Buch, Englisch, 248 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 518 g
Buch, Englisch, 248 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 518 g
ISBN: 978-0-521-86959-1
Verlag: Cambridge University Press
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Informationstheorie, Kodierungstheorie
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
Weitere Infos & Material
Preface; 1. Econometric information recovery; Part I. Traditional Parametric and Semiparametric Probability Models: Estimation and Inference: 2. Formulation and analysis of parametric and semiparametric linear models; 3. Method of moments, GMM, and estimating equations; Part II. Formulation and Solution of Stochastic Inverse Problems: 4. A stochastic-empirical likelihood inverse problem: formulation and estimation; 5. A stochastic-empirical likelihood inverse problem: inference; 6. Kullback-Leibler information and the maximum empirical exponential likelihood; Part III. A Family of Minimum Discrepancy Estimators: 7. The Cressie-Read family of divergence measures and likelihood functions; 8. Cressie-Read-MEL-type estimators in practice: evidence of estimation and inference sampling performance; Part IV. Binary Discrete Choice MPD-EML Econometric Models: 9. Family of distribution functions for the binary response-choice model; 10. Estimation and inference for the binary response model based on the MPD family of distributions; Part V. Optimal Convex Divergence: 11. Choosing the optimal divergence under quadratic loss; 12. Epilogue.