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

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  • Robert J. Hodrick

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

  • Robert J. Hodrick, 1991. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Interference and Measurement," NBER Technical Working Papers 0108, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0108
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    Cited by:

    1. John Ammer & Jianping Mei, 1995. "Strategic returns to international diversification: An application to the equity markets of Europe, Japan and North America," European Financial Management, European Financial Management Association, vol. 1(1), pages 49-59, March.
    2. Campbell, John Y & Ammer, John, 1993. "What Moves the Stock and Bond Markets? A Variance Decomposition for Long-Term Asset Returns," Journal of Finance, American Finance Association, vol. 48(1), pages 3-37, March.
    3. Garcia, R. & Bonomo, M., 1993. "Disappointment Aversion as a Solution to the Equity Premium and the Risk- Free Rate Puzzles," Cahiers de recherche 9334, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    4. Yutaka Kurihara, 2016. "Deterministic Elements of Japanese Stock Prices under Low Interest Rates," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 4(2), pages 24-30, April.
    5. West, Kenneth D., 1997. "Another heteroskedasticity- and autocorrelation-consistent covariance matrix estimator," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 171-191.
    6. Ammer, John & Mei, Jianping, 1996. "Measuring International Economic Linkages with Stock Market Data," Journal of Finance, American Finance Association, vol. 51(5), pages 1743-1763, December.
    7. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    8. Enrique Sentana, 1993. "The econometrics of the stock market I: rationality tests," Investigaciones Economicas, Fundación SEPI, vol. 17(3), pages 401-420, September.

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