Confidence intervals for the quantile of treatment effects in randomized experiments
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Fan, Yanqin | - |
dc.contributor.author | Park, Sang Soo | - |
dc.date.accessioned | 2021-09-06T21:36:36Z | - |
dc.date.available | 2021-09-06T21:36:36Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2012-04 | - |
dc.identifier.issn | 0304-4076 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/108782 | - |
dc.description.abstract | In this paper, we explore partial identification and inference for the quantile of treatment effects for randomized experiments. First, we propose nonparametric estimators of sharp bounds on the quantile of treatment effects and establish their asymptotic properties under general conditions. Second, we construct confidence intervals for the bounds and the true quantile by using the approach in Chernozhukov et al. (2009). Third, under additional conditions, we develop a new approach to construct confidence intervals for the bounds and the true quantile and refer to it as the order statistic approach. A simulation study is conducted to investigate the finite sample performance of both approaches. (C) 2011 Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE SA | - |
dc.subject | INSTRUMENTAL VARIABLES | - |
dc.subject | INFERENCE | - |
dc.subject | PARAMETERS | - |
dc.subject | MODELS | - |
dc.subject | IMPACTS | - |
dc.subject | SETS | - |
dc.title | Confidence intervals for the quantile of treatment effects in randomized experiments | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Sang Soo | - |
dc.identifier.doi | 10.1016/j.jeconom.2011.09.019 | - |
dc.identifier.wosid | 000302106300005 | - |
dc.identifier.bibliographicCitation | JOURNAL OF ECONOMETRICS, v.167, no.2, pp.330 - 344 | - |
dc.relation.isPartOf | JOURNAL OF ECONOMETRICS | - |
dc.citation.title | JOURNAL OF ECONOMETRICS | - |
dc.citation.volume | 167 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 330 | - |
dc.citation.endPage | 344 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Business & Economics | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalResearchArea | Mathematical Methods In Social Sciences | - |
dc.relation.journalWebOfScienceCategory | Economics | - |
dc.relation.journalWebOfScienceCategory | Mathematics, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Social Sciences, Mathematical Methods | - |
dc.subject.keywordPlus | INSTRUMENTAL VARIABLES | - |
dc.subject.keywordPlus | INFERENCE | - |
dc.subject.keywordPlus | PARAMETERS | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordPlus | IMPACTS | - |
dc.subject.keywordPlus | SETS | - |
dc.subject.keywordAuthor | Heterogeneous treatment effects | - |
dc.subject.keywordAuthor | Partial identification | - |
dc.subject.keywordAuthor | Quantile treatment effects | - |
dc.subject.keywordAuthor | Order statistic approach | - |
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