This paper considers a quasi-maximum likelihood estimation for the spatial dynamic panel data with both time and individual …xed e¤ects when both the number of individuals n and the number of time periods T can be large. Instead of using di¤erent estimation methods depending on whether the data generating process has time dummy e¤ects or not and whether it is stable, spatial cointegrated, or ex...

the paper presents an analysis of both energy intensity and energy demand for the italianindustrial sector. the aim of the paper is twofold: making a decomposition of energy intensity at the aggregate level and modeling energy demand at the firm level. the decomposition of energy intensity shows different patterns for the different sub-sectors in the period of interest. in the micro approach, p...

This paper studies quantile regression for spatial panel data models with varying coefficients, taking the time and location effects of impacts covariates into account, i.e., implications may change over location. Smoothing methods are employed approximating including B-spline local polynomial approximation. A fixed-effects (FEQR) estimator is typically biased in presence lag variable. The wild...

This paper adopts a random matrix approach to model spatial panel data and applies the analysis of regional economic disparity. A clustering method based on variable influence response structural relationship is proposed define distance, cluster from so that within class have same relationship, give specific algorithm for determining classification number in process relationship. The methods wi...