Multiple Equilibria, Bounded Rationality, and the Indeterminacy of Economic Outcomes: Closing the System with Institutional Parameters

The tenth in a series of excerpts from Minds, Models and Milieux: Commemorating the Centennial of the Birth of Herbert Simon.

Morris Altman

A critical point made by behavioral economists from a wide set of methodological perspectives is that individuals typically do not make decisions that are consistent with conventional economic theoretical norms of rational behavior. This is true of those building on the errors and biases or heuristics and biases approach derived from the research of Kahneman and Tversky (Kahneman, 2003, 2011; Thaler and Sunstein, 2008), and those building upon the bounded rationality approach introduced by Herbert Simon (1978, 1979, 1987; Altman, 1999; Gigerenzer, 2007; Smith, 2003). Such ‘irrational’ behavior form the perspective of the mainstream is considered to be inefficient or sub-optimal. And sub-optimal outcomes should not be able to survive—it would fail the test of the survival of the fittest. However, various and different socio-economic outcomes or solutions for the same specific decision problems appear to be consistent with the survival on the market place. This is even true of economic outcomes, when firms are not maximizing productivity. Both low and high productivity firms can survive simultaneously on in the market. Moreover, ethical or socially considerate firms, and other-giving and empathic individuals can also survive and persist, even if such behavior is often considered to be sub-optimal and irrational from the perspective of the conventional economic wisdom.

It was just such apparent anomalies that Herbert Simon attempts to address through the concept of multiple equilibria, set in contrast with the more mainstream focus on convergence towards some optimal and unique equilibrium. From this perspective, both inefficient and efficient economic entities can persist over time in equilibrium. Therefore, survival and existence need not be in any way indicative or proof of uniqueness or optimality or efficiency in outcomes or decision making processes.

It is important to note that conventional and dominant economic methodology that deduces optimality and efficiency and even uniqueness from survival and existence is derived from the methodological paradigm articulated by Milton Friedman (1953; see also, Alchain, 1950). He maintained that survival is proof of optimality and efficiency of both outcomes and decision-making processes. One can deduce from outcomes—from survival—that individuals or economic agents behave in a particular and unique fashion—optimally and efficiently.

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Heart Full of Rhythm: The Big Band Years of Louis Armstrong

Stay tuned for this forthcoming book, a follow up to the superb What a Wonderful World: The Magic of Louis Armstrong’s Later Years. The book’s webpage is here.

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Mr. Toole

Surprisingly enough, I hadn’t come across this before. Apparently the playwright was a student of Toole’s. If you are a Confederacy fan catch the show here.

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From Bounded Rationality to Expertise

The ninth in a series of excerpts from Minds, Models and Milieux: Commemorating the Centennial of the Birth of Herbert Simon.

Fernand Gobet

Introduction

Historically, a pervasive assumption in the social sciences, in particular economics, is that humans are perfect rational agents. Having full access to information and enjoying unlimited computational resources, they maximise utility when making decisions. As is well known, Herbert A. Simon rejected this assumption, calling it a “fantasy”, for two main reasons. First, the complexity of the environment makes it impossible for humans to have full access to information. Second, a number of important restrictions impede the human cognitive system, such as limited attention and slow learning rates. Therefore, humans display only a bounded rationality and must satisfice – i.e. make decisions that are good enough, but not necessarily optimal.

Research into expertise has contributed to the question of rationality in two important ways. First, to what extent can some of the very best amongst us – super experts – approximate full rationality? Second, by what means do experts, at least in part, circumvent the constraints imposed by bounded rationality?

This chapter takes the shape of a fugue, with the themes of bounded rationality and expertise first played in the background of personal recollections, and then elaborated with a more formal survey of Simon’s research into expertise. The themes are played a third and final time with a discussion of the heuristics (rules of thumb) proposed by Simon for having a successful career in science.

Becoming an expert: A personal recollection

My collaboration with Herbert A. Simon lasted over 10 years, including 6 years spent at Carnegie Mellon. While I was working on my PhD thesis on chess players’ memory, I secured a research fellowship from the Swiss National Science Foundation to work with him. The qualifications I listed in my introductory letter to Simon were rather limited: a first degree in psychology and the title of International Chess Master. Simon, who probably saw an opportunity to reactivate research he carried out on chess expertise in the sixties and seventies (see below), but which had been dormant since, accepted to host me.

Meeting the man

I can still recall our first meeting on a beautiful morning in January 1990. His office was welcoming, but also rather disorganised, with stacks of papers and books hiding his desk. The meeting was short but cordial, and Simon gave me advice about life and housing in Pittsburgh, and briefly talked about the projects he was currently involved in.

The second meeting was my first real scientific discussion with Simon. It was actually a shock. In a polite and friendly way, Simon demolished the research line I had in mind for my PhD. The idea was to elicit a chess grandmaster’s knowledge about a small and specific domain (Rook + pawn endgames), and to build a program implementing this knowledge. The aim, inspired by research on expert systems, was to compare the amount of procedural (knowing how) and declarative knowledge (knowing what). Simon found that the project was not realistic enough (“A player like Kasparov will give you lectures on Rook endgames for several days; what are you going to do with all these data?”). In addition, he thought that the project would dovetail better with the research of his colleague John Anderson. I can still feel the panic that invaded me when he told me this, as it was an invitation to sever collaboration before the end of the first meeting! In the discussion that followed, he made it clear that he would prefer a project directly linked to the “chunking theory” he had developed with Chase in the seventies to account for chess expertise. This influential theory, and in particular the computer model MAPP (Memory-Aided Pattern Perceiver) that implemented it in part, had been severely criticised, and Simon wanted to improve on it. Thus my first lesson was that Simon, while open to other ideas, was very selective about the research lines he invested time in, and made sure that they addressed his central interests.

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Companion to Wisdom Literature

Due to drop in March — featuring of course, Philo of Alexandria.

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McTaggart’s philosophy of time

Nice explication by Emily Thomas of McTaggart’s classic argument for the unreality of time. It was Michael Dummett who reinvigorated interest in McTaggart after decades of neglect.

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