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The need to understand the theories and applications of economic and finance risk has been clear to everyone since the financial crisis, and this collection of original essays proffers broad, high-level explanations of risk and uncertainty. The economics of risk and uncertainty is unlike most branches of economics in spanning from the individual decision-maker to the market (and indeed, social decisions), and ranging from purely theoretical analysis through individual experimentation, empirical analysis, and applied and policy decisions. It also has close and sometimes conflicting relationships with theoretical and applied statistics, and psychology. The aim of this volume is to provide an overview of diverse aspects of this field, ranging from classical and foundational work through current developments. - Presents coherent summaries of risk and uncertainty that inform major areas in economics and finance - Divides coverage between theoretical, empirical, and experimental findings - Makes the economics of risk and uncertainty accessible to scholars in fields outside economics
Updates and advances the theory of expected utility as applied to risk analysis and financial decision making.
A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.
At its core, economics is about making decisions. In the history of economic thought, great intellectual prowess has been exerted toward devising exquisite theories of optimal decision making in situations of constraint, risk, and scarcity. Yet not all of our choices are purely logical, and so there is a longstanding tension between those emphasizing the rational and irrational sides of human behavior. One strand develops formal models of rational utility maximizing while the other draws on what behavioral science has shown about our tendency to act irrationally. In Risk, Choice, and Uncertainty, George G. Szpiro offers a new narrative of the three-century history of the study of decision making, tracing how crucial ideas have evolved and telling the stories of the thinkers who shaped the field. Szpiro examines economics from the early days of theories spun from anecdotal evidence to the rise of a discipline built around elegant mathematics through the past half century’s interest in describing how people actually behave. Considering the work of Locke, Bentham, Jevons, Walras, Friedman, Tversky and Kahneman, Thaler, and a range of other thinkers, he sheds light on the vast scope of discovery since Bernoulli first proposed a solution to the St. Petersburg Paradox. Presenting fundamental mathematical theories in easy-to-understand language, Risk, Choice, and Uncertainty is a revelatory history for readers seeking to grasp the grand sweep of economic thought.
A comprehensive framework for assessing strategies for managing risk and uncertainty, integrating theory and practice and synthesizing insights from many fields. This book offers a framework for making decisions under risk and uncertainty. Synthesizing research from economics, finance, decision theory, management, and other fields, the book provides a set of tools and a way of thinking that determines the relative merits of different strategies. It takes as its premise that we make better decisions if we use the whole toolkit of economics and related fields to inform our decision making. The text explores the distinction between risk and uncertainty and covers standard models of decision making under risk as well as more recent work on decision making under uncertainty, with a particular focus on strategic interaction. It also examines the implications of incomplete markets for managing under uncertainty. It presents four core strategies: a benchmark strategy (proceeding as if risk and uncertainty were low), a financial hedging strategy (valuable if there is much risk), an operational hedging strategy (valuable for conditions of much uncertainty), and a flexible strategy (valuable if there is much risk and/or uncertainty). The book then examines various aspects of these strategies in greater depth, building on empirical work in several different fields. Topics include price-setting, real options and Monte Carlo techniques, organizational structure, and behavioral biases. Many chapters include exercises and appendixes with additional material. The book can be used in graduate or advanced undergraduate courses in risk management, as a guide for researchers, or as a reference for management practitioners.
The compilation of ground-breaking papers contained in this collection offers a complete description of the evolution of knowledge in the economics of risk and time, from its early twentieth-century explorations to its current diversity of approaches. The papers focus first on the basic decisions under uncertainty, and then on asset pricing. They cover both classical expected utility approach and its non-expected utility generalizations, with applications to dynamic portfolio choices, insurance, risk sharing, and risk prevention. Prefaced by an original introduction from the editor, this collection will be valuable for scholars in finance and macroeconomics, particularly those with an interest in the modeling foundations of consumer and investor decisions under uncertainty.
This book critically discusses and systematically compares J.M. Keynes and F. H. Knight, two giants in the history of economic thought. In 1921 they both published apparently similar books on risk, probability, and uncertainty. However, while Knight's contribution on risk and uncertainty is now well recognized, Keynes's work on probability and uncertainty has been somewhat ignored in the shadow of his more famous The General Theory of Employment, Interest and Money (1936). Focusing on an earlier yet equally important volume by Keynes, A Treatise on Probability (1921), this book sheds a light on his outstanding ideas and the lasting influence on his later works, including The General Theory. There are few books that systematically discuss Keynes and Knight, although there are remarkable comparisons between Keynes's concept of probability and uncertainty and Knight's distinction between a measurable risk and a non-measurable uncertainty. This timely book unifies Keynes and Knight into a new, comprehensive approach to a very complex human behavior
Annotation This book contains a collection of papers that address various aspects of risk, including riskmanagement and how it is applied to decisionmaking and the impact of risk on markets
Risks and uncertainties?market, financial, operational, social, humanitarian, environmental, and institutional?are the inherent realities of the modern world. Stock market crashes, demonetization of currency, and climate change constitute just a few examples that can adversely impact financial institutions across the globe. To mitigate these risks and avoid a financial crisis, a better understanding of how the economy responds to uncertainties is needed. Maintaining Financial Stability in Times of Risk and Uncertainty is an essential reference source that discusses how risks and uncertainties affect the financial stability and security of individuals and institutions, as well as probable solutions to mitigate risk and achieve financial resilience under uncertainty. Featuring research on topics such as financial fraud, insurance ombudsman, and Knightian uncertainty, this book is developed for researchers, academicians, policymakers, students, and scholars.
This edited volume looks at whether it is possible to be more transparent about uncertainty in scientific evidence without undermining public understanding and trust. With contributions from leading experts in the field, this book explores the communication of risk and decision-making in an increasingly post-truth world. Drawing on case studies from climate change to genetic testing, the authors argue for better quality evidence synthesis to cut through the noise and highlight the need for more structured public dialogue. For uncertainty in scientific evidence to be communicated effectively, they conclude that trustworthiness is vital: the data and methods underlying statistics must be transparent, valid, and sound, and the numbers need to demonstrate practical utility and add social value to people’s lives. Presenting a conceptual framework to help navigate the reader through the key social and scientific challenges of a post-truth era, this book will be of great relevance to students, scholars, and policy makers with an interest in risk analysis and communication.