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 InfoPaper provided by University of Toronto, Department of Economics in its series Working Papers with number laporte-04-01.
Length: 10 pages
Date of creation: 11 Mar 2005
Date of revision:
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panel data; treatment effects.;
Other versions of this item:
- Laporte, Audrey & Windmeijer, Frank, 2005. "Estimation of panel data models with binary indicators when treatment effects are not constant over time," Economics Letters, Elsevier, vol. 88(3), pages 389-396, September.
- 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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