Economics Of Uncertainty Research Articles

The Economics of Uncertainty and Insurance

This text provides an introduction to the analysis of economic decisions under uncertainty, with particular focus on insurance markets.

God, Ants and Thomas Bayes

The editors of this volume have invited me to present here my personal philosophy. But I cannot distinguish between my personal philosophy and my theoretical philosophy. As I explained in my autobiography (Markowitz 1990), when I was in high school I read science at a nontechnical level, like the ABC of Relativity , and the original writings of great philosophers. In particular, I was struck by David Hume’s (1776) argument that even though I release a ball a thousand times and, in every instant, it falls to the floor, that does not prove that it will necessarily fall to the floor the thousand-and-first time. In other words, even though Newton’s law of gravity worked in thousands of instances, that did not prove that it would never fail – such as in explaining the orbit of Mercury! Essentially, my philosophical interest in high school lay in the question “What do we know and how do we know it?” When I entered the Economics Department at the University of Chicago I was naturally drawn to the economics of uncertainty. In particular, the work of Leonard J. Savage (1954) – building on that of von Neumann and Morgenstern (1944) – presented, to me among many others, a convincing axiomatic argument that, in acting under uncertainty, one should maximize expected utility using probability beliefs where objective probabilities are not known. It is a corollary of the latter conclusion that, as information accumulates, one should shift one’s beliefs according to Bayes’s rule, reviewed later in this essay. (Hume, too, said that one should attach probabilities to beliefs but did not specify that Bayes’s rule should be used in response to growing evidence for or against various hypotheses.)

Uncertainty in the Theory of Public Finance

This paper discusses the role that the economics of uncertainty has played in the theory of public finance. From being mostly concerned with its choice-theoretic foundations in the 1950s and 1960s, the theory of expected utility maximisation and risk averse behaviour has contributed decisively to the development of several areas of the theory of public finance. Three of these have been chosen here to illustrate the general point: The theory of taxation and risk taking with focus on portfolio choice, the role of uncertainty in public expenditure analysis (emphasising the effect of public goods provision on private risk taking) and the theory of tax evasion and compliance.

On the Receipt of the Ronald H. Coase Medal: Uncertainty, the Economic Crisis, and the Future of Law and Economics

This paper discusses problems in economic analysis of law arising from the increased specialization of academic practitioners of this subfield of economics, which takes as its subject a uniquely fluid, contestable, and inveterately normative subject—namely, the law. As a result of the limited acquaintance of most economic analysts of law with macroeconomic theory (owing to their specialization in relevant fields of microeconomics), they have (with important exceptions, however) had trouble contributing to the understanding of the recent financial crisis. The crisis underscores the importance, across a range of issues including financial and antitrust law, of the economics of uncertainty (in the Knight-Keynes sense) and organization economics.

Limitations of integrated assessment models of climate change

The integrated assessment models (IAMs) that economists use to analyze the expected costs and benefits of climate policies frequently suggest that the “optimal” policy is to go slowly and to do relatively little in the near term to reduce greenhouse gas emissions. We trace this finding to the contestable assumptions and limitations of IAMs. For example, they typically discount future impacts from climate change at relatively high rates. This practice may be appropriate for short-term financial decisions but its extension to intergenerational environmental issues rests on several empirically and philosophically controversial hypotheses. IAMs also assign monetary values to the benefits of climate mitigation on the basis of incomplete information and sometimes speculative judgments concerning the monetary worth of human lives and ecosystems, while downplaying scientific uncertainty about the extent of expected damages. In addition, IAMs may exaggerate mitigation costs by failing to reflect the socially determined, path-dependent nature of technical change and ignoring the potential savings from reduced energy utilization and other opportunities for innovation. A better approach to climate policy, drawing on recent research on the economics of uncertainty, would reframe the problem as buying insurance against catastrophic, low-probability events. Policy decisions should be based on a judgment concerning the maximum tolerable increase in temperature and/or carbon dioxide levels given the state of scientific understanding. The appropriate role for economists would then be to determine the least-cost global strategy to achieve that target. While this remains a demanding and complex problem, it is far more tractable and epistemically defensible than the cost-benefit comparisons attempted by most IAMs.

Uncertainty in the Theory of Public Finance

This paper discusses the role that the economics of uncertainty has played in the theory of public finance. From being mostly concerned with its choice-theoretic foundations in the 1950s and ‘60s, the theory of expected utility maximization and risk averse behaviour has contributed decisively to the development of several areas of the theory of public finance. Three of these have been chosen here to illustrate the general point: Taxation and risk taking, the role of uncertainty in public expenditure and the theory of tax evasion and compliance.

AN INTERVIEW WITH PETER DIAMOND

Peter Diamond is one of the major contributors to economics during the last half century. His many contributions include research on growth, Social Security, public finance more generally, the economics of uncertainty, search theory, in particular, and economic dynamics, in general. This work has shaped the way we think about many economic problems, and the way in which we formalize them. Among his long list of honors and awards, he is a fellow of the Econometric Society, a Guggenheim Fellow, a Fellow of the American Academy of Arts and Sciences, a Member of the National Academy of Sciences, and a Nemmers Prize winner. The National Science Foundation has supported his work for the last 40 years. A recent check indicated 9 books and 132 published articles, and there are few signs of any slowdown.

On Inverse Utility and Third-Order Effects in the Economics of Uncertainty

We prove that the coefficient of absolute prudence is greater than k - times coefficient of absolute risk aversion for the utility function if and only if the coefficient of absolute prudence is (3-k) times the coefficient of absolute risk aversion for the inverse utility function. Moreover this is also equivalent to (k-2)-concavity of the first derivative of the inverse utility function.

The state‐contingent approach to production under uncertainty*

The central claim of this paper is that the state‐contingent approach provides the best way to think about all problems in the economics of uncertainty, including problems of consumer choice, the theory of the firm, and principal–agent relationships. This claim is illustrated by recent developments in, and applications of, the state‐contingent approach.

Testing for stochastic dominance using the weighted McFadden-type statistic

Abstract We demonstrate that when testing for stochastic dominance of order three and above, using a weighted version of the Kolmogorov–Smirnov-type statistic proposed by McFadden [1989. In: Fomby, T.B., Seo, T.K. (Eds.), Studies in the Economics of Uncertainty. Springer, New York, pp. 113–134] is necessary for obtaining a non-degenerate asymptotic distribution. Since the asymptotic distribution is complex, we discuss a bootstrap approximation for it in the context of a real application.

Government Insurance versus Market Insurance

This paper compares the provision of insurance by the government to provision by private firms in the market. The topic is one that has been much addressed in the proceedings of this Association. It was the subject of the First Annual Lecture of the Geneva Association by Kenneth J. Arrow (Arrow, 1978). Arrow’s defense and advocacy of government-provided insurance constituted much of the work for which he was awarded the Nobel Prize on the economics of uncertainty. More recently, it was the subject of the 15th Annual Lecture by Tony Atkinson (Atkinson, 1991), the 17th, by Assar Lindbeck (Lindbeck, 1994), and the 18th, by Pierre Pestieau (Pestieau, 1994), and formed the major underlying issue of the 19th Lecture by Richard Zeckhauser (Zeckhauser, 1996) and the 21st by Howard Kunreuther (Kunreuther, 1997). And, of course, this topic has been the subject of multiple individual articles in the Geneva Papers (see, for example, Faure, 1998; Meyer, 1996). My approach to the topic, however, is somewhat different. What I hope to do here is to examine critically the basic foundational assumptions that have served to justify governmental provision of insurance by comparison with our understanding of market insurance, and then more carefully to compare the operation of governmental insurance regimes to the operation of private market regimes. There is a sophisticated economic justification for the provision of insurance services by the government. An important feature of the justification is that the government – the state – is able to provide insurance in contexts in which a private market for insurance is unavailable. It is an empirical fact that, in most contexts in which governments provide insurance, private market insurance is or becomes unavailable. This empirical fact, however, has meant that there have been no ready contexts in which to compare government versus market insurance operations. As a consequence, in the long history of discussion of government insurance, comparisons with the private insurance market have been neglected. This paper is a first attempt to remedy that neglect.

Risk and Uncertainty in Assessment: exploring the contribution of economics to identifying and analysing the social dynamic in grading

ABSTRACT The social processes and political economy of grading in British higher education is a neglected topic. The aim of the paper is to stimulate interest in and empirical work about the secret garden of grading course work. In particular, the paper focuses on the contribution which the economics of uncertainty, as a conceptual framework, might make to revealing significant aspects of the real world of grading students’ coursework. Uncertainty, it is argued, is a powerful organising concept because it reveals the weight of obligation which academics may feel which pushes them towards awarding an appropriate grade in the context of public scrutiny of their grading and the anxious anticipation of possibly litigatious students hoping for the highest grade they can tweak out of the system. The paper is tentative and speculative yet the preliminary argument offered suggests that empirical work may now be appropriate.

Logconcavity versus Logconvexity: A Complete Characterization

This paper provides a complete characterization of logconcavity, an increasingly popular concept in the economics of uncertainty and information. New and known results are proven without assuming that density functions are differentiable. A systematic comparison between logconcavity and logconvexity is made and the source of the asymmetries between the two is investigated. The key difference is that logconcavity is preserved under one-sided integrations regardless of the types of distribution supports. This property, however, does not hold for logconvexity. Logconcavity for multivariate distributions is also discussed.Journal of Economic LiteratureClassification Number: D80.

The economics of financial markets

The Economics of Financial Markets presents a concise overview of capital markets, suitable for advanced undergraduates and for beginning graduate students in financial economics. Following a brief overview of financial markets - their microstructure and the randomness of stock market prices - this textbook explores how the economics of uncertainty can be applied to financial decision-making. The mean-variance model of portfolio selection is discussed, with analysis extended to the capital asset pricing model (CAPM). Arbitrage plays a pivotal role in finance and is studied in a variety of contexts, including the APT model of asset prices. Methods for the empirical evaluation of CAPM and APT are also discussed, together with the volatility of asset prices, the intertemporal CAPM and the equity premium puzzle. An analysis of bond contracts leads into an assessment of theories of the term structure of interest rates. Finally, financial derivatives are explored, focusing on futures and options contracts.

Duality and equilibrium prices in economics of uncertainty

A random variable (RV) X is given a minimum selling price (S) SU(X) := sup x {x + EU(X x)} and a maximum buying price (B) BP(X) := inf x {x + EP(X x)} where U(·) and P(·) are appropriate functions. These prices are derived from considerations of stochastic optimization with recourse, and are called recourse certainty equivalents (RCE's) of X. Both RCE's compute the "value" of a RV as an optimization problem, and both problems (S) and (B) have meaningful dual problems, stated in terms of the Csiszar -divergence I (p,q) := n X i=1 qi pi qi a generalized entropy function, measuring the distance between RV's with probability vectors p and q. The RCE SU was introduced in (5), studied further in (3), (4) and (6), and applied to production, investment and insurance problems. Here we study the RCE BP, and apply it to problems of inventory control (where the attitude towards risk determines the stock levels and order sizes) and optimal insurance coverage, a problem stated as a game between the insurance company (setting the premiums) and the buyer of insurance, maximizing the RCE of his coverage.

Economics of Radiation Protection: Equity Considerations

In order to implement cost-benefit analysis of protective actions to reduce radiological exposures, one needs to attribute a monetary value to the avoided exposure. Recently, the International Commission on Radiological Protection has stressed the need to take into consideration not only the collective exposure to ionising radiation but also its dispersion in the population. In this paper, by using some well known and some recent results in the economics of uncertainty, we discuss how to integrate these recommendations in the valuation of the benefit of protection.

Log-concave Probability Distributions: Theory and Statistical Testing

This paper studies the broad class of log-concave probability distributions that arise in economics of uncertainty and information. For univariate, continuous, and log-concave random variables we prove useful properties without imposing the dierentiability of density functions. Discrete and multivariate distributions are also discussed. We propose simple non-parametric testing procedures for log-concavity. The test statistics are constructed to test one of the two implications of log-concavity: increasing hazard rates and new-is-better-than-used (NBU) property. The tests for increasing hazard rates are based on normalized spacing of the sample order statistics. The tests for NBU property fall into the category of Hoeding’s U-statistics.

The Role of Risk Management and Insurance: Looking Beyond the Neo-classical Views on the Economics of Uncertainty

The Role of Risk Management and Insurance: Looking Beyond the Neo-classical Views on the Economics of Uncertainty

Does IO Economics Really Make the Case for Investments in IT: Comment on West and Courtney

West and Courtney [18] rely on industrial organization economics in general, and the economics of uncertainty in particular, for insights into the benefits of overcoming information constraints through information systems (IS) and improved information technologies (IT). This Comment argues that the IS researcher who looks to the economics of uncertainty to make a case for improved IT will only find support from a selective reading of a constantly expanding literature whose aims and inferences are easily misunderstood.

The Economics of Uncertainty and Information.

The Economics of Uncertainty and Information may be used in conjunction with Loffont's Fundamentals of Economics in an advanced course in microeconomics. Both texts provide a thorough account of modern thinking on the subject and a wealth of carefully chosen examples and problems.The first four chapters of The Economics of Uncertainty and Information summarize the essential tools of the analysis of uncertainty and information: the theory of individual behavior under uncertainty, the measures of risk aversion and the measures of risk, and the notions of certainty equivalence and information structure. Subsequent chapters introduce the theory of contingent markets, model systems of incomplete markets and define the concept of a perfect foresight equilibrium, cover two fundamental institutions for sharing risk - the stock market and insurance, show how the transmission of information by prices renders information structures endogenous, and study personalized exchange with asymmetric information.Each chapter concludes with a list of suggested readings and with auxiliary sections which go into more detail about certain aspects of the subject. The book concludes with review problems and exercises.Jean Jacques Laffont is Professor of Economic Sciences at the Universite des Sciences Sociales de Toulouse and Director of Studies at I'Ecole des Hautes Etudes en Sciences Sociales.