We are interested in making inference on the AR parameter in an AR(1) panel data model when the time-series dimension is …xed and the cross-section dimension is large. We consider a GMM estimator based on the second order moments of the observed variables. It turns out that when the AR parameter equals unity and certain restrictions apply to the other parameters in the model then local identi…c...

This paper is devoted to "Some Discrete Distributions Generated by Standard Stable Densities" (in short, Discrete Stable Densities). The large-sample properties of M-estimators as obtained by the "Generalized Method of Moments" (GMM) are discussed for such distributions. Some corollaries are proposed. Moreover, using the respective results we demonstrate the large-sample pro...

Abstract Environmental and energy issues have become a stumbling block to China’s sustainable development, so opening up green development path has the focus of much attention. To investigate impact finance on carbon dioxide (CO 2 ) emissions, this paper uses difference systematic generalized method moment (GMM) estimators. The research sample includes panel data for Chinese 30 provinces from 2...

The main aim of the current study is to explore relationship between working capital (WC) and firm performance. We chose a sample 326 Czech firms, including 20 certified firms from EFQM (European Foundation for Quality Management) Excellence Model Albertina database. was taken three sectors: manufacturing, automobile, construction. employed two-step system generalized method moment (GMM) techni...

We propose a new finite sample corrected variance estimator for the linear generalized method of moments (GMM) including one-step, two-step, and iterated estimators. Our formula also corrects over-identification bias in estimation on top commonly used correction Windmeijer (2005), which from estimating efficient weight matrix, so is doubly corrected. An important feature proposed double that it...