Dear Applied Statistics Workshop Community,
Our next meeting will be on November 1 (12:00 EST). Naijia Liu presents
"Synthetic Control Method with Pre-treatment Outcomes Missing" (Joint work
with Sooahn Shin and Soichiro Yamauchi).
<When>
November 1, 12:00 to 1:30 PM, EST
Lunch will be available for pick-up inside CGIS K354.
<Where>
In-person: CGIS K354
Zoom:
https://harvard.zoom.us/j/93217566507?pwd=elBwYjRJcWhlVE5teE1VNDZoUXdjQT09
<Abstract>
The synthetic control method (SCM) is commonly used in social science
research to estimate treatment effects. It involves creating a synthesized
control unit for the treated unit in observational studies. The quality of
this synthesized control unit is influenced by factors like the number of
pretreatment periods and missing values. Many empirical datasets,
particularly those with a panel structure, often encounter issues with
missing values. This project studies the impact of missing values on SCM
and provides theoretical guidance to the potential bias. We formulate SCM
with missing data in a vertical regression perspective. Under such setting,
missing values can be deemed as omitted variables. We show that the bias of
the ATT is decomposed into (1) weight of the missing unit for constructing
the synthetic control and (2) the imbalance between the missing units and
the weighted observed donor units. Building on these result, We propose a
sensitivity analysis for SCM with pretreatment outcomes missing not at
random. To illustrate the method in practice, we revisit a previous study
that examines the impact of Taiwan's expulsion from the International
Monetary Fund (IMF) in 1980 on its precautionary international reserves
using the SCM.
<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