Synthetic Control Inference for Staggered Adoption

Clicks: 3
ID: 315282
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #19 of 19 articles by views in econometrics journal

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Many policies are replicated by other policymakers at different times. We introduce a synthetic control methodology to study policies with staggered adoption. Our method estimates the dynamic average treatment effects on the treated using variation introduced by the staggered adoption of policies. Our method gives asymptotically unbiased estimators of many interesting quantities and delivers asymptotically valid inference. Applying the method to intergovernmental coordination reforms that centralize information sharing and enable joint policing across jurisdictions, we find that violent theft and cartel activity fall after adoption. Homicide is largely unchanged for most post-treatment periods, but rises later on.
Reference Key
openalex_W7162749791 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jianfei Cao, Shirley Lu, Hang Wu
Journal econometrics journal
Year 2026
DOI
10.1093/ectj/utag015
URL
https://doi.org/10.1093/ectj/utag015
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.