Dividend yields and expected stock returns: alternative procedures for inference and measurement
探讨了用股息收益率预测股票收益时，长期预测推断与测量的替代方法。蒙特卡洛分析显示Hansen和Hodrick方法有偏，而其他方法表现更好，包括VAR方法揭示预期收益的有趣模式。
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 (1991), 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.