DOT’s airline price gouging investigation and a political economy-based prediction

On Friday, the U.S. Department of Transportation announced it had launched an investigation into possible “unfair practices (e.g., price gouging) affecting air travel during the period of time that Amtrak service along the Northeast Corridor was delayed or suspended as a result of the May 12th derailment.” Five airlines received letters from the agency seeking information on prices for travel between airports most affected by the derailment. CBS News in New York had the story, as did many other media outlets.

In the statement released by the DOT Transportation Secretary Anthony Foxx said, “The idea that any business would seek to take advantage of stranded rail passengers in the wake of such a tragic event is unacceptable. This Department takes all allegations of airline price-gouging seriously, and we will pursue a thorough investigation of these consumer complaints.” The DOT was responding to consumer complaints and a letter from U.S. Senator Chris Murphy (D-CT).

Pure political theater.

The law DOT cites, 49 US Code § 41712, allows the department to investigate whether an airline “has been or is engaged in an unfair or deceptive practice or an unfair method of competition in air transportation or the sale of air transportation.” In the event the department finds price gouging, the sole remedy present in the law is to order the airlines to stop. Given that rail travel was restored after five days, prices have already returned to normal. No meaningful remedy is possible…

…unless DOT wants to go big: rather than finding the prices constituted unfair practices, the DOT could conclude that the airlines’ computerized pricing algorithms constitute unfair practices and order airlines to cease employing them. The airlines’ dynamic pricing systems are not popular with consumers, so they might make an appealing political target. Such a response would be meaningful, in that it would impose significant costs on airlines to reform their systems, but is such a conclusion likely?

The word “unfair” is not defined in the law; the DOT said it relies upon the U.S. Federal Trade Commission’s Policy Statement on Unfairness for a working definition. The policy statement provided a three factor approach to fairness. considering: (1) consumer injury, (2) violation of public policy, and (3) unethical or unscrupulous conduct. In practice the FTC relies only on the first two factors.

Under the policy, apparent consumer injury is judged against the commercial benefits associated with the trade practice. While dynamic pricing is unpopular with consumers, it is profitable for airlines. In addition, it likely produces prices and service quality that are, on average, better for consumers than otherwise. A balancing of apparent harms and apparent benefits should tilt in favor of dynamic pricing.

Here is my political economy-based prediction:

After a month or two the DOT will report finding that airline prices did jump suddenly after the derailment as demand for air travel jumped up. They will observe that initial price spikes resulted from airlines’ computerized pricing mechanisms and did not reflect an intent to “take advantage of stranded passengers in the wake of such a tragic event.” They will note that airlines responded by adding flights and pressing larger aircraft into service. The report will conclude temporary price spikes reflected the ordinary workings of supply and demand under short-lived extraordinary circumstances. No finding of unfair practices will result, and no trade practices will be condemned.

While the announcement of the investigation produced a lot of press, the release of the report will produce little press. A finding of “ordinary workings of supply and demand” is not newsworthy.

What is more, the DOT already knows this answer. It already believes there is nothing to find in the data it is requesting. Still, a Senator wrote a letter — by the way Senator Murphy sits on the Senate subcommittee that oversees the DOT budget — and the DOT responded.

The Senator himself, too, either already knows this answer or simply has not thought too hard about it. But why should he think about a future no-news report? The announcement of the investigation and the press that the announcement garnered, that was the goal. The rest is noise.

[Thanks to Tom Konrad for bringing the story to my attention.]

The sharing economy and the electricity industry

In a recent essay, the Rocky Mountain Institute’s Matthew Crosby asks “will there ever be an AirBnB or Uber for the electricity grid?” It’s a good question, a complicated question, and one that I have pondered myself a few times. He correctly identifies the characteristics of such platforms that have made them attractive and successful, and relates them to distributed energy resources (DERs):

What’s been missing so far is a trusted, open peer-to-peer (P2P) platform that will allow DERs to “play” in a shared economy. An independent platform underlies the success of many shared economy businesses. At its core, the platform monetizes trust and interconnection among market actors — a driver and a passenger, a homeowner and a visitor, and soon, a power producer and consumer — and allows users to both bypass the central incumbent (such as a taxi service, hotel, or electric utility) and go through a new service provider (Uber, Airbnb, or in the power sector, Google).

Now, as millions gain experience and trust with Airbnb, Uber and Lyft, they may likely begin to ask, “Why couldn’t I share, sell or buy the energy services of consumer-owned and -sited DERs like rooftop solar panels or smart thermostats?” The answer may lie in emerging business models that enable both peer-to-peer sharing of the benefits of DERs and the increased utilization of the electric system and DERs.

A P2P platform very explicitly reduces transaction costs that prevent exchanges between buyer and seller, earning revenue via a commission per transaction (and this is why Uber has in its sights such things as running your errands for you (video)). That reduction allows owners of underutilized assets (cars, apartments, solar panels, and who knows what else will evolve) to make someone else better off by selling them the use of that asset. Saying it that way makes the static welfare gain to the two parties obvious, but think also about the dynamic welfare gain — you are more likely, all other things equal, to invest in such an asset or to invest in a bigger/nicer asset if you can increase its capacity utilization. Deregulation catalyzed this process in the airline industry, and digital technology is catalyzing it now in rides and rooms. This prospect is exciting for those interested in accelerating the growth of DERs.

Note also that Crosby makes an insightful observation when he says that such P2P networks are more beneficial if they have access to a central backbone, which in this case would be the existing electricity distribution grid. Technologically, the edge of the network (where all of the cool distributed stuff is getting created) and the core of the network are complements, not substitutes. That is not and has not been the case in the electricity network, in large part because regulation has largely prevented “innovation at the edge of the network” since approximately the early 20th century and the creation of a standard plug for lights and appliances!

The standard static and dynamic welfare gain arguments, though, are not a deep enough analysis — we need to layer on the political economy analysis of the process of getting from here to there. As the controversies over Uber have shown, this process is often contentious and not straightforward, particularly in industries like rides and electricity, the incumbents in which have had regulatory entry barriers to create and protect regulatory rents. The incumbents may be in a transitional gains trap, where the rents are capitalized into their asset values, and thus to avoid economic losses to themselves and/or their shareholders, they must argue for the maintenance of the regulatory entry barrier even if overall social welfare is higher without it (i.e., if a Kaldor-Hicks improvement is possible). The concentration of benefits from maintaining the entry barrier may make this regulation persist, even if in aggregate the diffuse benefits across the non-incumbents is larger than the costs.

That’s one way to frame the current institutional design challenge in electricity. Given that the incumbent utility business model is a regulatory construct, what’s a useful and feasible way to adapt the regulatory environment to the new value propositions that new digital and distributed energy technologies have made possible? If it is likely that the diffuse economic and environmental benefits of P2P electricity exchange are larger than the costs, what does a regulatory environment look like that would enable P2P networks and the distribution grid to be complements and not substitutes? And how would we transfer the resources to the incumbents to get them out of the transitional gains trap, to get them to agree that they will serve as the intelligent digital platform for such innovation?

I think this is the question at the guts of all of the debate over the utility “death spiral”, the future utility business model, and other such innovation-induced dynamism in this industry. I’ve long argued that my vision of a technology-enabled value-creating electricity industry would have such P2P characteristics, with plug-level sensors that enable transactive automated control within the home, and with meshed connections that enable neighbors with electric vehicles and/or rooftop solar to exchange with each other (one place I made that argument was in my 2009 Beesley lecture at the IEA, captured in this 2010 Economic Affairs article). Crosby’s analysis here is consistent with that vision, and that future.

Complexity, heuristics, and the traveling salesman problem

Add this one to your long reads queue, because it’s well worth it: Tom Vanderbilt writes in Nautilus about the traveling salesman problem and how algorithmic optimization helps us understand human behavior more deeply. It’s a thorough and nuanced analysis of the various applications of algorithms to solve the traveling salesman problem — what’s the most efficient way (which you of course have to define, either in time or money or gasoline etc.) to deliver some number n of packages to some number d of destinations, given your number t of trucks/drivers? This is a tough problem for several reasons, and Vanderbilt’s discussion of those reasons is clear and interesting.

We can start with a simple transportation model with small numbers of packages, destinations, and trucks. But as the number of them increases, the problem to solve becomes increasingly complex, increasing at least exponentially if not more. Then think about what happens when the locations of the destinations change every day, as is the case for UPS and FedEx deliveries. Then think about what happens when you add in heterogeneity of the deliveries; Vanderbilt opens with a girl pointing out that her mother would never buy perishables and then leave them in the car all day, so the nature of the item changes the constraints on the definition of the efficient route.

Her comment reflects a basic truth about the math that runs underneath the surface of nearly every modern transportation system, from bike-share rebalancing to airline crew scheduling to grocery delivery services. Modeling a simplified version of a transportation problem presents one set of challenges (and they can be significant). But modeling the real world, with constraints like melting ice cream and idiosyncratic human behavior, is often where the real challenge lies. As mathematicians, operations research specialists, and corporate executives set out to mathematize and optimize the transportation networks that interconnect our modern world, they are re-discovering some of our most human quirks and capabilities.

One of the most intriguing aspects of implementing logistics that reflect good solutions to the TSP that Vanderbilt highlights is the humanity of the driver. Does the dispatcher know the driver, know that s/he is reliable or not? That may affect how to define the route, and how many stops or changes to put on that particular person’s schedule. Is the driver prone to fatigue, and how does that fatigue affect the driver’s decision-making? What are the heuristics or rules of thumb that different drivers use to make decisions in the face of uncertainty given the cognitive limitations of humans? How different will the different heuristics of different drivers be, and how to they affect the logistics of the system?

What Vanderbilt finds is that good logistics systems take the organic, emergent system that incorporates those heuristics into account when devising the TSP algorithm. They leave a human component in the logistics, but also use the human component to inform and change the algorithm. Another important element is data, because all such algorithms are going to work in conjunction with such data as location. GIS mapping capabilities improve the data used to establish, test, and monitor TSP algorithms.

Don’t bet against Netflix, at least not now

Michael Giberson

Jonathan Knee argues that Netflix is succeeding the way big media companies always have succeeded, in a time where such opportunities are less frequent than before. From The Atlantic:

The economic structure of the media business is not fundamentally different from that of business in general. The most-prevalent sources of industrial strength are the mutually reinforcing competitive advantages of scale and customer captivity. Content creation simply does not lend itself to either, while aggregation is amenable to both.


Netflix’s success in streaming video is therefore hardly paradoxical. The company sits squarely in the tradition of the most-successful media businesses: aggregators with strong economies of scale and customer captivity.

There is a lot more explication at the link.

Non-traffic causes of traffic congestion

Michael Giberson

Is this an unpriced external effect of shooting off fireworks on July 4?

July 5 tends to have an unusual number of animal-related traffic problems, as pets, spooked by the fireworks on the previous day, have a greater propensity to wander onto freeways.

From Eric Morris at the Freakonomicsblog, “Road Blocks: The Strange Things That Cause Traffic.”

Other non-traffic contributors to traffic congestion mentioned in the article: oil spills, antifreeze, oranges, lemons, livestock, wild animals, abandoned pets, suicides, homicides, discarded Christmas trees, and furniture and appliances including couches, chairs, refrigerators, and stoves.

Netflix recommendations: Deep or random?

Michael Giberson

I know that Netflix’s recommendation engine has some serious computation behind it, and it often offers up interesting and useful suggestions. But occasionally it puzzles me, and I wonder if it is incredibly deep in its analysis or simply somewhat random.

Case in point:

Suggested: American Experience: Into the Deep

American Experience: Into the Deep: America, Whaling & the World
Because you enjoyed:

It Might Get Loud


The Last Picture Show


So let’s get this straight, because I enjoyed a documentary about rock guitarists from different generations, and a classic Kurwasowa movie about a masterless samurai, and a black-and-white period piece about growing up in a small town in Texas, the artificial genius of Netflix thinks I’d enjoy a riveting documentary on the history of whaling in the United States?

Well, actually, it does sound kind of interesting …

Also, if they have any films about a rock-and-roll samurai sushi chef coming to a small town in Texas, I’d want to see that too.

The natural gas that didn’t come in from the cold

Michael Giberson

Among the complications caused by the cold weather last week, short supply of natural gas throughout much of the southwest United States. Reports indicate some gas wells were freezing up and loss of electric power to gas production systems, but more of the problem was loss of power to natural gas pipelines. And, as mentioned here Friday, in some cases the rolling blackouts in Texas cut power to the natural gas system, resulting in inadequate gas supplies, resulting in some gas-fired power plants being cut off from supply, hampering efforts to end the rolling blackouts. But the shortage wasn’t just a supply-side issue, a gas company official said demand for gas was the highest its been for 30 years.

Sources: Dallas Morning News, “Freeze knocked out coal plants and natural gas supplies, leading to blackouts,” and Wall Street Journal, “Texas Power Outages Cause Natural Gas Shortages In US Southwest.”

Hard hit New Mexico saw lawmakers spring into action. U.S. Representative Ben Ray Lujan is asking the Federal Energy Regulatory Commission to investigate. A state legislative committee is holding hearings today on the outages in the state. Thousands of Arizona gas consumers also lost service. Southern California gas supplies were difficult, but San Diego Gas & Electric and Southern California Gas Co. were able to maintain service to firm customers by drawing on nearby storage supplies and cutting off interruptible customers. (Interruptible customers are typically large industrial consumers who choose to pay a lower rate in exchange for agreeing to be among the first to be cut off during emergencies.)

Texas regulators are also asking questions, “Texas to Probe Rolling Blackouts.”

Texas officials have ordered an investigation into rolling blackouts that struck the state’s electric grid last week, including whether market manipulation played a role along with harsh weather in disrupting natural-gas and electricity supplies to millions of people.

The Public Utility Commission of Texas asked the state’s independent energy-market monitor, Daniel Jones, to conduct a probe to see if power generators, pipeline companies or others broke market rules. …

To be sure, Texas set an all-time winter power demand record one day during the storm, placing historic pressure on power providers.

Electricity-grid officials said Mr. Jones’ team will look at price patterns and power-plant outages remembering that, in California’s energy crisis of 2000-2001, unscrupulous power generators feigned equipment problems to drive up the price of electricity. A significant number of plants in Texas failed last week, and wholesale electricity prices briefly spiked.

Some commentators linked the electric power-gas pipeline interdependency issue to environmental regulation. As this Energy Information Administration document on natural gas compressor stations explains, compressor stations can be either electric or natural gas-fueled. As of the November 2007 date, most compressors were gas fueled, drawing gas from the pipeline itself to run the compressor station, but in some areas of the country “all or some may be electrically powered primarily for environmental or security reasons.” (Note that the document is dated before the current administration took office, so you can’t blame the White House for it.)

Pipelines head north and east from Texas in addition to west, but no reports of supply problems anywhere else in the country.

U.S. Natural Gas Pipeline Compressor Stations Illustration, 2008

U.S. Natural Gas Pipeline Compressor Stations Illustration, 2008. (EIA)