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Estimation of Econometric Model Using Nonlinear Full Information Maximum Likelihood: Preliminary Computer Results

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  • David A. Belsley
  • Kent D. Wall

Abstract

This working paper provides some preliminary results on the computational feasibility of nonlinear full information maximum likelihood (NECML) estimation. Severa1 of the test cases presented were also subjected to nonlinear three stage least square (NLBSLS) estimation in order to illustrate the relative performance of the two estimation techniques. In addition, certain other aspects central to practical implementation are highlighted. These include the effect of various computers on the efficiency of the code, as well as the relative merits of numerical and analytical generation of gradient information. Broadly speaking, NLFIML appears competitive in cost and superior in statistical properties to NL3SLS.

Suggested Citation

  • David A. Belsley & Kent D. Wall, 1976. "Estimation of Econometric Model Using Nonlinear Full Information Maximum Likelihood: Preliminary Computer Results," NBER Working Papers 0142, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:0142
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    References listed on IDEAS

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    1. Chow, Gregory C, 1973. "On the Computation of Full-Information Maximum Likelihood Estimates for Nonlinear Equation Systems," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 104-109, February.
    2. Dale W. Jorgenson & Jean-Jacques Laffont, 1974. "Efficient Estimation of Nonlinear Simultaneous Equations with Additive Disturbances," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 615-640, National Bureau of Economic Research, Inc.
    3. Ray C. Fair, 1973. "A Comparison of FIML and Robust Estimates of a Nonlinear Macroeconomic Model," NBER Working Papers 0015, National Bureau of Economic Research, Inc.
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