The Energy Footprint of Economic Complexity: How Does Energy Intensity Shape the Global Production Matrix?

This study examines the relationship between energy intensity and economic complexity across 135 countries over the period of 2000–2022, with particular attention paid to differences across income groups and their implications for sustainable development. Using data from the Harvard Growth Lab, the Heritage Foundation, the United Nations Development Programme, the KOF Swiss Economic Institute, and the World Bank, the analysis applies fixed-effects panel regression and panel Granger causality tests to assess the association and temporal direction between energy intensity and the Economic Complexity Index, while controlling for human capital, globalization, and economic freedom. The results show substantial heterogeneity across income groups. Lower energy intensity is significantly associated with higher economic complexity in high-income and upper-middle-income countries, whereas the relationship is not statistically significant in lower-middle-income and low-income countries. Panel Granger causality tests revealed a unidirectional predictive relationship from energy intensity to economic complexity in high-income, lower-middle-income, and low-income countries (p < 0.001), but no significant causal relationship in either direction in upper-middle-income countries. No evidence of reverse Granger causality from economic complexity to energy intensity was found in any income group. In higher-income economies, energy-efficiency improvements can be integrated with technological upgrading, industrial modernization, and the development of higher-value productive activities. In lower- and middle-income economies, the results suggest that energy-efficiency policies should be sequenced and combined with investments in human capital, productive and energy infrastructure, technological capabilities, and institutional capacity to support diversification. Energy intensity was positively and significantly associated with economic complexity in high-income (PIA; β = 0.0597, p < 0.05) and upper-middle-income economies (PIMA; β = 0.0393, p < 0.01). In contrast, the coefficients were not statistically significant for lower-middle-income (PIMB; β = 0.0327) and low-income economies (PIB; β = −0.00592). These findings suggest that the relationship between energy intensity and economic complexity varies across income groups, with statistically significant positive associations observed only among high-income and upper-middle-income economies. Overall, the findings highlight the importance of income-specific policy design when linking energy transition, productive transformation, and sustainable economic development.