1 Randomization in Practice

Unit of randomization Randomizing at the individual level Randomizing at the group level –School –Community / village –Health center –District How do you tell which level to randomize at?

Unit of randomization Individual randomization gives you a bigger sample size at lower cost Politically may be difficult to have unequal treatment within a community Program can only be implemented at a certain level Spillovers

How to randomize? The lottery Phase-in design Rotation design Encouragement design NB: These are not mutually exclusive 4

How to randomize? Simple case: the lottery –There is oversubscription: you have to choose who will benefit from the program. –Instead of choosing the beneficiaries on criteria (proximity, need), you choose them randomly Is it fair to allocate the program randomly? –Partial lottery –Pilot before full-scale implementation 5

How to randomize? Phase-in design: takes advantage of expansion –You may serve everybody, but not all at once –Choose the first people served randomly –The others will be the comparison, until they get served 6 Adapted from How to Randomize, Rachel Glennerster, J-PAL.

Phase-in Design 7 Adapted from How to Randomize, Rachel Glennerster, J-PAL.

How to randomize? Rotation design –You may serve half of the people, but don’t want to leave people out –Group A gets the program on Year 1, Group B on Year 2 –Group B is control in Year 1, Group B in Year 2 8

Rotation design 9 Adapted from How to Randomize, Rachel Glennerster, J-PAL.

How to randomize? 10 Encouragement design: What to do when you can’t randomize access -Sometimes practically or ethically impossible to randomize program access -But most programs have less than 100% take up -Randomize encouragement to receive treatment Adapted from How to Randomize, Rachel Glennerster, J-PAL.

Encouragement Design 11 Adapted from How to Randomize, Rachel Glennerster, J-PAL.

Key steps in conducting an experiment 1.Understand the program in depth (Theory of Change) 2.Design the study carefully 3.Randomly assign people to treatment or control 4.Collect baseline data ( → panel) 5.Verify that assignment looks random ( ← small sample) 6.Monitor process so that integrity of experiment is not compromised 12

Key steps in conducting an experiment (cont.) 7.Collect follow-up data for both the treatment and control groups in identical ways. 8.Estimate program impacts by comparing mean outcomes of treatment group vs. mean outcomes of control group. 9.Assess whether program impacts are statistically significant and practically significant. 13