Markets vs. Government when Rationality Is Unequally Bounded: Some Consequences of Cognitive Inequalities for Theory and Policy

Recognizing that human rationality has bounds that are unequal across individuals entails treating it as a special scarce resource, tied to individuals and used for deciding on its own uses. This causes a meta-mathematical difficulty to the axiomatic theories of human capital and resource allocation, and raises a new problem for comparative institutional analysis, allowing it to explain some so far little understood differences between markets and government. The policy implications strengthen the case against national planning, selective industrial policies, and government ownership of enterprises, but weaken the case against paternalism.Rationality; meta-mathematics; institutions; markets; government

Allocation of scarce resources when rationality is one of them: some consequences of cognitive inequalities for theory and policy

"Rationality" is understood in the empirical sense of cognitive abilities of human brains for solving economic problems, and consequently recognized bounded in individually unequal ways. This is shown to require treating it as a unique scarce resource, used for deciding on its own uses. This uniqueness disturbs axiomatic economics by a tangled hierarchy, and implies that rationality-allocation can approach efficiency only by means of an institutionally shaped trial-and-error evolution. Applied to the markets vs. government issue, a comparative institutional analysis of rationality-allocation yields novel insights with non-standard policy implications, and thus demonstrates that rationality-allocation matters.unequally bounded rationality; rationality-allocation; tangled hierarchy; institutionally shaped evolution; comparative institutional analysis

Post Walrasian Macro Policy and the Economics of Muddling Through

This paper expands on my earlier discussion of Post Walrasian macroeconomics policy. (Colander and van Ess 1996) First, it defines what I mean by Post Walrasian macroeconomics. Second, it discusses some of the theoretical differences between Post Walrasian and Walrasian macro theorizing as they relate to policy. Finally, it discusses how an acceptance of Post Walrasian economics might change the focus of macro policy discussions.

Modeling the Use of Nonrenewable Resources Using a Genetic Algorithm

This paper shows, how a genetic algorithm (GA) can be used to model an economic process: the interaction of profit-maximizing oil-exploration firms that compete with each other for a limited amount of oil. After a brief introduction to the concept of multi-agent-modeling in economics, a GA-based resource-economic model is developed. Several model runs based on different economic policy assumptions are presented and discussed in order to show how the GA-model can be used to gain insight into the dynamic properties of economic systems. The remainder outlines deficiencies of GA-based multi-agent approaches and sketches how the present model can be improved.

Virtuous and Adverse Selection within Economic Organizations

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The evolutionary theory of the firm: Routines, complexity and change

This paper provides an overview on the evolutionary theory of the firm. The specific feature of the evolutionary approach is that it explains the adaptive behaviors of firms through the tension between innovation and selection. It is suggested that the evolutionary theory can provide a useful basis for a theory of the firm which is concerned with change over time and development.theory of the firm, complexity, routines, change of routines

An Adversarial Interpretation of Information-Theoretic Bounded Rationality

Recently, there has been a growing interest in modeling planning with information constraints. Accordingly, an agent maximizes a regularized expected utility known as the free energy, where the regularizer is given by the information divergence from a prior to a posterior policy. While this approach can be justified in various ways, including from statistical mechanics and information theory, it is still unclear how it relates to decision-making against adversarial environments. This connection has previously been suggested in work relating the free energy to risk-sensitive control and to extensive form games. Here, we show that a single-agent free energy optimization is equivalent to a game between the agent and an imaginary adversary. The adversary can, by paying an exponential penalty, generate costs that diminish the decision maker's payoffs. It turns out that the optimal strategy of the adversary consists in choosing costs so as to render the decision maker indifferent among its choices, which is a definining property of a Nash equilibrium, thus tightening the connection between free energy optimization and game theory.Comment: 7 pages, 4 figures. Proceedings of AAAI-1