Multiple Regression with Inequality Constraints: Pretesting Bias, Hypothesis Testing and Efficiency
Multiple Regression with Inequality Constraints: Pretesting Bias, Hypothesis Testing and Efficiency
复制标题
具有不等式约束的多元回归：预检验偏差、假设检验和效率
DOI：
10.1080/01621459.1970.10481134
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发表时间：
1970
期刊：
影响因子：
--
通讯作者：
E. Prescott
中科院分区：
文献类型：
--
作者：
M. Lovell;E. Prescott
摘要本文在标准多元回归模型的背景下，分析了指定回归系数符号的不等式约束的处理问题。在计量经济学的实践中，当回归系数的符号不正确时，删除问题变量并重新估计方程是很常见的。本文表明，该过程会导致偏差，并可能导致参数估计效率低下。此外，我们表明，当使用删除符号不正确的变量后获得的最终回归测试模型中的其他回归系数时，可能会对显著性水平做出严重夸大的陈述。
Abstract This article analyzes, within the context of the standard multiple regression model, the problem of handling inequality constraints specifying the signs of certain regression coefficients. It is common econometric practice when regression coefficients are encountered with incorrect sign to delete the variables in question and reestimate the equation. This article shows that this procedure causes bias and can lead to inefficient parameter estimates. Furthermore, we show that grossly exaggerated statements concerning significance levels are likely to be made when other regression coefficients in the model are tested with the final regression obtained after deleting variables with incorrect sign.