Posts filed under ‘Myths and Realities’
| Peter Klein |
Via Michael Strong, a thoughtful review and critique of Western-style economic development programs and their focus on one-size-fits-all, “big idea” approaches. Writing in the New Republic, Michael Hobbs takes on not only Bono and Jeff Sachs and USAID and the usual suspects, but even the randomized-controlled-trials crowd, or “randomistas,” like Duflo and Banerjee. Instead of searching for the big idea, thinking that “once we identify the correct one, we can simply unfurl it on the entire developing world like a picnic blanket,” we should support local, incremental, experimental, attempts to improve social and economic well being — a Hayekian bottom-up approach.
We all understand that every ecosystem, each forest floor or coral reef, is the result of millions of interactions between its constituent parts, a balance of all the aggregated adaptations of plants and animals to their climate and each other. Adding a non-native species, or removing one that has always been there, changes these relationships in ways that are too intertwined and complicated to predict. . . .
[I]nternational development is just such an invasive species. Why Dertu doesn’t have a vaccination clinic, why Kenyan schoolkids can’t read, it’s a combination of culture, politics, history, laws, infrastructure, individuals—all of a society’s component parts, their harmony and their discord, working as one organism. Introducing something foreign into that system—millions in donor cash, dozens of trained personnel and equipment, U.N. Land Rovers—causes it to adapt in ways you can’t predict.
| Peter Klein |
In the opportunity-discovery perspective, profits result from the discovery and exploitation of disequilibrium “gaps” in the market. To earn profits an entrepreneur needs superior foresight or perception, but not risk capital or other productive assets. Capital is freely available from capitalists, who supply funds as requested by entrepreneurs but otherwise play a relatively minor, passive role. Residual decision and control rights are second-order phenomena, because the essence of entrepreneurship is alertness, not investing resources under uncertainty.
By contrast, the judgment-based view places capital, ownership, and uncertainty front and center. The essence of entrepreneurship is not ideation or imagination or creativity, but the constant combining and recombining of productive assets under uncertainty, in pursuit of profits. The entrepreneur is thus also a capitalist, and the capitalist is an entrepreneur. We can even imagine the alert individual — the entrepreneur of discovery theory — as a sort of consultant, bringing ideas to the entrepreneur-capitalist, who decides whether or not to act.
A scene from Fargo nicely illustrates the distinction. Protagonist Jerry Lundegaard thinks he’s found (“discovered”) a sure-fire profit opportunity; he just needs capital, which he hopes to get from his wealthy father-in-law Wade. Jerry sees himself as running the show and earning the profits. Wade, however, has other ideas — he thinks he’s making the investment and, if it pays off, pocketing the profits, paying Jerry a finder’s fee for bringing him the idea.
So, I ask you, who is the entrepreneur, Jerry or Wade?
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 |
That’s the conclusion of a new NBER paper by Andy Young, Matthew Higgins, Don Lacombe, and Briana Sell, “The Direct and Indirect Effects of Small Business Administration Lending on Growth: Evidence from U.S. County-Level Data” (ungated version here). “We find evidence that a county’s SBA lending per capita is associated with direct negative effects on its income growth. We also find evidence of indirect negative effects on the growth rates of neighboring counties. Overall, a 10% increase in SBA loans per capita is associated with a cumulative decrease in income growth rates of about 2%.” As the authors point out, SBA loans represent funds that also have alternative uses, and SBA-sponsored clients may not be the most worthy recipients (in terms of generating economic growth).
The results are largely robust and, perhaps more importantly, we never find any evidence of positive growth effects associated with SBA lending. Even when the estimated effects are statistically insignificant, the point estimates are always negative. Our findings suggest that SBA lending to small businesses comes at the cost of loans that would have otherwise been made to more profitable and/or innovative firms. Furthermore, SBA lending in a given county results in negative spillover effects on income growth in neighboring counties. Given the popularity of pro-small business policies, our findings should give reason for policymakers and their constituents to reevaluate their priors.
| 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 |
Here is a recent MIT Sloan Management Review piece by Peter and me, “Why Managers Still Matter.” We pick up on a number of themes of our 2012 book Organizing Entrepreneurial Judgment. A brief excerpt:
“Wikifying” the modern business has become a call to arms for some management scholars and pundits. As Tim Kastelle, a leading scholar on innovation management at the University of Queensland Business School in Australia, wrote: “It’s time to start reimagining management. Making everyone a chief is a good place to start.”
Companies, some of which operate in very traditional market sectors, have been crowing for years about their systems for “managing without managers” and how market forces and well-designed incentives can help decentralize management and motivate employees to take the initiative. . . .
From our perspective, the view that executive authority is increasingly passé is wrong. Indeed, we have found that it is essential in situations where (1) decisions are time-sensitive; (2) key knowledge is concentrated within the management team; and (3) there is need for internal coordination. . . . Such conditions are hallmarks of our networked, knowledge-intensive and hypercompetitive economy.