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
Part IV - Binary–Discrete Choice Minimum Power Divergence (MPD) Measures
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
Binary–Discrete Choice Minimum Power Divergence (MPD) Measures
Continuing with the Cressie-Read family of divergence measures, in Part IV we identify a new class of probability distributions and associated likelihood functions for the binary response model. MPD estimators, as well as empirical maximum likelihood (EML) estimators, for the binary response model are specified, asymptotic properties are assessed, and sampling experiments are used to illustrate finite sample performance. The resulting MPD class of distributions and associated estimators subsume the conventional logit model-estimator.
- Type
- Chapter
- Information
- An Information Theoretic Approach to Econometrics , pp. 167 - 168Publisher: Cambridge University PressPrint publication year: 2011