Tirole

13 October 2014 at 2:31 pm Peter G. Klein 17 comments

| Peter Klein |

As a second-year economics PhD student I took the field sequence in industrial organization. The primary text in the fall course was Jean Tirole’s Theory of Industrial Organization, then just a year old. I found it a difficult book — a detailed overview of the “new,” game-theoretic IO, featuring straightforward explanations and numerous insights and useful observations but shot through with brash, unsubstantiated assumptions and written in an extremely terse, almost smug style that rubbed me the wrong way. After all, game theory was supposed to add transparency and “rigor” to the analysis, bringing to light the hidden assumptions of the old-fashioned, verbal models, but Tirole combined math and ad hoc verbal asides in equal measure. (Sample statement: “The Coase theorem (1960) asserts that an optimal allocation of resources can always be achieved through market forces, irrespective of the legal liability assignment, if information is perfect and transactions are costless.” And then: “We conclude that the Coase theorem is unlikely to apply here and that selective government intervention may be desirable.”) Well, that’s the way formal theorists write and, if you know the code and read wisely, you can gain insight into how these economists think about things. Is it the best way to learn about real markets and real competition? Tirole takes it as self-evident that MIT-style theory is a huge advance over the earlier IO literature, which he characterizes as “the old oral tradition of behavioral stories.” He does not, to my knowledge, deal with the “new learning” of the 1960s and 1970s, associated mainly with Chicago economists (but also Austrian and public choice economists) that emphasized informational and incentive problems of regulators as well as firms.

Tirole is one of the most important economists in modern theoretical IO, public economics, regulation, and corporate finance, and it’s no surprise that the Nobel committee honored him with today’s prize. The Nobel PR team struggled to summarize his contributions for the nonspecialist reader (settling on the silly phrase that his work shows how to “tame” big firms) but you can find decent summaries in the usual places (e.g., WSJ, NYT, Economist) and sympathetic, even hagiographic treatments in the blogosphere (Cowen, Gans). By all accounts Tirole is a nice guy and an excellent teacher, as well as the first French economics laureate since Maurice Allais, so bully for him.

I do think Tirole-style IO is an improvement over the old structure-conduct-performance paradigm, which focused on simple correlations, rather than causal explanations and eschewed comparative institutional analysis, modeling regulators as omniscient, benevolent dictators. The newer approach starts with agency theory and information theory — e.g., modeling regulators as imperfectly informed principals and regulated firms as agents whose actions might differ from those preferred by their principals — and thus draws attention to underlying mechanisms, differences in incentives and information, dynamic interaction, and so on. However, the newer approach ultimately rests on the old market structure / market power analysis in which monopoly is defined as the short-term ability to set price above marginal cost, consumer welfare is measured as the area under the static demand curve, and so on. It’s neoclassical monopoly and competition theory on steroids, and hence side-steps the interesting objections raised by the Austrians and UCLA price theorists. In other words, the new IO focuses on more complex interactions while still eschewing comparative institutional analysis and modeling regulators as benevolent, albeit imperfectly informed, “social planners.”

As a student I found Tirole’s analysis extremely abstract, with little attention to how these theories might work in practice. Even Tirole’s later book with Jean-Jacques Laffont, A Theory of Incentives in Procurement and Regulation, is not very applied. But evidently Tirole has played a large personal and professional role in training and advising European regulatory bodies, so his work seems to have had a substantial impact on policy. (See, however, Sam Peltzman’s unflattering review of the 1989 Handbook of Industrial Organization, which complains that game-theoretic IO seems more about solving clever puzzles than understanding real markets.)

Entry filed under: - Klein -, History of Economic and Management Thought, Methods/Methodology/Theory of Science, Myths and Realities, People, Public Policy / Political Economy.

SBA Loans Reduce Economic Growth Rich Makadok on Formal Modeling and Firm Strategy

17 Comments Add your own

1. Jim Rose | 13 October 2014 at 3:19 pm

Reblogged this on Utopia – you are standing in it! and commented:
Good round-up, including link to the great paper by sam peltzman. I also found Tirole’s book to be terse and smug when studying it at ANU in 1990.
2. beckmill | 13 October 2014 at 3:20 pm

Thank you, Peter. I knew you’d be weighing in, and I’m glad you called a spade a shovel about the level of abstraction and the snide comments Tirole makes in his book (which has never, to my knowledge, come out in a second edition). I bought it a few years ago and tried to read it on my own, but then I found out I could get a root canal without anesthesia instead. I opted for that because it was less painful and the headache afterwards went away much faster.

FWIW, I much preferred the third edition of Mike Scherer’s book (‘Industrial Market Structure and Economic Performance,’ which added co-author David Ross). However, that one came out of the old S-C-P paradigm, which, despite the fact that it’s static, I like and use as an organizing tool inside an industry analysis.

I’ll take it on faith that a game-theoretic approach to IO is an improvement for regulatory use, as you noted. I still wonder, though, about its utility in an industry (or strategic-group) analysis. Any thoughts about that?

Perchance are there any books that approach IO from a game-theoretic perspective, but that are also accessible to those of us mere mortals who paddle around at the shallow end of the gene pool without PhDs in economics?? [Just kidding – I admire anyone with a PhD in economics from a top-tier school.]

But speaking of economists–and this IS off-topic–I remember Henry Mintzberg’s hilarious off-the-cuff comment at the Doctoral Consortium in strategic management at the 1986 Academy of Management meeting in Chicago. Responding to a question about the growing influence of economics and the increasing presence of economists in the strategy field, he held forth as to why he thought that was the case (greater rigor, economists looking to spread their reach and influence, etc.).

Then he said: “Remember this: You can relax the assumptions. . .but you can NEVER relax the economists!” The twenty or so of us there dissolved in a gale of laughter.
3. Nobel Prize for Economics Goes to Economist Who Studies Monopolies - Liberty Crier | 13 October 2014 at 11:45 pm

[…] industrial organization analysis, for the 2014 economics prize. As I discuss in more detail here, Tirole’s approach to IO is probably an improvement over the old structure-conduct-performance […]
4. Karym Metwally (@KarymMetwally) | 14 October 2014 at 12:43 am

Laws perverts … and regulations cannot be balanced, ie you cannot issue laws that would be beneficial to a free-market ecosystem and at the same time having stringent state regulation against monopolies.
5. Jean Tirole Wins Nobel Prize | FAITS ET ANALYSE ECONOMIQUES | 14 October 2014 at 3:56 am

[…] industrial organization analysis, for the 2014 economics prize. As I discuss in more detail here, Tirole’s approach to IO is probably an improvement over the old structure-conduct-performance […]
6. rmakadok | 14 October 2014 at 10:54 am

Hi, Warren. Peter invited me to reply to your comment, so I’ll try to offer a defense of formal economic modeling.

In answering Peter’s invitation, I’m at a bit of a disadvantage because I am definitely NOT an IO economist (perhaps because I actually CAN relax). Rather, I’m a strategy guy — far more interested in studying the private welfare of firms than the public welfare of economies (plus, it pays better and is more fun). So, I am in a much better position to comment on the benefits that the game-theoretic toolbox is currently starting to bring to the strategy field than on the benefits that it has brought to the economics discipline over the last four decades (i.e., since Akerlof’s 1970 Lemons paper really jump-started the trend).

Peter writes, “game theory was supposed to add transparency and ‘rigor’ to the analysis.” I have heard this argument many times (e.g., Adner et al, 2009 AMR), and I think it is a red herring, or at least a side show. Yes, formal modeling does add transparency and rigor, but that’s not its main benefit. If the only benefit of formal modeling were simply about improving transparency and rigor then I suspect that it would never have achieved much influence at all. Formal modeling, like any research tool or method, is best judged according to the degree of insight — not the degree of precision — that it brings to the field.

I can’t think of any empirical researcher who has gained fame merely by finding techniques to reduce the amount of noise in the estimate of a regression parameter that has already been the subject of other previous studies. Only if that improved estimation technique generates results that are dramatically different from previous results (or from expected results) would the improved precision of the estimate matter much — i.e., only if the improved precision led to a valuable new insight. In that case, it would really be the insight that mattered, not the precision. The impact of empirical work is proportionate to its degree of new insight, not to its degree of precision. The excruciatingly unsophisticated empirical methods in Ned Bowman’s highly influential “Risk-Return Paradox” and “Risk-Seeking by Troubled Firms” papers provide a great example of this point.

The same general principle is true of theoretical work as well. I can’t think of any formal modeler who has gained fame merely by sharpening the precision of an existing verbal theory. Such minor contributions, if they get published at all, are barely noticed and quickly forgotten. A formal model only has real impact when it generates some valuable new insight. As with empirics, the insight is what really matters, not the precision.

So, the relevant question should be: Does formal modeling generate valuable new insights? And if so, where and how?

I am aware of some ways in which formal modeling can help a theorist generate new insights. I would never say that formal modeling is absolutely necessary for generating any particular theoretical insight. Nor would I ever say that any particular insight could not be generated through verbal theorizing. Nevertheless, there are some kinds of theoretical insights that are just easier to see with the aid of a formal model. By analogy, you can, at least in principle, chop down any tree with just an axe, but there are some trees for which you would really much rather have a chainsaw, as a matter of convenience. I once heard an obstetrician convince an expectant mother to accept an epidural anesthetic by saying that it’s just a modern convenience, like air conditioning in the Atlanta summer. You can certainly survive without such modern conveniences, but why not use them if they’re readily available? That’s roughly how I think about formal modeling — just a helpful modern convenience.

Here are three kinds of insights for which formal modeling can be particularly helpful:

1.) Decomposing an effect into separate parts that may sometimes oppose each other — e.g., direct and indirect effects, or intended and unintended effects.

For example, in economics, the effect of a change in the price of a good on the quantity of that good demanded is decomposed into two separate parts — the substitution effect (a fairly direct effect) and the income effect (a somewhat indirect effect). In most situations — i.e., for “normal goods” — these two components of the effect move in the same direction, but sometimes — i.e., for “Giffen goods” — they move in opposite directions. It’s just easier to understand this kind of decomposition with the aid of a little math. I suppose that one could envision the possibility of a Giffen good without a formal model, but I imagine that it would be a lot harder.

An example of this sort of decomposition in the strategy field is in my 2013 SMJ article with David Ross, where we decompose the effect of product differentiation on profit into separate parts — a competitive-advantage effect and a rivalry-restraint effect. Sometimes these two parts move in the same direction, and sometimes in opposite directions. The math in our model helps to clarify when each part is strengthened or weakened, when they oppose each other, and when one might overwhelm the other. Could these results have been generated via verbal theorizing? In principle, I suppose so, but I think it would have been a lot harder — and I certainly could never have done it.

2.) Interaction effects

It may be relatively easy to envision the main effect that A increases B, but it may be a bit trickier to envision the interaction effects of how C, D, and E influence the strength of the effect of A on B. Is the effect of A on B dampened/undermined or amplified/reinforced when C, D, and E increase? A formal model can be quite helpful in answering such questions about interaction effects. Without a formal model, it may be difficult to develop a clear unambiguous argument for such interaction effects to be either positive or negative. Indeed,
without a formal model, a theorist might never even think of the possibility that C, D, and E could have an effect on the relationship between A and B. But such unanticipated interactions may just naturally drop out of a formal model, without even looking for them. In this regard, a formal model may even suggest new insights that the theorist had not previously contemplated.

For example, a basic agency-theoretic model in economics (e.g., Grossman & Hart, 1983 Econometrica) is about the main effect of performance-based incentives motivating behavior from an agent that is more consistent with the principal’s interests. But how is this main effect altered when the agent’s assigned tasks differ in their measurability? And how does such an interaction effect influence the division of labor among different agents? While a formal model may not be absolutely required to answer these interaction-effect questions, the one developed by Holmstrom & Milgrom (1991 JLEO) sure helps a lot.

Likewise, in the strategy field, I have often used formal models to hypothesize interaction effects on profit that would have been difficult (at least for me) to envision otherwise. My 2001 SMJ article finds that there is a negative interaction effect between the profitability of information-based advantages and the profitability of deployment-based advantages. My 2003 SMJ article finds a positive interaction effect between the profitability of skills and the profitability of motivation. My 2010 Management Science article finds a negative interaction effect between the profitability of competitive advantage and the profitability of rivalry restraint. I suppose that, in principle, someone else might have been able to envision these results without relying on a formal model, but I definitely could not have.

3.) Boundary conditions

In extreme cases, if an interaction effect is particularly severe, it can completely overwhelm the main effect. For example, A may ordinarily increase B, but if A and C have a negative interaction effect on B, then it is possible that a sufficiently large value of C may totally erase the effect of A on B, or perhaps even reverse the ordinary effect of A on B so that A actually decreases B. We often call this a “boundary condition” of the positive effect of A on B (i.e., C must be sufficiently low).

In this regard, Peter is correct that one benefit of formal modeling is “bringing to light the hidden assumptions of the old-fashioned, verbal models” — insofar as a “hidden assumption” is just an unrecognized boundary condition. However, that is only half of the story. A formal model not only can identify the boundary condition, but it can also make predictions about what happens when the boundary condition gets violated.

In economics, there are many examples of such boundary conditions being identified through formal modeling. For instance, consider Bertrand’s response to Cournot oligopoly — i.e., two firms can be sufficient to eliminate all profit from an industry if their behavior toward each other is sufficiently aggressive. Likewise, Akerlof shows that asymmetric information can be a boundary condition on the ability of markets to improve welfare. Were the formal models absolutely essential to achieving these insights about boundary conditions? Maybe not. But do the formal models help an awful lot in visualizing and explaining these boundary conditions? Certainly.

In the strategy field, a formal model by Luis Cabral & Miguel Villas-Boas (2005 Management Science) demonstrates a boundary condition on the idea that publicly-available synergies would increase the profit of firms in an industry, by showing that sometimes they can actually decrease firms’ profits. My own forthcoming SMJ paper, coauthored with Jens Schmidt and Thomas Keil, takes this boundary condition one step further by showing that even private, proprietary synergies can sometimes backfire and reduce profit. I cannot speak for Luis, Miguel, or my coauthors Jens and Thomas, but I know that I certainly could neither have envisioned nor anticipated this boundary condition without the tool of formal modeling.

Anyway, that’s my defense of formal modeling as a research tool.

For myself, I work really hard to make my formal modeling papers accessible to earthlings. I try to write them in a way that any reasonably intelligent MBA student could read them, skip over the math, and still get all of the main points. Unfortunately, most game theorists in the economics discipline and even some of the modelers in strategy do not share my philosophy about this. In my humble opinion, they do a disservice to themselves, their field, and their citation counts by neglecting this duty.

Thanks,
Rich
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10. ochatain | 16 October 2014 at 10:17 am

Hi Peter,

Thanks for your interesting post and also for sharing how you reacted to the style of Tirole’s textbook. My own reaction was, as you may guess, quite the opposite, although there is no denying this text is demanding. But this makes me realize that differences in background play a large role in shaping taste and their role should not be taken for granted.

One other thing: there is an entire chapter on regulatory capture in the Laffont-Tirole book, complete with references to the Chicago and public choice literatures.So it is a bit unfair to imply that Tirole, and by extension this entire stream of research, is naive about these matters. It is clearly not the case.

Thanks,

Olivier
11. Peter Klein | 16 October 2014 at 10:37 am

Olivier, thanks, these are good points. You are right about the Laffont-Tirole text, which includes a nice discussion of political economy. I should have been more precise that I had Tirole 1988 in mind. I was also thinking about books like Ken Train’s Optimal Regulation, which I was also exposed to at Berkeley and which totally glosses over these kinds of issues. My concern is that away from the research frontier, the Tirole style of analysis has tended to downplay public choice concerns, but I may be overstating the case.
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13. ochatain | 17 October 2014 at 7:23 am

Peter, it’s fair to say that issues of regulatory capture are not their main concern. I remember taking a contract theory class in a full fledged Laffont style, where capture was indeed mentioned as an aside but considered an advanced subject. Interestingly, my teacher at the time – who was absolutely outstanding – went on a few years later to take a position in the French antitrust agency.
14. stevepostrel | 17 October 2014 at 9:31 pm

Tirole’s 1988 book’s biggest problem to me is organizational structure. The arrangement of topics just doesn’t seem that natural and certain ideas are presented in odd contexts. So the reader can neither easily follow it in order nor readily dip into it as a reference via the index. But there are lots of little exercises and examples, which is a plus.
15. beckmill | 20 October 2014 at 3:39 pm

Tyler Cowen has a nice post about Tirole here. Lots of great links in it.
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