Inference in Nonparametric Instrumental Variables With Partial Identification
在部分识别框架下，为非参数工具变量模型构建了假设检验方法，推导了检验统计量的渐近分布，并提供了自助法临界值，可用于检验识别集是否满足特定约束，以及构建置信区域。
This paper develops methods for hypothesis testing in a nonparametric instrumental variables setting within a partial identification framework. We construct and derive the asymptotic distribution of a test statistic for the hypothesis that at least one element of the identified set satisfies a conjectured restriction. The same test statistic can be employed under identification, in which case the hypothesis is whether the true model satisfies the posited property. An almost sure consistent bootstrap procedure is provided for obtaining critical values. Possible applications include testing for semiparametric specifications as well as building confidence regions for certain functionals on the identified set. As an illustration we obtain confidence intervals for the level and slope of Brazilian fuel Engel curves. A Monte Carlo study examines finite sample performance.