diff_diff.compute_honest_did

diff_diff.compute_honest_did(results, method='relative_magnitude', M=1.0, alpha=0.05)

Convenience function for computing Honest DiD bounds.

Parameters:

• results (MultiPeriodDiDResults or CallawaySantAnnaResults) – Results from event study estimation.

• method (str) – Type of restriction (“smoothness”, “relative_magnitude”, “combined”).

• M (float) – Restriction parameter.

• alpha (float) – Significance level.

Returns:

Bounds and robust confidence intervals.

Return type:

HonestDiDResults

Examples

>>> bounds = compute_honest_did(event_study_results, method='relative_magnitude', M=1.0)
>>> print(f"Robust CI: [{bounds.ci_lb:.3f}, {bounds.ci_ub:.3f}]")