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The Restricted Least Squares Estimator: A Pedagogical Note
The authors obtain expressions for the restricted least squares estimator and its covariance matrix in the classical regression model when the matrix of regressors is not necessarily of full rank. The standard expressions for the restricted least squares estimator are not usable in the short rank case because they rely on the unrestricted estimator. But, in the presence of restrictions, the restricted least squares estimator may be computable even if the unrestricted…
A Gamma-distributed stochastic frontier model
服从 Gamma 分布的随机前沿模型
We modify the stochastic frontier model of Aigner, Lovell, and Schmidt to allow the one-sided part of the disturbance to have a two-parameter Gamma distribution rather than the less flexible half-normal distribution. Maximum-likelihood estimation and the estimation of firm-specific inefficiency estimates require the evaluation of integrals which have no closed form and for which there are no polynomial approximations available. We consider two methods of computing these…
Reverse Regression: The Algebra of Discrimination
反向回归：歧视的代数分析
How should discrimination in the marketplace be defined? The answer is less obvious than it might seem. As Conway and Roberts (1983) suggest, there are various definitions. The data may suggest that for given qualifications, in given jobs, women are paid less than men, suggesting discriminatory behavior. But the same data set may or may not suggest that at given salary levels, women and men have the same qualifications. What should we conclude in the case of a conflict? The…
Estimation of limited dependent variable models by ordinary least squares and the method of moments
Maximum likelihood estimation of stochastic frontier production models
Sample Selection Bias as a Specification Error: A Comment
On the Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model
Tobit 模型普通最小二乘估计量的渐近偏差
This paper presents a precise characterization of the bias of least squares in two limited dependent variable models, the Tobit model and the truncated regression model. For the cases considered, the method of moments can be used to correct the bias of OLS. For more general cases, the results provide approximations which appear to be relatively robust. 13, and o, . In this paper we present a precise characterization of that bias for the particular case in which xt, as well…