of one-period expected returns and expected-return news. As a result, the R2 from a regression of returns on cash …

We consider various MIDAS (Mixed Data Sampling) regression models to predict volatility. The models differ in the …

This paper considers the problem of conducting inference on the regression coefficient in a bivariate regression model … whether or not the innovations of the regression model are normally distributed …

to predict stock or bond market returns. Recent research argues that these results may be driven by an aggregate time …

This paper considers tests of the parameter on endogenous variables in an instrumental variables regression model. The …

. Local asymptotic power analysis shows that the power of the long-horizon predictive regression test dominates that of the … these problems, we suggest a moving block recursive Jackknife estimator of the predictive regression slope coefficient and …

on living arrangements using a regression discontinuity approach. We find strong evidence that more generous social … regression discontinuity estimates exhibit little sensitivity to the degree of flexibility in the specification, and perform very …

Quantile regression(QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a … approximation to the conditional expectation function even when the linear model is misspecified. Empirical research using quantile … regression with discrete covariates suggests that QR may have a similar property, but the exact nature of the linear …