ssBartik: an end-to-end pipeline for shift-share (Bartik) IV designs

Shift-share / Bartik instrumental-variable analysis in R has been spread across several single-purpose packages: ShiftShareSE (Kolesar) for AKM inference, bartik.weight (jjchern) for Rotemberg weights, and ssaggregate (Butts) for shock-level aggregation. ssBartik brings construction, diagnostics, estimation, exposure-robust inference and publication-ready visualisation into one consistent workflow, organised around the two identification routes of the modern literature (exogenous shares vs. exogenous shifts).

Details

The single entry point is [ssb_design()] (or the one-call [ssbartik()]). Choose the route with `exogenous`; the instrument is constructed identically either way, and the flag governs which diagnostics and controls apply.

Acknowledgements & references

Built with gratitude on the work of Michal Kolesar (ShiftShareSE), Kyle Butts (`ssaggregate`), Junjie (JJ) Chern (`bartik.weight`) and Paul Goldsmith-Pinkham (`bartik-weight`, the original Stata implementation). Core methods: Adao, Kolesar & Morales (2019, QJE); Borusyak, Hull & Jaravel (2022, REStud), Borusyak, Hull & Jaravel (2025, "A Practical Guide to Shift-Share Instruments") and Borusyak, Hull & Jaravel (2025, "Design-based identification with formula instruments: a review", Econometrics Journal 28(1), 83-108); Goldsmith-Pinkham, Sorkin & Swift (2020, AER).

See also

Useful links:

• https://github.com/takuma1102/ssBartik

• https://takuma1102.github.io/ssBartik/

• Report bugs at https://github.com/takuma1102/ssBartik/issues

Author

Maintainer: Takuma Iwasaki iwasakit@stanford.edu (affiliation: Stanford University)

Authors:

• Takuma Iwasaki iwasakit@stanford.edu (affiliation: Stanford University)