L8: Randomized Evaluations 2

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Slides for this lecture are available below. My notes.
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The material below is taken from the website J-PAL (Abdul Latif Jameel Poverty Action Lab) (highly recommended). Please check the website for more material.

Threats and Analysis

In the following video Don Greene illustrates some of the challenges that can occur while conducting a randomized evaluation and how researchers handle these challenges. He  uses two case studies to show how to analyze and interpret the results from a randomized evaluation in the presence of various threats to analysis, such as attrition and non-compliance.

Slides; Case Study: Deworming Program in Kenya; Case Study: Training and Wage Subsidies in Jordan.



How can results from one context inform policies in another? This lecture of Rachel Glennester provides a framework for how to apply evidence across contexts.


Please now answer Assignment 8 based on the reading for this lecture.

Deadline: Wednesday, October 7, at 15:15.

Suggested answers available here after the deadline.

Please connect to my Zoom (link in Absalon) on Wednesday, October 7, at 15:15


I will summarize the main ideas of this lecture and I will asnwer your questions.

After that you will have time to work online with your group. See below.

Group Work: Data analysis Plan (go to Activity)

Explain how you want to test the efficacy of your intervention: output measure, number of treatments, sample size, predictions and statistical analysis you intend to use.

Explain also how you plan to measure the necessary variables and how you want to gather your data.

Have in mind that testing behavioral interventions is the key step. Good policy design should use more pilots and trials to test if the intervention is working and to prevent the implementation of costly policies without generating results.

Together with your group, you have to fill the corresponding cell of this Google Spreadsheet. Deadline: before next lecture.

Summary for this lecture:

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