Modeling temporal treatment effects with zero inflated semi-parametric regression models: the case of local development policies in France

Hervé Cardot () and Antonio Musolesi ()
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Hervé Cardot: Institut de Mathématiques de Bourgogne, UMR CNRS 5584, Université de Bourgogne Franche-Comté

No 317, SEEDS Working Papers from SEEDS, Sustainability Environmental Economics and Dynamics Studies

Abstract: A semi-parametric approach is considered to estimate the variation along time of the effects of two public policies that were devoted to boost rural development in France. This statistical approach combines the exibility and modularity of additive models with the ability of panel data to deal with selection bias and to allow for the estimation of dynamic treatment effects. Since we face a kind of zero infl ated phenomenon that cannot be dealt with a continuous distribution, we introduce a mixture model with a mass at zero and a continuous density. We find evidence of interesting patterns of temporal treatment effects with relevant nonlinear policy effects. The adopted semi-parametric modeling also offers the possibility of making a counterfactual analysis at an individual level. The methodology is illustrated on a few municipalities for which the evolution of the potential outcomes is estimated and compared under the different possible treatments.

Keywords: Additive Models; Semi-parametric Regression; Panel Data; Policy Evaluation; Temporal Effects; Multiple Treatments; Local Development (search for similar items in EconPapers)
Pages: 44 pages
Date: 2017-08, Revised 2017-08
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Citations: View citations in EconPapers (1)

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http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0317.pdf First version, 2017 (application/pdf)
http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0317.pdf Revised version, 2017 (application/pdf)

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Working Paper: Modeling temporal treatment effects with zero inflated semi-parametric regression models: the case of local development policies in France (2017)
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