Abstract
Obtaining reliable cross-country estimates of the income and price elasticity of energy demand requires a panel data model that can simultaneously account for endogeneity, heterogeneity over time, cross-sectional heterogeneity, nonstationarity and cross-sectional dependence. We propose such an integrated framework and apply it to a very large dataset of 65 countries over the period 1960–2016 recently assembled by Liddle and Huntington (2020). We find that while the elasticities of income and price are non-linear, the income elasticity is generally in the range 0.6 to 0.8 and the price elasticity in the range −0.1 to −0.3. We also find that the income elasticity has been declining since the 1990s, which broadly corresponds to increasing awareness of the negative externalities associated with burning fossil fuels associated with the Kyoto Protocol. From a policy perspective, that the income energy elasticity is less than one, and has been declining since the 1990s, bodes well for climate change mitigation because it suggests that energy intensity will fall with economic growth.
Highlights
Energy demand has been investigated for more than half a century, employing a variety of frameworks (e.g., Brookes, 1972; Adams and Miovic, 1968; Casler, 1992; Jacobsen, 2015; Liddle et al, 2020)
Given that climate mitigation strategies are often based on lowering the carbon intensity of GDP, it is important to know if the income elasticity is less than unity, which implies that energy intensity will fall in a business-as-usual economic growth scenario (Liddle et al, 2020)
From a methodological perspective, obtaining reliable estimates of the income and price elasticity of energy demand in a cross-country panel data setting requires a modelling framework that can simultaneously account for endogeneity, heterogeneity over time, heterogeneity across countries, nonstationarity and cross-sectional dependence
Summary
Energy demand has been investigated for more than half a century, employing a variety of frameworks (e.g., Brookes, 1972; Adams and Miovic, 1968; Casler, 1992; Jacobsen, 2015; Liddle et al, 2020). To address the aforementioned issues, our main contribution in this study is to propose a (time-varying) structural equation panel data model, which simultaneously allows for endogeneity, nonstationarity, and cross-sectional dependence, and to illustrate its application to estimating income and price elasticities of energy demand using a large crosscountry dataset. It is important to note that while we use the energy elasticity literature to illustrate the application of our modelling framework, our proposed framework could be applied to several other areas of energy and environmental economics that routinely employ cross-country panel data, such as the Environmental Kuznets Curve and the relationship between income inequality and environmental degradation While these studies typically address one or more of cross-sectional dependence, endogeneity, heterogeneity or nonstationarity, none of these studies simultaneously address all of them. We employ Dataset 4 primarily as a robustness check and to provide a direct comparison with the time-varying estimates in Liddle et al (2020)
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