Nyarko, Y. (2010). Most Games Violate the Common Priors Doctrine. International Journal of Economic Theory, 6(1), 189-194.
The type of a player in a game describes the beliefs of that player about the types of others.
Nyarko, Y., Schotter, A., & Sopher, B. (2006). On the Informational Content of Advice: A Theoretical and Experimental Study. Economic Theory, 29(2), 433-452.
This paper examines the market for advice and the underlying perception that advice is useful and information…
Nyarko, Y. “The New Growth Theory.” Fundamental Economics- Volume I (EOLSS), edited by Majumdar et al., UNESCO, 2002.
This paper very briefly summarizes some of the new growth theory in economics. The emphasis will be on the role of knowledge in the growth process.
Nyarko, Y., & Schotter, A. (2002). An Experimental Study of Belief Learning using Elicited Beliefs. Econometrica, 70(3), 971-1005. (See data for this paper).
This paper investigates belief learning.
Nyarko, Y., & Schotter, A. (2000). Comparing Learning Models with Ideal Micro & Experimental Data Sets. New York University.
This paper compares three learning models. The models compared are the Reinforcement Learning Model of Erev and Roth, the EWA model of Camerer and Ho and a Belief Learning model in which beliefs are elicited from subjects using a proper scoring rule…
Nyarko, Y. (1998). The Truth is in the Eye of the Beholder: or Equilibrium in Beliefs and Rational Learning in Games, Working Paper (No. 98-12). C.V. Starr Center for Applied Economics, New York University.
Games with incomplete information or randomness in the moves of others typically have many decision-theoretically equivalent formulations of the type space…
Nyarko, Y. (1998). Learning, Quantal Response Equilibrium and Equilibrium in Beliefs, Working Paper (No. 01-03, revised 2001). C.V. Starr Center for Applied Economics, New York University.
This paper makes two points. First, the modeling used in the rational (Bayesian) learning literature can be generalized to handle the repeated shocks to preferences inherent and implicit in models of quantal response equilibria (QRE).
Nyarko, Y. (1998). Bayesian Learning and Convergence to Nash Equilibria without Common Priors. Economic Theory, 11(3), 643-655.
Consider an infinitely repeated game where each player is characterized by a ‘type’ which may be unknown to the other plays in the game. Suppose further that each player’s belief about others is independent of that player’s type…
Nyarko, Y. (1997). Convergence in Economic Models with Bayesian Hierarchies of Beliefs. Journal of Economic Theory, 74(2), 266-296.
I study a model where hierarchies of beliefs (the beliefs about the beliefs of other agents, etc.) are important. I provide conditions under which optimal actions of agents will converge to the Nash equilibrium of the model characterized by the true, previously unknown ``fundamentals.''
Jovanovic, B., & Nyarko, Y. (1997). Stepping-stone mobility. Carnegie-Rochester Conference Series on Public Policy, 46, 289-325.
People at the top of an occupational ladder earn more partly because they have spent time on lower rungs, where they have learned something. But what precisely do they learn?
Nyarko, Y., & Olson, L. J. (1996). Optimal Growth with Unobservable Resources and Learning. Journal of Economic Behavior & Organization, 29(3), 465-491.
This paper examines the problem of choosing optimal resource consumption from an imperfectly observable aggregate capital, wealth, or resource stock with the decision-maker learns about over time.
Jovanovic, B., & Nyarko, Y. (1996). The Bayesian Foundations of Learning by Doing. Econometrica, 64(6), 1299-1310.
This paper explores a one-agent Bayesian model of learning by doing and technological choice. To produce output, the agent can choose among various technologies…
Jovanovic, B., & Nyarko, Y. “Research and Productivity.” Creation and Transfer of Knowledge, edited by Navaretti et al., Springer, Berlin, Heidelberg, 1995.
We model research as a signal on an unknown parameter of a technology. We distinguish applied from basic research and show that firms in the same industry can optimally choose different research portfolios, and that basic research van seem to have a higher rate of return than applied research, even though it really doesn’t - essentially, firms on a “fast track” upgrading policy opt for basic research but fast and slow-track upgrading policies can coexist in a long-run equilibrium.
Jovanovic, B., & Nyarko, Y. (1995). A Bayesian Learning Model Fitted to a Variety of Empirical Learning Curves. Brookings Papers on Economic Activity. Microeconomics, (1), 247-305.
Where does technological progress come from and what determines its rate of advance? In answering these questions, it is useful to decompose technological progress into the invention of new techniques and products and the improvement of existing ones.
Kiefer, N., & Nyarko, Y. “Savage-Bayesian Models of Economics.” Essays in learning and rationality in economics and games, Basil Blackwell, 40-62, 1995.
The “state of the art” in learning models in economics is highly unsettled. On the one hand, we have the optimizing models in which learning occurs as a byproduct…
Jovanovic, B., & Nyarko, Y. (1995). The Transfer of Human Capital. Journal of Economic Dynamics and Control, 19(5-7), 1033-1064.
Most of our productive knowledge was handed down to us by previous generations. The transfer of knowledge from the old to the young is therefore a cornerstone of productivity growth.
Nyarko, Y., & Olson, L. J. (1994). Stochastic Growth When Utility Depends on Both Consumption and the Stock Level. Economic Theory, 4(5), 791-797.
This paper examines the dynamic behavior of optimal consumption and investment policies in the aggregate stochastic growth model when utility depends on both consumption and the stock level.
Nyarko, Y. (1994). On the Convexity of the Value Function in Bayesian Optimal Control Problems. Economic Theory, 4(2), 303-309.
I study the question on the convexity of the value function and Blackwell (1951)’s Theorem and relate this to the uniqueness of optimal policies…
Nyarko, Y., Woodford, M., & Yannelis, N. C. (1994). Bounded Rationality and Learning. Economic Theory, 4(6), 811-820.
Many have objected to the use of the Nash equilibrium (or more generally, Bayesian Nash equilibrium) concept in game theory, and similarly to the use of the rational expectations concept in the theory of competitive markets…
Nyarko, Y. (1993). Review of the book “Games, Strategies and Managers,” by John McMillan, Journal of Economic Literature, 31(2), 890-891.
Can the logic of game theory be presented as effectively in words as by mathematical models?
Nyarko, Y. (1994). Bayesian Learning Leads to Correlated Equilibria in Normal Form Games. Economic Theory, 4(6), 821-841.
Consider an infinitely repeated normal form game where each player is characterized by a “type” which may be unknown to the other players of the game…
Nyarko, Y. (1991). On the Convergence of Bayesian Posterior Processes in Linear Economic Models, Counting Equations and Unknowns. Journal of Economic Dynamics and Control, 15(4), 687-713.
I propose a technique, counting ‘equations’ and ‘unknowns’, for determining when the posterior distributions of the parameters of a linear regression process converge to their true values.
Nyarko, Y., & Olson, L. J. (1991). Stochastic Dynamic Models with Stock-Dependent Rewards. Journal of Economic Theory, 55(1), 161-168.
We examine the behavior of optimal consumption and investment policies in aggregate stochastic growth models when utility depends on both consumption and the stock level…
Nyarko, Y. (1991). Learning in Mis-Specified Models and the Possibility of Cycles. Journal of Economic Theory, 55(2), 416-427.
I study the problem of a monopolist maximizing a sum of discounted profits facing a linear demand curve whose slope and intercept are unknown. I show that if the monopolist has a mis-specified model…
Mitra, T., & Nyarko, Y. (1991). On the Existence of Optimal Processes in Non-Stationary Environments. Journal of Economics, 53(3), 245-270.
We consider an aggregative model of intertemporal allocation under uncertainty, in which the utility and production functions are allowed to be time dependent, the random shocks occurring in each period are entirely arbitrary…
Majumdar, M., Mitra, T., & Nyarko, Y. “Dynamic Optimization under Uncertainty: Non-Convex Feasible Set.” Joan Robinson and Modern Economic Theory, edited by George Feiwel, Macmillan Press, 545-590, 1989.
The object of the book is refinement, not reconstruction; it is study in ‘pure theory.’ The motive back of its presentation is twofold…
Kiefer, N., & Nyarko, Y. “Optimal Bayesian Control of a Nonlinear Regression Process with Unknown Parameters.” Modeling and Control of Systems, Lecture Notes in Control and Information Sciences, edited by Austin Blaquiére, Springer, Berlin, Heidelberg, 355-362, 1989.
Economic Agents operating in uncertain, stochastic environments can face a tradeoff between current period expected reward and accumulation of information of uncertain value.
Kiefer, N., & Nyarko, Y. (1989). Optimal Control of an Unknown Linear Process with Learning. International Economic Review, 30(3), 571-586.
Optimal control of a linear process with unknown parameters is considered when the horizon is infinite and rewards are discounted. Active learning strategies are considered…
Nyarko, Y. (1988). On Characterizing Optimality of Stochastic Competitive Processes. Journal of Economic Theory, 45(2), 316-329. Reprinted in Decentralization in Infinite Horizon Economies, edited by Mukul Majumdar, Westview Press, 100-113, 1992.
A condition is provided to replace the transversality condition in characterizing the optimality of competitive processes…
Kiefer, N., & Nyarko, Y. “Control of a Linear Regression Process with Unknown Parameters.” Dynamic Econometric Modelling, edited by Barnett et al., Cambridge University Press, 105-120, 1988.
Applications of forms of control theory to economic policy making have been studied by Theil (1958), Chow (1975, 1981), and Prescott (1972). Many of the applications are approximations to the optimal policy…