A semi-parametric two-stage projection type estimator of multivalued treatment effects

One of the most well documented regularities in evaluation literature like returns to schooling(or funding for programs) is that several factors come together to confound the measurement of its effect. First, in observational studies the true return is often individual specific, and so it is almost...

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Main Author: GHOSH, Aurobindo
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Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/soe_research/1176
https://ink.library.smu.edu.sg/context/soe_research/article/2175/viewcontent/SSRN_id971734.pdf
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spelling sg-smu-ink.soe_research-21752017-08-24T05:56:25Z A semi-parametric two-stage projection type estimator of multivalued treatment effects GHOSH, Aurobindo One of the most well documented regularities in evaluation literature like returns to schooling(or funding for programs) is that several factors come together to confound the measurement of its effect. First, in observational studies the true return is often individual specific, and so it is almost impossible to use a traditional treatment effect models with randomly assigned treatment and control groups. This endogeneity in the model further exacerbates our inability to conduct such trials. Second, the problem is not a classical treatment effect measurement problem where we have discrete or more often binary treatments. Hence, techniques like measuring the Local Average Treatment Effect (LATE) cannot be implemented as it is not very well defined for the continuous treatment case. Third, a traditional 2SLS approach might be misleading because of the non-Gaussian nature of response distribution, in particular, if different quantiles of response have differential effects. However, their technique is also not defined for continuous treatments, and cannot measure if different distributions of the treatment might have different effects on the response variable. In this paper, we propose the effects of different multi-valued treatment variable after conditioning for other covariates. 2009-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1176 https://ink.library.smu.edu.sg/context/soe_research/article/2175/viewcontent/SSRN_id971734.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Treatment Effect Instrumental variable Projection type estimator Quantile Regression Exogeneity Monotonicity Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Treatment Effect
Instrumental variable
Projection type estimator
Quantile Regression
Exogeneity
Monotonicity
Econometrics
spellingShingle Treatment Effect
Instrumental variable
Projection type estimator
Quantile Regression
Exogeneity
Monotonicity
Econometrics
GHOSH, Aurobindo
A semi-parametric two-stage projection type estimator of multivalued treatment effects
description One of the most well documented regularities in evaluation literature like returns to schooling(or funding for programs) is that several factors come together to confound the measurement of its effect. First, in observational studies the true return is often individual specific, and so it is almost impossible to use a traditional treatment effect models with randomly assigned treatment and control groups. This endogeneity in the model further exacerbates our inability to conduct such trials. Second, the problem is not a classical treatment effect measurement problem where we have discrete or more often binary treatments. Hence, techniques like measuring the Local Average Treatment Effect (LATE) cannot be implemented as it is not very well defined for the continuous treatment case. Third, a traditional 2SLS approach might be misleading because of the non-Gaussian nature of response distribution, in particular, if different quantiles of response have differential effects. However, their technique is also not defined for continuous treatments, and cannot measure if different distributions of the treatment might have different effects on the response variable. In this paper, we propose the effects of different multi-valued treatment variable after conditioning for other covariates.
format text
author GHOSH, Aurobindo
author_facet GHOSH, Aurobindo
author_sort GHOSH, Aurobindo
title A semi-parametric two-stage projection type estimator of multivalued treatment effects
title_short A semi-parametric two-stage projection type estimator of multivalued treatment effects
title_full A semi-parametric two-stage projection type estimator of multivalued treatment effects
title_fullStr A semi-parametric two-stage projection type estimator of multivalued treatment effects
title_full_unstemmed A semi-parametric two-stage projection type estimator of multivalued treatment effects
title_sort semi-parametric two-stage projection type estimator of multivalued treatment effects
publisher Institutional Knowledge at Singapore Management University
publishDate 2009
url https://ink.library.smu.edu.sg/soe_research/1176
https://ink.library.smu.edu.sg/context/soe_research/article/2175/viewcontent/SSRN_id971734.pdf
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