Bioenergy Technology and Carbon Intensity in U.S. and China: Threshold Roles of Capital Accumulation, Education and Inequality

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Bioenergy Technology and Carbon Intensity in U.S. and China: Threshold Roles of Capital Accumulation, Education and Inequality

Author Information
1
SICE, Xinjiang Normal University, Urumqi 830017, China
2
School of Government, ECUPL, Shanghai 201620, China
3
Digital Business and Capital Development Innovation Center, Beijing Technology and Business University, Beijing 102401, China
4
Department of Economics, University of Florida, Gainesville, FL 32611, USA
5
Food and Resource Economics Department, University of Florida, Gainesville, FL 32611, USA
*
Authors to whom correspondence should be addressed.

Received: 26 May 2025 Accepted: 30 September 2025 Published: 17 October 2025

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© 2025 The authors. This is an open access article under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

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Ecol. Civiliz. 2026, 3(1), 10017; DOI: 10.70322/ecolciviliz.2025.10017
ABSTRACT: Bioenergy technology holds significant promise for reducing carbon intensity and fostering sustainable development, yet its impact remains unclear. This article employs both a panel threshold model and a random forest model, analyzing data from the primary administrative regions in the United States and China to explore the threshold effects and regional heterogeneity of bioenergy technology on carbon intensity, where the bioenergy technology is measured using patent data. In the United States, the impact of bioenergy technology on carbon intensity initially shows a positive effect, which later turns negative as per capita capital stock increases. The technology’s inhibitory effect strengthens with higher levels of education but becomes insignificant as the Gini coefficient rises. In China, increasing per capita capital stock shifts the impact of bioenergy technology from negative to insignificant, while higher education levels enhance its inhibitory effect. The Gini coefficient, however, does not significantly affect the impact of technology. Additionally, these threshold effects exhibit notable regional variations. The study provides cross-country evidence of how institutional and structural conditions shape the carbon mitigation effects of bioenergy technology, offering practical insights for policies that combine trade facilitation, education, and inequality reduction with low-carbon energy transitions.
Keywords: Biomass energy; Sustainable development; Gini coefficient; Endowment structure; Human capital
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