Spurious Regression and Trending Variables*
分析了线性伪回归模型中因变量和解释变量不同非平稳行为的渐近和有限样本影响，推导了t统计量的概率阶数，并通过模拟验证了伪回归现象在双方非平稳时普遍存在。
Abstract This paper analyses the asymptotic and finite‐sample implications of different types of non‐stationary behaviour among the dependent and explanatory variables in a linear spurious regression model. We study cases when the non‐stationarity in the dependent and explanatory variables is deterministic as well as stochastic. In particular, we derive the order in probability of the t ‐statistic in a spurious regression equation under a variety of empirically relevant data generation processes, and show that the spurious regression phenomenon is present in all cases when both dependent and explanatory variables behave in a non‐stationary way. Simulation experiments confirm our asymptotic results.