BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Claremont Center for the Mathematical Sciences - ECPv6.15.17.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://colleges.claremont.edu/ccms
X-WR-CALDESC:Events for Claremont Center for the Mathematical Sciences
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20210314T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20211107T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20220313T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20221106T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20230312T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20231105T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221026T161500
DTEND;TZID=America/Los_Angeles:20221026T173000
DTSTAMP:20260416T021330
CREATED:20220830T231139Z
LAST-MODIFIED:20220928T195647Z
UID:2806-1666800900-1666805400@colleges.claremont.edu
SUMMARY:Frequentist Model Averaging in the Generalized  Multinomial Logit Model  (Prof. Tonia Zeng)
DESCRIPTION:Title: Frequentist Model Averaging in the Generalized Multinomial Logit Model \nSpeaker: Tonia Zeng\, Applied Business Sciences and Economics\, University of La Verne \nAbstract: The generalized multinomial logit (GMNL) model accommodates scale heterogeneity to the random parameters logit (RPL) model. It has been often used to study people’s preferences and predict people’s decisions in many areas\, such as health economics\, marketing\, agricultural studies\, transportation research and public policy. However\, there are few works studying the efficiency of this model estimator and the corresponding estimation and prediction risks. In this paper\, we use a frequentist model averaging (FMA) estimator to reduce the estimation and prediction risks of the GMNL model estimator. We show that the asymptotic squared error risk of the FMA estimator dominates that of the GMNL model estimator. The accuracy of the predicted choices is also higher based on the FMA estimates compared to the results based on the GMNL estimates. In the empirical analyses\, using the FMA estimator improves the percentage of correct predicted choices by 10% compared to the results based on the GMNL estimates. This paper provides a more efficient alternative to the GMNL model to capture people’s preferences and predict people’s choices. \n\n\n\n\n\nTong (Tonia) Zeng is an economics professor\, specializing in econometrics at the University of La Verne. She is visiting in the Institute of Mathematical Sciences at Claremont Graduate University this semester. Her research interests include discrete choice models\, model averaging and machine learning.
URL:https://colleges.claremont.edu/ccms/event/tonia-zeng/
LOCATION:Humanities Auditorium\, Scripps College\, and Zoom\, Claremont\, CA\, 91711\, United States
CATEGORIES:Colloquium
GEO:34.1035221214;-117.709766675
END:VEVENT
END:VCALENDAR