • David de Antonio Liedo

    () (Banco de España)

Abstract

This paper proposes the use of dynamic factor models as an alternative to the VAR-based tools for the empirical validation of dynamic stochastic general equilibrium (DSGE) theories. Along the lines of Giannone et al. (2006), we use the state-space parameterisation of the factor models proposed by Forni et al. (2007) as a competitive benchmark that is able to capture weak statistical restrictions that DSGE models impose on the data. Beyond the weak restrictions, which are given by the number of shocks and the number of state variables, the behavioural restrictions embedded in the utility and production functions of the model economy contribute to achieve further parsimony. Such parsimony reduces the number of parameters to be estimated, potentially helping the general equilibrium environment improve forecast accuracy. In turn, the DSGE model is considered to be misspecified when it is outperformed by the state-space representation that only incorporates the weak restrictions.

Suggested Citation

  • David de Antonio Liedo, 2010. "General Equilibrium Restrictions for Dynamic Factor Models," Working Papers 1012, Banco de España;Working Papers Homepage.
  • Handle: RePEc:bde:wpaper:1012
    as

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    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/10/Fic/dt1012e.pdf
    File Function: First version, April 2010
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    References listed on IDEAS

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    1. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    2. Claudio Borio & Mathias Drehmann, 2011. "Toward an Operational Framework for Financial Stability: “Fuzzy” Measurement and Its Consequences," Central Banking, Analysis, and Economic Policies Book Series,in: Rodrigo Alfaro (ed.), Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 4, pages 063-123 Central Bank of Chile.
    3. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    4. Rodrigo Alfaro & Mathias Drehmann, 2009. "Macro stress tests and crises: what can we learn?," BIS Quarterly Review, Bank for International Settlements, December.
    5. Thomas Breuer & Martin Jandacka & Klaus Rheinberger & Martin Summer, 2009. "How to Find Plausible, Severe and Useful Stress Scenarios," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 205-224, September.
    6. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    7. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
    8. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    9. Miroslav Misina & David Tessier & Shubhasis Dey, 2006. "Stress Testing the Corporate Loans Portfolio of the Canadian Banking Sector," Staff Working Papers 06-47, Bank of Canada.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    dynamic and static rank; factor models; DSGE models; forecasting;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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