DIME – FRAGILE STATESDUBAI, MAY 31 – JUNE 4

Steps in Implementing an Impact EvaluationVictor Orozco, Development IMpact Evaluation Initiative (DIME)

Steps

Build capacitySet learning

agenda

Design impact evaluation

Plan for IE implementatio

nConduct baseline

Roll out intervention

Collect follow up data

Analyze data

Feed results into policy

Step 1. Build capacity for IE

Objectives: Become informed consumers of impact

evaluation Set the learning agenda Use it as an internal management tool to

improve program over time

How Training Learning by doing

Step 2: Set learning agendaObjective:

Get answers to relevant policy and operational questions

How? Dialectic discussion involving key policy makers

and program managers Technical facilitation to structure framework of

analysis Focus on few critical policy (what) and

operational (how to) questions Discuss agenda with authorizing environment

and constituencies

Cont. 2: Questions Operational: design-choices of program

Institutional arrangements, Delivery mechanisms, Packages, Pricing/incentive

Management purpose Use random trials to test alternatives Measure effects on short term outcomes (months)

▪ take up rates, use, adoption Scale up better implementation modalities

Policy: effectiveness of program Accountability purpose Use random assignment or next best method Measure effects medium to long term Scale up/down, negotiate budget, inform

Step 3: Design IE

Exploit opportunities: Will roll-out take time? Is the budget allocated insufficient to cover everyone? Are there quantitative eligibility rules? If the program has universal access, does it have

imperfect take-up? Set scale:

Pilot to try out an intervention Large scale w. representative sample: more costly,

externally valid Large scale with purposeful sample: less costly,

indicative Do power calculation to determine

minimum sample size

Cont. Step 3

Select “best” method for each of your questions Feasible Requires least assumptions

Ethics Not to deny access to something for

which there is irrefutable evidence Test interventions before scale up when

you have no solid evidence

Step 4: Planning implementation Budget cost items

▪ Staff time (PROJECT FUNDS) and training (DIME)▪ Analytical services and field coordination (DIME)▪ Data collection (PROJECT FUNDS)▪ Discussions and dissemination (shared)

Timeline▪ Use it to organize activities, responsibilities and work

backwards to know when to start Team

▪ Government (program manager, economist/statistician); WB Project team (Task manager or substitute); Research team (Lead researcher, co-researchers, field coordinator); Data collection agency

Step 5: Assignment to treatment and control

The smallest unit of assignment is the unit of intervention Training and Credit: individuals and groups Municipal registration system: municipality

Create listing of treatment units assigned to the intervention and control units that are not

Explain assignment to responsible parties to avoid contamination

Step 6: Baseline data

Quality assurance : IE team (not data collection agency) to Design questionnaire and sample Define terms of reference for data

collection agency Train enumerators Conduct pilot Supervise data collection

Do not collect data before your design is ready and agreed

Cont. Step 6: Baseline data

Contract data collection agency Bureau of Statistics: Integrate with

existing data Ministry concerned: Ministry of

Agriculture/Water Resources/Rural Development

Private agencyAnalyze baseline data a feed back

into program and evaluation design if needed

Check for balance between treatment and control group: do they have similar average characteristics?

Step 7: Roll out interventionConduct intensive monitoring of roll-

out to ensure evaluation is not compromised

What if treatment and control receive the intervention?

What if all the control group receive some other intervention?

Step 8: Follow-up data

Collect follow-up data with the same sample and questionnaire as baseline data

At appropriate intervals

Step 9: Estimate program effects

Randomization: compare average outcomes for treatment and control group

Other methods: Use relevant econometric analysis , test assumptions, check robustness

Are the effects statistically significant? Basic statistical test tells whether differences are due to the

program or to noisy data Are they significant in real terms?

If a program is costly and its effects are small, may not be worthwhile

Are they sustainable? Is the trajectory of results sustained?

Step 10: Discuss, Disseminate and Feedback into policy Are you thinking about this only now? Discuss what are the policy implications of the

results What actions should be taken How to present them to higher ups to justify

changes/budget/scale up? Talk to policy-maker and disseminate to wider

audience If no one knows about it, it won’t make a

difference Make sure the information gets into the right

policy discussions Real time discussions Workshops Reports Policy briefs

Final step: Iterate

What do you need to learn next?