Arbeitspapier
Estimating Selection Models without Instrument with Stata
This article presents the eqregsel command for implementing the estimation and bootstrap inference of sample selection models via extremal quantile regression. The command estimates a semiparametric sample selection model without instrument or large support regressor, and outputs the point estimates of the homogenous linear coefficients, their bootstrap standard errors, as well as the p-value for a specification test.
- Language
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Englisch
- Bibliographic citation
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Series: IZA Discussion Papers ; No. 12486
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Single Equation Models; Single Variables: Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
Econometric Software
Wage Level and Structure; Wage Differentials
- Subject
-
extremal quantile regressions
sample selection models
eqregsel
- Event
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Geistige Schöpfung
- (who)
-
D'Haultfœuille, Xavier
Maurel, Arnaud
Qiu, Xiaoyun
Zhang, Yichong
- Event
-
Veröffentlichung
- (who)
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Institute of Labor Economics (IZA)
- (where)
-
Bonn
- (when)
-
2019
- Handle
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the 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
- D'Haultfœuille, Xavier
- Maurel, Arnaud
- Qiu, Xiaoyun
- Zhang, Yichong
- Institute of Labor Economics (IZA)
Time of origin
- 2019
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Iassopack: Model Selection and Prediction with Regularized Regression in Stata
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Estimating Fourier-sparse signals without a frequency gap
Estimating a semi-parametric duration model without specifying heterogeneity
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Estimating the gravity model without gravity using panel data
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