Opting Out in Germany for Non-Renewable Energy

While many people in Germany say they would use green energy if presented with a choice, very few consumers do so. In contrast, most people have been using green energy in a few German municipalities where citizens have had to opt out for non-renewable energy supplies rather than having to opt-in to get renewable ones. This case study also illustrates the connection between green power choices and clean air / environmental health, and the value of randomized control trials (RCTs) for measuring program impacts. Designated a Landmark case study by our Building Energy peer review panel in 2022.

Background

Note: To minimize site maintenance costs, all case studies on this site are written in the past tense, even if they are ongoing as is the case with this particular program. 

Opt-out designs have been proven to be effective in other domains, such as encouraging workers to save for retirement. We know that defaults matter, yet there are few examples of communities that have used an opt-out program to promote the use of energy from renewable sources. Such examples could be helpful as we learn to reduce our use of fossil fuels and turn to renewable energy sources. That transition is an important part of abating climate change.

Getting Informed

The experience of the first two communities (described below) was used when planning the randomized control trial in the third community example below.

Delivering the Program

Three Germany communities have elected to have citizens opt-out for non-renewable energy supplies, as outlined in http://www.law.harvard.edu/programs/olin_center/papers/pdf/Sunstein_951.pdf

The first community is Schönau in the Black Forest, consisting of about 2,500 people. In the aftermath of the Chernobyl disaster in the 1980s, a citizen referendum established an environmentally friendly energy supply, in which the Schönau Power Company became the incumbent utility and many of the Schönau citizens became owners of the cooperative. That company promoted solar energy and placed a great deal of reliance on renewables. Customers could opt out and use other energy sources, but they had to find relevant information in order to identify alternatives. Almost no one opted out: over many years, the opt-out rate was only slightly above zero percent.

The second natural experiment involves the former EnergieDienst GmbH, which supplied energy to an area in southern Germany. In 1999, the company established three separate tariffs. The default was green, and it turned out to be 8% cheaper than the previous tariff. The second option was less green but cheaper (by an additional 8%) and the third was greener but more expensive (by an additional 23%). If customers did not respond, they would remain with the default. About 94 percent of customers so remained, with 4.3 percent switching to the cheaper tariff, and the rest switching either to the greener alternative or to a different supplier.

More recently, a randomised control trial (RCT) was conducted in Germany to test the effect of the default rule (opt-out approach) on the use of green energy. The study involved 41,952 households, participating in a 4.5-week-long RCT and randomly assigned into one of two treatments. In the first treatment, people were asked whether they wanted to opt into green energy (renewable energy source); in the second, they were automatically enrolled into green energy, and asked whether they wanted to opt out. In both treatments, green energy was slightly more expensive.

The authors’ follow-up study strongly suggests that in both opt-in and opt-out conditions, consumers were not tricked or fooled; they were consciously aware of what they were doing.

Barriers

The following table summarizes the key barriers and how each was addressed.

Barrier	How it was addressed
Competing priorities	Switched from opt-in to opt-out Made the desired behavior the norm so people didn’t feel the need to make choices, while allowing them to opt-out if they wanted
Lack of knowledge and time	Made the desired behavior the norm so people didn’t feel the need to make choices, while allowing them to opt-out if they wanted

Measuring Achievements

The third example involved 41,952 households, participating in a 4.5-week-long RCT. Households were randomly assigned into one of two treatments. In the first treatment, people were asked whether they wanted to opt into green energy (renewable energy source); in the second, they were automatically enrolled into green energy, and asked whether they wanted to opt out. In both treatments, green energy was slightly more expensive. The measure of impact is the number of households choosing each type of energy.

Results

In the third example, conditional on the purchase of an energy contract, only 7.2% of purchased contracts in the opt-in treatment were green, but in the opt-out treatment, a remarkable majority of 69.1% of purchased contracts were green. Notably, this effect was robust after controlling for service quality of the chosen contract, base prices of electricity, and unit prices.

Notes

A significant barrier to replicability has been concern about public backlash. Utilities worry about low customer satisfaction and policy makers are weary of allowing utilities to change defaults in this way. Replicating this design in other jurisdictions may require navigating regulatory, logistic and cultural issues.

A controlled trail, such as the third example, should help disperse the public’s general distrust of opt-out designs. Further, the authors’ follow-up study strongly suggests that in both opt-in and opt-out conditions, consumers were not tricked or fooled; they were consciously aware of what they were doing.

Additional municipalities are beginning to switch to opt-out. For example, customers in the City of San José California with existing PG&E accounts were automatically enrolled in GreenSource in February 2019. Their electricity was generated from renewable sources such as wind and solar, and from carbon-free sources such as hydropower. GreenSource rates were cheaper than PG&E generation rates. Southern California Edison now offers opt-out programs as well, sourced by the Clean Power Alliance.

 

This case study was written in 2020 by Jay Kassirer.