Unconditional and Conditional Quantile Treatment Effect: Identification Strategies and Interpretations
AbstractThis paper reviews strategies that allow one to identify the effects of policy interventions on the unconditional or conditional distribution of the outcome of interest. This distiction is irrelevant when one focuses on average treatment effects since identifying assumptions typically do not affect the parameter's interpretation. Conversely, finding the appropriate answer to a research question on the effects over the distribution requires particular attention in the choice of the identification strategy. Indeed, quantiles of the conditional and unconditional distribution of a random variable carry a different meaning even if identification of both these set of parameters may require conditioning on observed covariates.
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Bibliographic InfoPaper provided by Dipartimento Scienze Economiche, Universita' di Bologna in its series Working Papers with number wp857.
Date of creation: Dec 2012
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- C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
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- Markus Frölich & Blaise Melly, 2007.
"Unconditional quantile treatment effects under endogeneity,"
CeMMAP working papers
CWP32/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Markus Frolich & Blaise Melly, 2010. "Estimation of quantile treatment effects with Stata," Stata Journal, StataCorp LP, vol. 10(3), pages 423-457, September.
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