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Measurement with minimal theory

Author

Listed:
  • Ellen R. McGrattan

Abstract

Applied macroeconomists interested in identifying the sources of business cycle fluctuations typically have no more than 40 or 50 years of data at a quarterly frequency. With sample sizes that small, identifi cation may not be possible even with correctly specifi ed representations of the data. In this article, I investigate whether small samples are indeed a problem for some commonly used statistical representations. I compare three?a vector autoregressive moving average (VARMA), an unrestricted state space, and a restricted state space?that are all consistent with the same prototype business cycle model. The statistical representations that I consider differ in the amount of a priori theory that is imposed, but all are correctly specifi ed. I fi nd that the identifying assumptions of VARMAs and unrestricted state space representations are too minimal: the range of estimates for statistics of interest for business cycle researchers is so large as to be uninformative.

Suggested Citation

  • Ellen R. McGrattan, 2010. "Measurement with minimal theory," Quarterly Review, Federal Reserve Bank of Minneapolis, issue July, pages 2-13.
    • Handle: RePEc:fip:fedmqr:y:2010:i:july:p:2-13:n:v.33no.1
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    Cited by:

    1. Victor Bystrov, 2020. "Identification and Estimation of Initial Conditions in Non-Minimal State-Space Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(4), pages 413-429, December.
    2. Paul Beaudry & Fabrice Collard & Patrick Fève & Alain Guay & Franck Portier, 2022. "Dynamic Identification in VARs," Working Papers hal-03863451, HAL.
    3. Charles Olivier Mao Takongmo, 2021. "DSGE models, detrending, and the method of moments," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 67-99, January.
    4. Canova, Fabio, 2014. "Bridging DSGE models and the raw data," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 1-15.
    5. Gianluca, MORETTI & Giulio, NICOLETTI, 2008. "Estimating DGSE models with long memory dynamics," Discussion Papers (ECON - Département des Sciences Economiques) 2008037, Université catholique de Louvain, Département des Sciences Economiques.
    6. Gianluca Moretti & Giulio Nicoletti, 2010. "Estimating DSGE models with unknown data persistence," Temi di discussione (Economic working papers) 750, Bank of Italy, Economic Research and International Relations Area.
    7. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.

    More about this item

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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