Empirical study on the effect of carbon tax on GHG emissions in select nations
Awanish Kumar
What the paper says
Purpose This study aims to understand the impact of carbon pricing on greenhouse gas emissions. It is necessary to evaluate the effectiveness of the carbon pricing mechanism on the ground level; therefore, this study provides valuable input about the policies of carbon taxes in OECD countries. Design/methodology/approach This study examines the effects of carbon prices on greenhouse gas emissions in five OECD nations (Denmark, Finland, Sweden, Norway and Slovenia), for the sample period of 1990–2019. The research employs Karl Pearson's correlation and the Phillips–Perron Unit root test to analyze the relationship between carbon prices and greenhouse gas emissions across these countries. Findings This study explores the relationship between carbon tax and greenhouse gas emissions, revealing mixed outcomes. Carbon pricing has significantly reduced emissions in Finland, Slovenia, Sweden and Denmark but has been ineffective in Norway, where emissions increased, likely due to the country's expanding oil and natural gas sectors. These findings highlight the limitations of carbon pricing in certain contexts and emphasize the need for national carbon pricing policies tailored to each country's unique economic and environmental characteristics to ensure effectiveness. Originality/value This research highlights the need for tailored carbon pricing schemes that account for each country's unique environmental and economic conditions. It calls for further studies on the long-term impact of carbon pricing across sectors and regions. The study suggests combining technological innovation, behavioral economics and environmental policies to enhance carbon tax effectiveness, offering valuable insights for governments shaping carbon pricing strategies.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.