Skip to main content

COMPEL Glossary / difference-in-differences-did

Difference-in-differences (DiD)

A quasi-experimental design comparing treated and control trajectories over time — identifying causal effect from differential change.

What this means in practice

Usable where randomisation is infeasible (e.g., rollout to business units) as long as parallel-trends assumption is defensible. Standard tool for AI-rollout value measurement.

Synonyms

DiD , diff-in-diff

See also

  • A/B test (RCT) — A randomised controlled trial in which units are randomly assigned to treatment (AI feature) and control (no feature or baseline feature).
  • Synthetic control — A counterfactual constructed from a weighted combination of untreated donor units — the "synthetic" version of the treated unit.
  • Counterfactual outcome — The outcome that would have occurred without the AI intervention — the benchmark against which incremental AI value is measured.
  • Regression discontinuity (RDD) — A quasi-experimental design using a threshold — e.g., a credit-score cutoff, an eligibility cutoff — to create a natural experiment near the cutoff.