(朱 /ʈʂu55/)(梓 /tsɯ21˦/)(月 /ɥœ51/)
also known as Jessie Ziyue Zhu
Master of Statistics and Data Science
[Master Project Repository]
KU Leuven
Master of Economics
[Master Project Presentation]
Universitat Pompeu Fabra
BSc in Economics
Wuhan University
[Show/hide Email]
ziyue[dot]zhu[at]maastrichtuniversity[dot]nl
Hello!
I am a PhD candidate in Labor Economics at the Research Centre for Education and the Labour Market (ROA), Maastricht University.
My research interests lie in:
Public Goods Contribution:
mixrandregret
[Repository]Can Information of Generative AI Technology Impact Vocational College Students’ Career Preferences? Evidence from Randomized Controlled Trials
with Yang Tianyu, Barbara Belfi, and Carla Haelermans (Draft Available Upon Request)
presented at: EALE (2024), ESPE (2024), LEER (9th, 2024)
Digital Transformation and Skill Mismatch: Evidence from Europe
with Yang Tianyu(Draft Available Upon Request)
Adult children's education and patterns of family support in China
with Rufei Guo, Lin Lin
Building up Employability: Evidence from VET Curricula Updates in the Netherlands
with Didier Fouarge, Barbara Belfi, and Melline Somers
presented at: Studi-BUCH Text-as-data workshop (2nd, 2024), Skills2Capabilities Project Meeting (EU Horizon), LEER (9th, 2024)
Fitting mixed logit random regret minimization models using maximum simulated likelihood
with Álvaro A. Gutiérrez-Vargas, Martina Vandebroek
the Stata Journal 24 (2) [Link]
[Show/hide abstract]
This article describes the mixrandregret command, which extends the randregret command introduced in Gutiérrez-Vargas et al.
(2021, The Stata Journal 21: 626-658) incorporating random coefficients for Random Regret Minimization models. The newly
developed command mixrandregret allows the inclusion of random coefficients in the regret function of the classical RRM
model introduced in Chorus (2010, European Journal of Transport and Infrastructure Research 10: 181-196). The command allows
the user to specify a combination of fixed and random coefficients. In addition, the user can specify normal and log-normal
distributions for the random coefficients using the commands' options. The models are fitted using simulated maximum likelihood
using numerical integration to approximate the choice probabilities.
the second Studi-BUCH Text-as-data workshop (Essen, Germany)
EU Horizon: Skills2Capabilities Meeting 2024 (Venice, Italy)
9th LEER Conference on Education Economics 2024 (Leuven, Belgium) [Abstract]
mixrandregret
Stata Conference 2022: London, the UK (presented by coauthor) [Link]
Master Thesis Supervision
Guest Lecture: Minerva (R studio) Workshop
Tutor at Maastricht University (Feb - Mar 2024):
Undergraduate Teaching Assistant at Wuhan University (Mar - Jun 2018):
Education/Labour Economics Materials:
Discrete Choice Modelling:
mixrandregret
[Repository]randregret
[Repository]Apollo
[Website]LaTex:
My Collection of Lecture Notes [EconResources]
Advice for PhD Students in Economics [EconGradAdvice]
I would like to thank Dr. Joy and Dr. Flora for their expertise in successfully waking me up in the morning and keeping me awake at night to make my research projects possible.
Dr. Joy PhD, Meowstricht University |
Dr. Flora PhD, Research Center for Kattencation and Labour Meowcat |
Thanks to Vasilios Mavroudis for the template! And thanks to Ali Siahkoohi for added CSS and switch theme function!