Optimal renewable-energy subsidies

We derive optimal subsidization of renewable energies in electricity markets. The analysis takes into account that capacity investment must be chosen under uncertainty about demand conditions and capacity availability, and that capacity as well as electricity generation may be sources of externalities. The main result is that generation subsidies should correspond to externalities of electricity generation (e.g., greenhouse gas reductions), and investment subsidies should correspond to externalities of capacity (e.g., learning spillovers). If only capacity externalities exist, then electricity generation should not be subsidized at all. Our results suggest that some of the most popular promotion instruments cause welfare losses

Pseudolikelihood estimation of the stochastic frontier model

Stochastic frontier analysis is a popular tool to assess firm performance. Almost universally it has been applied using maximum likelihood estimation. An alternative approach, pseudolikelihood estimation, which decouples estimation of the error component structure and the production frontier, has been adopted in several advanced settings. To date, no formal comparison has yet to be conducted comparing these methods in a standard, parametric cross sectional framework. We seek to produce a comparison of these two competing methods using Monte Carlo simulations. Our results indicate that pseudolikelihood estimation enjoys almost identical performance to maximum likelihood estimation across a range of scenarios, and out performs maximum likelihood estimation in settings where the distribution of inefficiency is incorrectly specified

Behavioral economics and energy conservation - a systematic review of nonprice interventions and their causal effects

Research from economics and psychology suggests that behavioral interventions can be a powerful climate policy instrument. This paper provides a systematic review of the existing empirical evidence on non-price interventions targeting energy conservation behavior of private households. Specifically, we analyze the four nudge-like interventions referred to as social comparison, pre-commitment, goal setting and labeling in 38 international studies comprising 91 treatments. This paper differs from previous systematic reviews by solely focusing on studies that permit the identification of causal effects. We find that all four interventions have the potential to significantly reduce energy consumption of private households, yet effect sizes vary immensely. We conclude by emphasizing the importance of impact evaluations before rolling out behavioral policy interventions at scale

Natural disasters and governmental aid : is there a charity hazard?

In the aftermath of natural disasters, governments frequently provide financial aid for affected households. This policy can have adverse effects if individuals anticipate it and forgo private precaution measures. While theoretical literature unequivocally suggests this so called “charity hazard”, empirical studies yield ambiguous results. Drawing on rich survey data from German homeowners, we analyze charity hazard for different flood precaution strategies, namely insurance uptake and non-financial protection measures, and different flood risk areas. Our results indicate a substantial charity hazard in the insurance market for individuals residing in flood-prone areas. In contrast, we find a positive correlation between governmental aid and non-financial protection measures. Moreover, our results suggest that insurance and non-financial protection measures are rather complements than substitutes. Finally, we provide suggestive evidence that status-quo bias might play an important role for insurance uptake

Consumer inattention, heuristic thinking and the role of energy labels

Energy labels have been introduced in many countries to increase consumers’ attention to energy use in purchase decisions of durables. In a discrete-choice experiment among about 5,000 households, we implement randomized information treatments to explore the effects of various kinds of energy labels on purchasing decisions. Our results show that adding annual operating cost information to the EU energy label promotes the choice of energy-efficient durables. In addition, we find that a majority of participants value efficiency classes beyond the economic value of the underlying energy use differences. Our results further indicate that displaying operating cost affects choices through two distinct channels: it increases the attention to operating cost and reduces the valuation of efficiency class differences

Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes

Data envelopment analysis (DEA) and stochastic frontier analysis (SFA), as well as combinations thereof, are widely applied in incentive regulation practice, where the assessment of efficiency plays a major role in regulation design and benchmarking. Using a Monte Carlo simulation experiment, this paper compares the performance of six alternative methods commonly applied by regulators. Our results demonstrate that combination approaches, such as taking the maximum or the mean over DEA and SFA efficiency scores, have certain practical merits and might offer an useful alternative to strict reliance on a singular method. In particular, the results highlight that taking the maximum not only minimizes the risk of underestimation, but can also improve the precision of efficiency estimation. Based on our results, we give recommendations for the estimation of individual efficiencies for regulation purposes and beyond

Germany’s Energiewende: A tale of increasing costs and decreasing willingness-to-pay

This paper presents evidence that the accumulating costs of Germany’s ambitious plan to transform its system of energy provision – the so-called Energiewende – are butting up against consumers’ decreased willingness-to-pay (WTP) for it. Following a descriptive presentation that traces the German promotion of renewable energy technologies since 2000, we draw on two stated-preference surveys conducted in 2013 and 2015 that elicit the households’ WTP for green electricity. To deal with the bias that typifies hypothetical responses, a switching regression model is estimated that distinguishes respondents according to whether they express definite certainty in their reported WTP. Our results reveal a strong contrast between the households’ general acceptance of supporting renewable energy technologies and their own WTP for green electricity

Mitigating hypothetical bias

The overestimation of willingness-to-pay (WTP) in hypothetical responses is a well-known finding in the literature. Various techniques have been proposed to remove or, at least, reduce this bias. Using about 30,000 responses on WTP for a variety of power mixes from a panel of 6,500 German households and the fixed-effects estimator to control for unobserved heterogeneity, this article simultaneously explores the effects of two common ex-ante approaches – cheap talk and consequential script – and the ex-post certainty approach to calibrating hypothetical WTP responses. Based on a switching regression model that accounts for the potential endogeneity of respondent certainty, we find evidence for a lower WTP among those respondents who classify themselves as definitely certain about their answers. Although neither cheap talk nor the consequential-script corrective reduce WTP estimates, receiving either of these scripts increases the probability that respondents indicate definite certainty about their WTP bids

Consequentiality and the Willingness-To-Pay for Renewables: Evidence from Germany

Based on hypothetical responses originating from a large-scale survey among about 7,000 German households, this study investigates the discrepancy in willingness-to- pay (WTP) estimates for green electricity across discrete-choice and open-ended valuation formats, thereby accounting for perceived consequentiality: respondents selfselect into two groups distinguished by their belief in the consequentiality of their answers for policy making. Recognizing that consequentiality status and WTP might be jointly influenced by unobservable factors, we employ a switching regression model that accounts for the potential endogeneity of respondents’ belief in consequences and, hence, biases from sample selectivity. Contrasting with the received literature, we find WTP bids that tend to be higher among those respondents who obtained questions in the open-ended format, rather than single binary choice questions. This difference shrinks, however, when focusing on individuals who perceive the survey as politically consequential

Zahlungsbereitschaft für grünen Strom: Die Kluft zwischen Wunsch und Wirklichkeit

Die Überschätzung der Zahlungsbereitschaft in rein hypothetischen Entscheidungssituationen ist ein in der Literatur wohlbekanntes Phänomen. Zur Eliminierung dieser Verzerrung wurden verschiedene Methoden vorgeschlagen, unter anderen der sogenannte Cheap-Talk-Ansatz und das Consequential-Skript. Auf Basis einer Erhebung unter mehr als 6.500 deutschen Haushalten untersucht dieser Beitrag die Effektivität dieser Korrektive. Nach unseren ökonometrischen Ergebnissen erweist sich allein Cheap Talk als effektiv, senkt jedoch die Zahlungsbereitschaft für grünen Strom nur bei jenen Befragten, die sich nicht ganz sicher hinsichtlich ihrer Angaben zur Zahlungsbereitschaft sind. Darüber hinaus zeigen unsere Befragungsergebnisse einen starken Kontrast zwischen der Unterstützung für erneuerbare Energien und der Zahlungsbereitschaft für grünen Strom. So sprechen sich 85,1% der Antwortenden für die Förderung erneuerbarer Energietechnologien aus, aber nur knapp die Hälfte der Antwortenden ist bereit, für grünen Strom zusätzliche Kosten in Kauf zu nehmen