We develop a model for decomposing the covariance structure of panel data on firms into a part due to permanent …

allowing for an arbitrary covariance structure between time periods. We also suggest a third technique, based on randomization …

that in the population minimizes the squared difference between the conditional expectation and the linear approximation … parameter, generally smaller than the White robust variance, and we propose a consistent estimator for the asymptotic variance …

. Finally, we introduce a random-effects type combination estimator that provides finite-sample efficiency gains over both …

This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix …; that is, the performance of the prewhitened kernel estimator is virtually indistinguishable from that of the VARHAC … estimator …

This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance … matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix …

-based covariance estimator motivated by a key financial economic consideration, the absence of arbitrage, in addition to statistical … considerations. We show that this estimator is highly efficient yet robust to market microstructure noise arising from bid-ask bounce …

covariance of forecast errors are time-varying, we can identify a modified CAFM model with measurement error -- which we also …

=quot;text-decoration:overline;quot;gt;lt;igt;Nlt;/igt;lt;/spangt; consistent estimator. Nonsingularity of the APE's information bound, and hence the appropriateness of Chamberlain's (1992 …) estimator, requires (i) the time dimension of the panel (lt;igt;Tlt;/igt;) to strictly exceed the number of random coefficients … propose a feasible estimator based on our identification result and characterize its large sample properties. While …