We recently covered a new report arguing that monthly Internet data caps could be bad for competition. Here with a different view is Scott Wallsten of the Technology Policy Institute, a Washington, DC think tank. The opinions expressed here are not necessarily those of Ars Technica.

Last year, The New York Times criticized usage-based broadband pricing, noting that “Moving an extra gigabyte of data at off-peak times costs virtually nothing.” More recently, a report by the advocacy group Public Knowledge suggested that broadband data caps, a form of usage-based pricing, are an inefficient way to manage congestion.

These claims are correct: while monthly caps may help control congestion if they impose binding constraints on high-volume users, pricing models truly aimed at congestion would target times and areas of congestion directly. That’s why the DC Metro system manages overcrowding by charging higher fares for travel at rush hour than for travel at off-peak times when crowds tend to be small—rather than by limiting each person’s total number of monthly rides.

But the critiques miss the key point: in industries with high fixed costs and low marginal costs, aside from congestion, efficient pricing has little to do with marginal costs. Pricing at marginal cost in such industries cannot produce sufficient revenues to cover costs. Instead, efficiency in these industries requires spreading the fixed costs over as broad a customer base as possible. Efficient pricing will, in general, charge users with high demand more than users with low demand even if those users impose no additional costs on the network.

This phenomenon is common throughout the economy. Airlines charge wildly different prices for nearly identical seats on any given flight: the businessperson who must be in Chicago for a meeting on Tuesday at noon is likely to pay far more than the grandparent who thought this might be a nice week to visit the family, even though the incremental cost to the airline of carrying them, given that the airplane will fly regardless of their presence, is almost zero.

This kind of price discrimination can allow resources to be deployed more efficiently and make consumers better off when it results in lower prices for consumers with weak demand but higher prices for consumers with strong demand. (See Jonathan B. Baker, “Competitive Price Discrimination: The Exercise of Market Power Without Anticompetitive Effects,” Antitrust Law Journal 70 (2003): 643–654; and Timothy J. Brennan, “Is Competition the Entry Barrier? Consumer and Total Welfare Benefits of Bundling,” 2005.) In that case, consumers are better off overall because the pricing schemes make the product available to more people.

Nevertheless, just because price discrimination can be good for consumers does not mean that it always is good for consumers. Any price discrimination requires some degree of market power, but firms with sufficient market power can use price discrimination to segment markets in ways that leave consumers worse off. For example, a firm may be able to set prices in ways that increase profits but not output if switching costs are too high, entry too difficult, or pricing models unfairly benefit the firm’s downstream products at the expense of a competitor.

It is not possible to conclude based on theory or conjecture alone whether a given pricing scheme, including those involving data caps, will ultimately harm or benefit consumers overall, but the test for determining the net effect of pricing schemes is, in principle, simple: do they increase output?

With voice service, for example, the answer would appear to be “yes.” Wireless voice pricing evolved from strictly pay-as-you-go to unlimited (with AT&T One Rate), to buckets of minutes, to today’s mix of almost every type of plan imaginable. At least partly as a result, wireless voice usage soared, especially among low-income people who tend to purchase pay-as-you-go plans.

But measuring broadband “output,” at least at this stage in its development, is more complicated. Is the relevant output measure "data consumption by a typical user," the "share of households with broadband connections," or perhaps some combination of those or other indicators? Should the relevant market be broader and include all broadband connections regardless of technology? How should the analysis incorporate effects on competition in downstream markets? These questions do not have easy answers, but they must be considered when evaluating whether a given pricing model is beneficial or harmful overall.

In short, the criticism that data caps are blunt instruments with respect to congestion is correct but largely irrelevant, as is the criticism that they don’t reflect the marginal cost of moving data. Different pricing models, including data caps, should be viewed as price discrimination similar to what occurs whenever firms need to find ways to cover large fixed costs. Then, the relevant question is how these plans affect consumers overall. Under some circumstances, new pricing models may create competitive issues, but consumers will be best served by fact-specific investigation rather than blanket prohibitions.

Critics of usage-based pricing should think twice before making it harder to experiment with pricing models. Heeding their criticism too quickly may well harm the very people—in particular, poor communities who have yet to adopt broadband—who public policy now aims to help.

Scott Wallsten is Vice President for Research and Senior Fellow at the Technology Policy Institute.