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.

Preface Acknowledgment Part I: Motivation and main ideas 1. Introduction 2. Basic ideas and methods 3. A stochastic formulation Part II: Standard control and filtering 4. Lingear control theory 5. The Kalman filter part III: robust control 6. Time domain games for robustness 7. Frequency domain games and criteria for robustness 8. Calibrating θ with detection probabilities 9. A permanent income model 10. Competitive equilibrium models 11. Competitive equilibrium under robustness 12. Asset pricing Part IV: Robust filtering 13. A robust filtering problem 14. Joint control and estimation Part V: More applications 15. Multiple agents 16. Robustness in forward looking models 17. Non-linear models 18. Ramsey plans 19. References 20. Index 21. Author Index 22. Matlab Index