The Expected Utility Model: Its Variants, Purposes, Evidence and ...

Schoemaker: The Expected Utility Model
553
ments of opportunity and out-of-pocket
costs. As Thaler (1980) argues, these biases
afflict organizational as well as individual
decision making.
From a positivistic perspective, the interpretation
of evidence counter to EU
theory is more complicated. A well-known
example of Friedman and Savage (1948)
notes that complex equations of rigid. body
mechanics and plane geometry may offer
excellent predictiops of the manner in
which expert billiard players take their
shots, even if these players are totally ignorant
of such equations. The reason is
that the geometric model captures well
what the players try to do. Since they are
experts, years of training and feedback
have led to heuristics that closely approximate
optimal behavior. Four conditions,
however, make this analogy of limited
value to economic behavior. First, most
people are not experts in economic matters
(Thaler, 1980). Second, learning from
feedback is not a simple or automatic activity
in daily decision making. Uncertainty,
environmental instability, improper
assessment frameworks, and lack
of insight into one's decision rules are all
serious obstacles to learning from experience
(Einhorn, 1980). Third, the optimality
of economic behavior in real-world settings
is often difficult to assess without
specific knowledge of the person's utility
function, the particular problem perception,
and the rationality criteria being pursued
(March, 1978). Finally, even if the
EU model did predict well (while its assumptions
are wrong) the notion that only
prediction matters is epistemologically
quite unappealing (Paul Samuelson, 1963).
For instance, it would be interesting to
know what makes the model so robust under
misspecification (Robyn Dawes, 1979).
A second reaction, from a positivistic
economic perspective, is to note that individual
biases and differences may not matter
in aggregate behavior. For example,
Stigler and Becker (1977) argued that peo-
ple may usefully be treated as similar in
basic tastes and preferences, both across
time and persons. Moreover, market
mechanisms may be presumed to correct
misperceptions and individual decision biases.
However, not necessarily. Paul
Kleindorfer and Kunreuther (1982) examined
analytically the effect of probability
misinformation (by firms and consumers)
on insurance markets. Using Rothschild's
and Joseph Stiglitz' (1976) solution to the
adverse selection problem (i.e., allowing
insurers to offer varying dollar premiums
as a function of total coverage), they established
various conditions under which the
market fails. Pratt, Wise and Zeckhauser's
1979 study on price differences among
highly similar consumer products also
demonstrates a failure of the market to
correct individual biases. Finally, Thomas
C. Schelling (1978) discusses many other
examples of "irrational" macro behavior,
such as drivers incurring a thirty minute
delay to have a one-minute peek at some
highway accident. The point to be made
is that the connection between micro and
macro behavior is too complex to argue
that at higher levels of social aggregation
individual biases generally wash out or
self-correct.
As a third discussion point, let us examine
the view that hypothetical and "artificial"
laboratory experiments have limited
implications for economic theory. Sociological
research (H. Schuman and M. P.
Johnson, 1976) indeed underscores the
consideration that intentions (i.e., hypothetical
choices) cannot be mechanically
substituted for, or assumed to be generally
highly correlated with, actual behavior. In
the context of gambles, however, several
empirical studies by Nathan Kogan and
Michael Wallach (1967) and Slovic (1969)
on the effect of hypothetical vs. real payoffs
suggest that cognitive processes and
decisions do not differ considerably between
these two conditions. Indeed, I
know of no evidence that suboptimal labo-