作者：HODRICK, RJ
摘要：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) ...
