A Consistent Model Specification Test for Nonparametric Estimation of Regression Function Models
提出一个通用框架，用于检验非参数平滑估计中回归函数的设定是否正确，可检验变量遗漏、非线性约束及参数/半参数模型的正确性，适用于独立同分布和时间序列数据，允许部分或全部解释变量为离散型。
This paper proposes a general framework for specification testing of the regression function in a nonparametric smoothing estimation context. The same analysis can be applied to cases as varied as testing for omission of variables, testing certain nonlinear restrictions in the regressors, and testing the correct specification of some parametric or semiparametric model of interest, for example, testing a certain type of nonlinearity of the regression function. Furthermore, the test can be applied to i.i.d. and time-series data, and some or all of the regressors are allowed to be discrete. A Monte Carlo simulation is used to assess the performance of the test in small and medium samples.