sampleSelection: Sample Selection Models

Two-step and maximum likelihood estimation of Heckman-type sample selection models: standard sample selection models (Tobit-2), endogenous switching regression models (Tobit-5), sample selection models with binary dependent outcome variable, interval regression with sample selection (only ML estimation), and endogenous treatment effects models. These methods are described in the three vignettes that are included in this package and in econometric textbooks such as Greene (2011, Econometric Analysis, 7th edition, Pearson).

Version: 1.2-12
Depends: R (≥ 2.10), maxLik (≥ 0.7-3), stats
Imports: miscTools (≥ 0.6-3), systemfit (≥ 1.0-0), Formula (≥ 1.1-1), VGAM (≥ 1.1-1), mvtnorm (≥ 0.9-9994)
Suggests: lmtest, Ecdat
Published: 2020-12-15
DOI: 10.32614/CRAN.package.sampleSelection
Author: Arne Henningsen [aut, cre], Ott Toomet [aut], Sebastian Petersen [ctb]
Maintainer: Arne Henningsen <arne.henningsen at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: sampleSelection citation info
Materials: NEWS
In views: CausalInference, Econometrics
CRAN checks: sampleSelection results


Reference manual: sampleSelection.pdf
Vignettes: Interval Regression with Sample Selection
Sample Selection Models
Using treatReg


Package source: sampleSelection_1.2-12.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sampleSelection_1.2-12.tgz, r-oldrel (arm64): sampleSelection_1.2-12.tgz, r-release (x86_64): sampleSelection_1.2-12.tgz, r-oldrel (x86_64): sampleSelection_1.2-12.tgz
Old sources: sampleSelection archive

Reverse dependencies:

Reverse imports: EMSS, HeckmanEM, localIV, ssmrob, xtsum
Reverse suggests: AER, hpa, marginaleffects, micsr, ssmodels, urbin
Reverse enhances: censReg, prediction, stargazer


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