Revisiting energy intensity in Europe: a econometric methods combination

Abstract

Objective: This work aims to revisit the role of dynamic capital stock on energy intensity in the context of European countries, as presented by Fuinhas et al. (2025). This research also resonates with the initiatives for sustainable innovation and responsibility of environmental resources highlighted in the Laudato si' encyclical (Vaticano, 2015), which stresses the ethical and social imperative to care for our Common Home through innovation and responsible energy use.

Methodology: A panel dataset spanning over 30 years was collected, encompassing more than 20 European countries. We considered carbon intensity as our dependent variable, while our variable of interest relates to capital structure, using trade openness, ecological footprint, and energy intensity as control variables. After applying a battery of preliminary diagnostic tests, namely: correlation matrix, VIF, cross-sectional dependence test, panel unit root test, cointegration test, and Hausman test. Whose results attested to the existence of phenomena such as cross-sectional dependence, a mix of both variables integrated of order one and borderline integrated of order 0 and 1, as well as cointegration between variables. These results suggest the application of a Panel Autoregressive Distributed Lag model, specified in its Unrestricted Error Correction form, not only for its ability to handle such data-specificities but also to capture both short- and long-term dynamics. A Moment's Quantile Regression was used to increase the robustness of our findings, as it is well-suited to account for heterogeneity across the distribution of energy intensity.

Originality: The methodology employed in our paper enabled the model to capture both short- and long-run effects of covariates on energy intensity, and it uniquely explores how these effects vary across the distribution using Moments Quantile Regression. In addition to computing ratios for both the dependent variable, carbon intensity, which is the ratio of carbon emissions to output, and the variable of interest, capital structure, which is the ratio of public to private capital stock.

Results: The results of our study indicate that when public capital is relatively scarce, private capital is more environmentally efficient. Both energy intensity and ecological footprint are positively associated with higher carbon intensity, indicating their contribution to environmental degradation. Conversely, a higher share of renewable energy and increased trade are associated with lower carbon intensity, resulting in reduced emissions in production and exports. These results are presented in the Panel Autoregressive Distributed Lag model, both in the short and long run, and were confirmed by our findings using the quantiles approach.

Practical implications: To improve energy efficiency, policymakers should promote public investment aimed at improving the environmental effectiveness of private capital, particularly by supporting green energy projects through national programs and European Union-funded initiatives. Given that profit motives do not drive the public sector, it is better positioned to facilitate the development of renewable energy, particularly in directing private capital toward environmentally sustainable sectors. This is essential because, as our results show, capital stock on its own can be associated with higher carbon intensity and environmental degradation, due to the private sector investment in more lucrative and established sectors that are usually more carbon-intensive. So, public policies must be drawn to guide that capital toward greener projects and initiatives. Additionally, policymakers should further encourage the adoption of renewable energy, promote trade openness to support cleaner production and technology transfer, and implement measures to reduce the ecological footprint.