Impact Evaluation Methods with Applications in Low- and Middle-Income Countries
Economic development is about making a difference in the lives of the poor, through interventions in the health, education, microfinance, transport, agriculture, and other sectors. This course will provide you with the experimental and statistical tools you need to measure the impacts you are hoping to see. How do you design and conduct a randomized control trial, and how do you evaluate the data using regression techniques? What other quasi-experimental methods can be used? How do you know you’re making a difference?
About this courseSkip About this course
Economic development is a process of trial and error, innovation and experimentation, success and failure. Given the right institutions, some not unfavorable resource endowments, and a bit of luck, incomes can grow, health can improve, and human development can flourish; other times, things don’t turn out so well.
Given the urgency of development challenges, it is imperative that we learn quickly from our mistakes and build robustly on our successes. The hope is that by understanding what kinds of innovations and policies “work” to improve the lives of the deprived and vulnerable, and how they work, we might be better placed to accelerate the process of development more generally. But how can policy makers and international development practitioners be sure they’re “making a difference?”
This course was created collaboratively by Georgetown University and the World Bank's Strategic Impact Evaluation Fund with support from the Georgetown Center for New Designs in Learning and Scholarship, Georgetown University Initiative of Innovation, Development and Evaluation (gui2de), and The Open Learning Campus of the World Bank Group.
At a glance
What you'll learnSkip What you'll learn
- Define impact evaluation and recognize its importance.
- Describe the importance of randomization and the problems that can arise in randomized controlled trials (RCTs).
- Identify statistical concepts and tools for program evaluation.
- Interpret the concept of regression and how it informs RCT results.
- Illustrate the balance between sample size and cost of trial.
- Explain the value and application of quasi experimental methods