Dividend Growth Predictability and the Price-Dividend Ratio

Conventional tests of present-value models over-reject the null of no predictability. In order to better account for the intrinsic probability of detecting predictive relations by chance alone, we develop a new nonparametric Monte Carlo testing method, which does not rely on distributional assumptions to aggregate the information from the time series of price-dividend ratios and dividend growth. We find evidence of return predictability, but no apparent evidence of dividend growth predictability in postwar US data, thus reconciling the diverging conclusions in the literature. Our findings are robust to the specification of the predictive information set, the choice of the sample period and the use of different cash-flow proxies.