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Randomized Control Trials

Randomized Control Trials . Difficulties to Consider. Costs. Cost of intervention itself often not difficult to justify Providing goods/services Only including promising possibilities New data are expensive Quality of evaluation dependent on quality of data

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Randomized Control Trials

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  1. Randomized Control Trials Difficulties to Consider

  2. Costs • Cost of intervention itself often not difficult to justify • Providing goods/services • Only including promising possibilities • New data are expensive • Quality of evaluation dependent on quality of data • More money spent on data is less money spent on providing the intervention to more people

  3. Creating the Control Group • Is it politically feasible to deny treatment to some people? • How important is it to measure how well the intervention works? • Issue of trade-offs • Ethics less contested if: • Budget constraints would have prevented everyone from receiving the intervention anyway • Everyone eventually receives the intervention and the control group is only denied it initially (phased-in rollout)

  4. Does Everyone Benefit? • Necessary to deny control group intervention • But don’t want to actively hurt them • Can’t deceive • Can’t make them worse off than they’d otherwise be • Some sort of small gift/compensation typical – careful not to make this into a second treatment • Must honor promises (phased-in rollout)

  5. Internal Validity • Was the control group valid? • Randomization worked • Intended treatment and control groups balanced • Actual treatment and control groups same as intended • Contamination from spillovers • Was the intervention consistent in all treatment areas? • Easier to guarantee in some cases than in others • Do data exist to rule out alternate hypotheses?

  6. External Validity • Will the subjects in the experiment be representative of the entire population who will eventually receive the intervention? • Logistically, much easier to do data collection in restricted area • Less likely that experiment will generalize to entire country

  7. Data Quality • Sensitive questions • How can we encourage subjects to give honest and complete answers? • Subjective questions • Self-reported vs quantitative measures • “recall error” • Hawthorne effect - People behave differently when they know they’re being watched • Might be desirable to follow them closely for more data • But that might make biases worse

  8. Cost-Effectiveness Comparisons • Resources are scarce – need to pick most effective programs • Need to be able to convert impacts from various projects into one set of units • How to compare improvement in nutrition to reduction in malaria?

  9. Scaling Up • Can intervention be implemented identically at scale? • If not, is RCT still informative? • Will the economy at large respond to the intervention at scale? (“general equilibrium effects”) • Prices might go down – economies of scale • Prices might go up – insufficient supply • Spillover effects could set in

  10. Final Thoughts • RCT is gold-standard in terms of identifying causality • But many complications arise during implementation • Need to weigh theoretical advantages against practicalities – is it really the best method?

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