Energy consumption and GDP: a panel data analysis with multi-level cross-sectional dependence

A fractionally integrated panel data model with a multi-level cross-sectional dependence is proposed. Such dependence is driven by a factor structure that captures comovements between blocks of variables through top-level factors, and within these blocks by non pervasive factors. The model can include stationary and non-stationary variables, which makes it flexible enough to analyze relevant dynamics that are frequently found in macroeconomic and financial panels. The estimation methodology is based on fractionally differenced block-by-block cross-sectional averages. Monte Carlo simulations suggest that the procedure performs well in typical samples sizes. This methodology is applied to study the long-run relationship between energy consumption and economic growth. The main results suggest that estimates in some empirical studies may have some positive biases caused by neglecting the presence non-pervasive cross-sectional dependence and longrange dependence processes.(c) 2021 EcoSta Econometrics and Statistics. Published by Elsevier B.V. All rights reserved.