Search results

Economic ideas are the product of contemplation, but also of our economic lives. In the history of ideas, Gérard Debreu’s shining book of 1959, Theory of Value, represents the pinnacle of purity in contemplating economic life. Rather than contextualizing this oeuvre through his intellectual life, as is usually done, this essay describes his axiomatic analysis by contextualizing it through his economic life. What do we learn about Debreu’s axioms on consumption when thinking of his own consumption? What do we learn about his theory of value when thinking of his own values? Historiographically, this approach permits the use of a widely neglected source in the history of economics: anecdotes. Epistemologically, blending axioms and anecdotes offers a description of how axioms regulate an economic discourse. Finally, this essay offers a language for the material dimensions of economic life that are so underexposed in Debreu’s own work.

Economics laboratories have become the primary locations of experimental economics research by the 1990s. They were a result of a decade long development from ad hoc opportune places to dedicated, purpose designed spaces. The distinctive feature of the economics laboratory and its key instrument became networked computers running custom-built software. However, the history of the economics laboratory is not just a history of evolving technology. I argue in this article that it is mainly a history of learning how to build an experimental economics community. Only a functioning community was able to change a physical place to a laboratory space. The distinction between place and space originates in the work of Michael de Certeau and I use it to analyze the evolution of economics laboratories. To this end, I analyze the case of Austin Hoggatt’s Management Science Laboratory at Berkeley in the 1960s as it illustrates the indispensability of creating a community centered on the laboratory. In contrast, the laboratories in Arizona and at Caltech since the 1980s, and in Amsterdam since the 1990s have become successful spaces, because, unlike Hoggatt, they focused equally on community building as on infrastructure and technology. This gave rise to social infrastructure and division of labor in the laboratory space.

The purpose of this paper is to illustrate how game theoretic solution concepts inform what classes of problems will be amenable to artificial intelligence and machine learning (AI/ML), and how to evolve the interaction between human and artificial intelligence.

The approach addresses the development of operational gaming to support planning and decision making. It then provides a succinct summary of game theory for those designing and using games, with an emphasis on information conditions and solution concepts. It addresses how experimentation demonstrates where human decisions differ from game theoretic solution concepts and how games have been used to develop AI/ML. It concludes by suggesting what classes of problems will be amenable to AI/ML, and which will not. It goes on to propose a method for evolving human/artificial intelligence.

Game theoretic solution concepts inform classes of problems where AI/ML 'solutions' will be suspect. The complexity of the subject requires a campaign of learning.

Though games have been essential to the development of AI/ML, practitioners have yet to employ game theory to understand its limitations.

Today Lionel Penrose is recognised as the co-author of one of the two leading indices of power in voting legislatures – a field of study that game theory in general, and cooperative game theory in particular, has been reclaiming from sociology and political science since the 1950s. The main claim of this paper is that Penrose developed his index so as to tackle questions that go vastly beyond the narrow domain of voting; namely, acute social issues during the Cold War such as the outburst and propagation of panics, the ideological susceptibility of populations, the escalation of military conflict and the successful installation of authoritarian regimes. Furthermore, by revisiting the history of the Penrose power index, the paper re-evaluates some of its key underlying assumptions: assumptions that have been heavily – and unfairly, as the paper argues – criticised over the last decade.

If everyone were indifferent between more and less and between this and that, the problems of allocating scarce resources would be trivialized. The necessity of choice, whether social or individual, would seem absurd. However, people persist in preferring certain “states of the world” to others. As a society is made up of individuals, it seems reasonable that a society's preferences should be “made up” of the preferences of its members. Therefore, any social welfare function, W, should be a function of the individual welfare functions, wi. That is,

A brief survey of the development of the study of risk and probability is given together with some basic observations on their application to insurance. This is followed with observations on the lack of appreciation of probability studies and an elementary feeling for probability by the public at large and a suggestion that the time is ripe for a new science museum involving basic economics and the exposition of the role of probability in finance.

Events surrounding September 11, 2001, have motivated increasing interest in identifying, assessing, and managing the risk of “extreme events.” This article introduces a new mathematical framework for the risk management of extreme event risk. In the article, the author proposes criteria based on “higher” (the third and fourth) moments that dominate variance (the second moment) in explaining the economics of insurance and reinsurance. Economic and financial implications are then applied to the underwriting and investment activities of insurers and reinsurers.