{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T01:40:40Z","timestamp":1759801240231,"version":"build-2065373602"},"reference-count":45,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T00:00:00Z","timestamp":1747612800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72273005"],"award-info":[{"award-number":["72273005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>We consider the inference on individual and time specific treatment effects on the treated within the framework of panel data approach for programme evaluation. We formulate the target problem as constructing prediction intervals for high\u2010dimensional linear regressions with weakly dependent data. Post\u2010LASSO OLS is used for estimation, while dependent wild bootstrap and simple residual bootstrap are used for the construction of prediction intervals. The proposed prediction intervals are proved to have asymptotic validity as the number of pretreatment times goes to infinity. In the proof, we also establish the model selection consistency of LASSO for dependent data and under bootstrap measure, which may be of independent interest. Monte Carlo experiments illustrate that our method outperforms existing methods in finite samples under a wide variety of data generating processes except nonstationary data. Two empirical applications are also provided.<\/jats:p>","DOI":"10.1002\/jae.3134","type":"journal-article","created":{"date-parts":[[2025,5,20]],"date-time":"2025-05-20T06:14:00Z","timestamp":1747721640000},"page":"655-668","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction Intervals of Panel Data Approach for Programme Evaluation"],"prefix":"10.1002","volume":"40","author":[{"given":"Hongyi","family":"Jiang","sequence":"first","affiliation":[{"name":"China Center for Economic Research, Institute of Digital Finance, National School of Development Peking University  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingyu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Economics Zhejiang University  Hangzhou Zhejiang China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Shen","sequence":"additional","affiliation":[{"name":"China Center for Economic Research, Institute of Digital Finance, National School of Development Peking University  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiankun","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Economics Louisiana State University  Baton Rouge Louisiana USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,5,19]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1257\/jel.20191450"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2009.ap08746"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1257\/000282803321455188"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2021.1971535"},{"issue":"1","key":"e_1_2_10_6_1","first-page":"802","article-title":"Robust Synthetic Control","volume":"19","author":"Amjad M.","year":"2018","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1257\/aer.20190159"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2021.1891924"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2021.1967163"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2021.1929245"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/rssb.12448"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2018.07.005"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2021.1979561"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm10159"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.3982\/ECTA20720"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2021.1920957"},{"issue":"5","key":"e_1_2_10_17_1","first-page":"1","article-title":"Can We Trust the Bootstrap in High\u2010Dimensions? 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