Impact of Economic Growth, Energy use and Research and Development Expenditure on Carbon Emissions: An Analysis of 29 OECD Countries

Abstract

This study attempts to investigate the impact of economic growth, energy use and research and development expenditure on carbon dioxide emissions for a panel of 29  Organisation for Economic Development and Cooperation (OECD) countries over 1995-2019. We employ two sets of econometric techniques.The first set of estimation techniques assumes cross sectional independence in the panel (also known as the first generation tests). The first generation tests include the panel unit root tests- Levin et al ( LLC), Im et al (IPS) ADF-Fisher and PP-Fisher unit root tests, Pedroni (1999) and Kao cointegration tests and the Fully Modified Ordinary Least Square (FMOLS) for computing output elasticities. The second set of econometric tests are performed after checking for cross sectional dependence using the second generation tests. These include Pesaran CD test, Breusch Pagan CD test, to establish cross sectional dependence followed by Cross-sectional augmented Im-Pesaran-Shin (CIPS) panel unit root test developed by Pesaran (2007)to test for panel stationarity followed by the error correction based panel cointegration test proposed by Westerlund and Edgerton (2007) with bootstrap. Augmented Mean Group (AMG) is performed to estimate output elasticities while Dumitrescu-Hurlin (DH) Panel Causality tests is done to ascertain causality between variables   We obtain the same results for the effect of GDP and energy use on carbon emissions from  the two strategies but conflicting results for the impact of research and development spending on carbon emissions, although there is evidence of stronger cointegration under the first generation tests. Based on findings from the two approaches, we conclude that with a rise in GDP, carbon emissions fall in OECD but increase with a rise in energy use. Aggregate research and development expenditure has a positive effect on carbon emissions under cross sectional independence but a neutral effect when estimated using cross-sectional dependence tests giving inconclusive results.