PRACTITIONERS CORNER A POSITIVE SEMI‐DEFINITE COVARIANCE MATRIX FOR HAUSMAN SPECIFICATION TESTS OF CONDITIONAL AND MARGINAL DENSITIES
针对豪斯曼检验中常用协方差估计在有限样本下可能非正半定导致检验统计量为负的问题，本文给出一个简单且一致的、在任何有限样本下都正半定的协方差矩阵。
ABSTRACT When the joint density of data can be factorized into a conditional and marginal densities, Hausman test can be used for diagnosing misspecifications of these densities. However, since common covariance estimates of the difference of the two estimators used in Hausman test need not be positive semi‐definite in finite samples, the test statistic may be negative. This paper presents a simple and consistent covariance matrix which is positive semi‐definite in any finite sample.