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Development Impact turns 6: six questions for our sixth birthday

David McKenzie's picture
We are proud to have kept the blog going for another year, and would like to note its 6th birthday. In lieu of presents, we’d love your thoughts on what things you would like to see more or less of going forward. In particular, any comments or feedback on the following would be great:

Weekly links March 31: inequality across firms and within households, measuring farm labor, should we fund research by lottery, and more…

David McKenzie's picture
  • In the Harvard Business Review, Nick Bloom discusses how a lot of inequality is getting driven by differences between firms: “companies are paying more to get more: boosting salaries to recruit top talent or to add workers with sought-after skills. The result is that highly skilled and well-educated workers flock to companies that can afford to offer generous salaries, benefits, and perks — and further fuel their companies’ momentum. Employees in less-successful companies continue to be poorly paid and their companies fall further behind”
  • Vox EU piece by Brown, van de Walle and Ravallion summarizing their work in two recent papers on the difficulties in targeting the poor “about three-quarters of underweight women and undernourished children are not found in the poorest 20% of households. This is consistent with evidence of considerable intra-household inequality”

10 journals for publishing a short economics paper

David Evans's picture
In the middle of the Ebola outbreak in West Africa, I noticed that there were numbers being released on the number of orphans the outbreak was creating, but no transparent methodology for where those numbers were coming from. My colleague Anna Popova and I constructed numbers based on age- and gender-specific mortality and fertility rates, and we submitted the paper to the Lancet. It was a short but – we thought – useful paper.

Should I stay or should I go? Marriage markets and household consumption

Berk Ozler's picture

“We propose a model of the household with consumption, production and revealed preference conditions for stability on the marriage market. We define marital instability in terms of the consumption gains to remarrying another individual in the same marriage market, and to being single. We find that a 1 percentage point increase in the wife’s estimated consumption gains from remarriage is significantly associated with a 0.6 percentage point increase in divorce probability in the next three years.”

Weekly links March 24: why those of us in our 40s matter so much, an ALMP program that may be working, more CSAE round-ups, and more…

David McKenzie's picture

The Iron Law of ALMPs: Offer a Program to 100 People, maybe 2 get jobs

David McKenzie's picture

I have just finished writing up and expanding my recent policy talk on active labor market policies (ALMPs) into a research paper (ungated version) which provides a critical overview of impact evaluations on this topic. While my talk focused more on summarizing a lot of my own work on this topic, for this review paper I looked a lot more into the growing number of randomized experiments evaluating these policies in developing countries. Much of this literature is very new: out of the 24 RCTs I summarize results from in several tables, 16 were published in 2015 or later, and only one before 2011.

I focus on three main types of ALMPs: vocational training programs, wage subsidies, and job search assistance services like screening and matching. I’ll summarize a few findings and implications for evaluations that might be of most interest to our blog readers – the paper then, of course, provides a lot more detail and discusses more some of the implications for policy and for other types of ALMPs.

Weekly links March 17: Irish insights, non-working rural women, changes afoot in IRBs, and more…

David McKenzie's picture

What’s new in education research? Impact evaluations and measurement – March round-up

David Evans's picture



Here is a curated round-up of recent research on education in low- and middle-income countries, with a few findings from high-income countries that I found relevant. All are from the last few months, since my last round-up.

If I’m missing recent articles that you’ve found useful, please add them in the comments!

A pre-analysis plan is the only way to take your p-value at face-value

Berk Ozler's picture

Andrew Gelman has a post from last week that discusses the value of preregistration of studies as being akin to the value of random sampling and RCTs that allow you to make inferences without relying on untestable assumptions. His argument, which is nicely described in this paper, is that we don’t need to assume nefarious practices by study authors, such as specification searching, selective reporting, etc. to worry about the p-value reported in the paper we’re reading being correct.

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