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

Carlos Vladimir Rodríguez-Caballero
Authors registered in the RePEc Author Service: Carlos Vladimir Rodriguez Caballero

Econometrics and Statistics, 2022, vol. 23, issue C, 128-146

Abstract: 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 long-range dependence processes.

Keywords: Cross-sectional dependence; Multi-level factor; Long memory; Energy-growth nexus (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:23:y:2022:i:c:p:128-146

DOI: 10.1016/j.ecosta.2020.11.002

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