Kenneth J. Arrow

Bio: Kenneth J. Arrow is an academic researcher from Stanford University. The author has contributed to research in topics: Social choice theory & General equilibrium theory. The author has an hindex of 113, co-authored 411 publications receiving 111221 citations. Previous affiliations of Kenneth J. Arrow include University of California & Princeton University.

Microeconomics and operations research: Their interactions and differences

Abstract: Dear Colleagues, this is not going to be a very formal lecture, I doubt that you are prepared to go through the latest discussions about the mathematical considerations for the long term discount rate, a very real problem, applicable to climate change. On this occasion, I would be rather reminiscent of the different strands indicated in my title, as exemplified in my career, so I will be alternating between evolutionary development in the two fields and a certain amount of autobiography, letting one illustrate the other, I hope. Since this lecture is so much about me, I loom more importantly in some of these matters in this talk than I did in reality. There are some interesting points about how I became an economist. My personal story was part of a broader tendency. 1936 to 1940 was the time of my college career. This was a period considerably worse than the current recession. This is the Great Recession; that was the Great Depression. It lasted a long time, unemployment rates were much higher than they are today, and my father went from a certainly comfortable position to living hand to mouth. Under these circumstances, you tend to develop a concern for security. This is quite rational and in accord with economic theory. Here I was, going to college with the idea that at some point this would lead to a career, and I had to consider the question of a potential job. I was sufficiently advanced analytically even to think about the idea of flexibility, a topic which has become more important in economic analysis. If you don’t know what the world will be like, you have to prepare for alternative occupations. Frommy high school days on, I had shown some degree of mathematical talent, and I had chosen mathematics as my college major. What career does this lead to? Well, one very obvious possibility is to become a high school teacher. If you asked me at that time, that’s exactly what I intended to be. Indeed, this involved using a considerable fraction of my valuable college time taking courses in education, educational psychology. I don’t think they contributed much to my long run future as it happens. Being a high school teacher was a very sensible idea. The job was very secure, and it paid pretty well by the standards of that day. In fact, it turned out there was only one problem with it: supply and demand. In 1933, the city had given an examination for high school teachers of mathematics. By 1940, there were still people who had passed that examination and had not yet been hired. The city would not give another examination until the list was used up. That’s when I decided to be a graduate student instead. But even before I knew quite how bad the situation was going to be, I considered, you never know about being a high school teacher. But what else could I do using a knowledge of mathematics? There was something called statistics. The mathematics department gave a course in statistics. It was given by someone who did not knowmuch about it, as I could see immediately. But he did have a good reading list. That was what got me started reading the original papers, and I became fascinated by the subject. When I started graduate studies, I wanted to study statistics. Statistics was not a field you could get a degree in anywhere. There was a distinguished statistician at Columbia, who was a Professor of Economics. His name was Harold Hotelling, a name that is still, I think, well known. He had written some interesting papers in economics, proper mathematical economics. The use of mathematics in economics was not widespread, but there was a tradition of that going back to the first half of the 19th century. [Note: This lecture was given on March 4, 2014 on the occasion of my being designated, “Stanford Engineering Hero.”]

Innovation and Increasing Retums to Scale

Abstract: There has been a long tradition, going back to Adam Smith (1776), that technological progress is somehow intrinsically associated with increasing Retums. In more recent times, this connection has been emphasized by Young (1928), Nicholas Kaldor (1957), and, still more recently, by Arrow (1962), Shell (1966), and Romer (1990). There is, however, more than one interpretation of the relation.

Team theory and decentralized resource allocation : an example

Abstract: : The traditional discussion of the price system and alternative forms of decentralized resource allocation in organizations and entire economics has an ambivalent attitude to the ease of transferring information from one locus in the economic system to another On the one hand, the very need for decentralization is based on the assumption that the transmission of information is costly If this were not so, there would be no reason not to transfer all information on the availability of resources and the technology of production to one place and compute at one stroke the optimum allocation of resources On the other hand, the literature has tended to seek algorithms which, in some sense, minimize the amount of information transferred but which at the same time yield in the end the fully optimal allocation of resources In short, there is no true trade-off between information costs and other resource costs

Prospect theory: an analysis of decision under risk

Abstract: This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choices among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular, people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. This tendency, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses. In addition, people generally discard components that are shared by all prospects under consideration. This tendency, called the isolation effect, leads to inconsistent preferences when the same choice is presented in different forms. An alternative theory of choice is developed, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights. The value function is normally concave for gains, commonly convex for losses, and is generally steeper for losses than for gains. Decision weights are generally lower than the corresponding probabilities, except in the range of low prob- abilities. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gambling. EXPECTED UTILITY THEORY has dominated the analysis of decision making under risk. It has been generally accepted as a normative model of rational choice (24), and widely applied as a descriptive model of economic behavior, e.g. (15, 4). Thus, it is assumed that all reasonable people would wish to obey the axioms of the theory (47, 36), and that most people actually do, most of the time. The present paper describes several classes of choice problems in which preferences systematically violate the axioms of expected utility theory. In the light of these observations we argue that utility theory, as it is commonly interpreted and applied, is not an adequate descriptive model and we propose an alternative account of choice under risk. 2. CRITIQUE

Absorptive capacity: a new perspective on learning and innovation

Abstract: In this paper, we argue that the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovative capabilities. We label this capability a firm's absorptive capacity and suggest that it is largely a function of the firm's level of prior related knowledge. The discussion focuses first on the cognitive basis for an individual's absorptive capacity including, in particular, prior related knowledge and diversity of background. We then characterize the factors that influence absorptive capacity at the organizational level, how an organization's absorptive capacity differs from that of its individual members, and the role of diversity of expertise within an organization. We argue that the development of absorptive capacity, and, in turn, innovative performance are history- or path-dependent and argue how lack of investment in an area of expertise early on may foreclose the future development of a technical capability in that area. We formulate a model of firm investment in research and development (R&D), in which R&D contributes to a firm's absorptive capacity, and test predictions relating a firm's investment in R&D to the knowledge underlying technical change within an industry. Discussion focuses on the implications of absorptive capacity for the analysis of other related innovative activities, including basic research, the adoption and diffusion of innovations, and decisions to participate in cooperative R&D ventures. **

Dynamic capabilities and strategic management

Abstract: The dynamic capabilities framework analyzes the sources and methods of wealth creation and capture by private enterprise firms operating in environments of rapid technological change. The competitive advantage of firms is seen as resting on distinctive processes (ways of coordinating and combining), shaped by the firm's (specific) asset positions (such as the firm's portfolio of difftcult-to- trade knowledge assets and complementary assets), and the evolution path(s) it has aflopted or inherited. The importance of path dependencies is amplified where conditions of increasing retums exist. Whether and how a firm's competitive advantage is eroded depends on the stability of market demand, and the ease of replicability (expanding intemally) and imitatability (replication by competitors). If correct, the framework suggests that private wealth creation in regimes of rapid technological change depends in large measure on honing intemal technological, organizational, and managerial processes inside the firm. In short, identifying new opportunities and organizing effectively and efficiently to embrace them are generally more fundamental to private wealth creation than is strategizing, if by strategizing one means engaging in business conduct that keeps competitors off balance, raises rival's costs, and excludes new entrants. © 1997 by John Wiley & Sons, Ltd.