Spurious Regression and Trending Variables

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. Copyright 2007 Blackwell Publishing Ltd and the Department of Economics, University of Oxford.