This paper analyzes predictive regressions in a panel data setting. The standard fixed effects estimator suffers from a small sample bias, which is the analogue of the Stambaugh bias in time-series predictive regressions. Monte Carlo evidence shows that the bias and resulting size distortions...

This paper considers the estimation of average autoregressive roots-near-unity in panels where the time-series have heterogenous local-to-unity parameters. The pooled estimator is shown to have a potentially severe bias and a robust median based procedure is proposed instead. This median...

I develop new asymptotic results for long-horizon regressions with overlapping observations. I show that rather than using auto-correlation robust standard errors, the standard t-statistic can simply be divided by the square root of the forecasting horizon to correct for the effects of the...

Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market microstructure noise. Using volatility signature...

This paper analyzes the asymptotic properties of long-horizon estimators under both the null hypothesis and an alternative of predictability. Asymptotically, under the null of no predictability, the long-run estimator is an increasing deterministic function of the short-run estimate and the...

This paper analyzes panel data inference in predictive regressions with endogenous and nearly persistent regressors. The standard fixed effects estimator is shown to suffer from a second order bias; analytical results, as well as Monte Carlo evidence, show that the bias and resulting size...

We test for efficiency in the market for Swedish co-ops by examining the negative relationship between the sales price and the present value of future rents. If the co-op housing market is efficient, the present value of co-op rental payments due to underlying debt obligations of the cooperative...

Methods of inference based on a unit root assumption in the data are typically not robust to even small deviations from this assumption. In this paper, we propose robust procedures for a residual-based test of cointegration when the data are generated by a near unit root process. A Bonferroni...

We analyze the factors driving the widely-noted persistence in asset return volatility using a unique dataset on global euro-dollar exchange rate trading. We propose a new simple empirical specification of volatility, based on the Kyle-model, which links volatility to the information flow,...

Using Monte Carlo simulations, I show that typical out-of-sample forecast exercises for stock returns are unlikely to produce any evidence of predictability, even when there is in fact predictability and the correct model is estimated.