Macroeconomic Models of the Equity Premium
Friday, Jan. 6, 2017 7:30 PM – 9:30 PM
- Chair: Sydney Ludvigson, New York University
Dividend Dynamics, Learning, and Expected Stock Index Returns
AbstractWe show that, in a frictionless and ecient market, an asset pricing model that
better describes investors' behavior should better forecast stock index returns. We
propose a dividend model that predicts, out-of-sample, 31.3% of the variation in
annual dividend growth rates (1976-2015). Further, when learning about dividend
dynamics is incorporated into a long-run risks model, the model predicts, out-ofsample,
22.4% of the variation in annual stock index returns (1976-2015). This
supports the view that both investors' aversion to long-run risks and learning about
these risks are important in determining asset prices and expected returns.
The Equity Premium and the One Percent
AbstractWe show that in a general equilibrium model with heterogeneity in risk aversion or belief, shifting wealth from an agent who holds comparatively fewer stocks to one who holds more reduces the equity premium. Since empirically the rich hold more stocks than do the poor, the top income share should predict subsequent excess stock market returns. Consistent with our theory, we find that when the income share of top earners in the U.S. rises, subsequent one year market excess returns significantly decline. This negative relation is robust to (i) controlling for classic return predictors such as the price-dividend and consumption-wealth ratios, (ii) predicting out-of-sample, and (iii) instrumenting with changes in estate tax rates. Cross-country panel regressions suggest that the inverse relation between inequality and returns also holds outside of the U.S., with stronger results in relatively closed economies (emerging markets) than in small open economies (Europe).
Maximum Likelihood Estimation of the Equity Premium
AbstractThe equity premium, namely the expected return on the aggregate stock market less the government bill rate, is of central importance to the portfolio allocation of individuals, to the investment decisions of firms, and to model calibration and testing. This quantity is usually estimated from the sample average excess return. We propose an alternative esti- mator, based on maximum likelihood, that takes into account informa- tion contained in dividends and prices. Applied to the postwar sample, our method leads to an economically significant reduction from 6.4% to 5.1%. Simulation results show that our method produces more reliable estimates under a wide range of specifications.
- G1 - Asset Markets and Pricing