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DTSTAMP:20250303T063207
DTSTART;TZID=America/Detroit:20250424T150000
DTEND;TZID=America/Detroit:20250424T160000
SUMMARY:Careers / Jobs:Wipfli 101: Building your Personal Brand on LinkedIn
DESCRIPTION:Event Details:Date: April 24th\, 2025Time: 3:00-4:00 PM CSTLocation: VirtualWhat to Expect:Join us for an insightful virtual event where you'll get an in-depth look at Wipfli’s services and culture. This session will cover essential tips on what to include in your LinkedIn profile to make it stand out. You'll also learn about content creation and personal branding strategies to enhance your professional presence.Don't miss the opportunity to engage in a live Q&amp\;A session where you can get your questions answered by our experts!
UID:132317-21870756@events.umich.edu
URL:https://events.umich.edu/event/132317
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:
LOCATION:
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20250409T112315
DTSTART;TZID=America/Detroit:20250424T160000
DTEND;TZID=America/Detroit:20250424T172000
SUMMARY:Workshop / Seminar:A Pairwise Differencing Distribution Regression Approach for Network Models
DESCRIPTION:A novel estimation method for distribution regressions in a network setting is proposed. It considers the effects of covariates on the entire outcome distribution rather than solely on the mean. I adopt a semiparametric approach by considering two-way unit-specific effects. Thus\, I extend the standard distribution regression approach to a network setting by estimating multiple binary choice models with two-way fixed effects for different thresholds of the distribution. I employ a conditional maximum-likelihood approach that differences out the unit-specific effects\, avoiding the incidental parameter problem. This method yields consistent point estimates that converge at a parametric rate and remain asymptotically unbiased in the tails of the outcome distribution\, where the underlying network can be seen as sparse. Monte Carlo simulations validate these findings for single cut-off points and the overall outcome distribution. The empirical application focuses on gravity equations for bilateral trade\, demonstrating the effectiveness of the proposed approach in cases where the outcome variable is bounded below at zero.
UID:133823-21873598@events.umich.edu
URL:https://events.umich.edu/event/133823
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Economics,seminar
LOCATION:Lorch Hall - 301
CONTACT:
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