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Mixing Forecasts in Linear Simultaneous Equations Under Quadratic Loss

In: Contributions to Consumer Demand and Econometrics

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  • Esfandiar Maasoumi

Abstract

In the econometric literature a great variety of ‘improved’ estimators have been proposed which are commonly expressible as mixtures of traditional estimators. Minimum risk (MELO) Bayesian estimators, Steinlike and pre-test estimators, mixed regression and Minimum Mean Squared Error (MMSE) are examples of such estimators. See Zellner and Vandaele (1975) and Maasoumi (1978, 1984). Zellner and Vandaele (1975) consider the Bayesian interpretations of such estimators, Sawa (1973) considers a MMSE combination of the OLS and 2SLS structural estimators, and Newbold and Granger (1974) is an example where informal mixtures of predictors have been investigated and observed to perform well.

Suggested Citation

  • Esfandiar Maasoumi, 1992. "Mixing Forecasts in Linear Simultaneous Equations Under Quadratic Loss," Palgrave Macmillan Books, in: Ronald Bewley & Tran Hoa (ed.), Contributions to Consumer Demand and Econometrics, chapter 10, pages 176-188, Palgrave Macmillan.
    • Handle: RePEc:pal:palchp:978-1-349-12221-9_10
    DOI: 10.1007/978-1-349-12221-9_10
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