[Acmsmajors] Fw: ECON 488- open for registration

[Math & ACMS Student Services Office via Acmsmajors]

ECON 488A – Causal Inference
Sln 13897
TTh 8:30-10:20am
MUE 155

In this course we study methods for recovering causal relationships in economics. These methods underpin applied research in social and biomedical sciences, and have many applications in industry, tech companies, consulting firms, et cetera. For example, we may want to establish whether: (a) studying economics increases earnings, for a group of undeclared students; (b) a particular pricing strategy increases a firm’s profits; or (c) higher migration helps or hinders the economic outcomes of existing residents. The recent surge of interest in causal inference is exemplified by the award of the 2021 “Nobel Prize in Economic Sciences” to Joshua Angrist and Guido Imbens for their work on ‘the analysis of causal relationships’. Many elements of this course are based on inferential methods that they pioneered. Sample topics include: treatment/control, regression adjustment, matching (exact, nearest-neighbor), difference-in-difference, synthetic controls, instrumental variables, local average treatment effect (LATE), and regression discontinuity design. We may also discuss how machine learning has recently been used to enrich the classical methods. By the end of the course, students will be able to approach problems of causal inference that are routinely considered at public and private research institutions and agencies, economic consulting companies, as well as in major technology companies and retailers. This includes the ability to set up, run, and interpret the findings of the methods learned in class. This course is designed for upper-lever undergraduate, or master-level, students in economics and related fields.





Ahna Kotila (she/her)

Academic Services Director

Department of Economics



314 Savery Hall, Box 353330

Seattle, WA  98195-3330

akotila at uw.edu<mailto:akotila at uw.edu> / https://econ.washington.edu



[cid:ii_193457d50ab4cdccc1]


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman11.u.washington.edu/pipermail/acmsmajors/attachments/20241119/ebf9e7d2/attachment.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image001.gif
Type: image/gif
Size: 1303 bytes
Desc: image001.gif
URL: <http://mailman11.u.washington.edu/pipermail/acmsmajors/attachments/20241119/ebf9e7d2/attachment.gif>