La formación de gobierno en 1981: el gabinete Calvo-Sotelo

In their book, titled ‘Decision Making’, Bell et al. (1988a) presented the following taxonomy of decision making under uncertainty:

• Normative – logically consistent decision making procedures, or how people should decide what to do;

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• Descriptive – decisions people make, and how people go about deciding what to do; and

• Prescriptive – how to help people to make good decisions and how to train people to make better decisions.

This sub-section (2.3.2) is based largely on the introduction of ‘Decision Making’ (Bell et

al., 1988a), and is devoted to a discussion of this taxonomy.

Normative decision making

Normative decision making describes the way that people ought to make decisions. Fishburn (1988) reviewed the traditional theory of von Neumann and Morgenstern (1944) and surveyed attempts to adapt this theory to accommodate the mounting evidence that many authors were finding the theory too restrictive. Bell and Raiffa (1988b) set

themselves the goal of ‘explaining’ the axioms of von Neumann and Morgenstern in such a way as to leave all readers lifelong devotees of expected utility theory.

Shafer (1988) made a substantial contribution to understanding when he presented a constructive procedure for making decisions. His complaint about subjective expected utility theory was that it was doomed to fail as a prescriptive tool because it required inputs such as probabilities and an understanding of utility which were not natural to a decision maker. He built a theory around goals rather than values, and beliefs rather than

probabilities which, even if aesthetically less pleasing to purists, had the prospect of achieving more success in practice (Bell et al., 1988c). Shafer and Tversky (1988)

explained the belief function approach more thoroughly. They stated quite clearly that their work was intended neither as a description nor as a prescription. Rather, they investigated the normative implications of their ideas (Bell et al., 1988c).

Dempster (1988) examined the various roles possible for a quantitative theory of evidence by distinguishing between a truthful theory and a truthful application of the theory. He argued that one normative theory should not be expected to be useful in all situations, and that normative theorists would do well to supply a range of tools for applied use.

Bell (1988), in a similar way to Schelling (1988), took as a premise that people suffer from being disappointed (in a way that they would be prepared to pay to avoid). People are disappointed when the outcome of a decision made under uncertainty is lower than their

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expectations. His paper showed how a normative model may be constructed to take account of the detrimental (and positive) effects of disappointment and used the model to derive implications for human behaviour (Bell et al., 1988c).

Bell and Raiffa (1988a) considered whether the traditional concepts of diminishing marginal economic value and risk aversion are really equivalent, as it is often assumed. They argued that the usual measure of risk aversion confounds two concepts, decreasing marginal value, and ‘intrinsic risk aversion’. While a person’s value curve may quite properly vary with the commodity over which it is measured (thus altering the measure of risk aversion), these authors hypothesized that a person’s intrinsic aversion to risk (dislike of uncertainty) remains constant across situations. Regret and disappointment were two ideas that arose from considering factors that might contribute to intrinsic risk aversion (Bell et al., 1988c).

Descriptive decision making

Descriptive decision making addresses the issue of how people actually make decisions. Tversky and Kahneman (1988), McNeil et al. (1988), and Slovic et al. (1988) all produced sound evidence that suggests people may arrive at opposite conclusions when data are presented in different, but mathematically equivalent, ways. Such behaviour is strictly ruled out by normative models, so these results are of tremendous significance to those who try to understand how people think (description) and to those who try to apply normative principles in the face of such potential distortions (prescription) (Bell et al., 1988c).

Many scholars have questioned whether the traditional normative paradigms really capture the essence of what is important in making a decision (Bell et al., 1988c). March (1988) drew attention to the dynamic nature of the world, especially to a decision maker’s uncertainty about his/her own future preferences. He explained apparent anomalies from the normative approach by the need for people to be resilient in the real world. Simon (1988) discussed his famous premise that people aim to achieve satisfactory rather than optimal results from their decisions. Einhorn and Hogarth (1988) gave a comprehensive review of critiques of traditional normative paradigms. They concluded with implications for prescriptive work

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Schelling (1988) cited evidence that suggests people may derive pleasure that they will pay for from experiences in which the brain (temporarily) suspends logical analysis. He said that we may cry when a movie character dies even though logic tells us the actor is still alive and that the script is fiction. This and other examples led him to question ‘who is in charge?’ If the mind is the ultimate consumer of our actions, should we be trying to frustrate its desires via logical thinking?

Argyris (1988) looked at the impediments, created by social upbringing, to the identification by decision makers and decision scientists alike of non-traditional (and optimal) solutions to problems. He argued that, when decision makers dislike the outcome of a decision, they infer that something was wrong about their decision and ignore the possibility that there might be something wrong about the values and process that produced their decision. While the aim of Argyris was to improve the chances of helping people to make better decisions (prescriptive decision making), the majority of his article was descriptive in illustrating how people think (Bell et al., 1988c).

Prescriptive decision making

In the classification of decision making developed by Bell et al. (1988a), prescriptive decision making addressed the issue of how to help people make good decisions and how to train people to make better decisions. Edwards et al. (1988) described an application in which multiple objective analysis was used to rank research projects. Along the way they told many of the lessons they had learned over years of using decision analysis in the field (Bell et al., 1988c). Keeney (1988) suggested that people would do well to analyse their value systems as a means of identifying decisions that could be made. However, he noted the reverse is more usually the case: a decision situation leads to an analysis of values. By pursuing value-focused thinking, Keeney argued, a person may derive greater incremental benefit from opportunities for decisions.

Fischhoff et al. (1988) described a number of difficulties that stand in the way of any analyst who attempts to measure the values of a decision maker. While alerting the reader to the potential pitfalls, they argued it may be mistaken as a premise, both in reality and as a practical matter, to assume that people have values that await quantification. Decision aids might be developed that exploit the insights to be gleaned from the inherent instability of values (Bell et al., 1988c).

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Hershey et al. (1988) identified five sources of distortion in the assessment of utility functions. This was a descriptive contribution to a normative theory with prescriptive implications (Bell et al., 1988c). Fong et al. (1988) questioned whether formal statistical training would help people to avoid common reasoning errors in everyday life. While their results do support such a conclusion, it is somewhat alarming to see how often even trained people fall into such traps. The difficulty of the task ahead of those wishing to make

prescriptive contributions was clearly underlined by this study (Bell et al., 1988c). Since then, prescriptive theory has been used and applied in much empirical work (Motiwalla, 1991; Sarma, 1993; Huber et al., 2002; Meacham, 2004).