Book contents
- Frontmatter
- Contents
- Preface
- One Econometric Information Recovery
- Part I Traditional Parametric and Semiparametric Econometric Models: Estimation and Inference
- Part II Formulation and Solution of Stochastic Inverse Problems
- Part III A Family of Minimum Discrepancy Estimators
- Part IV Binary–Discrete Choice Minimum Power Divergence (MPD) Measures
- Part V Optimal Convex Divergence
- Abbreviations
- Index
Preface
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- One Econometric Information Recovery
- Part I Traditional Parametric and Semiparametric Econometric Models: Estimation and Inference
- Part II Formulation and Solution of Stochastic Inverse Problems
- Part III A Family of Minimum Discrepancy Estimators
- Part IV Binary–Discrete Choice Minimum Power Divergence (MPD) Measures
- Part V Optimal Convex Divergence
- Abbreviations
- Index
Summary
In one sense, the idea for this book started 15 years ago with a six-hour meeting of the two authors between planes at the O’Hare Hilton. At this meeting, maximum entropy and empirical likelihood principles were the major areas of discussion. Since that time the two of us have worked together and have only looked forward. As a result, Econometric Foundations appeared in 2000, and a range of related information theoretic articles emerged in the last decade. Pieces of some of these articles appear in this book.
This book was a pleasure to write. We hope the reader will feel our enthusiasm in entering the information theoretic world and leaving behind many conventional econometric methods that we spent a good part of our lives learning.
- Type
- Chapter
- Information
- An Information Theoretic Approach to Econometrics , pp. xv - xviPublisher: Cambridge University PressPrint publication year: 2011