Autocorrelation, structural breaks and the predictive ability of dividend yield

We study whether dividend yield (DY) can predict aggregate stock returns while controlling for the effects of structural breaks in the parameters and bias induced by autocorrelation in the predictor variable. To do so we apply the Bai and Perron (BP) (1998, 2000) methodology to test for structural breaks and the bias-adjusted predictability test of Lewellen (2004). We show that although DY predicts market returns during the period 1946 to 1989, there exist 'natural' subsamples bounded by statistically detectable structural breaks that can last for long periods of time (up to 11 years in duration) when DY does not show significant forecasting power. This has important implications in that even if in the long-run DY actually provides strong predictive ability, investors should be mentally prepared for long dry spells of unpredictability with respect to DY.