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:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0300
TZOFFSETTO:+0200
TZNAME:EET
DTSTART:20251026T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250324
DTEND;VALUE=DATE:20250325
DTSTAMP:20260710T144407
CREATED:20250106T140407Z
LAST-MODIFIED:20250106T140407Z
UID:17724-1742774400-1742860799@crest.science
SUMMARY:Dimitrios Xefteris (University of Cyprus): "Information Aggregation by Voting and Costly Political Influence"
DESCRIPTION:Doctoral course: “Information Aggregation by Voting and Costly Political Influence” \n24/03/2025 – 26/03/2025 – 31/03/2025 – 02/04/2025 \nReferent: Matias Nunez \n
URL:https://crest.science/event/dimitrios-xefteris-university-of-cyprus-information-aggregation-by-voting-and-costly-political-influence-2/
CATEGORIES:Doctoral Courses,Economics
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20250324T121500
DTEND;TZID=Europe/Helsinki:20250324T133000
DTSTAMP:20260710T144407
CREATED:20250303T070842Z
LAST-MODIFIED:20250319T075844Z
UID:17922-1742818500-1742823000@crest.science
SUMMARY:Leo KAAS (Goethe University Frankfurt) "Job ladder and wealth dynamics in general equilibrium"
DESCRIPTION:[vc_row][vc_column][vc_column_text]Macro seminar\nTime : 12h15 – 13h30 \nDate : 24th  March 2025 \nSalle 3001 \nLeo KAAS (University Frankfurt) “Job ladder and wealth dynamics in general equilibrium” \nAbstract: This paper develops a macroeconomic model that combines an incomplete-markets overlapping-generations economy with a job ladder featuring sequential wage bargaining\, endogenous search effort of employed and non-employed workers\, and differences in match quality. With these ingredients our model provides a joint microfoundation for the three main inputs in aggregate production: capital\, employment and labor efficiency. The calibrated model offers a good fit to the empirical age profiles of search activity\, job-finding rates\, wages and savings. We use the model to analyze the impact of tax and transfer policies for labor market dynamics and aggregate economic activity via capital\, employment and labor efficiency channels. Lower unemployment benefits and a less progressive tax schedule bring about welfare losses for a newborn worker which are mainly driven by higher consumption risk and costlier search effort; both policies have differential effects along the age\, income and wealth dimensions.  \nOrganizer : Franck MALHERBET  \n
URL:https://crest.science/event/leo-kaas-university-frankfurt-job-ladder-and-wealth-dynamics-in-general-equilibrium/
CATEGORIES:Macroeconomics,Seminars
ATTACH;FMTTYPE=:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20250324T140000
DTEND;TZID=Europe/Helsinki:20250324T153000
DTSTAMP:20260710T144407
CREATED:20250318T071350Z
LAST-MODIFIED:20250318T071350Z
UID:17817-1742824800-1742830200@crest.science
SUMMARY:Solenne GAUCHER (CMAP) - Classification and regression under fairness constraints
DESCRIPTION:Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:00 pm\nDate: 24th March\nPlace: 3001 \n  \nSolenne GAUCHER (CMAP) – Classification and regression under fairness constraints \n  \n Abstract:  \nArtificial intelligence (AI) is increasingly shaping the decisions that affect our lives—from hiring and education to healthcare and access to social services. While AI promises efficiency and objectivity\, it also carries the risk of perpetuating and even amplifying societal biases embedded in the data used to train these systems.Algorithmic fairness aims to design and analyze algorithms capable of providing predictions that are both reliable and equitable. \n  \nIn this talk\, I will introduce one of the main approaches to achieving this goal: statistical fairness. After outlining the basic principles of this approach\, I will focus specifically on a fairness criterion known as “demographic parity\,” which seeks to ensure that the distribution of predictions is identical across different populations. I will then discuss recent results related to regression and classification problems under this fairness constraint\, exploring scenarios where differentiated treatment of populations is either permitted or prohibited. \n  \nOrganizers: \nAnna KORBA (CREST)\, Karim LOUNICI (CMAP) \, Jaouad MOURTADA (CREST) \nSponsors:\nCREST-CMAP \n
URL:https://crest.science/event/solenne-gaucher-cmap-classification-and-regression-under-fairness-constraints/
CATEGORIES:Seminars,Statistics
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR