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Dividend Yields and Expected Stock Returns: Alternative Procedures for Interference and Measurement

55 Pages Posted: 27 Jun 2007  

Robert J. Hodrick

Columbia Business School - Finance and Economics; National Bureau of Economic Research (NBER)

Date Written: July 1991

Abstract

Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the Hansen and Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in Richardson and Smith (1989), a reformulation of the regression as in Jegadeesh (1990), and a vector autoregression (VAR) as in Campbell and Shiller (1988), Kandel and Stambaugh (1988), and Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns.

Suggested Citation

Hodrick, Robert J., Dividend Yields and Expected Stock Returns: Alternative Procedures for Interference and Measurement (July 1991). NBER Working Paper No. t0108. Available at SSRN: https://ssrn.com/abstract=995152

Robert J. Hodrick (Contact Author)

Columbia Business School - Finance and Economics ( email )

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New York, NY 10027
United States

National Bureau of Economic Research (NBER)

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