A GENERAL CLASS OF NON-NESTED TEST STATISTICS FOR MODELS DEFINED THROUGH MOMENT RESTRICTIONS
提出了一类新的Cox非嵌套检验统计量，适用于通过过度识别矩条件定义的模型，并研究了其渐近性质，通过蒙特卡洛模拟检验了其表现。
In this article, we introduce a new class of Cox’s non-nested test statistics for models defined through overidentifying moment restrictions that depend on a finite dimensional parameter vector. In addition to showing that the GEL test statistics proposed in Smith (1997, Economic Journal 107, 503–519) and Ramalho and Smith (2002, Journal of Econometrics 107, 99–125) are members of this class, we reveal that further members can be constructed using the artificial compound model approach, which was originally applied by Atkinson (1970, Journal of the Royal Statistical Society, Series B 32, 323–335) in the parametric setting. We investigate the asymptotic properties of the statistics and propose tests based on modified versions of these statistics that have correct asymptotic size in a uniform sense, a requirement not satisfied by existing Cox’s non-nested tests. A Monte Carlo study examines the performance of the proposed tests.