Estimation of panel data models with binary indicators when treatment effects are not constant over time
AbstractWe show that two commonly employed estimation procedures to deal with correlated unobserved heterogeneity in panel data models, within-groups and first-differenced OLS, can lead to very different estimates of treatment effects when these are not constant over time and treatment is a state that only changes occasionally. It is therefore important to allow for flexible time varying treatment effects when estimating panel data models with binary indicator variables as is illustrated by an example of the effects of marital status on mental wellbeing.
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Bibliographic InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 88 (2005)
Issue (Month): 3 (September)
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Web page: http://www.elsevier.com/locate/ecolet
Other versions of this item:
- Audrey Laporte & Frank Windmeijer, 2005. "Estimation of Panel Data Models with Binary Indicators when Treatment Effects are not Constant over Time," Working Papers laporte-04-01, University of Toronto, Department of Economics.
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
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- Katharina Hauck & Nigel Rice, 2004. "A longitudinal analysis of mental health mobility in Britain," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 981-1001.
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