Estimation of Energy Elasticities: A Comprehensive Review of Production, Cost, and Energy Demand Functions

This study examines the methodological landscape and empirical trends in energy elasticity estimation, reviewing literature published from 2017 to 2026. It employs a hierarchical taxonomy to categorize the selected articles by functional form (production, cost, and energy demand), model specification (static and dynamic), and data structure (panel and time-series). Key findings include: First, the review distinguishes production, cost, and energy demand function approaches and synthesizes the literature by showing how these approaches are associated with different data structures and econometric modeling strategies. Second, the analysis highlights the prevalent use of econometric techniques, such as Generalized Method of Moment (GMM) and Autoregressive Distributed Lag (ARDL), to effectively address endogeneity and non-stationarity in recent energy data. Finally, the contribution of this study lies in its structured synthesis of diverse econometric methodologies based on specific data characteristics. By providing a structured roadmap that matches estimation techniques with their corresponding data structures, this review offers guidance for researchers and policymakers to ensure robust and reliable energy elasticity estimates in an era of rapid global energy transitions.