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Title:When outcome heterogeneously matters for selection: A generalized selection correction estimator PDF Logo
Authors:Reichert, Arndt
Tauchmann, Harald
Issue Date:2012
Series/Report no.:Ruhr Economic Papers 372
Abstract:The classical Heckman (1976, 1979) selection correction estimator (heckit) is misspecified and inconsistent if an interaction of the outcome variable and an explanatory variable matters for selection. To address this specification problem, a full information maximum likelihood estimator and a simple two-step estimator are developed. Monte-Carlo simulations illustrate that the bias of the ordinary heckit estimator is removed by these generalized estimation procedures. Along with OLS and the ordinary heckit procedure, we apply these estimators to data from a randomized trial that evaluates the effectiveness of financial incentives for weight loss among the obese. Estimation results indicate that the choice of the estimation procedure clearly matters.
Subjects:selection bias
interaction
heterogeneity
generalized estimator
JEL:C24
C93
Persistent Identifier of the first edition:doi:10.4419/86788427
ISBN:978-3-86788-427-3
Document Type:Working Paper
Appears in Collections:Publikationen von Forscherinnen und Forschern des RWI
Ruhr Economic Papers, RWI

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