On the interactions of unit roots and exogeneity
研究了数据生成过程中单位根的存在与条件变量弱外生性或强外生性对估计和推断的影响，通过渐近分布分析和蒙特卡洛模拟验证了弱外生性在单方程估计中的重要作用。
The paper considers the impact on estimation and inference of interactions between the existence of unit roots in a data generation process and the presence or absence of weak and strong exogeneity of conditioning variables for the parameters of interest in individual cointegrated linear relationships. The asymptotic distributions of estimators for single equation conditional linear relations are analyzed in conjunction with a Monte Carlo study. The results confirm the important role of weak exogeneity in single equation estimation from integratedcointegrated data; highlight the advantages of using an asymptotic analysis to understand the complicated interactions observed; and reveal the accuracy of the limiting distributions in characterizing finite sample behaviour.