Home > Uncategorized > Richard Thaler gets the 2017 ‘Nobel prize’

Richard Thaler gets the 2017 ‘Nobel prize’

from Lars Syll

150511_tbq_thaler_portraitToday The Royal Swedish Academy of Sciences announced that it  has decided to award The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for 2017 to Richard Thaler.

A good choice for once!

To yours truly Thaler’s main contribution has been to show that one of the main building blocks of modern mainstream economics — expected utility theory — is fundamentally wrong.

If a friend of yours offered you a gamble on the toss of a coin where you could lose €100 or win €200, would you accept it? Probably not. But if you were offered to make one hundred such bets, you would probably be willing to accept it, since most of us see that the aggregated gamble of one hundred 50–50 lose €100/gain €200 bets has an expected return of €5000 (and making our probabilistic calculations we find out that there is only a 0.04% risk of losing any money).

Unfortunately – at least if you want to adhere to the standard neoclassical expected utility maximization theory – you are then considered irrational! A mainstream neoclassical utility maximizer that rejects the single gamble should also reject the aggregate offer.

In Matthew Rabin’s and Richard Thaler’s modern classic Risk Aversion it is forcefully and convincingly shown that expected utility theory does not explain actual behaviour and choices. 

What is still surprising, however, is that although the expected utility theory is obviously descriptively inadequate, colleagues and microeconomics textbook writers all over the world gladly continue to use it, as though its deficiencies were unknown or unheard of.

That cannot be the right attitude when facing scientific anomalies. When models are plainly wrong, you’d better replace them! Or as Rabin and Thaler have it:

It is time for economists to recognize that expected utility is an ex-hypothesis, so that we can concentrate our energies on the important task of developing better descriptive models of choice under uncertainty.

What many of the works of Thaler show is that expected utility theory is an ‘ex-hypothesis.’ Or as Monty Python has it:

ex-ParrotThis parrot is no more! He has ceased to be! ‘E’s expired and gone to meet ‘is maker! ‘E’s a stiff! Bereft of life, ‘e rests in peace! If you hadn’t nailed ‘im to the perch ‘e’d be pushing up the daisies! ‘Is metabolic processes are now ‘istory! ‘E’s off the twig! ‘E’s kicked the bucket, ‘e’s shuffled off ‘is mortal coil, run down the curtain and joined the bleedin’ choir invisible!! THIS IS AN EX-PARROT!!

An ex-parrot that transmogrifies truth shouldn’t just be marginally mended. It should be replaced!

  1. paul davidson
    October 10, 2017 at 11:26 pm

    The trouble with Thaler and behaviort theory is his theory assumes that in the real world there is information regarding the future outcome of any decision made today [this minute] so that rational choice will allow one to maximize utility, income, etc.

    But Time is a device that prevents everything from happening at onec and the payoff of any decision will occur minutes, days ,months, years in the future. Thus one’s decision today canont be rationalized to show the future outcome exceeds the current costs as long as the future is UNCERTAIN [non reli=ably predictable].

    post Keynesian theory as I have written — shows Keynes was the first behavioralist since he argued investment decisions were made based on “animal spirits’ rather than calculating known future profits vs. current costs! Thaler merely assumes decision makers are human and therefore irrational. While PosT Keynesian theory assumes because the future is UNCERTAIN there is no information available at the moment if decision to make the future payout of any decision knowable and therefore maing choice between “knowable” outcomes rational!

    THe obvious example is why are ALL market transactIons organized via money contracts and not real contracts as used by rational decision makers in mainstream theory. The Keynes- Post Keynesian answer is that by the use of spot and forward ,money contracts decision makers try to make legally certain the cash inflow and outflow of their bank accounts and therefore rmaintain liquidity.

    All of this explained in one chapter of my new book WHO’S AFRAID OF JOHN MAYNARD KEYNES? {Ps;grave/Macmillan., October 2017]

  2. October 11, 2017 at 11:51 am

    While I largely agree with Paul Davidson, the work of Thaler and others does not assume such information always exists, but shows that even if and when such information does exist decision makers still do not habitually behave in the manner predicted of them by expected utility theory.

  3. October 11, 2017 at 12:24 pm

    Lars, how I laughed at the suitability of your Monty Python quote to the state of economics, and how I agree with your conclusion: even its wording. (Transmogrifying a pussy into a moggy)!

    Paul, I’m as appreciative of Keynes as you are, but he was “thinking outside the box”, so in my opinion it is more important to catch the drift of his thought than to hang on his every word. I admire him as one of the very few economists who, not only as a writer but as a statesman who worked himself to death promoting necessary change, actually improved life for my generation. Surely his phrase “animal spirits” referred to his observation of behaviour in the stock markets, where other people’s goods and credit-worthiness are being gambled with? What you say about Time doesn’t apply to them, but it does to real investment decisions, where intuitive feeling for the TYPE of thing which works in particular TYPES of real market involves a different TYPE of rationality: one drawing more often on tacit experimental observation and calculation than on formalised book knowledge.

    How to transmogrify the moggy into a pussy? Looking at the terms you use above, Paul, I would suggest that decisions do not choose sets of outcomes but set aims, which if there is only money reduces to maximising acquisition of it. In real life, where the detailed aims are numerous and conflicting, nevertheless there is a different TYPE of aim to which the detailed aims stand as means to ends: the aim of survival of you and yours, whereof the means develops from milk for babies to safe homes for adults to offices, workshops and infrastructure for developers of better ways and means. The moggy we now have is the quantitative monetary model. The pussy we need is a real economy, wherein behaviour not only takes time but is continuous, which it can only be insofar as we enable nature to recycle what we harvest from the produce of solar power cycles.

    Because generic ways of preventing and dealing with uncertainty have already been discovered (if outside economics), we don’t have to live with conflicts of aims: we agree to drive on one side or the other, give way to minor traffic at roundabouts, and steer/speed up/divert using timely observations of present, past and approaching errors. Governments need to understand this and teach it by means of legal conventions, instead of legalising monetary fraud, ill-gotten property and arms profiteering. We need to tell them so.

  4. October 11, 2017 at 12:29 pm

    paul d–my view is Thaler is simply renaming what you call uncertainty as irrationality. Veblen may have been first behaviorist.

  5. robert locke
    October 11, 2017 at 1:59 pm

    When I was visiting the British Academy of Management’s library in he 1970’s I noticed a barrel of books to be discarded, in which I found randomly (how is that for research method) a book by Stafford Beer on Operational Research. I took it, read it, and pushing on further looked at the Journal of Operational Research, to follow the trail of thought in it of operational research. The result was two chapters in my book, Management and Higher Education Since 1940, Cambridge University Press, 1989, The New Paradigm, the use of science in management decision making (math modeling, decision theory) and the New Paradigm
    Revisited, growing doubts about the new paradigm. I wrote (p.30) “The doubts were not just expressed by knowledgeable outsiders. They crept up among those whose very occupational raison d’etre arose from the creation of the new paradigm in management studies. As the 1960s turned into the 1970s, the opposition within OR was neither exceptional, nor inconsequential.. The decade the late 1970s was a culmination of a decade of ever-increasing and deepening criticism at the very center of the new paradigm.” Ch 2, 30-55.

    My book, published I989, was researched in the 1980s, looking back at preceding decades. It was not a case of critiques persisting but diminishing as the new paradigm established itself, but of the critiques increasing to stop the paradigm from establishing itself.

    Here we are 28 years after I revisited the new paradigm, still rehashing the same stuff. I think OR people were rational scientists since they were involved in the critique themselves, but I cannot understand mainline economists as other than enemies of the people.

    • October 11, 2017 at 5:26 pm

      Robert, I too have Stafford Beer’s book, though my mentor was Patrick Rivett, who found the organiser of a successful rescue operation was the telephone operator: the only person with all the latest information. What I don’t see is the connection between OR and economics, unless you are saying the main criticisms of OR came from NIMBY economists. So we agree on mainline economists. What do you see as the alternative?

      I’ve just been looking up evolutionary economist Jason Potts, whose views are comparable but not identical to mine; we met in Brisbane in 2000. He offered me a copy of his impending book (it won that year’s Schumpeter Prize), which didn’t materialised and at £84 I haven’t yet bought, though it seems there are now cut-price offers. In any case, I turned up this abstract by him, which may be helpful on understanding where to look for paradigm change:

      “One interpretation of complexity science is that it distinguishes two types of science—an equilibrium science of forces, as begun by Newton, and a complexity science of rules, as exemplified by Wolfram (2002). If you accept that argument, then there are also two types of economics—an equilibrium economics in which forces move resources around the economy, and a complexity economics in which generic rules structure knowledge in an economy (Dopfer & Potts, 2008). However, this also implies two types of economic policy—a policy framework based on reallocating resources and a policy framework based on redesigning rules (Colander & Kupers, 2014). Modern economic policy generally engages in both, but we argue that this reflects the idea that modern economic policy has not caught up with complexity science. We illustrate how this difference plays out in the particular domain of innovation policy”.

      Rules communicate information, not force, and generic rules (as in my comment above) amount to conventions applying to all we do, not to specifics (where rules can be avoided by slight modifications).

      • robert locke
        October 11, 2017 at 7:28 pm

        Dave, as an historian I have not been concerned with the epistemology of OR and economics, but in the association of the people involved in both subjects and in the institutions in which they worked that brought the two together. Although British Operational Research during World War Two set the example for the Americans, and British OR teams were especially active in the new nationalized industries postwar, English educational tradition hobbled the development of OR studies in higher education because of a missing utilitarianism. The first university-based course, inspired by Sir Charles Goodeve of the Operational Research Club and Professor Egon Pearson, the eminent statistician, came only in 1949, and then in typical English academic fashion as a one-time, three-month evening course, not as a regular university program. A British university did not offer another short-term OR course for five years. Nor could business schools have perked up an interest in OR studies in Britain for the simple reason that, until the late 1960s, Britain had no business schools, with MBA and PhD research programs, where such a transformation could have occurred. People studying economics in the UK could not have learned much about OR methods through mingling with OR in academia.

        On the other hand, US academic institutions, always interested in utilitarian education, got involved. The Case Institute of Technology in Cleveland started the first operations research (OR) unit at the urging of industry (with financial support from the Chesapeake and Ohio Railroad Co.) and the US Air Force (which funded research on airplane design). The institute organized a national conference in November 1951 on OR in business and industry attended by 150 people from all over the country. Several other leading American universities established OR programs (Carnegie, University of California, Los Angeles (UCLA), Ohio State, Chicago, Johns Hopkins, Cornell, University of Pennsylvania, etc.). Among these, Ohio State and Case engaged actively in industrial consultancy from the mid 1950s on. These universities also worked with private consulting firms, some of which were large. Booz, Allen, and Hamilton, for instance, had fifty-two offices, which counseled clients on OR. Arthur D. Little got into OR early on. Generally, if private industry and consultants evinced any interest in OR, the Department of Defense readily provided funds to push the new techniques. Not surprisingly, since mathematics and scientific method prevailed in them, departments of industrial administration, especially in engineering institutions, pioneered the work. The OR teams at Case and Massachusetts Institute of Technology (MIT) were good examples. Another was the Graduate School of Industrial Administration (GSIA) established at the Carnegie Institute of Technology in 1949. GSIA promoted the new paradigm and “had an impact out of all proportion to its seniority” . It required entering students to demonstrate a mathematical prerequisite in calculus and it employed “the analytic, normative, mathematical, and scientific mode of instruction”. Researchers in these places, thinking the methods could and should be applied in marketing, finance, and other business disciplines, expanded beyond industrial administration.

        Most Importantly, the Rand Corporation working on OR problems for the US Air Force gave birth to George Dantzig’s linear programming algorithms in 1947. Postwar military planners and the economists who worked with them at Rand believed the new toolkit would transform neoclassical economics into a prescriptive science. At Rand in 1948, the economist Kenneth Arrow used the toolkit in his work on Rational Choice Theory. The neoclassical economists Joseph Dorfman, Paul Samuelson, and Robert Solow applied linear programming to their subject as well (in Linear Programming and Economic Analysis, 1958)

        There is also a close connection between OR education and finance education in business schools, whose modeling got us into so much trouble in the financial crisis. Stanley R. Pliska’s and J. Michael Harrison’s careers followed the path from operations research into social science. Both did PhDs in OR at Stanford University, Harrison in 1970, and Pliska in 1972, before moving into mathematical finance, Harrison at Stanford’s Graduate School of Business, and Pliska in the business school at the University of Illinois, Chicago Circle. Accordingly, their first job experiences and academic papers handled typical OR problems; only later did their interest shift to quantitative analysis of derivative markets in a landmark collaboration.

      • October 11, 2017 at 9:10 pm

        Robert, thanks for this. The UK picture feels familiar, the US picture reminded me of what I’d read in Mirowski, Machine Dreams p.174/5 (which entirely missed the scientific point of Shannon): Weaver’s “the mixed team approach of operations analysis”. (Mirowski seems to endorse this at p.182, albeit recognising the primacy of paymasters). This seems to me nearer your stakeholder management than over-mathematical
        specialisation, Robert. As an individual I found it was one of the few jobs where one could exercise general rather than specialised knowledge; I think the great but (these days) sadly neglected economist E F Schumacher would have agreed.

      • robert locke
        October 12, 2017 at 7:13 am

        A propos the difference in academic networking between economics and OR in the UK and the US. A famous English economist, (was it John Hicks) was hurryingly attempting to learn something about linear programing before a trip to the US where it had been imbibed by US economists, so that he (the English economist) would know what the Americans were talking about. Your mentor in a 1981 article in the j of op research, noted that 80% of OR people in the UK go through their entire career without publishing anything. Unimaginable in publish or perish OR academized US circles.

      • October 12, 2017 at 7:36 am

        From my own experience I suspect that the main reason for OR workers not publishing much in the UK was down to their being employees subject to military and commercial secrecy. But getting back to trying to be positive, what did you think of Jason Potts’s argument?

      • robert locke
        October 12, 2017 at 11:52 am

        Jason Potts I don’t know and at 84 pounds, this retiree will have to pass.

        It was J.R. Hicks, who published an article, “Linear Theory” in The Economic Journal, 71, 1961, that I cite in my 1989 book Management and Higher Education Since 1940, CUP p.150 with the comment that to do this article Hicks “went to America to find the economists who could explain Linear programing to him. He wrote H W Kuhn of Princeton, Kenneth Arrow, and George Dantzig of the Rand think tank. Hicks own education in mathematics had ended in 1923.”

        I must insist that we make a mistake to go back to Walrus and other neoclassical thinkers to learn about the physico-mathematization of economics. The analytical tools economists imbibed from OR were a much great transformative influence on the discipline.

      • October 12, 2017 at 10:41 pm

        Sorry If I’ve irritated. My thought had been Jason too might have been surprised at the price of his book! But I was referring to the abstract I quoted on Oct 11: 5.26 pm, not suggesting you should read or have read the book. I had hoped the distinction between forces and information I have been making in vain these last several years might have clicked coming more lucidly from someone else.

        I think I understand what you are saying about OR and economic mathematics. Is it that the type and extent of the mathematics changed?

      • robert locke
        October 13, 2017 at 6:29 am

        Dave, yes it is the math, Joseph Dorfman, Paul Samuelson, and Robert Solow in Linear Programming and Economic Analysis, 1958, include a section explaining the math of linear programing to economists, because they knew it would be new to them.

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