IOP Publishing
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posted on 2019-07-18, 15:13 authored by Michael Wicki

Replication Data for: "In Search of Politically Feasible Policy-Packages for Sustainable Passenger Transport: Insights from Choice Experiments in China, Germany, and the USA" by Michael Wicki, Lukas Fesenfeld, and Thomas Bernauer

Abstract: The main obstacle to making the transportation sector ecologically more sustainable is political feasibility. Effective policy-interventions usually encounter strong public opposition as they interfere in costly ways with people’s daily lives, unveiling a dilemma between political feasibility and environmental policy effectiveness. Evidencing the existence of this dilemma, the literature on attitudes towards different policy instrument types maintains that so-called push measures are less supported by citizens than pull measures, and that market-based instruments tend to be less supported than non-market instruments. While these findings may uphold when considering single policy instruments, whether they continue to do so when considering policy-packages, that is, simultaneously implemented policy-interventions consisting of several policy instruments, remains unclear. To identify politically feasible and effective policy-packages aimed at greening the transportation sector we use choice experiments with representative samples of citizens from China, Germany, and the USA (N=4’876). Contrary to existing literature, we find that public support does not necessarily depend on the instrument type but rather on specific policy design and is highly context dependent. Moreover, despite significant differences between the three country contexts considered, various combinations of policy measures appear to be both potentially effective and supported by most citizens. Altogether, these results suggest that carefully bundled policy-packages may allow governments to employ instruments that would not be politically feasible if introduced in isolation.


ERC Advanced Grant ‘Sources of Legitimacy in Global Environmental Governance’ (Grant: 295456)


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