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One of the major challenges that our world faces today and in the future is human-induced climate change. The primary cause of global warming, leading to climate change, is the burning of fossil fuels for energy and transport, which increases the concentration of greenhouse gases in the atmosphere. Energy efficiency and renewable energy sources are considered by many as the proverbial "silver bullet" to avoid the worst climate change scenarios. However, the support for and success of any effort to improve energy efficiency and expand renewable energies strongly depends on preferences and choices of consumers. In four distinct but related essays, the present doctoral thesis examines consumer preferences for alternative-fuel vehicles and building energy retrofits. It makes use of data from two dedicated Germany-wide surveys, one of car buyers and the other of house owners. Each of these surveys included a discrete choice experiment, where respondents were faced with hypothetical choice situations. The car buyers were asked to select the car they preferred most from sets of seven vehicles with different fuel types. The house owners, on the other hand, first selected their preferred retrofit alternative from binary choice sets and then indicated whether they would actually undertake the selected retrofit activity if it were on the market. Similar choice experiments have been used before in transportation and energy research. But in contrast to previous studies, this work includes a wider range of alternative fuels and explicitly considers environmental benefits of energy retrofits. Based on the choice data, barriers to the widespread adoption of alternative-fuel vehicles and building energy retrofits are identified, and it is examined to what extent environmental aspects influence consumer choice behavior in Germany. The doctoral thesis confirms existing evidence on the impact of fuel availability on demand for alternative-fuel vehicles, primarily coming from North America, in the German context (Chapter 2). It makes important contributions to the growing, but heterogeneous literature that seeks to elicit willingness to pay for carbon abatements, carbon offsets, or climate policy in general (Chapters 3 and 4). Finally, it attempts to explain the persistent low retrofit rate in Germany and makes suggestions on how to stimulate energy retrofits in an effective and cost-efficient way (Chapter 5).

Previous literature on the distribution of willingness to pay has focused on its heterogeneity distribution without addressing exact interval estimation. In this paper we derive and analyze Bayesian confidence sets for quantifying uncertainty in the determination of willingness to pay for carbon dioxide abatement. We use two empirical case studies: household decisions of energy-efficient heating versus insulation, and purchase decisions of ultralow- emission vehicles. We first show that deriving credible sets using the posterior distribution of the willingness to pay is straightforward in the case of deterministic consumer heterogeneity. However, when using individual estimates, which is the case for the random parameters of the mixed logit model, it is complex to define the distribution of interest for the interval estimation problem. This latter problem is actually more involved than determining the moments of the heterogeneity distribution of the willingness to pay using frequentist econometrics. A solution that we propose is to derive and then summarize the distribution of point estimates of the individual willingness to pay under different loss functions.

Residential buildings strongly contribute to global CO2 emissions due to the high energy demand for electricity and heating, particularly in industrialised countries. Within the EU, decentralised heat generation is of particular relevance for future climate policy, as its emissions are not covered by the EU ETS. We conducted a choice experiment concerning energy retrofits for existing houses in Germany. In the experiment, the approximately 400 sampled house owners could either choose a modern heating system or an improved thermal insulation for their home. We used standard and mixed logit specifications to analyse the choice data. We found environmental benefits to have a significant impact on choices of heating systems. However, they played no role in terms of insulation choices. Based on the estimated mixed logit model, we further obtained WTP measures for CO2 savings.

Motorised individual transport strongly contributes to global CO2 emissions, due to its intensive usage of fossil fuels. Current political efforts addressing this issue (i.e. emission performance standards in the EU) are directed towards car manufacturers. This paper focuses on the demand side. It examines whether CO2 emissions per kilometre is a relevant attribute in car choices. Based on a stated preference experiment among potential car buyers from Germany, different mixed logit specifications are estimated. In addition, distributions of willingness to pay measures for an abatement of CO2 emissions are obtained. The results suggest that the emissions performance of a car matters substantially, but its consideration varies heavily across the sampled population. In particular, some evidence on gender, age and education effects on climate concerns is provided.