Working Paper: NBER ID: w21557
Authors: Ravi Jagannathan; Binying Liu
Abstract: We present a latent variable model of dividends that predicts, out-of-sample, 39.5% to 41.3% of the variation in annual dividend growth rates between 1975 and 2016. Further, when learning about dividend dynamics is incorporated into a long-run risks model, the model predicts, out-of-sample, 25.3% to 27.1% of the variation in annual stock index returns over the same time horizon, and learning contributes approximately half of the predictability in returns. These findings support the view that both investors' aversion to long-run risks and their learning about these risks are important in determining the stock index prices and expected returns.
Keywords: No keywords provided
JEL Codes: G10; G11; G12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Incorporating learning about dividend dynamics (G35) | Enhances predictability of stock index returns (G17) |
| Investor learning (G11) | Influences stock pricing behavior (G41) |
| Dividend model (G35) | Predicts variation in annual dividend growth rates (G35) |
| Aversion to long-run risks and learning about these risks (D81) | Determine asset prices and expected returns (G19) |