Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79698
Authors: 
Tauchmann, Harald
Reichert, Arndt
Year of Publication: 
2013
Series/Report no.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2013: Wettbewerbspolitik und Regulierung in einer globalen Wirtschaftsordnung - Session: Microeconometrics D20-V2
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.
JEL: 
C24
C93
I12
Document Type: 
Conference Paper

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