Sounds good... but what will it cost? Making the case for rigorous costing in impact evaluation research

Imagine two government programs—a job training program and a job matching program—that perform equally well in terms of boosting employment outcomes. Now think about which is more cost-effective. If your answer is ‘no idea’ you’re not alone! Most of the time, we don’t have the cost evidence available to discern this important difference.

Putting government in the driver’s seat to generate and use impact evaluations in the Philippines

Impact evaluations are sometimes criticised for being supply-driven. It is hard to know for sure. There is no counterfactual to what would have happened without the impact evaluation. Regardless of whether this is true or not, one of the ways to ensure that an impact evaluation is more demand-driven is to put the government in the driver’s seat for increasing the demand for evaluation.

3ie: from take-off to cruising through an ever changing world

Even though it’s been over three years since I joined 3ie, I was still fascinated to read Howard White’s reflections on how it all started. A question that has often come up for me as well is about why I’m in Delhi. As Howard said, the vision of an organisation having its locus of authority be in the Global South, is something that attracted me as well.

3ie: from starting up to taking off

Back in 2008, 3ie was just my laptop and me. It has come a long way since then. Although I bid farewell to the organisation in 2015, I have continued to watch how the organisation has grown. What has 3ie achieved in the last ten years?

Misdiagnosis and the evidence trap: a tale of inadequate program design

Imagine you wake up tomorrow with a headache, sore throat and fever, perhaps nothing unusual at this time of the year. You drag yourself out of bed and head to your doctor to ask her for something to make you feel better. However, if you had first looked up your symptoms on the net, you would have been surprised to find that headache, sore throat and fever can be caused by 136 different conditions, among them typhoid fever, measles, and brain tumour.

Agricultural innovation: where does the evidence lie?

Improving agricultural innovations and technologies in developing countries is of paramount importance to increase agricultural production and income sustainability. Although many agricultural technologies are available, adoption remains low among smallholder farmers.

Promoting latrine use in rural India: what does the evidence say?

India is responsible for the majority of the world’s open defecation – a practice that spreads disease and cuts lives short. To address the issue, the Indian government’s Swachh Bharat Mission (SBM; Clean India Mission), which completes its third year, has been providing toilets, particularly in rural areas where they are most needed.  SBM has also made explicit the importance of behaviour change and getting people to use those toilets.

Strengthening impact evaluation ecosystems by supporting local research teams

Building a culture of evidence is a tall order, one that demands the engagement of different stakeholders committed to evidence-informed policy. While we embed capacity-building activities in our grant programmes, we continue to explore alternative approaches beyond our grants to increase local researchers’ familiarity with impact evaluation, so the pool of research centers able to provide impact evaluation services in a given country expands.

How many scientific facts are there about science, technology, and innovation for development?

In a recent blog post, Ronda Zelezny-Green and Alexandra Tyers claim “now scientific fact: mobile money can lift women out of poverty”. The scientific fact they cite comes from a new study [gated] published in Science by Tavneet Suri and William Jack. This study is an impact evaluation of M-PESA in Kenya using a quasi-experimental design, and it finds that increased access to M-PESA is associated with a decrease in poverty.

What’s first for replication studies is what’s next for 3ie’s replication programme

Many consider pure replication, where the replication researcher starts with the original data set and writes code to recreate the published results according to the methods described in the publication, to be the second step in replication analysis. So, what is the first?