Narrowing the Energy Efficiency Gap: The Impact of Educational Programs, Online Support Tools and Energy-Related Investment Literacy

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Department of Economics, Centro de Investigación y Docencia Económicas (CIDE)Last revision: September 21, 2017 AbstractThere is evidence that many individuals make suboptimal investment decisions when the benefits and costs associated with that decision are distributed over time. One example is the decision to adopt new electrical appliances, with the benefits of choosing a more energyefficient device materializing only in the future. This paper analyses the impact of the level of an individual's energy-related investment literacy on the adoption of energy-efficient appliances. Moreover, the empirical analysis explores the impact of decision support tools such as educational slides on the probability that individuals identify the appliance with the lowest lifetime cost, which is ideally also the most energy-efficient appliance. To test the influence of these decision support tools, we developed an online randomized controlled trial and implemented it on two independently chosen samples of the Swiss population. One treatment offers a short education program on how to calculate the lifetime cost of an appliance -via a set of information slides. The second intervention provides access to an online calculator that supports the investment decision-making of the individual. Results across the two samples are encouraging. We find that i) pre-treatment energy and investment literacy positively impact on the probability of identifying the appliance with the lowest lifetime cost; ii) the reinforcement of energy-related investment literacy increases the rate at which individuals identify the appliance with the lowest lifetime cost; and iii) while both interventions are effective in increasing the chances that an appliance with the lower lifetime cost is chosen, the online calculator turned out to be more effective than the educational program. Public policy implications are discussed.

A Model-based Clustering Approach for Analyzing Energy-related Financial Literacy and Its Determinants

“…As discussed in Blasch et al (2017b), the higher marginal effect in the refrigerator experiment is likely due to the fact that in this experiment, the most cost-efficient appliance could only be identified when comparing lifetime usage costs of both appliances, which requires some calculation. Similarly, the marginal effects in Blasch et al (2017c) for the two decision aids, and for the choice of lifetime cost calculation strategy, are found to be very similar with the results reported in Table 9. 21 To summarize, the main model estimation results are found to be comparable to the results reported in Blasch et al (2017b) and Blasch et al (2017c) that uses separate variables for energy literacy (numeric score from 0 to 11) and investment literacy (dichotomous variable) -this provides support to the clustering approach as a sophisticated alternative to less refined aggregation strategies and serves as a robustness check towards the crucial role played by energy-related financial literacy in the domain of appliance choice.…”

“…Table 8 finds a positive role of both MID-literacy and HIGH-literacy groups on the probability to opt for a lifetime cost calculation strategy and in turn to identify the appliance with the lowest lifetime cost. The two decision aids (TRSLIDE and TRCALC) are found to have a positive impact on the probability that an appliance with the lowest lifetime cost is chosen and, similar to the results in Blasch et al (2017c), the calculator tool is found to be more effective than the information slides. Table 9 reports the marginal effects of our variables of interest similar to the ones reported in the two studies.…”

“…First, we consider the light bulb and refrigerator RCTs in Blasch et al (2017b) and the HSEU-Bern RCT in Blasch et al (2017c). We focus only on the bivariate probit (BP) and recursive bivariate probit (RBP) settings as these are the two main economic models pursued in these studies (with RBP as the preferred model).…”

“…Table 7 reports the (re-)estimation results using literacy based clusters for the two experiments in Blasch et al (2017b). Table 8 reports the (re-)estimation results using literacy based clusters for the HSEU-Bern RCT in Blasch et al (2017c). Note that in these results, literacy is now captured using latent clusters with the LOW-literacy (i.e.…”

“…Literacy is captured using latent clusters with ERFL-LOW as reference. Blasch et al (2017c). Literacy is captured using latent clusters with ERFL-LOW as reference.…”