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Maximum Likelihood Methods

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Econometrics

Part of the book series: Springer Study Edition ((SSE))

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Abstract

In dealing with the problem of estimating the parameters of a structural system of equations, we had not, in previous chapters, explicitly stated the form of the density of the random terms appearing in the system. Indeed, the estimation aspects of classical least squares techniques and their generalization to systems of equations are distribution free, so that no explicit assumption need be made with respect to the distribution of the error terms. On the other hand, in considering various tests of significance on 2SLS or 3SLS estimated parameters of a structural system, we have occasionally found it convenient to assert (joint) normality of the structural error terms. Under this assumption, the derivation of the asymptotic distribution of such estimators is simplified considerably.

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Authors and Affiliations

  1. Columbia University, USA

    Phoebus J. Dhrymes (Professor of Economics)

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  1. Phoebus J. Dhrymes
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© 1974 Springer-Verlag New York Inc

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Dhrymes, P.J. (1974). Maximum Likelihood Methods. In: Econometrics. Springer Study Edition. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-9383-2_7

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  • DOI: https://doi.org/10.1007/978-1-4613-9383-2_7

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-90095-7

  • Online ISBN: 978-1-4613-9383-2

  • eBook Packages: Springer Book Archive

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