Weekly links May 14: Microcredit summarized, better targeting of vocational training, (almost) destroy your own graphs, and more….

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·       A new VoxDevLit is out on microcredit. A very nice summary of the literature, although on first read I was wondering where all the discussion was of new forms of microloans taking place through digital means,   like M-Shwari where borrowers can borrow as little as $1 through their phones, but then realized that some of this is covered in the previous literature review done on mobile money. The review never defines what it means by microcredit, and I realize that the term is less clear than it used to be when everyone all had a Grameen-like model in mind.

·       At Ideas for India, Wiji Arulampalam and co-authors summarize an experiment done to improve the targeting and effectiveness of vocational training for rural disadvantaged youth. They aim to address the mismatch between the types of jobs available after training and what youth might expect through a couple of classroom sessions that explain more what training entails and what jobs are typical afterwards, and find that this increases the likelihood that youth stay in the jobs in which they were placed, with heterogenous effects (no impact for women, impact for men; it selects less educated youth, while more educated youth drop out after seeing the jobs likely).

·       Katie Hoeberling on the BITSS blog looks back on insights from the first year of the Social Science Prediction Platform: “Since launching nearly ten months ago, the SSPP has welcomed over 1,700 users and 19 projects that have collected over 1,600 predictions…For the most part, researchers have collected predictions of summary statistics and treatment effects. While the SSPP is clearly useful for experimental work, it seems to work just as well for observational research. Arun Advani, Elliott Ash, David Cai, and Imran Rasul, for example, collected economists’ predictions on the prevalence of race-related research in economics journals, showing later that most overestimated these rates”

·       Andrew Gelman on how you do not want to smooth graphs too much, in a nice short post called “any graph should contain the seeds of its own destruction”.

·       Dany Bahar interviews Seema Jayachandran and discusses her work on how gender gaps arise and have impacts in early life.

·       The Guardian has a selection of striking and innovative photos from the shortlisted projects in the 2021 CAP Prize for African photography

Authors

David McKenzie

Lead Economist, Development Research Group, World Bank

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