Econometric Methods for Program Evaluation
Causal Question / Estimand
A survey of the methods that identify the ATT (and related parameters) of programs and policies — organizing the credibility-revolution toolkit by the identifying assumption each method invokes.
Identification Strategy
Reviews the main designs and what licenses each: selection-on-observables (Ignorability + Overlap, via regression, matching, and Propensity-Score weighting); regression discontinuity; difference-in- differences and Parallel-Trends; synthetic control; and instrumental variables. The organizing theme is that credible program evaluation comes from a transparent, defensible identification strategy, not from estimation machinery.
Key Assumptions
Covers the field’s assumptions: Ignorability, Overlap, Parallel-Trends, Continuity-at-Cutoff, Convex-Hull-Restriction, Exclusion-Restriction, all on a Potential-Outcomes/SUTVA base.
Threats to Validity
Method-specific: unobserved confounding (selection on observables), manipulation (RD), non-parallel trends (DiD), poor fit / extrapolation (synthetic control), invalid or weak instruments (IV).
Setting / Data
n/a — methodological review (econometrics).
Key Claims
- Modern program evaluation is organized around identification strategies, each with an explicit, often untestable, key assumption.
- No method dominates; choice depends on the assignment mechanism and available data.
- Estimation is secondary to a credible identification argument.
Connections
- A map of the whole vault: links Foundations, DiD, IV, RDD, PSM, SCM.
- Companion broad surveys: ImbensWooldridge2009-ProgramEvaluation, AngristPischke2010-CredibilityRevolution.
Citation
Abadie, A., & Cattaneo, M. D. (2018). Econometric Methods for Program Evaluation. Annual Review of Economics, 10, 465–503.