50 Pages Posted: 17 Mar 2000
Date Written: May 1999
When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's finite-sample properties, derived here, can depart substantially from the standard regression setting. Bayesian posterior distributions for the regression parameters are obtained under specifications that differ with respect to (i) prior beliefs about the autocorrelation of the regressor and (ii) whether the initial observation of the regressor is specified as fixed or stochastic. The posteriors differ across such specifications asset allocations in the presence of estimation risk exhibit sensitivity to those differences.
Suggested Citation: Suggested Citation
Stambaugh, Robert F., Predictive Regressions (May 1999). NBER Working Paper No. t0240. Available at SSRN: https://ssrn.com/abstract=205390
By Owen Lamont