This database provides access to impact evaluations of World Bank-supported interventions and impact evaluations undertaken by World Bank staff over the past few years. This database is an ongoing process and currently covers impact evaluations of social funds, conditional cash transfer programs, and health, water, urban, and transport sector interventions. Other sectors will be added progressively.
This database only includes impact evaluations (ex-ante and ex-post), where an intervention outcome is assessed against an explicit counterfactual. No other criteria were used. The database does not discriminate on the basis of quality. Hence, inclusion in the database does not imply World Bank endorsement of the methodology or findings.
Some evaluations and interventions might appear under different queries, since some interventions have more than one impact evaluation or cover more than one sector, and some evaluations cover more than one intervention.
For each impact evaluation, the database provides a quick description of the intervention under scrutiny, the evaluation design, the results of the impact evaluation (the results reported are significant at the 5% level, unless otherwise noted), and a link to the document, if publicly available. The interface allows the user to search the database by country, region, sector and/or evaluation method. The following categories are used to classify evaluation methods. These categories are in practice often combined:
- Randomization or Experimental Design. This method applies to interventions where participants are randomly assigned to the intervention. Participants and non-participants have the same ex-ante probability of participating in the intervention. Impact can be estimated by comparing the two groups.
- Propensity Score Matching. This method calculates propensity scores (probability of participating in the intervention as a function of observed characteristics) for participants and non-participants. Participants are matched to non-participants on the basis of their scores.
- Pipeline Comparison. This method uses those who have applied and are eligible to receive the intervention in the future, but have not yet received it, as a comparison group. Their only difference with the current recipients is that they haven’t yet received the intervention.
- Simulated counterfactual. This method is used for interventions affecting the entire population, for which no comparison group can be identified. A counterfactual distribution of outcomes in the absence of the intervention is simulated on the basis of a theoretical model and information on the situation prior to the intervention.
- Difference in means or Single Difference. This method estimates impacts by comparing the value of the indicator of interest for the recipients and the non-recipients.
- Difference-in-difference or Double Difference. This method estimates impacts by comparing the value of the indicator of interest between the recipients and non-recipients (first difference) before and after an intervention (second difference).
- Instrumental Variables. This method uses instrumental variables (that affect receipt of the intervention but not the outcomes of interest) to control for selection bias when intervention placement is not random.
We welcome your comments, as well as suggestions for impact evaluations that could be included in the database. Please send these to email@example.com.
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