By Ariel Scheib
John Harsanyi was born on May 29, 1920, in Budapest,
Hungary. After high school, Harsanyi attended the University of
Budapest (today: Eötvös Loránd University). In 1944,
Harsanyi was taken captive by the Nazis
due to his Jewish origins. On his way to the railway station to be deported
to an Austrian concentration
camp, Harsanyi escaped and was kept hidden by a Jesuit priest in
the cellar of their monestary.
After the war, in 1946, Harsanyi re-enrolled at the
University of Budapest to obtain his Ph.D. in philosophy with minors
in sociology and psychology. From September 1947 to June 1948, he worked
as a faculty member at the University Institute of Sociology, but had
to leave because of his anti-Communist views.
On December 30, 1950, Harsanyi escaped from Eastern
Europe and the spread of Communism and moved to Sydney,
Australia. However, his degrees from Hungary were not acknowledged
in Australia, so he attended school at the University of Sydney. In
1953, Harsanyi received his M.A. in economics. He was appointed Lecturer
of Economics at the University of Queensland in 1954, but moved in 1956
to Stanford after receiving a Rockefeller Fellowship. It was at Stanford
that Harsanyi received his Ph.D. in economics, under the guidance of
Kenneth Arrow (Nobel Prize recipient for economics in 1972).
Harsanyi returned to Australia to work at the Australian
National University in Canberra. His interest in game theory, however,
was not welcomed in Australia and Harsanyi soon came back to the United
States to teach economics at Wayne State University in Detroit. Then,
in 1964, Harsanyi was appointed Professor at the Business School of
the University of California, Berkeley (later extended to the Department
of Economics), where he remained until retirement.
Harsanyi published four books on his research of game
theory: Rational Behavior and Bargaining Equilibrium in Games and
Social Situations (1977), Essays on Ethics, Social Behavior,
and Scientific Explanation (1976), Papers in Game Theory
(1982), and A General Theory of Equilibrium Selection in Games
He was a member of the National Academy of Science,
a Fellow of the American Economic Association, and a Distinguished Fellow
of the American Economic Association.
He was awarded the Nobel
Prize for Economics in 1994 for his work in game theory. Game theory
is the mathematical analysis of human behavoir in competitive situations.
Harsanyi contributed to the study of game theory in mathematics by developing
the analysis of games of incomplete information. Harsanyi had hoped
that game theory would produce more peaceful political institutions
and a higher standard of living.
John Harsanyi died on August 9, 2000, at the age of
The following press release
from the Royal Swedish Academy of Sciences
describes Harsanyi's work:
In games with complete information, all of the players
know the other players' preferences, whereas they wholly or partially
lack this knowledge in games with incomplete information. Since the
rationalistic interpretation of Nash equilibrium is based on the assumption
that the players know each others' preferences, no methods had been
available for analyzing games with incomplete information, despite the
fact that such games best reflect many strategic interactions in the
This situation changed radically in 1967-68 when John Harsanyi published
three articles entitled Games with Incomplete Information Played by
Bayesian Players, (Management Science 14, 159-82, 320-34 and 486-502).
Harsanyi's approach to games with incomplete information may be viewed
as the foundation for nearly all economic analysis involving information,
regardless of whether it is asymmetric, completely private or public.
Harsanyi postulated that
every player is one of several "types",
where each type corresponds to a set of
possible preferences for the player and
a (subjective) probability distribution
over the other players' types. Every player
in a game with incomplete information chooses
a strategy for each of his types. Under
a consistency requirement on the players'
probability distributions, Harsanyi showed
that for every game with incomplete information,
there is an equivalent game with complete
information. In the jargon of game theory,
he thereby transformed games with incomplete
information into games with imperfect information.
Such games can be handled with standard
An example of a situation with incomplete information is when private
firms and financial markets do not exactly know the preferences of the
central bank regarding the tradeoff between inflation and unemployment.
The central bank's policy for future interest rates is therefore unknown.
The interactions between the formation of expectations and the policy
of the central bank can be analyzed using the technique introduced by
Harsanyi. In the most simple case, the central bank can be of two types,
with adherent probabilities: Either it is oriented towards fighting
inflation and thus prepared to pursue a restrictive policy with high
rates, or it will try to combat unemployment by means of lower rates.
Another example where similar methods can be applied is regulation of
a monopoly firm. What regulatory or contractual solution will produce
a desirable outcome when the regulator does not have perfect knowledge
about the firm's costs?
Game theory is a mathematical method for analyzing strategic interaction.
Many classical analyses in economics presuppose such a large number
of agents that each of them can disregard the others' reactions to their
own decision. In many cases, this assumption is a good description of
reality, but in other cases it is misleading. When a few firms dominate
a market, when countries have to make an agreement on trade policy or
environmental policy, when parties on the labor market negotiate about
wages, and when a government deregulates a market, privatizes companies
or pursues economic policy, each agent in question has to consider other
agents' reactions and expectations regarding their own decisions, i.e.,
As far back as the early nineteenth century, beginning with Auguste
Cournot in 1838, economists have developed methods for studying strategic
interaction. But these methods focused on specific situations and, for
a long time, no overall method existed. The game-theoretic approach
now offers a general toolbox for analyzing strategic interaction.
Whereas mathematical probability theory ensued from the study of
pure gambling without strategic interaction, games such as chess, cards,
etc. became the basis of game theory. The latter are characterized by
strategic interaction in the sense that the players are individuals
who think rationally. In the early 1900s, mathematicians such as Zermelo,
Borel and von Neumann had already begun to study mathematical formulations
of games. It was not until the economist Oskar Morgenstern met the mathematician
John von Neumann in 1939 that a plan originated to develop game theory
so that it could be used in economic analysis.
The most important ideas
set forth by von Neumann and Morgenstern
in the present context may be found in
their analysis of two-person zero-sum games.
In a zero-sum game, the gains of one player
are equal to the losses of the other player.
As early as 1928, von Neumann introduced
the minimax solution for a two-person zero-sum
game. According to the minimax solution,
each player tries to maximize his gain
in the outcome which is most disadvantageous
to him (where the worst outcome is determined
by his opponent's choice of strategy).
By means of such a strategy, each player
can guarantee himself a minimum gain. Of
course, it is not certain that the players'
choices of strategy will be consistent
with each other. von Neumann was able to
show, however, that there is always a minimax
solution, i.e., a consistent solution,
if so-called mixed strategies are introduced.
A mixed strategy is a probability distribution
of a player's available strategies, whereby
a player is assumed to choose a certain "pure" strategy
with some probability.
Harsanyi Autobiography"; HaasNews;