This project advances the argument that policy makers face a dilemma between the ambition and the sectoral scope of policies. Increasing the ambition and simultaneously the scope of climate policy often challenging. A large scope implies heterogenous target groups which may create backlash. The dilemma can best be overcome when technological, institutional and behavioural change first occurs in low resistance sectors that trigger transformation processes in other sectors. Besides these theoretical contributions, the project develops a new computer-based approach to systematic literature reviewing with «supervised machine learning». This method contributes to a better understanding which mechanisms increase the political feasibility across sectors. These are then specifically investigated with the Swiss case and other western countries. Thus, this project shows which policies facilitate a sequential increase climate policy ambition across sectors.
Bold emission reduction requires intensive cross-sectoral climate policies. Policy intensity, however, varies in the energy, transport, food and housing sectors. Existing research focusses on single sectors, predominantly the energy sector. The Paris Agreement calls for a sequential increase of the intensity and effectiveness of policies in different sectors. It is therefore crucial to better understand this cross-sectoral sequencing, the temporal ordering of policies overtime. The established sequencing theory with focus on the energy sector posits that policies which reward climate friendly behaviour create positive feedback and foster pro-environmental coalition building, subsequently allowing for more intensive carbon pricing with higher resource commitments. Yet, the low popular support for the Swiss CO2 law shows that negative cross-sectoral feedback can inhibit sequencing which the established theory insufficiently accounts for. Therefore, this dissertation asks: What conditions lead to increasing climate policy intensity in different sectors over time? This dissertation theorises that policy makers face a breadth versus intensity dilemma. Policies with broad cross-sectoral scope create more homogenous rules for a heterogenous target group, thus mobilising opponents and creating backlash against more intensive climate policy. The dilemma can be overcome when policies in one sector improve opportunities for cross-sectoral technological, behavioural and institutional change. Subsequently, these changes allow for an intensification of climate policy across sectors. In a systematic literature review, the project summarises existing theory and evidence on barriers to more intensive climate policy in different sectors and contributes a novel supervised machine learning method for article screening. Empirically, it presents the first quantitative study of policy sequencing, using new data collected by scraping law databases. With qualitative mixed-methods, it traces the barriers to more intensive policy in Switzerland. The results will have implications for climate research, policy makers and the public by showing what sectors and policies to target first to increase the political feasibility of intensive cross-sectoral climate policy.
Last updated:15.12.2022
