This paper proposes estimating linear dynamic panels by explicitly exploiting the endogeneity of lagged dependent variables and expressing the crossmoments between the endogenous lagged dependent variables and disturbances in terms of model parameters. These moments, when recentered, form the...

The ordinary least squares (OLS) estimator for spatial autoregressions may be consistent as pointed out by Lee (2002), provided that each spatial unit is influenced aggregately by a significant portion of the total units. This paper presents a unified asymptotic distribution result of the...

In this paper, we propose an efficient weighted average estimator in Seemingly Unrelated Regressions. This average estimator shrinks a generalized least squares (GLS) estimator towards a restricted GLS estimator, where the restrictions represent possible parameter homogeneity specifications. The...

This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares...

Knowledge Management makes businesses sustainable and enhances their competitive edge. Therefore, this study aims to investigate the relationship between knowledge management and green product competitive advantage through the mediating role of green process innovation. To achieve the...