A "pretense of knowledge" problem? 2

In the comments section to my previous post on this topic Donal Curtin makes the point that

However, unfortunately but unavoidably, it is the job of regulators to set some prices in situations where important markets aren't functioning competitively. I'd prefer if it wasn't, and personally I'd fire the price regulation gun only as a last resort if all other more market-friendly options were exhausted. But that said, even generally pro-market governments find themselves setting some prices. I agree that the process is imperfect, and there are multiple methodology and other choices to make along the way each of which introduces room for error. But sometimes it has to be done, and as well as you can manage, and preferably (as ComCom tends to do) with investment-friendly "err on the high side" numbers, to keep investment flowing into the regulated sector. The opportunity cost point is fine, but I wonder if in practice it's addressed (albeit in some rough and ready fashion) when regulators set a rate of return equal to that earned by "similar" sorts of activity, given that they're likely to be the sorts of activities the regulated company would otherwise have pursued?

My point here would be, and let me go all Coaseian for a moment, that comparative institutional analysis is needed. The first thing the regulators have to show is that their "wrong solution" is likely to be better than the market "wrong solution". It is possible that the regulated outcome is worse that the unregulated one. As Coase said in an interview with Reason magazine in 1997:

Reason: You said you're not a libertarian. What do you consider your politics to be?

Coase: I really don't know. I don't reject any policy without considering what its results are. If someone says there's going to be regulation, I don't say that regulation will be bad. Let's see. What we discover is that most regulation does produce, or has produced in recent times, a worse result. But I wouldn't like to say that all regulation would have this effect because one can think of circumstances in which it doesn't.

Reason: Can you give us an example of what you consider to be a good regulation and then an example of what you consider to be a not-so-good regulation?

Coase: This is a very interesting question because one can't give an answer to it. When I was editor of The Journal of Law and Economics, we published a whole series of studies of regulation and its effects. Almost all the studies--perhaps all the studies--suggested that the results of regulation had been bad, that the prices were higher, that the product was worse adapted to the needs of consumers, than it otherwise would have been. I was not willing to accept the view that all regulation was bound to produce these results. Therefore, what was my explanation for the results we had? I argued that the most probable explanation was that the government now operates on such a massive scale that it had reached the stage of what economists call negative marginal returns. Anything additional it does, it messes up. But that doesn't mean that if we reduce the size of government considerably, we wouldn't find then that there were some activities it did well. Until we reduce the size of government, we won't know what they are.

My issue is that regulators don't seem to think like this, they just seem to assume that whatever they do will be better than what it occurring without their intervention. And I just want them to show that their regulated outcome is likely to be better than the current, albeit imperfect, market situation.

A "pretense of knowledge" problem?

Over at the, ever interesting, Economics New Zealand blog Donal Curtin writes,

Chorus got bowled like ninepins this morning by the Court of Appeal, having earlier been skittled by the High Court.

The cases were about the Commerce Commission proposing a big reduction in the price Chorus could charge for UBA, or as it is formally defined, "the additional UBA service component, which allowed access seekers to supply broadband services over Telecom’s copper access lines without investing in their own equipment or software". In other words, the bits and bobs that carry broadband traffic across the gap between the copper line from your place and the start of an ISP's network.

The reduction (roughly halving the price) had been based on a benchmarking exercise, where the Commission (as required by the Telecommunications Act) looked at the prices overseas for UBA as a quick and dirty proxy for what it might well cost here. There's lots more about the exact details of the benchmarking comparability exercise, but that's the gist of it.

and

So now on we go to the Commission's final word on the UBA price, which will be determined by modelling the actual costs of an efficient provider in New Zealand (Chorus had exercised its right to object to the benchmark stab at the price and to have local costs estimated explicitly).

So what's my problem here? In short, it isn't the job of courts or regulators to determine costs or prices. About the only thing you can say about outcomes determined by such procedures is that they are wrong. As I noted in a post a couple of days ago, Dixit on costs, Avinash Dixit writes that,

In other words, opportunity costs are the correct measure. But these are based on expectations and calculations done within firms, and are not available in reported data.

If we accept this, then its not clear what basis the regulator or the courts have for determining costs and thus prices. At best these bodies have to deal with "reported data" but as noted such data misses some of the most important determines of opportunity costs. Without measures of theses how can a regulator or court arrive at any sensible view on what costs are?

Looks like there is a bit of the "pretense of knowledge" problem here.

Dixit on costs

From Avinash Dixit's new book, Microeconomics: A Very Short Introduction, comes this discussion of costs and the supply curve. Dixit is discussing an example of calculating a short-run supply curve for crude oil.

Although this example makes the idea of a supply curve stand out vividly, it is merely illustrative. First, data are not available for all countries; for example Russia and China are omitted for want of cost data. Second, countries or regions are not the right unit of analysis. Ideally we should have data on lifting costs and capacities for all the thousands of individual wells. These differ greatly within a country; they would generate a smooth supply curve instead of the large steps shown. Finally and most importantly, lifting costs are not correct short-run marginal costs. Firms that operate the wells have the choice of leaving oil in the ground, thus producing at less than full capacity, if they believe that prices will rise in the future. In other words, opportunity costs are the correct measure. But these are based on expectations and calculations done within firms, and are not available in reported data. Therefore this example can be used to improve understanding of the ideas, but should not be taken literally (Emphasis added).

One implication of the bit in bold is that, at best, without detailed firm level data you cannot estimate a supply curve. But as expectations are subjective, at least to some degree, it may be impossible to get data on the opportunity costs at all. The expectations held by members of the firm will differ depending on the particular person being asked. Also even if that person can detail their expectations well enough to be part of a quantifiable data set, the data will change person by person. Thus the whole idea of an objective cost function that can be estimated from "the data" becomes untenable.

Now there's a thought that could ruin an econometrician's day.