![Worker cleans solar panels](/sites/default/files/styles/full_width/public/images/2024/02/homepage_q1_2024%20%281%29.jpg?itok=rgz08qmO)
![Massachusetts Institute of Technology logo](/themes/custom/jpal/assets/mit-logo-gray.png?1704975626)
Our mission is to reduce poverty by ensuring that policy is informed by scientific evidence. We do this through research, policy outreach, and training.
![Women work at a textile factory](/sites/default/files/styles/full_width_medium_cropped/public/images/2024/03/ESG_Blog_Lead.jpg?itok=8Z0p9YEQ)
Blog
J-PAL expands efforts to promote corporate sustainability and social impact partnerships
After 20 years of evidence generation and synthesis delivered in partnership with cross-sector stakeholders, in the next decade, J-PAL is accelerating our work to bring evidence-based strategies to drive corporate sustainability and social impact.
![Three people looking at a computer screen](/sites/default/files/styles/full_width_medium_cropped/public/images/2024/02/shutterstock_288576791.jpg?itok=dZmTyW_-)
Blog
Regression to the mean: What it is and why it matters for impact evaluations
Regression to the mean is a statistical phenomenon where extreme outcomes tend to be followed by more moderate outcomes—closer to the mean. In the field of social policy, this could mean that individuals selected to participate in a program because of an extreme signal will naturally return back...
![A two-page journal entry](/sites/default/files/styles/full_width_medium_cropped/public/images/2024/03/Journal%20page%202%20%281%29.jpg?itok=ESXozYBx)
Blog
What not-to-do: Wisdom from years of trials (and errors)
In this three-part series, J-PAL South Asia Executive Director Shobhini Mukerji reflects on the lessons learnt from these experiences as she builds her What-Not-Do-List to realise J-PAL’s goal of a poverty-free world.
![An aerial shot of a village.](/sites/default/files/styles/full_width_medium_cropped/public/images/2024/02/shutterstock_2372265849%20%281%29.jpg?itok=1J6bmH0b)
Blog
New resource: Incorporating remote sensing data into randomized evaluations
A growing number of economists are incorporating remotely sensed (RS) data—satellite data in particular—into their studies. For randomized evaluations, remote data collection offers alluring possibilities: lower data collection costs, a longer time series of data both before and after an...