TY - DATA T1 - Regulation, Governance and Carbon Dioxide Emissions: Some Global Lessons AU - Jiang, Weimin DO - 10.17632/DHN2CDWNWB.6 UR - https://data.mendeley.com/datasets/dhn2cdwnwb/6 AB - Abstract: How regulation affects environmental protection has generated much attention amongst scholars. However, studies have produced inconsistent results, often derived from a narrow focus on one particular country/region and or inconsistent regulatory definitions. This study analysed panel data obtained from World bank and quality of government institute (QoG) from 1996 to 2014, using World Bank’s definition of regulatory quality. We contrasted different countries according to their stages of economic development and political regimes. The findings support the Environment Kuznets Curve (EKC) that economic growth facilitates carbon reduction. Regulatory quality had significant effects on reducing carbon emissions for democracies, with an inverted ‘U’ shaped curve for democracies and a ‘U’ shaped curve for dictatorships. Data Description: Our variables are obtained from the authoritative sources, for example World Development Indicators were taken from the World Bank and data on regimes from the Quality of Government (QoG) Institute. We measured regulatory quality through the World Bank’s Regulatory Quality Index, which captures perceptions of government capacity ‘to formulate and implement sound policies and regulations that permit and promote private sector development.’ Data (kg per 2010 US$ of GDP) from the World Bank was used as the main measure for carbon emissions. Heterogeneity amongst countries necessitated control variables, choice reflecting usage in previous studies. First, we incorporated the GDP annual percentage growth rate, reflective of findings that economic growth raises carbon emissions. The stage of economic development, measured by per capita GDP, was also included, reflective of the EKC-concept that as countries shift from middle to high-income status economic growth starts to facilitate carbon emission reductions. Industrialization, measured by ‘Industry (including construction), value added (% of GDP)’ and urbanization, measured by ‘Urban population (% of total)’, were included to reflect consensus that industrialization and urbanization raise carbon emissions. The percentage of the land area allocated to forests, the percentage of electricity generated from fossil fuels and the percentage of renewable energy consumption were included to reflect the effect of energy structure on carbon emissions. Finally, an education measure, the number of years of secondary schooling, was incorporated to reflect observed connections between educational attainment and carbon emissions. Contact Email: vsficy@foxmail.com KW - Public Administration KW - Environmental Economics PY - 2020 PB - Mendeley ER -