Arbeitspapier
Bootstrap tests of stochastic dominance with asymptotic similarity in the boundary
We propose a new method of testing stochastic dominance which improves on existing tests based on bootstrap or subsampling. Our test requires estimation of the contact sets between the marginal distributions. Our tests have asymptotic sizes that are exactly equal to the nominal level uniformly over the boundary points of the null hypothesis and are therefore valid over the whole null hypothesis. We also allow the prospects to be indexed by infinite as well as finite dimensional unknown parameters, so that the variables may be residuals from nonparametric and semiparametric models. Our simulation results show that our tests are indeed more powerful than the existing subsampling and recentered bootstrap.
- Language
-
Englisch
- Bibliographic citation
-
Series: cemmap working paper ; No. CWP08/08
- Classification
-
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
Model Evaluation, Validation, and Selection
- Subject
-
Set estimation , Size of test , Unbiasedness , Similarity , Bootstrap , Subsampling
Bootstrap-Verfahren
Stochastischer Prozess
Nichtparametrisches Verfahren
- Event
-
Geistige Schöpfung
- (who)
-
Linton, Oliver
Song, Kyungchul
Whang, Yoon-Jae
- Event
-
Veröffentlichung
- (who)
-
Centre for Microdata Methods and Practice (cemmap)
- (where)
-
London
- (when)
-
2008
- DOI
-
doi:10.1920/wp.cem.2008.0808
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Linton, Oliver
- Song, Kyungchul
- Whang, Yoon-Jae
- Centre for Microdata Methods and Practice (cemmap)
Time of origin
- 2008