Robustness / Lars Peter Hansen, Thomas J. Sargent.

Preface, xv -- Acknowledgments, xvii -- Part I. Motivation and main ideas -- Introduction, 3 -- 2. Basic ideas and methods, 25 -- 3. A stochastic formulation, 53 -- Part II. Standard control and filtering -- 4. Linear control theory, 67 -- 5. The kalman filter, 103 -- Part III. Robust control -- 6. Static multiplier and constraint games, 119 -- 7. Time domain games for attaining robustness, 139 -- 8. Frequency domain games and criteria for robustness, 173 -- Calibrating misspecification fears with detection error probabilities, 213 -- 10. A permanent income model, 223 -- Part IV. Multi-agent problems -- 11. Competitive equilibria without robustness, 253 -- 12. Competitive equilibria with robustness, 271 -- 13. Asset pricing, 29514. Risk sensitivity, model uncertainty, and asset pricing, 307 -- 15. Markov perfect equilibria with robustness, 327 -- 16. Robustness in forward-looking models, 333 -- Part V. Robust estimation and filtering -- 17. Robust filtering with commitment, 359 -- 18. Robust filtering without commitment, 383 -- Part VI. Extensions -- 19. Alternative approaches, 403 -- References, 413 -- Index, 427 -- Author index, 431 -- Matlab index, 435

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.