The likelihood ratio test under nonstandard conditions: Testing the markov switching model of gnp
非标准条件下的似然比检验:检验 GNP 的马尔可夫转换模型
A theory of testing under non-standard conditions is developed. By viewing the likelihood as a function of the unknown parameters, empirical process theory enables us to bound the asymptotic distribution of standardized likelihood ratio statistics, even when conventional regularity conditions (such as unidentified nuisance parameters and identically zero scores) are violated. This testing methodology is applied to the Markov switching model of GNP proposed by Hamilton…