4/4

📖 Draft available for free until publication:
👉 papers.ssrn.com/sol3/papers....

We welcome feedback, praise, bug reports, and citations 😇
#DID #causalinference #econometrics #socialscience #bookdrop

3/4

Real examples, real confusion, real fixes.

We’ve been asked many many many hard DID questions over the years.
This book tries to answer them — with proofs & packages.

Bonus: A practitioners' checklist.

2/4

What’s inside?

✅ A survival guide for DID in the wild
📉 When TWFE goes rogue
⚠️ When trends aren’t so parallel
🔍 When your control group is... questionable

Methods illustrated by revisiting 4 empirical articles so yes, there's code (Stata. R coming soon. Python fans, courage.).

but governments—who fund the research behind these tools—apply them too rarely to their own policies. In this piece, Xavier D'Haultfoeuille and I argue for greater use of evaluation tools in public decision-making and for ensuring that these tools remain accessible public goods.

Dofile and datasets to replicate our empirical applications in Chapters 3 and 4 are available from SSC:

ssc desc cc_xd_didtextbook
net get cc_xd_didtextbook

Chapter 5 on designs with variation in treatment timing is in good shape. Chapter 6 on designs with variation in treatment dose is also in good shape. So what's left is essentially Chapter 7, on general designs.