Testing for Heterogeneous Parameters in Least-Squares Approximations
提出基于重抽样估计的检验方法，用于判断线性最小二乘估计中参数是否具有共同均值或独立同分布，适用于截面数据模型。
This paper suggests tests for the heterogeneity of parameters in linear least-squares estimation. The tests are based on the properties of resampled estimates, and test the hypotheses that the parameters have a common mean, or that they are independently and identically distributed. The tests can be viewed as the analogue of those based on recursive residuals, in cross-sectional models. We analyse the properties of tests based on jack-knifed estimates in the linear regression model, and compare their performance in a small empirical application.