Posts filed under ‘Methods/Methodology/Theory of Science’
Peter invited me to reply to [Warren Miller's] 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. (more…)
| 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.)
| Peter Klein |
Here at O&M we have been somewhat skeptical of the behavioral social science literature. Sure, in laboratory experiments, people often behave in ways inconsistent with “rational” behavior (as defined by neoclassical economics). Yes, people seem to use various rules-of-thumb in making complex decisions. And yet, it’s not clear that the huge literature on such biases and heuristics tells us much we don’t already know.
An interesting essay by Steven Poole argues the behavioralists’ claims are overstated, mainly by relying on a narrow, superficial notion of rationality as the benchmark case. Contemporary psychology suggests that people interpret the questions posed in laboratory experiments in a nuanced, contextual manner in which their seemingly “irrational” answers are actually reasonable.
There are many other good reasons to give ‘wrong’ answers to questions that are designed to reveal cognitive biases. The cognitive psychologist Jonathan St B T Evans was one of the first to propose a ‘dual-process’ picture of reasoning in the 1980s, but he resists talk of ‘System 1’ and ‘System 2’ as though they are entirely discrete, and argues against the automatic inference from bias to irrationality. . . . In general, Evans concludes that a ‘strictly logical’ answer will be less ‘adaptive to everyday needs’ for most people in many such cases of deductive reasoning. ‘A related finding,’ he continues, ‘is that, even though people may be told to assume the premises of arguments are true, they are reluctant to draw conclusions if they personally do not believe the premises. In real life, of course, it makes perfect sense to base your reasoning only on information that you believe to be true.’ In any contest between what ‘makes perfect sense’ in normal life and what is defined as ‘rational’ by economists or logicians, you might think it rational, according to a more generous meaning of that term, to prefer the former. Evans concludes: ‘It is far from clear that such biases should be regarded as evidence of irrationality.’
Poole also argues strongly against the liberal-paternalist “nudges” advocated by Cass Sunstein and Richard Thaler, noting that “there is something troubling about the way in which [nudging] is able to marginalise political discussion.” Moreover, “nudge politics is at odds with public reason itself: its viability depends precisely on the public not overcoming their biases.” Poole concludes:
[T]here is less reason than many think to doubt humans’ ability to be reasonable. The dissenting critiques of the cognitive-bias literature argue that people are not, in fact, as individually irrational as the present cultural climate assumes. And proponents of debiasing argue that we can each become more rational with practice. But even if we each acted as irrationally as often as the most pessimistic picture implies, that would be no cause to flatten democratic deliberation into the weighted engineering of consumer choices, as nudge politics seeks to do. On the contrary, public reason is our best hope for survival. Even a reasoned argument to the effect that human rationality is fatally compromised is itself an exercise in rationality. Albeit rather a perverse, and – we might suppose – ultimately self-defeating one.
Worth a read. Even climate-change skepticism gets a nod, in a form consistent with some reflections here.
| Nicolai Foss |
As readers of this blog will know, probably to a nauseating extent, microfoundations have been central in much (macro) management theory over the last decade. Several articles, special issues, and conferences have been dedicated to microfoundations, most recently a Strategic Management Society Special Conference at the Copenhagen Business School. Some, uhm, highlyspirited exchanges have taken place (e.g., AoM 2013), with proponents of those foundations being accused of economics imperalism and whatnot, and critics of microfoundations receiving push-back for endorsing defunct Durkheimian collectivism (an obviously justified criticism). Here is recent civilized exchange on the subject between Professor Rodolphe Durand, HEC Paris, and myself. Complete with heavy Euro accents of different origins.
| Peter Klein |
Carl Menger’s methodology has been described as essentialist. Rather than building artificial models that mimic some attributes or outcomes of an economic process, Menger sought to understand the essential characteristics of phenomena like value, price, and exchange. As Menger explained to his contemporary Léon Walras, Menger and his colleagues “do not simply study quantitative relationships but also the nature [or essence] of economic phenomena.” Abstract models that miss these essential features — even if useful for prediction — do not give the insight needed to understand how economies work, what entrepreneurs do, how government intervention affects outcomes, and so on.
I was reminded of the contrast between Menger and Walras when reading about Henri Matisse and Pablo Picasso, the great twentieth-century pioneers of abstract art. Both painters sought to go beyond traditional, representational forms of visual art, but they tackled the problem in different ways. As Jack D. Flam writes in his 2003 book Matisse and Picasso: The Story of Their Rivalry and Friendship:
Picasso characterized the arbitrariness of representation in his Cubist paintings as resulting from his desire for “a greater plasticity.” Rendering an object as a square or a cube, he said, was not a negation, for “reality was no longer in the object. Reality was in the painting. When the Cubist painter said to himself, ‘I will paint a bowl,’ he set out to do it with the full realization that a bowl in a painting has nothing to do with a bowl in real life.” Matisse, too, was making a distinction between real things and painted things, and fully understood that the two could not be confused. But for Matisse, a painting should evoke the essence of the things it was representing, rather than substitute a completely new and different reality for them. In contract to Picasso’s monochromatic, geometric, and difficult-to-read pictures, Matisse’s paintings were brightly colored, based on organic rhythms, and clearly legible. For all their expressive distortions, they did not have to be “read” in terms of some special language or code.
Menger’s essentialism is concisely described in Larry White’s monograph The Methodology of the Austrian School Economists and treated more fully in Menger’s 1883 book Investigations Into the Method of the Social Sciences. For more on economics and art, see Paul Cantor’s insightful lecture series, “Commerce and Culture” (here and here).
[An earlier version of this post appeared at Circle Bastiat.]
| Nicolai Foss |
Here is a new paper by major Stanford finance scholar, Paul Pfleiderer on what he calls “chameleon models” and their misuse in finance and economics. Lots of catchy concepts, e.g., “theoretical cherry picking” and “bookshelf models,” and an fine critical discussion of Friedmanite instrumentalism. The essence of the paper is this:
Chameleons arise and are often nurtured by the following dynamic. First a bookshelf model is constructed that involves terms and elements that seem to have some relation to the real world and assumptions that are not so unrealistic that they would be dismissed out of hand. The intention of the author, let’s call him or her “Q,” in developing the model may to say something about the real world or the goal may simply be to explore the implications of making a certain set of assumptions. Once Q’s model and results
become known, references are made to it, with statements such as “Q shows that X.” This should be taken as short-hand way of saying “Q shows that under a certain set of assumptions it follows (deductively) that X,” but some people start taking X as a plausible statement about the real world. If someone skeptical about X challenges the assumptions made by Q, some will say that a model shouldn’t be judged by the realism of its assumptions, since all models have assumptions that are unrealistic. Another rejoinder made by those supporting X as something plausibly applying to the real world might be that the truth or falsity of X is an empirical matter and until the appropriate empirical tests or analyses have been conducted and have rejected X, X must be taken seriously. In other words, X is innocent until proven guilty. Now these statements may not be made in quite the stark manner that I have made them here, but the underlying notion still prevails that because there is a model for X, because questioning the assumptions behind X is not appropriate, and because the testable implications of the model supporting X have not been empirically rejected, we must take X seriously. Q’s model (with X as a result) becomes a chameleon that avoids the real world filters.
| Nicolai Foss |
After about a decade of methodological discussion (involving some preaching on both sides of the debate), the micro-foundations project in macro-management research is now beginning to take off in the “doing” dimension. Specifically, scholars are building micro-foundational theory and they are wrestling with the empirical challenges in the micro-foundations. The theoretical and empirical challenges largely derive from the inherent multi-level nature of the micro-foundations project. Theory-building cannot just be somehow moving, say, individual-level organizational behavior insights to the organizational level, but must be genuinely multi-level which raises tricky issues of aggregation and downward causation. Data sampling will necessarily have to take place at at least two levels. This is complicated and usually expensive. Access to good micro-level data is particularly troublesome (one of the advantages of living in a socialist country like Denmark is that the Big Nanny literally looks after her children: We have register data that is incredibly detailed regarding human capital dimensions (i.e., not just gender, age, education, etc., but also complete job history, school and university grades , criminal record, household income, history of medication, etc. — and this is for each and every employee in the DK economy)).
One of the areasis in which the micro-foundations project is being realized in the theoretical and empirical dimensions is what is increasingly often referred to as “strategic human capital.” This is an emerging field (it has its own interest group at the Strategic Management Society) that is quite overlapping with “strategic human resource management,” and which links strategic management, traditional SHR and HR, and human capital theory. The February special issue of Journal of Management, expertly edited by Patrick Wright, Russ Coff and Thomas Moliterno, three key drivers in the SHRM/SHC field, contains ten fine papers on SHC. The introductory essay by the editors nicely lays out the main challenges and issues. Many of the challenges are quite “low-practical” — e.g., people trained in strategy focus a lot on endogeneity, where HR and OB people focus a lot on construct validity issues that strategy folks care less about. Yet, such differences may be quite decisive–as the editors learned while handling the review process! The editors also deal with key issues, such as what are the important dimensions of human capital for the purposes of the SHM field, how can human capital be characterized at different analytical levels, and what are the antecedents and consequences of human capital. I look forward to sinking my teeth into the research articles in the coming week.