Sample Selection Models in R: Package sampleSelection

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Standard

Sample Selection Models in R: Package sampleSelection. / Toomet, Ott; Henningsen, Arne.

I: Journal of Statistical Software, Bind 27, Nr. 7, 2008, s. 1-23.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Toomet, O & Henningsen, A 2008, 'Sample Selection Models in R: Package sampleSelection', Journal of Statistical Software, bind 27, nr. 7, s. 1-23. <http://www.jstatsoft.org/v27/i07>

APA

Toomet, O., & Henningsen, A. (2008). Sample Selection Models in R: Package sampleSelection. Journal of Statistical Software, 27(7), 1-23. http://www.jstatsoft.org/v27/i07

Vancouver

Toomet O, Henningsen A. Sample Selection Models in R: Package sampleSelection. Journal of Statistical Software. 2008;27(7):1-23.

Author

Toomet, Ott ; Henningsen, Arne. / Sample Selection Models in R: Package sampleSelection. I: Journal of Statistical Software. 2008 ; Bind 27, Nr. 7. s. 1-23.

Bibtex

@article{5bcb73303af611dfad7f000ea68e967b,
title = "Sample Selection Models in R: Package sampleSelection",
abstract = "This paper describes the implementation of Heckman-type sample selection models in R. We discuss the sample selection problem as well as the Heckman solution to it, and argue that although modern econometrics has non- and semiparametric estimation methods in its toolbox, Heckman models are an integral part of the modern applied analysis and econometrics syllabus. We describe the implementation of these models in the package sampleSelection and illustrate the usage of the package on several simulation and real data examples. Our examples demonstrate the effect of exclusion restrictions, identification at infinity and misspecification. We argue that the package can be used both in applied research and teaching.",
author = "Ott Toomet and Arne Henningsen",
year = "2008",
language = "English",
volume = "27",
pages = "1--23",
journal = "Journal of Statistical Software",
issn = "1548-7660",
publisher = "The Foundation for Open Access Statistics",
number = "7",

}

RIS

TY - JOUR

T1 - Sample Selection Models in R: Package sampleSelection

AU - Toomet, Ott

AU - Henningsen, Arne

PY - 2008

Y1 - 2008

N2 - This paper describes the implementation of Heckman-type sample selection models in R. We discuss the sample selection problem as well as the Heckman solution to it, and argue that although modern econometrics has non- and semiparametric estimation methods in its toolbox, Heckman models are an integral part of the modern applied analysis and econometrics syllabus. We describe the implementation of these models in the package sampleSelection and illustrate the usage of the package on several simulation and real data examples. Our examples demonstrate the effect of exclusion restrictions, identification at infinity and misspecification. We argue that the package can be used both in applied research and teaching.

AB - This paper describes the implementation of Heckman-type sample selection models in R. We discuss the sample selection problem as well as the Heckman solution to it, and argue that although modern econometrics has non- and semiparametric estimation methods in its toolbox, Heckman models are an integral part of the modern applied analysis and econometrics syllabus. We describe the implementation of these models in the package sampleSelection and illustrate the usage of the package on several simulation and real data examples. Our examples demonstrate the effect of exclusion restrictions, identification at infinity and misspecification. We argue that the package can be used both in applied research and teaching.

M3 - Journal article

VL - 27

SP - 1

EP - 23

JO - Journal of Statistical Software

JF - Journal of Statistical Software

SN - 1548-7660

IS - 7

ER -

ID: 18899432