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Is Entrepreneurship the Key to Achieving Environmental Sustainability? A Data-Driven Analysis from the Asia-Pacific Region

doi: 10.3390/su151914523
This study examines the relationship between entrepreneurship density and environmental quality in 28 Asia-Pacific countries using the PMG estimator as a panel data estimation method in the context of the ARDL model. The study finds that entrepreneurship density has no statistically significant short-term effects on CO2 emissions in all three economic sectors, but it appears to have statistically significant effects on CO2 emissions in agriculture and industry in the long run. The study suggests that the nature of entrepreneurship activities and their impact on the environment changes from low-income to high-income countries, with entrepreneurship activities with innovations and creativity primarily found in the industrial sector, improving economic efficiency and reducing industrial emissions. However, entrepreneurship activities with natural resource rents, such as large land use or forest rents, can cause environmental degradation. The study provides further insights by interacting entrepreneurship density with the income variable, revealing that entrepreneurship density has different effects on sectoral emissions in low, lower-middle, upper-middle, and high-income countries. Finally, the study provides interesting findings on the relationship between entrepreneurship density and environmental quality, such as biodiversity and water quality.
- Australian National University Australia
- University of Economics Ho Chi Minh City Viet Nam
- University of Economics Ho Chi Minh City Viet Nam
- IPAG Business School France
Environmental effects of industries and plants, TJ807-830, entrepreneurship, TD194-195, Renewable energy sources, Environmental sciences, GE1-350, environmental sustainability, panel data analysis
Environmental effects of industries and plants, TJ807-830, entrepreneurship, TD194-195, Renewable energy sources, Environmental sciences, GE1-350, environmental sustainability, panel data analysis
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