For all its elaborate theories and models, economics always reduces to comparisons. Should we build A rather than B? Will I be better off if I eat D rather than C? How much will it cost me to produce F instead of E? At root, the ultimate goal of economics is simple: assessing the alternatives and finding the best possible outcome. This basic mathematical concept underlies all introductions to the field of economics, yet as advanced students progress through the discipline, they often lose track of this foundational idea when presented with real-world complications and uncertainty. In Competitive Agents in Certain and Uncertain Markets, Robert G. Chambers develops an integrated analytic framework for treating consumer, producer, and market equilibrium analyses as special cases of a generic optimization problem. He builds on lessons learned by all beginning students of economics to show how basic concepts can still be applied even in complex and highly uncertain conditions. Drawing from optimization theory, Chambers demonstrates how the same unified mathematical framework applies to both stochastic and non-stochastic decision settings. The book borrows from both convex and variational analysis and gives special emphasis to differentiability, conjugacy theory, and Fenchel's Duality Theorem. Throughout, Chambers includes practical examples, problems, and exercises to make abstract material accessible. Bringing together essential theoretical tools for understanding decision-making under uncertainty, Competitive Agents in Certain and Uncertain Markets provides a unified framework for analyzing a broad range of microeconomic decisions. This book will be an invaluable resource for advanced graduate students and scholars of microeconomic theory.

This book demonstrates 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. The authors demonstrate that dual methods apply under uncertainty and that the dual representations can be developed for stochastic technologies. Moreover, proper exploitation of the properties of alternative primal and dual representations of preferences allows analysts to generalize and extend the results of the existing literature on preferences under uncertainty, thus making expected-utility theory largely superfluous for many decisions.

This book demonstrates 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. The authors demonstrate that dual methods apply under uncertainty and that the dual representations can be developed for stochastic technologies. Moreover, proper exploitation of the properties of alternative primal and dual representations of preferences allows analysts to generalize and extend the results of the existing literature on preferences under uncertainty, thus making expected-utility theory largely superfluous for many decisions.

This book contains a modern treatment of production economics from a dual perspective, with a special emphasis on recent developments in the field. The book prepares the reader to apply the tools and concepts of the dual approach production economics to real world problems and data sets. Among other topics covered are flexible function forms, aggregation across inputs and outputs using the theory of separable structures, aggregation over economic optimizing firms, the representation of multioutput technologies, and the analysis and measurement of technical change from both a primal and dual perspective.