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Estimation of Panel Data Models with Binary Indicators when Treatment Effects are not Constant over Time

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Author Info
Audrey Laporte
Frank Windmeijer

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Abstract

We 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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File URL: http://repec.economics.utoronto.ca/files/UT-ECIPA-LAPORTE-04-01.pdf
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Publisher Info
Paper provided by University of Toronto, Department of Economics in its series Working Papers with number laporte-04-01.

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Length: 10 pages
Date of creation: 11 Mar 2005
Date of revision:
Handle: RePEc:tor:tecipa:laporte-04-01

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Related research
Keywords: panel data; treatment effects.;

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Find related papers by JEL classification:
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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References listed on IDEAS
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  1. 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. [Downloadable!]
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