The Economics of Risk and Time
Christian Gollier
GREMAQ and IDEI, University of Toulous

File type: PDF

Pages: 349

Introduction
Uncertainty is everywhere. There is no field in economics in which risk is
not an important dimension of the decision-making environment. The theory of
finance provides the most obvious example of this. Similarly, most recent developments
in macroeconomics have been made possible by recognizing the importance
of risk in explaining individual decisions. Consumption patterns, investments
and labor decisions can only be understood completely if uncertainty is
taken into account into the decision-making process. Environmental economics
provides another illustration. Public opinion is now very sensitive to the presence
of potentially catastrophic risks related, for example, to the greenhouse effect and
genetic manipulations. Environmental economists introduced probabilistic scenarios
in their models to exhibit socially efficient levels of prevention efforts.
Finally, the extraordinary contributions of asymmetric information to game theory
have heightened interest in uncertainty among economists.
We are lucky enough to have a well-accepted and unified framework to introduce
uncertainty in economic modelling. Namely, we are indebted to John von
Neumann and Oskar Morgenstern who in the mid-forties developed the expected
utility theory building on Daniel Bernoulli’s idea that agents facing risk maximize
the expected value of the utility of their wealth. Expected utility theory (EU) is
now fifty years old. It is a ubiquitous instrument in economic modelling. Most
economists recognize that the theory has been very useful for explaining the functioning
of our economies. The aim of this book is to provide a detailed analysis
of the implications of the expected utility model to the economic theory.
It is important to note that expected utility theory does not provide any hint
as to which specific utility function should be used by decision makers. We must
confess that the empirical estimation of utility functions of real world decision
makers is still in the early stage of development.
This precludes most economists from using particular utility functions to solve
their specific problems. For example, because expected utility the study of optimal
behavior in the presence of several sources of risk, very complex financial theory
relies heavily on the mean-variance approximation — in which interactions
between different risks are easily analyzed — of expected utility. This approximation
is exact only for very specific utility functions, like quadratic or exponential
ones. The same observation holds for macroeconomics, in which it has
been possible to treat dynamic uncertainties only by restricting utility functions
to very specific subsets of increasing and concave functions.