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首页> 外文期刊>Journal of Econometrics >A Numerically Stable Quadrature Procedure for the One-Factor Random-Component Discrete Choice Model.
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A Numerically Stable Quadrature Procedure for the One-Factor Random-Component Discrete Choice Model.

机译:一因素随机分量离散选择模型的数值稳定正交过程。

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摘要

The Gaussian quadrature formula had been popularized by Butler and Moffitt (1982) for the estimation of the error component probit panel model. Borjas and Sueyoshi (1994) pointed out some numerical and statistical difficulties of applying it to models with group effects. With a moderate or large number of individuals in a group, the likelihood function of the model evaluated by the Gaussian quadrature formula can be numerically unstable, and at worst, impossible to evaluate. Statistical inference may also be inaccurate. We point out that some of these difficulties can be overcome with a carefully designed algorithm and the proper selection of the number of quadrature points. However, with a very large number of individuals in a group, the Gaussian quadrature formulation of integral may have large numerical approximation errors.
机译:高斯正交公式已由Butler和Moffitt(1982)推广用于估计误差分量概率面板模型。 Borjas和Sueyoshi(1994)指出了将其应用于具有群体效应的模型的一些数值和统计困难。对于一组中的中等数量或大量个体,通过高斯正交公式评估的模型的似然函数在数值上可能不稳定,并且在最坏的情况下无法评估。统计推断也可能不准确。我们指出,这些困难中的一些可以通过精心设计的算法和正交点数量的适当选择来克服。但是,在一个组中有大量个体的情况下,积分的高斯正交公式可能具有较大的数值逼近误差。

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