Dear Applied Statistics Workshop Community,
Welcome back! Our first meeting of the semester will be on September 6
(12:00 EST). Keyon Vafa presents "Decomposing Changes in the Gender Wage
Gap over Worker Careers."
<When>
September 6, 12:00 to 1:30 PM, EST
Lunch will be available for pick-up at 11:30 (CGIS K354).
<Where>
In-person: CGIS K354
Zoom:
https://harvard.zoom.us/j/93217566507?pwd=elBwYjRJcWhlVE5teE1VNDZoUXdjQT09
<Abstract>
Abstract: A large literature in labor economics seeks to decompose gender
wage gaps into different sources, including portions explained by
cross-gender differences in education and occupation. While career
histories contain valuable information about sources of gender wage
disparities, they are too high-dimensional to include in standard
econometric techniques. This talk presents new machine learning methods for
decomposing gender wage gaps over worker careers. We develop a "foundation
model" of career trajectories to summarize worker histories with
low-dimensional representations. We show how to fine-tune the foundation
model on small survey datasets while ensuring that the representations do
not omit features of history whose exclusion would bias decompositions. On
data from the Panel Study of Income Dynamics, our method explains more of
the gender wage gap than standard techniques. Finally, we propose a new
decomposition of the change in gender wage gaps over workers careers into
two sources: gender differences in initial characteristics and gender
differences in worker transitions. Using representations from the
foundation model, we show that early in careers, the gender wage gap
widens, driven by males transitioning to higher-paying characteristics than
females; meanwhile, later in careers, the gender wage gap narrows, driven
by female initial characteristics setting up workers for more wage growth
than those of males.
<2023 Schedule>
GOV 3009 Website:
https://projects.iq.harvard.edu/applied.stats.workshop-gov3009
Calendar:
https://calendar.google.com/calendar/u/0?cid=Y18zdjkzcGF2OWZqa2tsZHJidTlzbm…
Best,
Jialu
--
Jialu Li
Department of Government
Harvard University
jialu_li(a)g.harvard.edu