On the Consistency of Nonlinear FIML
Examples are given which show that:(i) normality is not Necessary for the consistency of the quasi maximum likelihood estimator in the nonlinear simultaneous equations model (nonlinear FIML) even when there are major departures from linearity; and (ii) the lemma which is used extensively by Amemiya  in the theoretical development of the properties of nonlinear FIML under the assumption of normality is, as presently stated, incorrect.
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Volume (Year): 50 (1982)
Issue (Month): 5 (September)
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ray C. Fair & William R. Parke, 1979.
"Full Information Estimates of a Nonlinear Macroeconometric Model,"
Cowles Foundation Discussion Papers
519, Cowles Foundation for Research in Economics, Yale University.
- Fair, Ray C. & Parke, William R., 1980. "Full-information estimates of a nonlinear macroeconometric model," Journal of Econometrics, Elsevier, vol. 13(3), pages 269-291, August.
- Gallant, A. Ronald, 1977. "Three-stage least-squares estimation for a system of simultaneous, nonlinear, implicit equations," Journal of Econometrics, Elsevier, vol. 5(1), pages 71-88, January.
- Amemiya, Takeshi, 1974. "The nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 2(2), pages 105-110, July.
- Gallant, A Ronald & Holly, Alberto, 1980. "Statistical Inference in an Implicit, Nonlinear, Simultaneous Equation Model in the Context of Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 48(3), pages 697-720, April.
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