Quantile Regression in the Presence of Sample Selection
AbstractMost sample selection models assume that the errors are independent of the regressors. Under this assumption, all quantile and mean functions are parallel, which implies that quantile estimators cannot reveal any (per definition non-existing) heterogeneity. However, quantile estimators are useful for testing the independence assumption, because they are consistent under the null hypothesis. We propose tests for this crucial restriction that are based on the entire conditional quantile regression process after correcting for sample selection bias. Monte Carlo simulations demonstrate that they are powerful and two empirical illustrations indicate that violations of this assumption are likely to be ubiquitous in labor economics.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by University of St. Gallen, School of Economics and Political Science in its series Economics Working Paper Series with number 1109.
Length: 33 pages
Date of creation: Mar 2011
Date of revision:
Sample selection; quantile regression; independence; test;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Louis N. Christofides & Alexandros Polycarpou & Konstantinos Vrachimis, 2013.
"Gender Wage Gaps, 'Sticky Floors' and 'Glass Ceilings' in Europe,"
1301, University of Guelph, Department of Economics.
- Louis N. Christofides & Alexandros Polycarpou & Konstantinos Vrachimis, 2013. "Gender Wage Gaps, ‘Sticky Floors’ and ‘Glass Ceilings’ in Europe," University of Cyprus Working Papers in Economics 02-2013, University of Cyprus Department of Economics.
- DOORLEY Karina & SIERMINSKA Eva, 2011. "Beauty and the beast in the labor market: Evidence from a distribution regression approach," CEPS/INSTEAD Working Paper Series 2011-62, CEPS/INSTEAD.
- Schwiebert, Jörg, 2012. "Semiparametric Estimation of a Sample Selection Model in the Presence of Endogeneity," Diskussionspapiere der Wirtschaftswissenschaftlichen FakultÃ¤t der Leibniz UniversitÃ¤t Hannover dp-504, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- Huber, Martin & Mellace, Giovanni, 2011. "Sharp bounds on causal effects under sample selection," Economics Working Paper Series 1134, University of St. Gallen, School of Economics and Political Science.
- Martin Huber & Blaise Melly, 2012. "A test of the conditional independence assumption in sample selection models," Working Papers 2012-11, Brown University, Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Martina Flockerzi).
If references are entirely missing, you can add them using this form.