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.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP08/08

Klassifikation
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
Model Evaluation, Validation, and Selection
Thema
Set estimation , Size of test , Unbiasedness , Similarity , Bootstrap , Subsampling
Bootstrap-Verfahren
Stochastischer Prozess
Nichtparametrisches Verfahren

Ereignis
Geistige Schöpfung
(wer)
Linton, Oliver
Song, Kyungchul
Whang, Yoon-Jae
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2008

DOI
doi:10.1920/wp.cem.2008.0808
Handle
Letzte Aktualisierung
10.03.2025, 11:45 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Linton, Oliver
  • Song, Kyungchul
  • Whang, Yoon-Jae
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2008

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