| Peter Klein |
Russ Coff has assembled an impressive list of syllabi and reading lists for PhD courses in strategy, innovation, research methods, and related subjects. Feel free to send him additional suggestions. Many useful references here for faculty and students teaching or taking these courses, and for anybody wishing to learn more about classic and contemporary literature in strategic management research.
| Peter Klein |
Joe Gillis: You’re Norma Desmond. You used to be in silent pictures. You used to be big.
Norma Desmond: I *am* big. It’s the *pictures* that got small.
– Sunset Boulevard (1950)
John List gave the keynote address at this weekend’s Southern Economic Association annual meeting. List is a pioneer in the use by economists of field experiments or randomized controlled trials, and his talk summarized some of his recent work and offered some general reflections on the field. It was a good talk, lively and engaging, and the crowd gave him a very enthusiastic response.
List opened and closed his talk with a well-known quote from Paul Samuelson’s textbook (e.g., this version from the 1985 edition, coauthored with William Nordhaus): “Economists . . . cannot perform the controlled experiments of chemists and biologists because they cannot easily control other important factors.” While professing appropriate respect for the achievements of Samuelson and Nordhaus, List shared the quote mainly to ridicule it. The rise of behavioral and experimental economics over the last few decades — in particular, the recent literature on field experiments or RCTs — shows that economists can and do perform experiments. Moreover, List argues, field experiments are even better than using laboratories, or conventional econometric methods with instrumental variables, propensity score matching, differences-in-differences, etc., because random assignment can do the identification. With a large enough sample, and careful experimental design, the researcher can identify causal relationships by comparing the effects of various interventions on treatment and control groups in the field, in a natural setting, not an artificial or simulated one.
While I enjoyed List’s talk, I became increasingly frustrated as it progressed. I found myself — I can’t believe I’m about to write these words — defending Samuelson and Nordhaus. Of course, not only neoclassical economists, but nearly all economists, especially the Austrians, have denied explicitly that economics is an experimental science. “History can neither prove nor disprove any general statement in the manner in which the natural sciences accept or reject a hypothesis on the ground of laboratory experiments,” writes Mises (Human Action, p. 31). “Neither experimental verification nor experimental falsification of a general proposition are possible in this field.” The reason, Mises argues, is that history consists of non-repeatable events. “There are in [the social sciences] no such things as experimentally established facts. All experience in this field is, as must be repeated again and again, historical experience, that is, experience of complex phenomena” (Epistemological Problems of Economics, p. 69). To trace out relationships among such complex phenomena requires deductive theory.
Does experimental economics disprove this contention? Not really. List summarized two strands of his own work. The first deals with school achievement. List and his colleagues have partnered with a suburban Chicago school district to perform a series of randomized controlled trials on teacher and student performance. In one set of experiments, teachers were given various monetary incentives if their students improved their scores on standardized tests. The experiments revealed strong evidence for loss aversion: offering teachers year-end cash bonuses if their student improved had little effect on test scores, but giving teacher cash up front, and making them return it at the end of the year if their students did not improve, had a huge effect. Likewise, giving students $20 before a test, with the understanding that they have to give the money back if they don’t do well, leads to large improvements in test scores. Another set of randomized trials showed that responses to charitable fundraising letters are strongly impacted by the structure of the “ask.”
To be sure, this is interesting stuff, and school achievement and fundraising effectiveness are important social problems. But I found myself asking, again and again, where’s the economics? The proposed mechanisms involve a little psychology, and some basic economic intuition along the lines of “people respond to incentives.” But that’s about it. I couldn’t see anything in these design and execution of these experiments that would require a PhD in economics, or sociology, or psychology, or even a basic college economics course. From the perspective of economic theory, the problems seem pretty trivial. I suspect that Samuelson and Nordhaus had in mind the “big questions” of economics and social science: Is capitalism more efficient than socialism? What causes business cycles? Is there a tradeoff between inflation and unemployment? What is the case for free trade? Should we go back to the gold standard? Why do nations to go war? It’s not clear to me how field experiments can shed light on these kinds of problems. Sure, we can use randomized controlled trials to find out why some people prefer red to blue, or what affects their self-reported happiness, or why we eat junk food instead of vegetables. But do you really need to invest 5-7 years getting a PhD in economics to do this sort of work? Is this the most valuable use of the best and brightest in the field?
My guess is that Samuelson and Nordhaus would reply to List: “We’re are big. It’s the economics that got small.”
See also: Identification versus Importance
| 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 Klein |
A couple of recent NBER papers of interest to O&Mers, one from Doug Irwin, another from Luis Garicano and Esteban Rossi-Hansberg:
Adam Smith’s “Tolerable Administration of Justice” and the Wealth of Nations
Douglas A. Irwin
NBER Working Paper No. 20636, October 2014
In the Wealth of Nations, Adam Smith argues that a country’s national income depends on its labor productivity, which in turn hinges on the division of labor. But why are some countries able to take advantage of the division of labor and become rich, while others fail to do so and remain poor? Smith’s answer, in an important but neglected theme of his work, is the security of property rights that enable individuals to “secure the fruits of their own labor” and allow the division of labor to occur. Countries that can establish a “tolerable administration of justice” to secure property rights and allow investment and exchange to take place will see economic progress take place. Smith’s emphasis on a country’s “institutions” in determining its relative income has been supported by recent empirical work on economic development.
Knowledge-based Hierarchies: Using Organizations to Understand the Economy
Luis Garicano, Esteban Rossi-Hansberg
NBER Working Paper No. 20607, October 2014
We argue that incorporating the decision of how to organize the acquisition, use, and communication of knowledge into economic models is essential to understand a wide variety of economic phenomena. We survey the literature that has used knowledge-based hierarchies to study issues like the evolution of wage inequality, the growth and productivity of firms, economic development, the gains from international trade, as well as offshoring and the formation of international production teams, among many others. We also review the nascent empirical literature that has, so far, confirmed the importance of organizational decisions and many of its more salient implications.
Update: See also Irwin’s article in Monday’s WSJ: “The Ultimate Global Antipoverty Program.”
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.)