Monitoring Parameter Constancy with Endogenous Regressors
针对含内生回归元的线性回归模型，提出基于工具变量和最小二乘的CUSUM型参数变化监测检验，发现最小二乘法在早期结构变化时更敏感，并应用于日本菲利普斯曲线分析。
This article proposes monitoring tests for parameter change in linear regression models with endogenous regressors. We consider a CUSUM‐type test based on the instrumental variable (IV) estimation, as the IV method is standard for models with endogenous regressors. In addition, we propose a test based on the residuals from the least squares (LS) estimation. We show that for a given boundary function, both tests have the same limiting distribution under the null hypothesis, whereas their powers are different. In particular, when a structural change occurs early in a monitoring period, the test based on the LS method tends to detect it more rapidly than that based on the IV method. We apply our methods to investigate the Japanese Phillips curve and show that the LS‐based test performs well to detect a change in 2007, while neither test finds evidence of a change after 2013.