Empirical Likelihood Ratio Tests of Conditional Moment Restrictions With Unknown Functions
提出针对条件矩模型的经验似然比检验，允许参数包含无穷维成分，研究了检验统计量的极限分布，并通过蒙特卡洛模拟和恩格尔曲线应用验证了方法。
This article introduces empirical likelihood ratio tests for conditional moment models in which the unknown parameter contains infinite-dimensional components. We allow unknown functions to be included in the conditional moment restrictions. We discusses (1) the limiting distribution of the sieve conditional empirical likelihood ratio (SCELR) test statistic for functionals of parameters under the null hypothesis and local alternatives; and (2) the limiting distribution of the SCELR test statistic for conditional moment restrictions (a consistent specification test) under the null hypothesis and local alternatives. A Monte Carlo study examines finite sample performance. We then apply these tests in an empirical application to construct confidence intervals for Engel curves and test restrictions on the curves.