{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T01:08:07Z","timestamp":1791594487987,"version":"4.3.4"},"reference-count":45,"publisher":"The Econometric Society","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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>We propose using a permutation test to detect discontinuities in an underlying economic model at a known cutoff point. Relative to the existing literature, we show that this test is well suited for event studies based on time\u2010series data. The test statistic measures the distance between the empirical distribution functions of observed data in two local subsamples on the two sides of the cutoff. Critical values are computed via a standard permutation algorithm. Under a high\u2010level condition that the observed data can be coupled by a collection of conditionally independent variables, we establish the asymptotic validity of the permutation test, allowing the sizes of the local subsamples to be either be fixed or grow to infinity. In the latter case, we also establish that the permutation test is consistent. We demonstrate that our high\u2010level condition can be verified in a broad range of problems in the infill asymptotic time\u2010series setting, which justifies using the permutation test to detect jumps in economic variables such as volatility, trading activity, and liquidity. These potential applications are illustrated in an empirical case study for selected FOMC announcements during the ongoing COVID\u201019 pandemic.<\/jats:p>","DOI":"10.3982\/qe1775","type":"journal-article","created":{"date-parts":[[2023,1,19]],"date-time":"2023-01-19T12:26:04Z","timestamp":1674131164000},"page":"37-70","source":"Crossref","is-referenced-by-count":10,"title":["Permutation\u2010based tests for discontinuities in event studies"],"prefix":"10.3982","volume":"14","author":[{"given":"Federico A.","family":"Bugni","sequence":"first","affiliation":[{"name":"Department of Economics, Northwestern University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Li","sequence":"additional","affiliation":[{"name":"School of Economics, Singapore Management University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiyuan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Economics, Singapore Management University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2359","published-online":{"date-parts":[[2023]]},"reference":[{"key":"quan200248-bib-0001","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/S1386-4181(01)00024-6","volume":"5","author":"Amihud","year":"2002","journal-title":"Journal of Financial Markets"},{"key":"quan200248-bib-0002","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1111\/j.1540-6261.1996.tb05206.x","volume":"51","author":"Andersen","year":"1996","journal-title":"Journal of Finance"},{"key":"quan200248-bib-0003","doi-asserted-by":"crossref","first-page":"821","DOI":"10.2307\/2951764","volume":"61","author":"Andrews","year":"1993","journal-title":"Econometrica"},{"key":"quan200248-bib-0004","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0167-7152(01)00009-8","volume":"53","author":"Antoch","year":"2001","journal-title":"Statistics & Probability Letters"},{"key":"quan200248-bib-0005","doi-asserted-by":"crossref","first-page":"47","DOI":"10.2307\/2998540","volume":"66","author":"Bai","year":"1998","journal-title":"Econometrica"},{"key":"quan200248-bib-0006","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1111\/1467-9868.00282","volume":"63","author":"Barndorff-Nielsen","year":"2001","journal-title":"Journal of the Royal Statistical Society, Series B"},{"key":"quan200248-bib-0007","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/jjfinec\/nbi022","volume":"4","author":"Barndorff-Nielsen","year":"2006","journal-title":"Journal of Financial Econometrics"},{"key":"quan200248-bib-0008","doi-asserted-by":"crossref","first-page":"2005","DOI":"10.1093\/restud\/rdy003","volume":"85","author":"Bollerslev","year":"2011","journal-title":"Review of Economic Studies"},{"key":"quan200248-bib-0009","doi-asserted-by":"crossref","first-page":"2005","DOI":"10.1093\/restud\/rdy003","volume":"85","author":"Bollerslev","year":"2018","journal-title":"Review of Economic Studies"},{"key":"quan200248-bib-0010","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.jeconom.2020.02.004","volume":"221","author":"Bugni","year":"2021","journal-title":"Journal of Econometrics"},{"key":"quan200248-bib-0011","doi-asserted-by":"crossref","unstructured":"Bugni, Federico A., Jia Li, and Qiyuan Li (2023), \u201cSupplement to \u2018Permutation-based tests for discontinuities in event studies\u2019.\u201d Quantitative Economics Supplemental Material, 14, https:\/\/doi.org\/10.3982\/QE1775.","DOI":"10.3982\/QE1775"},{"key":"quan200248-bib-0012","doi-asserted-by":"crossref","first-page":"2295","DOI":"10.3982\/ECTA11757","volume":"82","author":"Calonico","year":"2014","journal-title":"Econometrica"},{"key":"quan200248-bib-0013","doi-asserted-by":"crossref","first-page":"1577","DOI":"10.1093\/restud\/rdx062","volume":"85","author":"Canay","year":"2017","journal-title":"The Review of Economic Studies"},{"key":"quan200248-bib-0014","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1515\/jci-2013-0010","volume":"3","author":"Cattaneo","year":"2015","journal-title":"Journal of Causal Inference"},{"key":"quan200248-bib-0015","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1002\/pam.21985","volume":"36","author":"Cattaneo","year":"2017","journal-title":"Journal of Policy Analysis and Management"},{"key":"quan200248-bib-0016","doi-asserted-by":"crossref","unstructured":"Chernozhukov, Victor, Kaspar Wuthrich, and Yinchu Zhu (2018), Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data. 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