Principal Stratification in sample selection problems with non normal error terms

Giovanni Mellace and Roberto Rocci

No 194, CEIS Research Paper from Tor Vergata University, CEIS

Abstract: The aim of the paper is to relax distributional assumptions on the error terms, often imposed in parametric sample selection models to estimate causal effects, when plausible exclusion restrictions are not available. Within the principal stratification framework, we approximate the true distribution of the error terms with a mixture of Gaussian. We propose an EM type algorithm for ML estimation. In a simulation study we show that our estimator has lower MSE than the ML and two-step Heckman estimators with any non normal distribution considered for the error terms. Finally we provide an application to the Job Corps training program.

Keywords: Causal inference; principal stratification; mixture models; EM algorithm; sample selection. (search for similar items in EconPapers)
JEL-codes: C10 C13 C31 C34 C38 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2011-05-02, Revised 2011-05-02
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://ceistorvergata.it/RePEc/rpaper/RP194.pdf Main text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rtv:ceisrp:194

Ordering information: This working paper can be ordered from
CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
https://ceistorvergata.it

Access Statistics for this paper

More papers in CEIS Research Paper from Tor Vergata University, CEIS CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma. Contact information at EDIRC.
Bibliographic data for series maintained by Barbara Piazzi ().