This paper proposes a new criterion for the M-estimation models based on a least squares approximation, which is proved to be selection consistent. Compared with the existing criteria, this new one has two attractive features. One is that model selection based on it has much lower computational...

This paper proposes a new statistic to test independence of high-dimensional data. The simulation results suggest that the performance of the test based on our statistic is comparable to the existing ones, and under some circumstances it may have higher power. Therefore, the new statistic can be...

This paper theoretically explains why bias correction appears in two statistics recently developed by Baltagi et al. (2011, 2012), which are designed to test the sphericity and cross-sectional dependence of the errors in the fixed effects panel model respectively. Our explanation shows that the...

This paper investigates the test of joint significance for binary choice model with multiple integrated explanatory variables. It is found that for the widely used logit and probit models, even though the estimators have a different convergence rate under null hypothesis compared with the case...

This paper develops new model selection criteria for regression with heteroskedastic and autocorrelated errors. We prove the selection consistency of the introduced criteria and evaluate their performance by simulation. The results suggest that the new criteria may bring significant improvement...