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This paper shows that popular linear fixed-effects panel-data estimators (first-differences, within-transformation) are biased and inconsistent when applied in a discrete-time hazard setting, that is, one with the outcome variable being a binary dummy indicating an absorbing state, even if the...
Persistent link: https://www.econbiz.de/10012120020
Persistent link: https://www.econbiz.de/10002644261
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...
Persistent link: https://www.econbiz.de/10009669647
Persistent link: https://www.econbiz.de/10010398949
This paper demonstrates that popular linear fixed-effects panel-data estimators are biased andinconsistent when applied in a discrete-time hazard setting - that is, one in which the outcomevariable is a binary dummy indicating an absorbing state, even if the data-generating process isfully...
Persistent link: https://www.econbiz.de/10012514912
Persistent link: https://www.econbiz.de/10013429687
The classical Heckman (1976, 1979) selection correction estimator (heckit) is mis-specified and inconsistent if an interaction of the outcome variable and an explanatory variable matters for selection. To address this specifi cation problem, a full information maximum likelihood estimator and a...
Persistent link: https://www.econbiz.de/10014164886
The classical Heckman (1976, 1979) selection correction estimator (heckit) is misspecified and inconsistent, if an interaction of the outcome variable with an explanatory variable matters for selection. To address this specification problem, a full information maximum likelihood (FIML) estimator...
Persistent link: https://www.econbiz.de/10011489191
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...
Persistent link: https://www.econbiz.de/10010344665
When analyzing what determines the efficiency of production, regressing efficiency scores estimated by DEA on explanatory variables has much intuitive appeal. Simar and Wilson (2007) show that this nai͏̈ve two-stage estimation procedure suffers from severe flaws, that render its results, and...
Persistent link: https://www.econbiz.de/10011854094