Working Papers in Economics,
University of Gothenburg, Department of Economics

Abstract: Stock return predictability is a central issue in empirical finance. Yet no comprehensive study of international data has been performed to test the predictive ability of lagged explanatory variables. In fact, most stylized facts are based on U.S. stock-market data. In this paper, I test for stock return predictability in the largest and most comprehensive data set analyzed so far, using four common forecasting variables: the dividend- and earnings-price ratios, the short interest rate, and the term spread. The data contain over 20,000 monthly observations from 40 international markets, including markets in 22 of the 24 OECD countries.

I also develop new asymptotic results for long-run regressions with overlapping observations. I show that rather than using auto-correlation robust standard errors, the standard t-statistic can simply be divided by the square root of the forecasting horizon to correct for the effects of the overlap in the data. Further, when the regressors are persistent and endogenous, the long-run OLS estimator suffers from the same problems as does the short-run OLS estimator, and similar corrections and test procedures as those proposed by Campbell and Yogo (2003) for the short-run case should also be used in the long-run; again, the resulting test statistics should be scaled due to the overlap.

The empirical analysis conducts time-series regressions for individual countries as well as pooled regressions. The results indicate that the short interest rate and the term spread are fairly robust predictors of stock returns in OECD countries. The predictive abilities of both the short rate and the term spread are short-run phenomena; in particular, there is only evidence of predictability at one and 12-month horizons. In contrast to the interest rate variables, no strong or consistent evidence of predictability is found when considering the earnings- and dividend-price ratios as predictors. Any evidence that is found is primarily seen at the long-run horizon of 60 months. Neither of these predictors yields any consistent predictive power for the OECD countries.

The interest rate variables also have out-of-sample predictive power that is economically significant; the welfare gains to a log-utility investor who uses the predictive ability of these variables to make portfolio decisions are substantial.

Keywords: Predictive regressions; long-horizon regressions; panel data; stock return predictability

JEL-codes: C22; C23; G12; G15

67 pages, February 2, 2005

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