The role of government spending within the environmental Kuznets curve framework: evidence from G7 countries

Abstract

This study assesses the role of government spending on environmental sustainability based on a framework that combines the environmental Kuznets curve (EKC) hypothesis with the Armey curve hypothesis. Specifically, the inverted U -shaped relationships between carbon (CO 2 ) emissions and economic growth (EKC hypothesis) and between government spending and economic growth (Armey curve hypothesis) are analyzed using a composite EKC model tested for cross-sectional dependence and heterogeneity, panel unit root, panel co-integration, and the augmented mean group estimation. In so doing, this study pursues a potential transmission mechanism leading from government spending to CO 2 emissions through the growth channel and presents a novel way to develop a better understanding of how economic growth policy and energy policy can be synchronized. Empirical results show that economic growth acts as a transmitter between government spending and CO 2 emissions in the USA, UK, and Canada. However, the composite EKC hypotehesis is confirmed only for the USA and Canada, where the optimal level of government spending that maximizes CO 2 emissions is 29.87% and 29.22% of GDP, respectively. In contrast, the optimal level of government spending equivalent to 28.30% of GDP minimizes CO 2 emissions in the UK. The key policy implication is that governments can achieve sustainable economic growth by setting standards for their spending levels.

On the Nexus between Economic growth and Environmental Degradation in 28 Countries Classified by Income Level: A Panel Data with an Error-components Model

“…First, notice that β 1 = 0.93, which means that per unit change in GDPpc, there will be a growth on CO2pc emissions 1 Collinearity problems are expected when the same independent variables are used with different exponents. Pirgaip et al (2023) procedure includes the natural logarithm of the GDP, and then they elevated it to the power of two. The correct procedure seems to be taking the square GDP, and after applying natural logarithm.…”