If someone claims that individuals behave as if they violate the independence axiom when making decisions over simple lotteries, it is invariably on the basis of experiments and theories that must assume the IA through the use of the random lottery incentive mechanism. We refer to someone who holds this view as a Bipolar Behaviorist, exhibiting pessimism about the axiom when it comes to characterizing how individuals directly evaluate two lotteries in a binary choice task, but optimism about the axiom (...) when it comes to characterizing how individuals evaluate multiple lotteries that make up the incentive structure for a multiple-task experiment. We reject the hypothesis about subject behavior underlying this stance: we find that preferences estimated with a model that assumes violations of the IA are significantly affected when one elicits choices with procedures that require the independence assumption, as compared to choices elicited with procedures that do not require the assumption. The upshot is that one cannot consistently estimate popular models that relax the IA using data from experiments that assume the validity of the RLIM. (shrink)

This paper examines methodological issues raised by revealed preference theory in economics: particularly contemporary revealed preference theory. The paper has three goals. First, to make the case that revealed preference theory is a broad research program in choice theory—not a single theory—and understanding this diversity is essential to any methodological analysis of the program. Second, to explore some of the existing criticisms of revealed preference theory in a way that emphasizes how the effectiveness of the critique depends on the particular (...) version of revealed preference under consideration. Finally, three additional criticisms are presented that are aimed specifically at contemporary revealed preference theory. (shrink)

The authors explore the history of experiments in economics, provide examples of different types of experiments and show that the growing use of experimental methods is transforming economics into an empirical science.

It is widely held that Bayesian decision theory is the final word on how a rational person should make decisions. However, Leonard Savage--the inventor of Bayesian decision theory--argued that it would be ridiculous to use his theory outside the kind of small world in which it is always possible to "look before you leap." If taken seriously, this view makes Bayesian decision theory inappropriate for the large worlds of scientific discovery and macroeconomic enterprise. When is it correct to use Bayesian (...) decision theory--and when does it need to be modified? Using a minimum of mathematics, Rational Decisions clearly explains the foundations of Bayesian decision theory and shows why Savage restricted the theory's application to small worlds. The book is a wide-ranging exploration of standard theories of choice and belief under risk and uncertainty. Ken Binmore discusses the various philosophical attitudes related to the nature of probability and offers resolutions to paradoxes believed to hinder further progress. In arguing that the Bayesian approach to knowledge is inadequate in a large world, Binmore proposes an extension to Bayesian decision theory--allowing the idea of a mixed strategy in game theory to be expanded to a larger set of what Binmore refers to as "muddled" strategies. Written by one of the world's leading game theorists, Rational Decisions is the touchstone for anyone needing a concise, accessible, and expert view on Bayesian decision making. (shrink)

In this study, Don Ross explores the relationship of economics to other branches of behavioral science, asking, in the course of his analysis, under what interpretation economics is a sound empirical science. The book explores the relationships between economic theory and the theoretical foundations of related disciplines that are relevant to the day-to-day work of economics -- the cognitive and behavioral sciences. It asks whether the increasingly sophisticated techniques of microeconomic analysis have revealed any deep empirical regularities -- whether technical (...) improvement represents improvement in any other sense. Casting Daniel Dennett and Kenneth Binmore as its intellectual heroes, the book proposes a comprehensive model of economic theory that, Ross argues, does not supplant, but recovers the core neoclassical insights, and counters the caricaturish conception of neoclassicism so derided by advocates of behavioral or evolutionary economics. Because he approaches his topic from the viewpoint of the philosophy of science, Ross devotes one chapter to the philosophical theory and terminology on which his argument depends and another to related philosophical issues. Two chapters provide the theoretical background in economics, one covering developments in neoclassical microeconomics and the other treating behavioral and experimental economics and evolutionary game theory. The three chapters at the heart of the argument then apply theses from the philosophy of cognitive science to foundational problems for economic theory. In these chapters, economists will find a genuinely new way of thinking about the implications of cognitive science for economics, and cognitive scientists will find in economic behavior, a new testing site for the explanations of cognitive science. (shrink)

Classic analysis of the subject and the development of personal probability; one of the greatest controversies in modern statistcal thought.

Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about (...) fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market. As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions. (shrink)