01783cam a22002777 4500001000600000003000500006005001700011006001900028007001500047008004100062100002200103245012300125260006600248300005700314490004100371500001500412520069400427530006001121538007201181538003601253588002501289710004201314830007601356856003701432856003601469w0090NBER20200328111750.0m o d cr cnu||||||||200328s1975 mau fo 000 0 eng d1 aAmemiya, Takeshi.14aThe Maximum Likelihood Stage Least Squares Estimator in the Nonlinear Simultaneous Equations Model /cTakeshi Amemiya. aCambridge, Mass.bNational Bureau of Economic Researchc1975. a1 online resource:billustrations (black and white);1 aNBER working paper seriesvno. w0090 aJune 1975.3 aThe consistency and the asymptotic normality of the maximum likelihood estimator in the general nonlinear simultaneous equation model are proved. It is shown that the proof depends on the assumption of normality unlike in the linear simultaneous equation model. It is proved that the maximum likelihood estimator is asymptotically more efficient than the nonlinear three-stage least squares estimator if the specification is correct, However, the latter has the advantage of being consistent even when the normality assumption is removed. Hausrnan' s instrumental-variable-interpretation of the maximum likelihood estimator is extended to the general nonlinear simultaneous equation model. aHardcopy version available to institutional subscribers aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web.0 aPrint version record2 aNational Bureau of Economic Research. 0aWorking Paper Series (National Bureau of Economic Research)vno. w0090.40uhttp://www.nber.org/papers/w009040uhttp://dx.doi.org/10.3386/w0090