Information Matrix Test, Parameter Heterogeneity and ARCH: A Synthesis
将White信息矩阵检验应用于带自相关误差的线性回归模型，发现其一个分量等价于Engle的ARCH拉格朗日乘子检验，从而建立了信息矩阵检验、ARCH与参数异质性之间的联系，并提出了条件偏度与静态偏度变异的检验。
We apply the White information matrix (IM) test to the linear regression model with autocorrelated errors. A special case of one component of the test is found to be identical to the Engle Lagrange multiplier (LM) test for autoregressive conditional heteroskedasticity (ARCH). Given Chesher's interpretation of the IM test as a test for parameter heterogeneity, this establishes a connection among the IM test, ARCH and parameter variation. This also enables us to specify conditional heteroskedasticity in a more general and convenient way. Other interesting by-products of our analysis are tests for the variation in conditional and static skewness which we call tests for "heterocliticity".