Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement
探讨了长期预测中推断与测量的替代方法，以股息收益率预测股票收益为例。蒙特卡洛分析显示Hansen和Hodrick方法在长期存在偏差，而其他方法（如VAR）表现更优，揭示了预期股票收益的有趣模式。
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.