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The use of energy labels is mandated by law in China, Europe, the US, and many other countries. Energy labels provide coarse but easy-to-process information designed to help complex decisions. Professer Yu Gao and her coauthors evaluated the impact of adding simple, but accurate energy cost information at different aggregation levels to energy labels. Their interdisciplinary paper contributing to policy designs related to carbon neutralization is accepted by Nature Energy (5-year Impact Factor: 68.8), a subsidiary of Nature. They conducted a field experiment with an online retailer of energy-using durables, measuring customers’ search and purchases of refrigerators. Providing precise energy costs leads to purchases of products with lower prices and in lower energy-efficiency classes, but with similar overall energy and total costs. These results highlight that energy cost information draws users’ attention to the total cost of products and suggests that energy classes allow prospective buyers to save on cognitive effort.

Considering the individual discount rates, products’ average lifetime, and present and future energy prices, the energy usage of durable goods is a nontransparent, complex, and time-varying attribute. Information about appliances’ energy efficiency is often given through some coarse rankings, but rarely through exact estimates of products’ energy costs. The use of energy efficiency labels is mandated by law in many countries to inform consumers and help them overcome their behavioral failures when they trade-off complex product attributes. Whilethe provisionof information through coarse signals is justified based on the notion of limited attention and cognitive capacity, the expected effect of adding information on the running cost to energy labels in a natural shopping environment for large appliances is still ambiguous.

European energy labels classify products into efficiency classes through lettergrades - A+++, A++, A+, with higher grades being associated with higher efficiency ranking. We evaluate the impact of adding accurate cost information to coarse signals provided through energy labels on consumers’ choices. We conduct a Randomized Controlled Trial in Italy examining online purchases of refrigerators. Ourtreatments add yearlyor lifetime energy cost information to that provided through the label, and the onlinesetting allows us to observe behavior under minimal demand effects and gives us access to consumers’ search and purchasing data to examine the decision-making process and its outcomes.

Our sample comprises customers who viewed a refrigerator from the desktop version of the website between June 1st and October 16th, 2018. Each customer visiting the retailer’s website for the first time during this period was randomly assigned to one of three treatments: (a) the control treatment consisted in the retailer’s standard website, with information on refrigerators’ energy usage in kWh and the EU-label energy-efficiency class; (b) the 1-year treatment added information on products’ yearly energy usage cost; and (c) the 15-year treatment added information on products’ lifetime energy usage cost. Theanalysis combines four sources of data: the navigation data extracted daily from theonlineretailer, data from the retailer’s product catalogue on refrigerators’ characteristics, the daily priceinformation for each refrigerator viewed on the website, and the socioeconomic characteristics.

Treatment effects on purchase decisionsWe first evaluate the direct impact of adding energy cost information to the energy class and energy usage information available by default on the likelihood of making a purchase,and on the characteristics of refrigerators bought. The result shows that being treated does not affect the overall likelihood that a user buys a refrigerator, and treated customers buy cheaper refrigerators. Despite this shift in purchases from higher to lower efficiency classes, the average energy cost of refrigerators bought is not significantly higher among treated users. The impact of information on energy costs is economically meaningful. Distribution of lifetime energy cost and total cost of purchased refrigerators by energy class and treatment shows that, the treatment induces a shift in purchases from more expensiveto cheaper products with lower total costs, particularly where energy and total costs overlap, and are therefore more directly comparable, across energy classes.

Treatment effect on search patterns. The results on purchases indicate that providing information on energy costs on top of the energy labels affects users’choice of products. We exploit available website navigation data to study whether these different choices result from different search patterns induced by the treatments. Product prices appearless relevant for search than for purchase decisions, and we do not observe significantly different effects betweenthe1-year and 15-year treatments on overall search outcomes. The distributions of energy and total costs of viewed products by treatment and energy classindicate that users search over a wide range of products before selecting what to buy. The treatments cause a shift in product views towards refrigerators with lower total costs. Increases in energy costs and efficiency class of viewed products go together, confirms that energy class is an imprecise indicator of energy efficiency. It suggests that users may underestimate the energy consumption of products in high-efficiency classes and of less efficient products within each class.

In general, we find that adding energy costs information to energy labels does not affect the overall likelihood of purchasing a refrigerator but shifts the distribution of purchases away from top-ranked A+++ products toward lower-graded ones with lower prices. Such shift does not come at the expense of higher energy cost since it occurs where the distributions of energy costs of the different classes overlap. We can infer that providing information on energy-using appliances’energy costs, on top of the energy class and usage information included in the standard EU energy label, directs purchases towards cheaper products in lower efficiency classes, but with similar energy cost and total costs. This result is consistent wit hconsumers’overweighting energy class in their purchase decisions when energy cost information is not provided in a readily accessible form. The finding that treatments increase search time on low energy-efficiency class products supports the claim that energy cost information draws users’attention to the total cost of products and suggests that energy labels allow prospective buyers to save on cognitive effort.

Given the not statistically significant impact of providing simple but accurate cost information on the total cost of purchases, and the added cognitive and time costs of a more elaborate search process, it is unclear whether the provision of energy cost information improves customers’ welfare. Nonetheless, the fact that the EU energy label allows for substantial overlap in energy costs between similar products in different energy classes raises the question of whether the provision of energy cost information within the EU label may improve its transparency. This issue is not restricted to the European case, as labels in several other countries rely on similar rules to compute energy-efficiency classes. Moreover, as energy costs might temporarily increase as part of the energy transition, the fact that energy classes draw consumers’ attention away from energy costs may have unintended social and economic implications, and might delay the uptake of energy-efficient products.

About author

Dr. Gao Yu is an assistant professor in the Department of Applied Economics, Guanghua School of Management. She obtained her phD from Erasmus University in the Netherlands in 2017, majoring in behavioral economics. She is interested in decision making under uncertainty and intertemporal choices. She also applies behavioral and decision theories to help individuals make better decisions, such as energy-efficient adoptions, pension enrollments and climate change mitigation.