Advanced Econometrics Takeshi Amemiya

Methods of Iteration

Be it for the maximum likelihood or the nonlinear least squares estimator, we cannot generally solve the equation of the form (4.1.9) explicitly for 0. Instead, we must solve it iteratively: Start from an initial estimate of 0 (say 0,) and obtain a sequence of estimates {§„} by iteration, which we hope will converge to the global maximum (or minimum) of QT or at least a root of Eq. (4.1.9). Numerous iterative methods have been proposed and used. In this section we shall discuss several well-known methods that are especially suitable for ob­taining the maximum likelihood and the nonlinear least squares estimator. Many of the results of this section can be found in Goldfeld and Quandt (1972), Draper and Smith (1981), or, more extensively, in Quandt (1983).

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Advanced Econometrics Takeshi Amemiya

Nonlinear Limited Information Maximum Likelihood Estimator

In the preceding section we assumed the model (8.1.1) without specifying the model for Y( or assuming the normality of u, and derived the asymptotic distribution of the class of …

Results of Cosslett: Part II

Cosslett (1981b) summarized results obtained elsewhere, especially from his earlier papers (Cosslett, 1978, 1981a). He also included a numerical evalua­tion of the asymptotic bias and variance of various estimators. We …

Other Examples of Type 3 Tobit Models

Roberts, Maddala, and Enholm (1978) estimated two types of simultaneous equations Tobit models to explain how utility rates are determined. One of their models has a reduced form that is …

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