GCRI · Mathematics, statistics and data
Causal inference and impact evaluation
Causal inference and impact evaluation develop methods to determine whether and how interventions or exposures cause outcomes. They separate genuine effects from correlation. Economic Development stewards this page for the Nexus Consortium.
01Register
Causal inference and impact evaluation on the record.
The Global Centre for Risk and Innovation
- 01InstitutionThe Global Centre for Risk and Innovation (GCRI)
- 02The methodWhat causal inference and impact evaluation covers
- 03Reference practiceCausal inference follows evaluation and reporting standards
- 04In systemic risk workWhat actually reduced risk
- 05Applied inPlatforms that apply this method
- 06StewardshipWho maintains this page
- 07SourcesWhere this page’s references lead
02The method
What causal inference and impact evaluation covers.
- 01
Core methods
randomised controlled trials; difference-in-differences; instrumental variables; regression discontinuity; matching and weighting; causal graphical models.
- 02
Data and instruments
experimental data; panel datasets; administrative records; natural experiments; survey data.
- 03
Validation
Identification assumptions are probed through placebo tests, falsification checks and sensitivity analysis. Replication across settings tests external validity.
- 04
Limits
Unobserved confounding and spillovers can bias estimates. Effects found in one context may not transfer to another.
- 05
Use in risk decisions
Causal inference shows which risk reduction measures actually work. It supports allocating resources toward interventions with demonstrated effect across connected risks.
03Reference practice
Causal inference follows evaluation and reporting standards.
| Reference | What it sets |
|---|---|
| OECD DAC evaluation criteria | Evaluation of interventions |
| EQUATOR guidelines | Reporting of studies |
| GRADE | Certainty of evidence |
04Process
How the process runs.
Process
Causal inference and impact evaluation: PRISMA 2020 review reporting
PRISMA 2020 is a reporting guideline for systematic reviews; the steps follow its checklist, not a mandated sequence, and no Nexus document adopts it.
01 Plan
- 01Registration and protocolRecord · The review teamThe guideline asks for registration details, access to the protocol and any amendments.
- 02Eligibility criteriaRecord · The review teamThe guideline asks for the inclusion and exclusion criteria and how studies were grouped.
02 Find and select
- 03Search: sources and strategiesStep · The review teamThe guideline asks for the information sources and the full search strategies. It does not fix which sources are used.
- 04Selection of studiesStep · The review teamThe guideline asks how studies were judged eligible, including how many reviewers screened. It does not fix the number of reviewers.
- 05Flow diagramRecordThe flow diagram shows the number of records found, the number of studies included and the reasons for exclusion.
03 Analyse
- 06Data collectionStep · The review teamThe guideline asks how data were collected from reports and which data items were sought.
- 07Risk of biasStep · The review teamThe guideline asks for the methods and tools used to assess risk of bias.
- 08SynthesisModel · The review teamThe guideline asks for the effect measures and the synthesis methods. It does not prescribe meta-analysis.
- 09Certainty of evidenceStep · The review teamThe guideline asks for the methods used to assess certainty, and reports the result per outcome. It does not name a grading scale.
04 Report
- 10Review reportRecordThe guideline helps authors report why the review was done, what they did and what they found.
ReportsOutline of an externally published reporting guideline, not a Nexus process and not a record of operation. PRISMA 2020 mainly covers reviews of intervention effects. No Nexus page names it. Every programme is at service level R0.
05In systemic risk work
What actually reduced risk.
Risk reduction investments need evidence of effect. Causal inference (experiments, natural experiments, difference-in-differences, synthetic controls) identifies effects, but disasters are rare and contexts differ, so external validity is the main limit.
- State identification assumptions.
- Assess transferability to other contexts.
- Avoid attributing outcomes to interventions without a counterfactual.
- Applications on Economic Development and Human Development.
07Stewardship
Who maintains this page.
Economic Development stewards causal inference and impact evaluation: it keeps this description current and reviews how the method is applied across the platforms.
08Sources
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
09Questions
Questions and answers.
Why does one institution host every method page?
GCRI hosts the STEM Commons so that each method has one canonical description. Platforms link to it rather than repeat it, which keeps definitions consistent.
How do I suggest a correction to a method page?
Write to the integrity concern form with the passage and the reason.
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Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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