On self-interested preferences for burden sharing rules: An econometrics analysis for the costs of energy policy measures - Elke D. Groh; Andreas Ziegler (Philipps-University Marburg, School of Business and Economics, 2017)
This paper examines the acceptance of burden sharing rules that refer to the costs of the Ger-man energy transition, which is one of the most challenging and disputed national climate and energy policy measures. Based on data from a comprehensive survey of more than 2,200 citi-zens, the empirical analysis reveals that the polluter-pays rule has by far the highest support compared with the ability-to-pay rule and especially compared with the equal-pay rule, which is widely refused in the sample. Since the distribution of the costs of the German energy tran-sition is largely in line with the polluter-pays rule, its strong support seems to contribute to the high acceptance of the energy transition at all. The main result of our econometric analysis with multivariate binary and ordered probit models is that not only some attitudinal factors like environmental values and political identification, but especially economic self-interest is relevant since (equivalent) energy expenditures have a significantly negative effect on the support of the polluter-pays rule and especially (equivalent) income has a significantly nega-tive effect on the preference for the ability-to-pay rule. These results suggest that the use of distributional arguments for the criticism of energy policy measures is not necessarily value-driven on the basis of real perceptions of distributive justice, but can also be strategically mo-tivated to prevent and combat economically unfavorable measures. Together with the strong general support of the polluter-pays rule, these results suggest that a sharp reorientation of the German energy transition due to distributional arguments is not very useful.
Keywords: Q54; Q48; Q42; 330; Climate change; climate and energy policy measures; burden sharing rules; economic self-interest; attitudinal factors; multivariate binary and ordered probit models