BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CREST - ECPv5.1.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:CREST
X-ORIGINAL-URL:https://crest.science
X-WR-CALDESC:Events for CREST
BEGIN:VTIMEZONE
TZID:Europe/Helsinki
BEGIN:DAYLIGHT
TZOFFSETFROM:+0200
TZOFFSETTO:+0300
TZNAME:EEST
DTSTART:20200329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0300
TZOFFSETTO:+0200
TZNAME:EET
DTSTART:20201025T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20201005T140000
DTEND;TZID=Europe/Helsinki:20201005T151500
DTSTAMP:20260801T022020
CREATED:20200917T131023Z
LAST-MODIFIED:20200917T131023Z
UID:12459-1601906400-1601910900@crest.science
SUMMARY:Chao GAO (University of Chicago) - " Iterative Algorithm for Discrete Structure Recovery "
DESCRIPTION:\nThe Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:15 pm\nDate: 5th of October 2020\nPlace: Visio\nChao GAO (University of Chicago) – ” Iterative Algorithm for Discrete Structure Recovery “ \nAbstract: We propose a general modeling and algorithmic framework for discrete structure recovery that can be applied to a wide range of problems. Under this framework\, we are able to study the recovery of clustering labels\, ranks of players\, signs of regression coefficients\, cyclic shifts\, and even group elements from a unified perspective. A simple iterative algorithm is proposed for discrete structure recovery\, which generalizes methods including Lloyd’s algorithm and the power method. A linear convergence result for the proposed algorithm is established in this paper under appropriate abstract conditions on stochastic errors and initialization. We illustrate our general theory by applying it on several representative problems: (1) clustering in Gaussian mixture model\, (2) approximate ranking\, (3) sign recovery in compressed sensing\, (4) multireference alignment\, and (5) group synchronization\, and show that minimax rate is achieved in each case. \n \nOrganizers:\nCristina BUTUCEA (CREST)\, Alexandre TSYBAKOV (CREST)\, Karim LOUNICI (CMAP) \, Zoltan SZABO (CMAP)\nSponsors:\nCREST-CMAP\n \n\n
URL:https://crest.science/event/chao-gao/
CATEGORIES:Statistics
ATTACH;FMTTYPE=:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20201005T150000
DTEND;TZID=Europe/Helsinki:20201005T160000
DTSTAMP:20260801T022020
CREATED:20200914T073202Z
LAST-MODIFIED:20241104T133307Z
UID:12449-1601910000-1601913600@crest.science
SUMMARY:Ioana MARINESCU ( Université de Pennsylvanie )   - "Unemployment Insurance and Job Search Behavior"
DESCRIPTION:\nThe Microeconometrics Seminar: \nTime: 03:00 pm – 4:00 pm\nDate: Monday\, 5th of october 2020\nby visio\nIoana MARINESCU ( Université de Pennsylvanie ) – “Unemployment Insurance and Job Search Behavior” \nAbstract: Unemployment insurance (UI) can affect unemployment duration and re-employment wages\, through various dimensions of unemployed workers’ job search behavior. We shed light on the effects of UI on job search behavior using new longitudinal data: we link administrative registers to data from a major online search platform\, and track the job applications sent over the unemployment spells of about 500\,000 French workers. We identify changes in individual search behavior caused by UI around benefits exhaustion\, after accounting for changes in the sample composition—i.e. dynamic selection—and for the effect of the time spent unemployed—i.e. duration dependence. We show that search effort (the count of job applications) increases by at least 50% during the year preceding benefits exhaustion and remains relatively high thereafter. The target monthly wage decreases by at least 2.4% during the year preceding benefits exhaustion\, and remains relatively low thereafter. We document particularly large dynamic selection around benefits exhaustion\, as some workers increase their search effort more before exhaustion and find a job faster. We also show evidence for duration dependence: workers decrease their target wage by 1.5% over each year of unemployment\, irrespective of their UI status. Overall\, the effect of UI on individual search behavior is consistent with the predictions of search models and constitutes evidence against search-free models where UI merely subsidizes leisure. \nJoint with Daphné Skandalis (Federal Reserve Banks – Federal Reserve Bank of New York)\n \nOrganizers:\n\nBenoît SCHMUTZ (Laboratoire de Microéconométrie-CREST)\nAnthony STRITTMATTER (Laboratoire de Microéconométrie-CREST)\nSponsors:\nCREST\n \n\n
URL:https://crest.science/event/iona-marinescu/
CATEGORIES:Applied Seminar,Economics,Microeconometrics,Seminars
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR