Robustness
1st Edition
Published on 22. August 2016
464 pages
978-1-4008-2938-5 (ISBN)
Description
The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted?
Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics.
Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.
Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics.
Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.
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Lars Peter Hansen | Thomas J. Sargent
Robustness
Book
06/2016
Princeton University Press
€37.70
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Lars Peter Hansen | Thomas J. Sargent
Robustness
Book
11/2007
Princeton University Press
€76.75
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Persons
Lars Peter Hansen is the Homer J. Livingston Distinguished Service Professor in the Department of Economics at the University of Chicago. Thomas J. Sargent is professor of economics at New York University and senior fellow at the Hoover Institution. He is the author of The Conquest of American Inflation and the coauthor of The Big Problem of Small Change (both Princeton).
Content
Preface xv
Acknowledgments xvii
Part I: Motivation and main ideas
Chapter 1: Introduction 3
Chapter 2: Basic ideas and methods 25
Chapter 3: A stochastic formulation 53
Part II: Standard control and filtering
Chapter 4: Linear control theory 67
Chapter 5: The Kalman filter 103
Part III: Robust control
Chapter 6: Static multiplier and constraint games 119
Chapter 7: Time domain games for attaining robustness 139
Chapter 8: Frequency domain games and criteria for robustness 173
Chapter 9: Calibrating misspecification fears with detection error probabilities 213
Chapter 10: A permanent income model 223
Part IV: Multi-agent problems
Chapter 11: Competitive equilibria without robustness 253
Chapter 12: Competitive equilibria with robustness 271
Chapter 13: Asset pricing 295
Chapter 14: Risk sensitivity, model uncertainty, and asset pricing 307
Chapter 15: Markov perfect equilibria with robustness 327
Chapter 16: Robustness in forward-looking models 333
Part V: Robust estimation and filtering
Chapter 17: Robust filtering with commitment 359
Chapter 18: Robust filtering without commitment 383
Part VI: Extensions
Chapter 19: Alternative approaches 403
References 413
Index 427
Author Index 431
Matlab Index 435
Acknowledgments xvii
Part I: Motivation and main ideas
Chapter 1: Introduction 3
Chapter 2: Basic ideas and methods 25
Chapter 3: A stochastic formulation 53
Part II: Standard control and filtering
Chapter 4: Linear control theory 67
Chapter 5: The Kalman filter 103
Part III: Robust control
Chapter 6: Static multiplier and constraint games 119
Chapter 7: Time domain games for attaining robustness 139
Chapter 8: Frequency domain games and criteria for robustness 173
Chapter 9: Calibrating misspecification fears with detection error probabilities 213
Chapter 10: A permanent income model 223
Part IV: Multi-agent problems
Chapter 11: Competitive equilibria without robustness 253
Chapter 12: Competitive equilibria with robustness 271
Chapter 13: Asset pricing 295
Chapter 14: Risk sensitivity, model uncertainty, and asset pricing 307
Chapter 15: Markov perfect equilibria with robustness 327
Chapter 16: Robustness in forward-looking models 333
Part V: Robust estimation and filtering
Chapter 17: Robust filtering with commitment 359
Chapter 18: Robust filtering without commitment 383
Part VI: Extensions
Chapter 19: Alternative approaches 403
References 413
Index 427
Author Index 431
Matlab Index 435
