Strategies in dynamic games can be derived as the solutions of stochastic dynamic optimization problems. General solutions to such problems can be elusive, even with modern techniques. Simon (1955, 1957) showed that an important class of ‘linear-quadratic’ problems obey on ‘certainty equivalence’ – such stochastic dynamic optimization problems can be solved as if there is no uncertainty, by substituting expected values for all uncertain state variables. This insight became the basis for Simon’s ‘bounded rationality’ as well as rational expectations in economics.
KeywordsHousing Price Rational Expectation Dynamic Optimization Problem Random Shock Dynamic Programming Problem
- Bertsekas, D.P. 1976. Dynamic programming and stochastic optimal control. New York: Academic.Google Scholar
- Hansen, L.P., and T.J. Sargent. 2007. Robustness. Princeton: Princeton University Press.Google Scholar
- Holt, C.C., F. Modigliani, J.F. Muth, and H.A. Simon. 1960. Planning production, inventories and work force. Englewood Cliffs: Prentice Hall.Google Scholar
- Lucas Jr., R.E., and T.J. Sargent. 1981. Rational expectations and econometric practice. Minneapolis: University of Minnesota Press.Google Scholar
- Simon, H.A. 1957. Models of man. New York: Wiley.Google Scholar
- Simon, H.A. 1992. Rational decision-making in business organizations: Nobel memorial lecture, 8 December 1987. In Nobel lectures, economic sciences, 1969–1980, ed. E. Lindbeck. Singapore: World Scientific Publishing.Google Scholar