difference-in-differences estimation and inference for Python
For the following use cases
- Balanced panels, unbalanced panels & repeated cross-section
- Two + Multiple time periods
- Fixed + Staggered treatment timing
- Binary + Multi-Valued treatment
- Heterogeneous treatment effects & triple difference
- Parallelized estimation & multiplier bootstrap (joblib, via
n_jobs)
see the Documentation for more details.
The latest release can be installed using pip
pip install differencesrequires Python >= 3.10
the ATTgt class implements the estimation procedures suggested by Callaway and Sant'Anna (2021) , Sant'Anna and Zhao (2020) and the multi-valued treatment case discussed in Callaway, Goodman-Bacon & Sant'Anna (2021)
import differences
df = differences.generate_data() # requires the [all] extra: pip install differences[all]
att_gt = differences.ATTgt(data=df, cohort_column='cohort')
att_gt.fit(formula='y', n_jobs=-1)
att_gt.aggregate('event')differences ATTgt was inspired by