Employing power kernels suggested in earlier work by the authors (2003), this paper shows how to refine methods of robust inference on the mean in a time series that rely on families of untruncated kernel estimates of the long-run parameters. The new methods improve the size properties of...

In order to reduce the finite sample bias and improve the rate of convergence, local polynomial estimators have been introduced into the econometric literature to estimate the regression discontinuity model. In this paper, we show that, when the degree of smoothness is known, the local...

In Andrews and Guggenberger (2003) a bias-reduced log-periodogram estimator d_{LP}(r) for the long-memory parameter (d) in a stationary long-memory time series has been introduced. Compared to the Geweke and Porter-Hudak (1983) estimator d_{GPH}=d_{LP}(0), the estimator d_{LP}(r) for r larger...

In time series regression with nonparametrically autocorrelated errors, it is now standard empirical practice to construct confidence intervals for regression coefficients on the basis of nonparametrically studentized t-statistics. The standard error used in the studentization is typically...