  This paper examines three types of spurious regressions where both the
dependent and independent variables contain deterministic trends, stochastic
trends, or breaking trends. We show that the problem of spurious regression
disappears if the trend functions are included as additional regressors. In the
presence of autocorrelation, we show that using a Feasible General Least Square
(FGLS) estimator can help alleviate or eliminate the problem. Our theoretical
results are clearly reflected in finite samples. As an illustration, we apply
our methods to revisit the seminal study of Yule (1926).
