Quasi experimental methods: Difference in differences
Quasi experimental methods:
Difference in differences
Prashant Bharadwaj
University of California, San Diego
March 24th, 2010
Material in this presentation developed from CEGA and World Bank materials.
Quick re©\cap
1. While using non experimental data to infer causal
relationships, we must think through sample
selection and omitted variables bias
2. Comparing just pre©\post or participant vs non©\
participant is not enough
3. This lecture is about differencing out the potential
omitted variables bias
Difference©\in©\Differences, Graphically
Treatment
Control
Pre
Post
Difference©\in©\Differences, Graphically
Effect of program using
only pre©\ & post©\ data
from T group (ignoring
general time trend).
Pre
Post
Difference©\in©\Differences, Graphically
Effect of program using
only T & C comparison
from post©\intervention
(ignoring pre©\existing
differences between T & C
groups).
Pre
Post
................
................
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