This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance...

In the context of long memory, the finite-sample distortion of statistic distributions is so large, that bootstrap confidence intervals (percentile and percentile-t) for the long memory parameter do not perform better than the corresponding asymptotic confidence interval. In this paper, we...

This paper studies the estimation of dynamic covariance matrices with multiple conditioning variables, where the matrix size can be ultra large (divergent at an exponential rate of the sample size). We introduce an easy-to-implement semiparametric method to estimate each entry of the covariance...

A measure of location is examined that places itself where the signed rank deviations are as close to zero as possible. A solution algorithm is sketched. The measure is robust to outliers. In three illustrative real data examples we find the measure is usually intermediate between mean and...

We consider a new class of estimators for volatility functionals in the setting of frequently observed Itô diffusions which are disturbed by i.i.d. noise. These statistics extend the approach of pre-averaging as a general method for the estimation of the integrated volatility in the presence of...

Originating from cooperative game theory, Shapley values have become one of the most widely used measures for variable importance in applied Machine Learning. However, the statistical understanding of Shapley values is still limited. In this paper, we take a nonparametric (or smoothing)...

The issue presented in this research is whether mobile phone may be considered e-learning technology for students in Thailand. The objective of the research is to provide a practical tool for academics, researchers, and policymakers in evaluating the linkage between e-learning and mobile phone....

We propose a root-N-consistent estimator for binary response panel data where the individual specific effect may be correlated with the regressors. The estimator is asymptotically normal with a simple variance matrix