文章基本信息

标题：Non-Negativity of a Quadratic form with Applications to Panel Data Estimation, Forecasting and Optimization
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作者：Bhimasankaram Pochiraju ; Sridhar Seshadri ; Dimitrios Thomakos 等
期刊名称：Stats
电子版ISSN：2571-905X
出版年度：2020
卷号：3
期号：3
页码：185-202
DOI：10.3390/stats3030015
出版社：MDPI AG
摘要：For a symmetric matrix B, we determine the class of Q such that Q t BQ is non-negative definite and apply it to panel data estimation and forecasting: the Hausman test for testing the endogeneity of the random effects in panel data models. We show that the test can be performed if the estimated error variances in the fixed and random effects models satisfy a specific inequality. If it fails, we discuss the restrictions under which the test can be performed. We show that estimators satisfying the inequality exist. Furthermore, we discuss an application to a constrained quadratic minimization problem with an indefinite objective function.
关键词：quadratic form; Non-negativity; Hausman test; optimization quadratic form ; Non-negativity ; Hausman test ; optimization