Investigaciones sobre integración y uso de las TIC

In interpreting the key findings of behavioural economics, it is important to note that many of those findings have been obtained in laboratory settings. This is especially so for some of the well-publicised results on seeming departures from the canonical model of rational decision-making (which I will refer to as the ‘rational actor’ model), including the findings about inconsistency in preferences and the

1 Regional Head, Asia-Pacific, CRA International. The views expressed in this paper are my own and do not necessarily reflect those of CRA International or of any of its clients. This paper was prepared for the Roundtable on Policy Implications of Behavioural Economics held by the Productivity Commission on 8 and 9 August 2007.

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roles of anchoring, framing and loss aversion in the decision-making process.²

There is a crucial proposition in the philosophy of science, usually referred to as the Duhem-Quine problem, which is highly relevant to the evaluation of those results.

That proposition states that any experiment jointly tests for a hypothesis and a set of background conditions associated with the experiment — for example, in terms of the measurement instruments used, the ambient conditions in the laboratory and so on.³ The inferences drawn from the experiment must therefore refer both to the hypothesis and the conditions under which it has been tested — for example, in saying that a material, when tested under particular circumstances, is found to act in particular ways, which may or may not be consistent with a wider theory.

The Duhem-Quine problem is important in economic experiments because the relevant hypotheses are inherently difficult to test. For example, assessing whether preferences over lotteries are transitive requires some way of eliciting truthful revelation of certainty equivalents, which cannot be done without an intervening technique, such as the widely-used Becker-de Groot-Marschak mechanism.⁴ As a result, good experiments in economics involve highly-stylised, controlled environments, in which the researcher tries to make formal and explicit such background factors as the selection and motivation of the subjects, the extent of communication between them, the information provided, the techniques used to elicit outcomes, the duration of the experiment and the manner in which the data were recorded. A robust result from such experiments is one which has been found to persist in the face of changes in these background conditions.⁵

The Duhem-Quine problem is one of several reasons why the claim that behavioural experiments ‘disprove’ conventional economics is an egregious instance of ‘naïve falsificationism’. But even putting that aside, there are significant implications for the attempted generalisation of experimental findings to the world outside the laboratory.

In particular, before generalising from the laboratory to the external world, it is crucial to ask in what relevant respects the carefully-controlled conditions that

2 A convenient summary is in Rubinstein (2006).

3 A concise statement of the Duhem-Quine problem and its implications for Popperian falsificationism can be found in Hausman (2003).

4 In a Becker-de Groot-Marschak elicitation, a subject is asked to state a reservation price for a lottery, which is then auctioned. If the auction price (which may be the result of a draw by the experimenters from a uniform distribution) exceeds the reservation price, then the subject is paid the reservation price; otherwise, the lottery is drawn and the subject receives the outcome of that draw. Faced with this procedure, truthful revelation is a dominant strategy for a rational decision maker.

5 See generally Guala 2005.

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characterise formal experiments differ from the inherently more complex environment of actual economies. This is a question experimenters have naturally given considerable thought to, with their focus being on two sets of factors.

The first are those factors that affect the salience of the situation to the subject — for example, in terms of the extent of what is at stake. It seems reasonable to suppose (and indeed is central to the ‘rational ignorance’ model of information acquisition) that a decision-maker considering a choice in which much is at stake will act differently from an experimental subject undertaking a laboratory exercise for a few dollars an hour.

The second relevant set of differences goes to the scope for learning, including through interaction with others taking similar decisions. Here, too, it seems reasonable to suppose that a decision-maker faced with say, a complex choice between uncertain options, will find it more natural to deal with that choice in a manner consistent with Expected Utility theory after multiple transactions (perhaps associated with investing in options markets) than will an experimental subject on his or her first exposure to the curious compound lotteries used to test Allais’s paradox.^6,7

These differences are obviously highly significant and they have led behavioural economists to seek to vary their experimental design in ways that better reflect choice in non-laboratory conditions.⁸ They have also led some scholars, reviewing those efforts, to doubt the external validity and practical relevance of many of the

‘contrarian’ results that behavioural economics has obtained.⁹ However, it seems to me that the real difficulty with these results — especially in terms of their implications for policy, including in the area of consumer protection — lies elsewhere.

6 The Allais paradox is a way of showing that a decision-maker orders uncertain prospects in a way that is inconsistent with the postulate that choices are independent of irrelevant alternatives.

Basically, it is this postulate that makes it possible to represent preferences over uncertain prospects as a linear function of the utilities of the basic outcomes, that is, as the expectation of utilities. See for example, Rubinstein (2006, pp. 95–96).

7 This expectation is consistent with the results of the laboratory experiments — see for example, Conlisk (1989). The same point can be made about findings of decay effects in contributions to repeated public goods games — behaviour converges to a lower level of contribution (that is, to greater self-regarding behaviour) over time.

8 See for example, Camerer, Hogarth (1999).

9 See, for example, Binmore (1999). A parallel line of criticism centres on the ad hoc nature of many explanations in behavioural economics, and the seeming lack of a unifying, parsimonious, approach to understanding economic behaviour. See, for example, Elster (1986).

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