{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T13:56:32Z","timestamp":1767966992358,"version":"3.49.0"},"reference-count":18,"publisher":"The Econometric Society","issue":"3","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["QE"],"abstract":"<jats:p>This paper considers estimation and inference for heterogeneous counterfactual effects with high\u2010dimensional data. We propose a novel robust score for debiased estimation of the unconditional quantile regression (Firpo, Fortin, and Lemieux (2009)) as a measure of heterogeneous counterfactual marginal effects. We propose a multiplier bootstrap inference and develop asymptotic theories to guarantee the size control in large sample. Simulation studies support our theories. Applying the proposed method to Job Corps survey data, we find that a policy, which counterfactually extends the duration of exposures to the Job Corps training program, will be effective especially for the targeted subpopulations of lower potential wage earners.<\/jats:p>","DOI":"10.3982\/qe1896","type":"journal-article","created":{"date-parts":[[2022,7,7]],"date-time":"2022-07-07T09:56:45Z","timestamp":1657187805000},"page":"955-978","source":"Crossref","is-referenced-by-count":11,"title":["Unconditional quantile regression with high\u2010dimensional data"],"prefix":"10.3982","volume":"13","author":[{"given":"Yuya","family":"Sasaki","sequence":"first","affiliation":[{"name":"Department of Economics, Vanderbilt University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takuya","family":"Ura","sequence":"additional","affiliation":[{"name":"Department of Economics, University of California, Davis"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yichong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Economics, Singapore Management University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2359","published-online":{"date-parts":[[2022]]},"reference":[{"key":"quan200218-bib-0001","doi-asserted-by":"crossref","DOI":"10.1214\/17-AOS1671","volume":"46","author":"Belloni","year":"2018","journal-title":"The Annals of Statistics"},{"key":"quan200218-bib-0002","doi-asserted-by":"crossref","first-page":"233","DOI":"10.3982\/ECTA12723","volume":"85","author":"Belloni","year":"2017","journal-title":"Econometrica"},{"key":"quan200218-bib-0003","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1093\/biomet\/asu056","volume":"102","author":"Belloni","year":"2014","journal-title":"Biometrika"},{"key":"quan200218-bib-0004","doi-asserted-by":"crossref","first-page":"1705","DOI":"10.1214\/08-AOS620","volume":"37","author":"Bickel","year":"2009","journal-title":"The Annals of Statistics"},{"key":"quan200218-bib-0005","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1007\/978-1-4419-9076-1_4","volume-title":"Proceedings of the Second Seattle Symposium in Biostatistics","author":"Chen","year":"2004"},{"key":"quan200218-bib-0006","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1257\/aer.p20171038","volume":"107","author":"Chernozhukov","year":"2017","journal-title":"American Economic Review"},{"key":"quan200218-bib-0007","doi-asserted-by":"crossref","first-page":"C1","DOI":"10.1111\/ectj.12097","volume":"21","author":"Chernozhukov","year":"2018","journal-title":"Econometrics Journal"},{"key":"quan200218-bib-0008","first-page":"1787","volume":"42","author":"Chernozhukov","year":"2014","journal-title":"The Annals of Statistics"},{"key":"quan200218-bib-0009","first-page":"1564","volume":"42","author":"Chernozhukov","year":"2014","journal-title":"The Annals of Statistics"},{"key":"quan200218-bib-0010","unstructured":"Chernozhukov, Victor, Juan Carlos Escanciano, Hidehiko Ichimura, Whitney K. 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