Generalised empirical likelihood testing in semiparametric conditional moment restrictions models
展示了如何用广义经验似然方法对半参数条件矩限制模型进行设定检验，提出了类似Kolmogorov-Smirnov和Cramer von Mises的检验统计量，并应用于工具变量平滑系数模型和删失非线性分位数回归模型，蒙特卡洛结果显示了良好的有限样本性质。
This paper shows how generalized empirical likelihood can be used to obtain specification tests in semiparametric conditional moment restrictions models. The resulting test statistics are similar in spirit to classical Kolmogorov–Smirnov and Cramer von Mises goodness‐of‐fit statistics and are based on an integrated version of the original moment restrictions. The results are applied to test the correct specification of an instrumental variable smooth varying coefficient model and of a censored non‐linear quantile regression model. Monte Carlo results suggest that the proposed tests have competitive finite sample properties.