Semiparametric Efficiency Bounds for Microeconometric Models
A Survey
(Sprache: Englisch)
Semiparametric Efficiency Bounds for Microeconometric Models: A Survey offers a partial review of the vast literature in econometrics and statistics on calculating semiparametric efficiency bounds for a large class of models used in applied economics...
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Semiparametric Efficiency Bounds for Microeconometric Models: A Survey offers a partial review of the vast literature in econometrics and statistics on calculating semiparametric efficiency bounds for a large class of models used in applied economics research. The main role of the efficiency bound is to give a lower bound to the asymptotic variance of an estimator. An estimator with asymptotic variance equal to the efficiency bound can therefore be said to be asymptotically efficient. These bounds are also useful for understanding how the features of a given model affect the accuracy of parameter estimation. This monograph will help researchers learn more about efficiency bounds, their calculation, and their usefulness in semiparametric estimation, in an accessible manner.
Inhaltsverzeichnis zu „Semiparametric Efficiency Bounds for Microeconometric Models “
Introduction; 1. Efficiency bounds; 2. Population mean; 3. Population quantiles; 4. Distribution functions without auxiliary information; 5. Distribution functions with auxiliary information; 6. Functionals of conditional expectations; 7. Partially linear models; 8. Binary choice models; 9. Density weighted average derivatives; 10. Unconditional moment restriction models; 11. Conditional moment restriction models; 12. Linear models; 13. Moment condition models and stratified sampling; 14. Censored models; 15. Nonparametric regression with endogenous regressors; 16. Conclusion; Appendices; References.
Bibliographische Angaben
- Autoren: Thomas A. Severini , Gautam Tripathi
- 258 Seiten, Maße: 15,6 x 23,4 cm, Taschenbuch, Englisch
- Verlag: Now Publishers Inc
- ISBN-10: 160198734X
- ISBN-13: 9781601987341
- Erscheinungsdatum: 29.11.2013
Sprache:
Englisch
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