Now that I am home for a couple of weeks I am going to catch up on some things, including Mike’s excellent post on the “naming of names” in electric reliability violations. In that post he notes
FERC Chairman Pat Wood drew attention to “naming of names” in the recent quarterly compliance, and encouraged the public to check the reports. He said he thought the “Scarlet Letter” factor would serve to encourage compliance with NERC’s reliability standard.
I love this invocation of the “Scarlet Letter”, because it concisely captures something crucial in modern transactions that has been missing for too long in electric power: a valuable reputation mechanism, and the proliferation of the information for customers to evaluate a producer’s performance. Your initial reaction may be “wait a minute, my utility advertises all the time and tells me how many employees are waiting to take my calls about service outages.” That’s not what I’m talking about in terms of reputation formation. I’m talking about real, on-the-ground information about performance, provided by a (theoretically) neutral third party. I say “theoretically” because groups like NERC have their own agendas in setting the standards by which we evaluate producer performance, and we should take those agendas into account. But still.
The importance of reputation mechanisms, and the availability of unbiased information that enables them to work to enforce good outcomes, has been long known and studied in economics. One of my favorite recent examples is the EPA 33/50 program, analyzed by Arora and Cason (1995). The goal of the voluntary 33/50 program was a 33% reduction in chemical emissions (of 17 toxins on the Toxic Release Inventory list) from 1988 levels by 1992, and a 50% reduction by 1995. But instead of mandating a particular technology to use and a particular level of emission, this program enabled firms to use technologies that they chose in meeting the targets.
How was the 33/50 program enforced? Public recognition. The firms who met these targets were listed on the EPA website, lauded for their accomplishments, given awards for outstanding performance. Firms who participated, and received this public recognition, came from the chemicals, plastics, metals, electricity, and transportation industries, among others. Firms could use these accolades in their marketing to customers. To the extent that customers care about pollution reduction, they will make their choices based on that information (and furthermore, the flexibility of technology choice might have made the cleaner firms also the cheaper, or at least not costlier, firms).
The 33/50 program was an excellent example of using a reputation mechanism and the public provision of information to enforce a better outcome in a decentralized manner.
In an experimental analysis that complements the 33/50 analysis, Cason and Gangadharan (2002) look at environmental labeling and reputation formation when consumers have incomplete information. One of their most interesting results is that sellers chose to incur the cost of getting third-party verification of the quality of their goods, and that this verification enabled them to take advantage of reputation formation to increase their profits. In so doing they also increased consumer surplus and, therefore, total surplus. Certification overcame the moral hazard problem in supplier quality choice with imperfectly informed consumers.
So when Chairman Wood invokes the “Scarlet Letter” and encourages electricity customers to make use of the information available to them on the performance of their energy suppliers, he knows what he’s talking about. Reputation matters, and having a third party provide information can enable the reputation formation that benefits both producers and consumers.
Seema Arora and Tim Cason, “An Experiment in Voluntary Environmental Regulation: Participation in EPA’s 33/50 Program.” Journal of Environmental Economics and Management 28 (1995): 27-86.
Tim Cason and Lata Gangadharan, “Environmental Labeling and Incomplete Consumer Information in Laboratory Markets.” Journal of Environmental Economics and Management 43 (2002): 113-134.