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无需预先知道函数形式也能一致估计弹性AI 解读

We consider an open question in applied price theory: Without a priori knowledge of a firm's cost function or a consumer's indirect utility function, is it possible to estimate price and substitution elasticities consistently by observing a demand system? As the work of White [30], Guilkey, Lovell, and Sickles [19], and others has shown, ordinary flexible functional forms such as the translog cannot achieve this objective. We find that if one is prepared to assume that…

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隐式非线性联立方程模型中最大似然估计框架下的统计推断AI 解读

A. Ronald Gallant, Alberto Holly, Statistical Inference in an Implicit, Nonlinear, Simultaneous Equation Model in the Context of Maximum Likelihood Estimation, Econometrica, Vol. 49, No. 2 (Mar., 1981), p. 554

隐式非线性联立方程模型中基于最大似然估计的统计推断AI 解读

A. Ronald Gallant, Alberto Holly, Statistical Inference in an Implicit, Nonlinear, Simultaneous Equation Mode in the Context of Maximum Likelihood Estimation, Econometrica, Vol. 48, No. 3 (Apr., 1980), pp. 697-720

非线性回归中参数函数的显式估计量AI 解读

Abstract When repetitive estimations are to be made under field conditions using data that follow a nonlinear regression law, a simple polynomial function of the observations has considerable appeal as an estimator. The polynomial estimator of finite degree with smallest average mean squared error is found. Conditions are given such that as degree increases it converges in probability to the Bayes estimator and its average mean squared error converges to the lower bound of…

非线性回归中参数函数的显式估计量AI 解读

When repetitive estimations are to be made under field conditions using data that follow a nonlinear regression law, a simple polynomial function of the observations has considerable appeal as an estimator. The polynomial estimator of finite degree with smallest average mean squared error is found. Conditions are given such that as degree increases it converges in probability to the Bayes estimator and its average mean squared error converges to the lower bound of all square…

非线性回归设定检验：一个非正则情形AI 解读

A statistical test of whether an additive nonlinear term in the response function should be omitted from a nonlinear regression specification is considered. The regularity conditions used to obtain the asymptotic distributions of the customary test statistics are violated when the null hypothesis of omission is true. Moreover, standard iterative algorithms are likely to perform poorly when the data support the null hypothesis. Methods designed to circumvent these…

具有自相关误差的非线性回归AI 解读

An estimator of the parameters of a nonlinear time series regression is obtained by using an autoregressive assumption to approximate the variance-covariance matrix of the disturbances. Considerations are set forth which suggest that this estimator will have better small sample efficiency than circular estimators. Such is the case for examples considered in a Monte Carlo study.

非线性回归模型中部分参数的检验AI 解读

The problem of testing for the location of a subset of the parameters entering the response function of a nonlinear regression model is considered. Two test statistics—the likelihood ratio test statistic and a test statistic derived from the asymptotic normality of the least squares estimator—for this problem are discussed and compared. The large-sample distributions of these statistics are derived and Monte Carlo power estimates are compared with power computed using the…