TY - JOUR
AU - Campbell, John Y
AU - Shiller, Robert J
TI - Stock Prices, Earnings and Expected Dividends
JF - National Bureau of Economic Research Working Paper Series
VL - No. 2511
PY - 1988
Y2 - February 1988
DO - 10.3386/w2511
UR - http://www.nber.org/papers/w2511
L1 - http://www.nber.org/papers/w2511.pdf
N1 - Author contact info:
John Y. Campbell
Morton L. and Carole S.
Olshan Professor of Economics
Department of Economics
Harvard University
Littauer Center 213
Cambridge, MA 02138
Tel: 617/496-6448
Fax: 617/495-7730
E-Mail: john_campbell@harvard.edu
Robert J. Shiller
Yale University, Cowles Foundation
Box 208281
30 Hillhouse Avenue
New Haven, CT 06520-8281
Tel: 203/432-3708
Fax: 203/432-6167
E-Mail: robert.shiller@yale.edu
AB - This paper presents estimates indicating that, for aggregate U.S. stock market data 1871-1986, a long historical average of real earnings is a good predictor of the present value of future real dividends. This is true even when the information contained in stock prices is taken into account. We estimate that for each year the optimal forecast of the present value of future real dividends is roughly a weighted average of moving average earnings and current real price, with between 2/3 and 3/4 of the weight on the earnings measure. This means that simple present value models of stock prices can be strongly rejected. We use a vector autoregressive approach which enables us to compute the implications of this for the behavior of stock prices and returns. We estimate that log dividend-price ratios are more variable than, and virtually uncorrelated with, their theoretical counterparts given the present value models. Annual returns on stocks are quite highly correlated with their theoretical counterparts, but are two to four times as variable. Our approach also reveals the connection between recent papers showing forecastability of long-horizon returns on corporate stocks, and earlier literature claiming that stock prices are too volatile to be accounted for in terms of simple present value models. We show that excess volatility directly implies the forecastability of long-horizon returns.
ER -