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Thinking about how to target anti-poverty programs: ordeals or proxy means tests?

Markus Goldstein's picture
When we want to target a poor population for an anti-poverty program, we first need to figure out who is actually poor.    This isn’t straightforward – there are a range of potential targeting criteria and options.    In countries where poverty is less dense and data is decent, two of the more common options are self-targeting and proxy means tests.    A nice recent paper by Vivi Alatas, Abjijit Banerjee, Rema Hanna, Benjamin Olken, Ririn Purnamasari, and Matthew Wai-Poi sheds some light on the r

Three new papers on measuring stuff that is difficult to measure

David McKenzie's picture
There are a number of things we would like to measure for which a direct question may be refused or met with an inaccurate answer. Three new papers demonstrate some of the methods that can be used to help overcome these problems.

Paper 1: List randomization for measuring illegal migration

Behind low rates of participation in micro-insurance: a misunderstanding of the insurance concept?

Jed Friedman's picture
Micro-insurance pilot programs begin with grand hopes that the target population will enroll and obtain program benefits, but many are disappointed that after much planning and effort so few actually take up the program. Apparently take-up rates greater than 30% are rare and often do not exceed 15%. Furthermore, only a fraction of beneficiaries choose to renew their participation after the initial enrollment period.

Weekly links June 27: badly managed Indian schools, evaluating peace-building, the perils of misunderstanding significance, new power calculations, and more…

David McKenzie's picture
  • In the LSE Centrepiece, Renata Lemos and Daniela Scur have a short piece summarizing new results from measuring management in retail, health, education and manufacturing in India: “In retail, the top 10% of Indian stores are better managed than 40% of US stores and 57% of UK stores. But in education, only 8% of US schools and 1% of UK schools are less well managed than the best 10% of Indian schools.”

Friday links June 21: measuring the cost of microfinance, cost-ineffective monitoring, new Stata commands, and more…

David McKenzie's picture
  • On the FAI blog, Jonathan Morduch discusses the problems of trying to measure the cost of microfinance and why the profession underfocuses on costs – “if you’re not the kind of person who gets pleasure from filling out income tax forms, you’re probably not the kind of person who enjoys calculating microfinance subsidies”.

When field studies diverge from lab experiments: the case of incentivized blood donations: Guest post by Mario Macis

Do economic incentives crowd out individuals’ intrinsic motivation for certain activities that are performed in the absence of explicit rewards, such as volunteering in soup kitchens, recycling, or giving blood? This is an important question with implications for public policy and has been explored on Development Impact with a number of recent posts (here is the latest one from Jed).

Public randomization ceremonies

Damien de Walque's picture

With Jake Robyn* and Gaston Sorgho**

Randomization might- at first – sound like a scary word for health policy makers and professionals. They read medical journals and know from their training that randomized trials are scientifically rigorous designs to evaluate the impact of a program. But their first inclination might be to prefer to have the randomized trial in somebody else’s backyard. Randomization seems politically difficult. How to explain it to the people who will have to wait for the new intervention? Will it not create a backlash with the people who are randomly assigned to the control group? How will the population be convinced that the random allocation was fair and that there were no back room deals?

Our experience in many countries is that public randomization ceremonies are an excellent platform to build support for randomization and for the entire impact evaluation process. In Cameroon, we organized public randomization ceremonies in three Regions to assign health facilities to four study groups in an impact evaluation of performance-based financing (PBF) in the health sector. Held in the regional capitals and combined with the official launching of the project in each Region, we invited representatives of each facility, district health management teams, and local government, who all took part themselves in the randomization. Each of the randomization ceremonies received close oversight from the central and regional levels of the Ministry of Public Health. This made the randomization process completely fair and transparent to all health facilities participating in the study.