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Generalized Spectral Estimation

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  • Jeremy Berkowitz

Abstract

This paper provides a famework for estimating parameters in a wide class of dynamic rational expectations models. The framework recognizes that RE models are often meant to match the data only in limited ways. In particular, interest may focus on a subset of frequencies. This paper designs a frequency domain version of GMM. The estimator has several advantages over traditional GMM. Aside from allowing band-restricted estimation, it does not require making arbitrary instrument or weighting matrix choices. The framework also includes least squares, maximum likelihood, and band restricted maximum likelihood as special cases.

Suggested Citation

  • Jeremy Berkowitz, "undated". "Generalized Spectral Estimation," Finance and Economics Discussion Series 1996-37, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
  • Handle: RePEc:fip:fedgfe:1996-37
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    File URL: http://www.federalreserve.gov/pubs/feds/1996/199637/199637pap.pdf
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    References listed on IDEAS

    as
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    5. Durlauf, Steven N., 1991. "Spectral based testing of the martingale hypothesis," Journal of Econometrics, Elsevier, vol. 50(3), pages 355-376, December.
    6. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    7. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    8. Engle, Robert F, 1974. "Band Spectrum Regression," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(1), pages 1-11, February.
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