Testing exclusion restrictions and additive separability in sample selection models

Martin Huber, Giovanni Mellace

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

Standard sample selection models with non-randomly censored outcomes assume (i) an exclusion restriction (i.e., a variable affecting selection, but not the outcome) and (ii) additive separability of the errors in the selection process. This paper proposes tests for the joint satisfaction of these assumptions by applying the approach of Huber and Mellace (Testing instrument validity for LATE identification based on inequality moment constraints, 2011) (for testing instrument validity under treatment endogeneity) to the sample selection framework. We show that the exclusion restriction and additive separability imply two testable inequality constraints that come from both point identifying and bounding the outcome distribution of the subpopulation that is always selected/observed. We apply the tests to two variables for which the exclusion restriction is frequently invoked in female wage regressions: non-wife/husband’s income and the number of (young) children. Considering eight empirical applications, our results suggest that the identifying assumptions are likely violated for the former variable, but cannot be refuted for the latter on statistical grounds.
OriginalsprogEngelsk
TidsskriftEmpirical Economics
Vol/bind47
Udgave nummer1
Sider (fra-til)75-92
ISSN0377-7332
StatusUdgivet - aug. 2014

Fingeraftryk

Sample Selection
Selection Model
Separability
exclusion
Restriction
Testing
Endogeneity
Moment Inequalities
Wages
Variable Selection
Inequality Constraints
Regression
Likely
husband
Imply
wage
income
regression
Sample selection model
Exclusion

Citer dette

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Testing exclusion restrictions and additive separability in sample selection models. / Huber, Martin; Mellace, Giovanni.

I: Empirical Economics, Bind 47, Nr. 1, 08.2014, s. 75-92.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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AB - Standard sample selection models with non-randomly censored outcomes assume (i) an exclusion restriction (i.e., a variable affecting selection, but not the outcome) and (ii) additive separability of the errors in the selection process. This paper proposes tests for the joint satisfaction of these assumptions by applying the approach of Huber and Mellace (Testing instrument validity for LATE identification based on inequality moment constraints, 2011) (for testing instrument validity under treatment endogeneity) to the sample selection framework. We show that the exclusion restriction and additive separability imply two testable inequality constraints that come from both point identifying and bounding the outcome distribution of the subpopulation that is always selected/observed. We apply the tests to two variables for which the exclusion restriction is frequently invoked in female wage regressions: non-wife/husband’s income and the number of (young) children. Considering eight empirical applications, our results suggest that the identifying assumptions are likely violated for the former variable, but cannot be refuted for the latter on statistical grounds.

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