Data, Distribution, and Modeling Innovations in Spatiotemporal Energy Economics

George Halkos

MPRA Paper from University Library of Munich, Germany

Abstract: The objective of the present review is to synthesize recent state-of-the-art advances in the field of energy economics. The present review aims to elucidate the interconnections among various applicable and practical methodologies that may facilitate a sustainable energy transition and therefore the novelty lies in the cross-cutting, methodological integration and forward-looking perspective that informs both academic research and practical policy development in the context of sustainable energy transitions. The contribution of this review is fourfold. First, it systematically compiles the core empirical advancements within different sectors of the energy domain, providing a structured assessment of contemporary research efforts. Second, it critically examines the challenges associated with data availability and reviews methodological innovations designed to address these limitations. Third, it consolidates developments in spatiotemporal econometric techniques, highlighting their significance in capturing dynamic spatial and temporal dimensions of energy systems. Fourth, it presents emerging machine learning-based approaches for forecasting, underscoring their potential to enhance predictive capabilities and inform policy and investment decisions. By integrating insights across these domains, the review offers a comprehensive framework for understanding the methodological evolution in energy economics and identifies pathways for future research that support the global pursuit of a sustainable energy future.

Keywords: energy economics; energy policy; energy transition; energy modelling and forecasting. (search for similar items in EconPapers)
JEL-codes: Q0 Q01 Q40 Q43 Q47 Q48 Q51 (search for similar items in EconPapers)
Date: 2025-06-11
New Economics Papers: this item is included in nep-ene, nep-env and nep-for
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