Panel-Data Estimation in Finance: Testable Assumptions and Parameter (In)Consistency
研究了金融面板数据应用中估计量一致性的必要条件：严格外生性假设，提出了检验方法，发现常见回归中该假设常被拒绝，导致推断错误，并给出解决建议。
We investigate the strict-exogeneity assumption, a necessary condition for estimator consistency in many finance panel-data applications. We outline tests for strict exogeneity in both traditional (non–instrumental variable (IV)) and IV settings. When we apply these tests in common traditional finance panel regressions, we find that the strict-exogeneity assumption is often strongly rejected, suggesting large inference errors. We test for strict exogeneity in specific finance panel-data IV settings and illustrate the potential for these tests to help confirm, or rule out, the validity of common panel-data IV estimators. We offer recommendations to address the strict-exogeneity issue in finance research.