Inference in Nonlinear Econometric Models with Structural Change
将线性回归模型的结构变化经典检验扩展到多种非线性模型，提出了Wald、拉格朗日乘子和似然比类检验统计量，并允许观测值存在异质性和时间依赖，为非线性参数计量经济模型的估计与检验提供了统一框架。
This paper extends the classical test for structural change in linear regression models (see Chow (1960)) to a wide variety of nonlinear models, estimated by a variety of different procedures. Wald, Lagrange multiplier-like, and likelihood ratio-like test statistics are introduced. The results allow for heterogeneity and temporal dependence of the observations. In the process of developing the above tests, the paper also provides a compact presentation of general unifying results for estimation and testing in nonlinear parametric econometric models.