How effective is carbon taxation on residential heating demand? A household-level analysis. (January 2022)

• Record Type: Journal Article
• Authors: Ott, Laurent; Weber, Sylvain
• Is Part Of: Energy policy. Volume 160(2022)
• Publication Date: 2022-01
• Subjects: Carbon tax -- Energy consumption -- Fossil fuel -- Policy evaluation -- Inverse probability of treatment weighting -- Difference-in-differences; C21 -- C23 -- H23 -- Q41 -- Q58; Energy policy -- Periodicals; Politique énergétique -- Périodiques; Electronic journals; 333.79
• DOI: 10.1016/j.enpol.2021.112698
• Languages: English
• ISSNs: 0301-4215

Abstract

Abstract: This paper investigates the impact of the Swiss CO2 levy on households' heating demand. Using a difference-in-differences approach combined with inverse probability of treatment weighting, we test whether the 2016 and 2018 carbon tax rate increases had a short-run impact on Swiss households' heating and hot water expenditures—i.e. a proxy for heating consumption. Micro-level data from the Swiss Household Energy Demand Survey are used to estimate the models. Our regression analysis shows that heating consumption decreases with time for all households, but it does not detect any clear short-run impact of the CO2 levy on fossil fuel users in comparison to non-fossil fuel users. We nevertheless find that many factors significantly affect heating consumption, such as setting the thermostat at a lower temperature. Even though further research is needed regarding possible long-run impacts, our findings challenge the relevance of this policy instrument under its current form to lower households' CO2 emissions. Considering that its rate is regularly increased based on short-run emission targets, households may have too little time to adapt. The tax design might thus need to be revised to take into account the slow reaction time. Highlights: The effect of the Swiss CO2 tax is assessed using a difference-in-difference model. Taxing CO2 seems not effective to lower households' heating demand in the short run. The design of carbon taxes should account for this finding. Inverse probability of treatment weighting effectively lowers covariate imbalances.