Join Prof. Clément de Chaisemartin in this in-depth training on Difference-in-Differences (DiD) — a powerful econometric tool for causal inference and policy evaluation.
0:00 Opening
2:24 2 Data, notation, and assumptions
3:33 2.1 Group-level panel data
7:35 2.2 Treatment and potential outcomes
10:17 2.3 Identifying assumptions
24:40 2.4 Framework for statistical inference
57:35 3 Classical DID design
1:03:38 3.1 Target parameters
1:11:14 3.2 Two-Way Fixed Effects estimators
Hosted by: LISER & DSEFM, University of Luxembourg
Local Organizer: Andrea Albanese
https://sites.google.com/site/researchandreaalbanese/
Source material: de Chaisemartin, Clément and d'Haultfoeuille, Xavier, Credible Answers to Hard Questions: Differences-in-Differences for Natural Experiments (June 21, 2023)
What you’ll learn in the class:
• DiD basics and core assumptions
• Latest methodological innovations
• Staggered vs non-staggered adoption
• Discrete and continuous treatment
🔗 Download source book:
SSRN: https://ssrn.com/abstract=4487202
DOI: http://dx.doi.org/10.2139/ssrn.4487202
Ideal for: PhD students, researchers and practitioners working on policy evaluation and causal inference.
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