Jose A. Scheinkman '74
Jose A. Scheinkman was born on January 11, 1948, in Rio de Janeiro, Brazil. He attended the Universidade Federal do Rio de Jandeiro from March 1966 to December 1969, where he obtained his BA in economics.
From 1967 until 1969, he was an undergraduate fellow from the National Research Council of Brazil taking courses at the Instituto de Matematica Pura e Aplicada, where he obtained a MS degree in mathematics in 1970.
He was a full-time graduate student in the Department of Economics at the University of Rochester between September 1970 and May 1973, where he received a MA degree (1973) and a PhD degree (1974) in economics.
He worked under the supervision of Professor Lionel W. Mckenzie. From 1973 to 1999 he taught at the University of Chicago and was the Alvin H. Baum Distinguished Service Professor of Economics. Now he is the Theodore A. Wells'29 Professor of Economics at Princeton University.
Jose A. Scheinkman is a leading scholar in dynamic optimization theory, optimal growth theory and nonlinear dynamics with its applications in economics and finance. He is a fellow of the Econometric Society (elected in 1978) and a fellow of American Academy of Arts and Sciences (elected in 1992).
Jose A. Scheinkman's influential papers include:
"On the Differentiability of the Value Function in Dynamic Models of Economics", with L.M. Benveniste, Econometrica, 47, 1979.
In the applications of dynamic programming, one usually wants to know whether the value function is differentiable. This paper provides a simple sufficient condition. This condition is easy to verify in practice and widely used in macroeconomics and other fields in economics. It is exposited in the well-known graduate textbook: Recursive Methods in Economic Dynamics by N.L. Stokey and R.E. Lucas with E.C. Prescott. In recent years, every graduate student at Rochester has studied this famous theorem.
"Nonlinear Dynamics and Stock Returns", with B. LeBaron, Journal of Business, 62, 1989.
In this well-known paper Scheinkman and LeBaron applied, for the first time, the tools on nonlinear dynamics to study financial data. Examining stock returns, they found evidence for nonlinearities, but not for low dimensional chaotic dynamics. This research project also led to the development of the BDS test, (see W. Brock, W. Dechert, B. LeBaron, and J. Scheinkman, "A Test for Independence Based on the Correlation Dimension", Econometric Reviews, 15(3), 1996) which has become a standard tool for the detection of nonlinearities in time series.
Jianjun Miao (September 2000)