Posts filed under ‘Myths and Realities’
| Peter Klein |
Justin Fox reports on a recent high-powered behavioral economics conference featuring Raj Chetty, David Laibson, Antoinette Schoar, Maya Shankar, and other important contributors to this growing research stream. But he refers also to the “Summers critique,” the idea that key findings in behavioral economics research sound like recycled wisdom from business practitioners.
Summers [in 2012] told a story about a college acquaintance who as a cruel prank signed up another classmate for 60 different subscriptions of the Book-of-the-Month-Club ilk. The way these clubs worked is that once you signed up, you got a book in the mail every month and were charged for it unless you (a) sent the book back within a certain period of time or (b) went through the hassle of extricating yourself from the club altogether. Customers had to opt out in order to not keep buying books, so they bought more books than they otherwise would have. Book marketers, Summers said, had figured out the power of defaults long before economists had.
More generally, Fox asks, “Have behavioral economists really discovered anything new, or have they simply replaced some wrong-headed notions of post-World War II economics with insights that people in business have understood for decades and maybe even centuries?”
I took exactly the Summers line in a 2010 post, observing that behavioral economics “often seems to restate common, obvious, well-known ideas as if they are really novel insights (e.g., that preferences aren’t stable and predictable over time). More novel propositions are questionable at best.” I used a Dan Ariely column on compensation policy as an example:
He claims as a unique insight of behavioral economics that when people are evaluated according to quantitative measures of performance, they tend to focus on the measures, not the underlying behavior being measured. Well, duh. This is pretty much a staple of introductory lectures on agency theory (and features prominently in Steve Kerr’s classic 1975 article). Ariely goes on to suggest that CEOs should be rewarded not on the basis of a single measure of performance, but multiple measures. Double-duh. Holmström (1979) called this the “informativeness principle” and it’s in all the standard textbooks on contract design and compensation structure (e.g., Milgrom and Roberts, Brickley et al., etc.) (Of course, agency theory also recognizes that gathering information is costly, and that additional metrics are valuable, on the margin, only if the benefits exceed the costs, a point unmentioned by Ariely.)
Maybe Larry and I should hang out.
| Peter Klein |
Technology in his view is not the mechanical “application of science” to production; it is a field of knowledge by itself, quite different in its incentives, its modes of transmission, and its culture. It is affected by science, but in turn provides “pure research” with its instruments and much of its agenda. In many cases, [Rosenberg] noted, scientists were confronted by the fact that things they had previously declared to be impossible were actually carried out by engineers and mechanics and had to admit somewhat sheepishly that were possible after all.
The same issue is raised in Margaret Jacob’s book The First Knowledge Economy: Human Capital and the European Economy, 1750-1850 (Cambridge University Press, 2014), which “argues persuasively for the critical importance of knowledge in Europe’s economic transformation during the period from 1750 to 1850, first in Britain and then in selected parts of northern and western Europe.” In other words, as noted by Erik Hornung:
She especially focusses on the marriage between theoretical sciences and applied mechanical knowledge which helped creating many technological innovations during the Industrial Revolution. She, thus, aims at rectifying the prevalent hypothesis that technological progress resulted from tinkering of skilled but science-ignorant engineers. An impressive set of new archival sources supports her argument that English engineers were, indeed, well aware of and heavily influenced by recent advances in natural sciences.
| Peter Klein |
I just wanted to bring your attention to a PDW I am organizing for the upcoming AoM meeting, where we will engage in frank and in-depth discussions about the problems and merits of the popular notion of “entrepreneurial opportunity”. We have been fortunate to gather a collection of very strong scholars and independent thinkers as presenters and discussants in this PDW: Richard J. Arend, Dimo Dimov, Denis Grégoire, Peter G. Klein, Moren Lévesque, Saras Sarasvathy, and Matthew Wood. . This illustrious group of colleagues will make sure the deliberations do not focus on a “beauty contest” between “discovery” and “creation” views but instead reach beyond limitations of both.
I encourage you to join us for this session, and to make absolutely sure I won’t send you to the wrong place at the right time I have copied the details straight from the online program:
Title: Entrepreneurial Opportunity: The Oxygen or Phlogiston of Entrepreneurship Research? (session #365)
Date & Time: Saturday, August 08, 2015, 12:30:00 PM – 3:00:00 PM
Hotel & Room: Vancouver Convention Centre, Room 012
Further elaboration follows below. Heartily welcome!
| Peter Klein |
Jeffrey Selingo raises an important point about the distinction between “public” and “private” universities, but I disagree with his analysis and recommendation. Selingo points out that the elite private universities have huge endowments and land holdings, the income from which, because of the universities’ nonprofit status, is untaxed. He calls this an implicit subsidy, worth billions of dollars according to this study. “Such benefits account for $41,000 in hidden taxpayer subsidies per student annually, on average, at the top 10 wealthiest private universities. That’s more than three times the direct appropriations public universities in the same states as those schools get.”
I agree that the distinction between public and private universities is blurry, but not for the reasons Selingo gives. First, a tax break is not a “subsidy.” Second, there are many ways to measure the “private-ness” of an organization — not only budget, but also ownership and governance. In terms of governance, most US public universities look like crony capitalists. The University of Missouri’s Board of Curators consists of a handful of powerful local operatives, all political appointees (and all but one lawyers) and friends of the current and previous governors. At some levels, there is faculty governance, as there is at nominally private universities. In terms of budget, we don’t need to invent hidden subsidies, we need only look at the explicit ones. If we include federal research funding, the top private universities get a much larger share of their total operating budgets from government sources than do the mid-tier public research universities. (I recently read that Johns Hopkins gets 90% of its research budget from federal agencies, mostly NIH and NSF.) And of course federal student aid is relevant too.
So, what does it mean to be a “private” university?
| Peter Klein |
Two of my favorite writers on the economic organization of science, Terence Kealey and Martin Ricketts, have produced a recent paper on science as a “contribution good.” A contribution good is like a club good in that it is non-rivalrous but at least partly excludable. Here, the excludability is soft and tacit, resulting not from fixed barriers like membership fees, but from the inherent cognitive difficulty in processing the information. To join the club, one must be able to understand the science. And, as with Mancur Olson’s famous model, consumption is tied to contribution — to make full use of the science, the user must first master the underlying material, which typically involves becoming a scientist, and hence contributing to the science itself.
Kealey and Ricketts provide a formal model of contribution goods and describe some conditions favoring their production. In their approach, the key issue isn’t free-riding, but critical mass (what they call the “visible college,” as distinguished from additional contributions from the “invisible college”).
The paper is in the July 2014 issue of Research Policy and appears to be open-access, at least for the moment.
Modelling science as a contribution good
Terence Kealey, Martin Ricketts
The non-rivalness of scientific knowledge has traditionally underpinned its status as a public good. In contrast we model science as a contribution game in which spillovers differentially benefit contributors over non-contributors. This turns the game of science from a prisoner’s dilemma into a game of ‘pure coordination’, and from a ‘public good’ into a ‘contribution good’. It redirects attention from the ‘free riding’ problem to the ‘critical mass’ problem. The ‘contribution good’ specification suggests several areas for further research in the new economics of science and provides a modified analytical framework for approaching public policy.
| Peter Klein |
The old Keynesian idea that war is good for the economy is not taken seriously by anyone outside the New York Times op-ed page. But much of the discussion still focuses on macroeconomic effects (on aggregate demand, labor-force mobilization, etc.). The more important effects, as we’ve often discussed on these pages, are microeconomic — namely, resources are reallocated from higher-valued, civilian and commercial uses, to lower-valued, military and governmental uses. There are huge distortions to capital, labor, and product markets, and even technological innovation — often seen as a benefit of wars, hot and cold — is hampered.
A new NBER paper by Zorina Khan looks carefully at the microeconomic effects of the US Civil War and finds substantial resource misallocation. Perhaps the most significant finding relates to entrepreneurial opportunity — individuals who would otherwise create significant economic value through establishing and running firms, developing new products and services, and otherwise improving the quality of life are instead motivated to pursue government military contracts (a point emphasized in the materials linked above). Here is the abstract (I don’t see an ungated version, but please share in the comments if you find one):
The Impact of War on Resource Allocation: ‘Creative Destruction’ and the American Civil War
B. Zorina Khan
NBER Working Paper No. 20944, February 2015
What is the effect of wars on industrialization, technology and commercial activity? In economic terms, such events as wars comprise a large exogenous shock to labor and capital markets, aggregate demand, the distribution of expenditures, and the rate and direction of technological innovation. In addition, if private individuals are extremely responsive to changes in incentives, wars can effect substantial changes in the allocation of resources, even within a decentralized structure with little federal control and a low rate of labor participation in the military. This paper examines war-time resource reallocation in terms of occupation, geographical mobility, and the commercialization of inventions during the American Civil War. The empirical evidence shows the war resulted in a significant temporary misallocation of resources, by reducing geographical mobility, and by creating incentives for individuals with high opportunity cost to switch into the market for military technologies, while decreasing financial returns to inventors. However, the end of armed conflict led to a rapid period of catching up, suggesting that the war did not lead to a permanent misallocation of inputs, and did not long inhibit the capacity for future technological progress.
| Peter Klein |
We’ve addressed the widely held, but largely mistaken, view of creative artists and entrepreneurs as auteurs, isolated and misunderstood, fighting the establishment and bucking the conventional wisdom. In the more typical case, the creative genius is part of a collaborative team and takes full advantage of the division of labor. After all, is our ability to cooperate through voluntary exchange, in line with comparative advantage, that distinguishes us from the animals.
Christian Caryl’s New Yorker review of The Imitation Game makes a similar point about Alan Turing. The film’s portrayal of Turing (played by Benedict Cumberbatch) “conforms to the familiar stereotype of the otherworldly nerd: he’s the kind of guy who doesn’t even understand an invitation to lunch. This places him at odds not only with the other codebreakers in his unit, but also, equally predictably, positions him as a natural rebel.” In fact, Turing was funny and could be quite charming, and got along well with his colleagues and supervisors.
As Caryl points out, these distortions
point to a much broader and deeply regrettable pattern. [Director] Tyldum and [writer] Moore are determined to suggest maximum dramatic tension between their tragic outsider and a blinkered society. (“You will never understand the importance of what I am creating here,” [Turing] wails when Denniston’s minions try to destroy his machine.) But this not only fatally miscasts Turing as a character—it also completely destroys any coherent telling of what he and his colleagues were trying to do.
In reality, Turing was an entirely willing participant in a collective enterprise that featured a host of other outstanding intellects who happily coexisted to extraordinary effect. The actual Denniston, for example, was an experienced cryptanalyst and was among those who, in 1939, debriefed the three Polish experts who had already spent years figuring out how to attack the Enigma, the state-of-the-art cipher machine the German military used for virtually all of their communications. It was their work that provided the template for the machines Turing would later create to revolutionize the British signals intelligence effort. So Turing and his colleagues were encouraged in their work by a military leadership that actually had a pretty sound understanding of cryptological principles and operational security. . . .
The movie version, in short, represents a bizarre departure from the historical record. In fact, Bletchley Park—and not only Turing’s legendary Hut 8—was doing productive work from the very beginning of the war. Within a few years its motley assortment of codebreakers, linguists, stenographers, and communications experts were operating on a near-industrial scale. By the end of the war there were some 9,000 people working on the project, processing thousands of intercepts per day.
The rebel outsider makes for good storytelling, but in most human endeavors, including science, art, and entrepreneurship, it is well-organized groups, not auteurs, who make the biggest breakthroughs.