Arbeitspapier

Semiparametric selection models with binary outcomes

This paper addresses the estimation of a semiparametric sample selection index model where both the selection rule and the outcome variable are binary. Since the marginal effects are often of primary interest and are difficult to recover in a semiparametric setting, we develop estimators for both the marginal effects and the underlying model parameters. The marginal effect estimator uses only observations where the selection probability is above a certain threshold. A key innovation is that this high probability set is adaptive to the data. The model parameter estimator is a quasi-likelihood estimator based on regular kernels with bias corrections. We establish their large sample properties and provide simulation evidence confirming that these estimators perform well in finite samples.

Sprache
Englisch

Erschienen in
Series: Working Paper ; No. 2014-03

Klassifikation
Wirtschaft
Thema
Semiparametric Binary Selection
Marginal Effects

Ereignis
Geistige Schöpfung
(wer)
Klein, Roger
Shen, Chan
Vella, Francis
Ereignis
Veröffentlichung
(wer)
Rutgers University, Department of Economics
(wo)
New Brunswick, NJ
(wann)
2014

Handle
Letzte Aktualisierung
20.09.2024, 08:23 MESZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Klein, Roger
  • Shen, Chan
  • Vella, Francis
  • Rutgers University, Department of Economics

Entstanden

  • 2014

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