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AbstractThis paper empirically and jointly analyses the relations between risk aversion, standard time discounting, present bias, and loss aversion and household stated adoption of low to high stake energy efficiency technologies (EETs) (light emitting diodes (LEDs), energy efficient appliances, and retrofit measures). The analysis relies on a large representative sample drawn from eight European Union countries. Preferences over time, risk and losses were elicited and jointly estimated from participant choices in incentivized, context-free multiple price list experiments. The findings from econometrically estimating EET adoption equations suggest that present-biased individuals are less likely to adopt EETs. They also provide (weak) evidence that individuals which are more risk-averse, or more loss-averse, or which exhibit a lower discount factor are less likely to adopt EETs. Finally, omitting one or several of the time and risk or loss-aversion parameters when estimating the EET adoption equations did not appear to cause omitted variable bias.
International audienceImplicit discount rates (IDRs) are employed in energy models to capture household investment decisions, yet the factors behind the IDR and their respective implications for policy-making usually remain blurred and fractional. The proposed comprehensive framework distinguishes three broad categories of factors underlying the IDR for household adoption of energy-efficient technologies (EETs): preferences (notably over time, risk, loss, debt, and the environment), predictable (ir)rational behavior (bounded rationality, rational inattention, behavioral biases), and external barriers to energy efficiency. Existing empirical findings suggest that the factors underlying the IDRs that differ across household characteristics and technologies should be accounted for in energy models. Furthermore, the framework allows for a fresh look at the interplay of IDRs and policies. We argue that a simple observation of high IDRs (or observing correlations between IDRs and socio-economic characteristics) does not provide guidance for policy-making since the underlying sources cannot be identified. Instead, we propose that some of the factors underlying the IDR - notably external barriers - can be changed (through directed policy interventions) whereas other factors - notably preferences and predictable (ir)rational behavior - are innate and can only be taken into account (through reactive policy interventions)
Ever since Ellsberg (1961), the distinction between risk, where agents assign well-defined probabilities to possible outcomes, and ambiguity, where agents do not, has been of particular interest. Using a carefully-designed field experiment, we elicit information about risk and ambiguity preferences among 197 French farmers and structurally estimate these preferences. We use cumulative prospect theory and a multiple-prior model in order to model risk and ambiguity preferences, respectively. We find that farmers are risk, ambiguity, and loss averse, and that probability distortion differs in gains vs. losses, as well as in risk vs. ambiguity. These findings can have important implications for policy design.
This paper empirically analyzes how individual characteristics are associated with risk aversion, loss aversion, time discounting, and present bias. To this end, we conduct a large-scale demographically representative survey across eight European countries. We elicit preferences using incentivized multiple price lists and jointly estimate preference parameters to account for their structural dependencies. Our findings suggest that preferences are linked to a variety of individual characteristics such as age, gender, and income as well as some personal values. We also report evidence on the relationship between cognitive ability and preferences. Incentivization, stake size, and the order of presentation of binary choices matter, underlining the importance of controlling for these factors when eliciting economic preferences.
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