Instrumental variable estimation of treatment effects for duration outcomes
AbstractIn this article we propose and implement an instrumental variable estimation procedure to obtain treatment effects on duration outcomes. The method can handle the typical complications that arise with duration data of time-varying treatment and censoring. The treatment effect we define is in terms of shifting the quantiles of the outcome distribution based on the Generalized Accelerated Failure Time (GAFT) model. The GAFT model encompasses two competing approaches to duration data; the (Mixed) Proportional Hazard (MPH) model and the Accelerated Failure Time (AFT) model. We discuss the large sample properties of the proposed Instrumental Variable Linear Rank (IVLR), and show how we can, with one additional step, improve upon its efficiency. We discuss the empiricalimplementation of the estimator and apply it to the Illinois re-employment bonus experiment.
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Bibliographic InfoPaper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2007-20.
Date of creation: 21 Jun 2007
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censoring; duration model; instrumental variable; treatment effect;
Other versions of this item:
- Bijwaard, Govert, 2007. "Instrumental Variable Estimation of Treatment Effects for Duration Outcomes," IZA Discussion Papers 2896, Institute for the Study of Labor (IZA).
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
- J64 - Labor and Demographic Economics - - Mobility, Unemployment, and Vacancies - - - Unemployment: Models, Duration, Incidence, and Job Search
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