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Generalized Least Squares Estimation of Linear Models Containing Rational Future Expectations

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  • Nijman, Theo
  • Palm, Franz

Abstract

The authors discuss the choice of approximations for unobserved expectations underlying consistent estimators in linear rational expectations models with future expectations. They show how estimators that are more efficient than the commonly used GMM estimators can be obtained if it is assumed that the future expectation depends on a finite number of variables only. Numerical results for a simple model illustrate the related efficiency of various estimators. Copyright 1991 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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  • Nijman, Theo & Palm, Franz, 1991. "Generalized Least Squares Estimation of Linear Models Containing Rational Future Expectations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(2), pages 383-389, May.
  • Handle: RePEc:ier:iecrev:v:32:y:1991:i:2:p:383-89
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    Cited by:

    1. Nijman, T.E. & Palm, F.C., 1991. "Recent Developments in Modeling Volatility in Financial Data," Papers 9168, Tilburg - Center for Economic Research.
    2. Zou, L., 1993. "Ownership structure and efficiency : An incentive mechanism approach," Other publications TiSEM a72a05c2-b3f2-47c7-a003-f, Tilburg University, School of Economics and Management.
    3. van Wijnbergen, Sweder, 1992. "Trade Reform, Policy Uncertainty, and the Current Account: A Non-Expected-Utility Approach," American Economic Review, American Economic Association, vol. 82(3), pages 626-633, June.
    4. Van Soest, Arthur & Kooreman, Peter, 1990. "Coherency of the indirect translog demand system with binding nonnegativity constraints," Journal of Econometrics, Elsevier, vol. 44(3), pages 391-400, June.
    5. Kapteyn, Arie & Kooreman, Peter & van Soest, Arthur, 1990. "Quantity Rationing and Concavity in a Flexible Household Labor Supply Model," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 55-62, February.
    6. Kapteyn, Arie & Kooreman, Peter, 1992. "Household labor supply: What kind of data can tell us how many decision makers there are?," European Economic Review, Elsevier, vol. 36(2-3), pages 365-371, April.
    7. Strijbosch, L.W.G. & Heuts, R.M.J., 1994. "Investigating several alternatives for estimating the lead time demand distribution in a continuous review inventory model," Other publications TiSEM dc1f886c-0122-4da9-9598-8, Tilburg University, School of Economics and Management.
    8. Alogoskoufis, George S. & van der Ploeg, Frederick, 1991. "On budgetary policies, growth, and external deficits in an interdependent world," Journal of the Japanese and International Economies, Elsevier, vol. 5(4), pages 305-324, December.
    9. Barten, A.P., 1992. "The estimation of mixed demand systems," Other publications TiSEM 182f4296-e95b-4dea-aa8b-d, Tilburg University, School of Economics and Management.
    10. Nijman, T.E. & Palm, F.C., 1991. "Recent developments in modeling volatility in financial data," Other publications TiSEM 0c1ff78c-d484-43bb-bcc3-a, Tilburg University, School of Economics and Management.

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