Let’s begin with a super meta-analysis on the effects of conditional cash transfers on education! García and Saavedra provide an excellent review of the literature and confirm overall trends in results. Four takeaways emerge (see also graphs above): there are clear effects on schooling; little impacts on learning; there are relatively high costs of implementation; but the high heterogeneity in all those results calls for caution in formulating firm CCT cost-benefit conclusions.
But that’s not the only review out this week… there are at least two other great summaries of cash transfers design and impacts! One is by Dwyer et al contrasting 87 programs in high vs low- and middle-income countries: what’s the difference? For once is the steep benefit “cliffs” in advanced economies. The other review is by Sida, which produced a crisp review of the literature on cash transfers. Drawing from 152 studies, the evidence is organized around core thematic sectors – economic effects, health, education, gender, and social cohesion – as well as on a subset of design choices, including payments, transfer selection, conditionality, and graduation approaches (h/t Pontus Korsgren).
And education also features in a new study on Kenya: Austrian et al evaluate what happened 4 years after a cash transfer-plus program was implemented in the county’s pastoralist areas. They found that there was no impact on girls initially enrolled in school (11-14 years old at the time); yet among girls that weren’t enrolled, the program reduced marriage by a sizable 34% and pregnancy by 43%.
Let’s stay in Africa, but turning to electricity subsidies! The JDE version of the paper by Berkouwer et al on Ghana’s Covid-19 electricity relief program is out. The program included a subsidy of 50kWh (worth $3.5) for April–June 2020 to ‘lifeline’ customers (those who used less than 50kWh/month at baseline), and monthly transfers worth 50% of baseline usage for all other residential customers. How did it work? The subsidy was regressive in incidence, with households “… receiving the least average relief are those who use less electricity, pay a landlord or other intermediary for electricity, or share an electricity meter — characteristics of low-income households”. Design was compounded by implementation hurdles, including delays, technological challenges, information constraints, and targeting based on meters rather than households.
From Africa to LAC: Rolon et al have a paper reviewing LAC’s social protection Covid responses in rural areas, including with a comparison of four interesting and relatively less-known transfer programs – i.e., Argentina’s PACyD, Belize’s CERC, Mexico’s Bienpesca, and Panama’s Plan Panamá Agro Solidario.
From LAC to Europe: Avlijas produced a handy review of social protection programs for the self-employed across the EU. The report focuses on sickness, accidents at work and occupational diseases, and unemployment benefits with analysis based on pre-Covid data (but it also briefly discusses pandemic responses on p.39-40). Bonus! The growing family of “basic income pilots” has a new member: Wales will offer £1,600/month for 2 years to 500 young care leavers (h/t Heather Kindness, Will Wiseman).
And from the EU to the US! The writing was on the wall, but now there are numbers: a brief by Parolin et al estimates that in January 2022, the expiration of the monthly Child Tax Credit program pushed 3.7 million children in poverty, representing a 5 percentage point increase in child poverty (now at 17%).
News from Asia? Consumption ≠ nutrition! Bartell et al present new evidence on the effects of food subsidies (PDS) in India’s state of Andhra Pradesh: they show that the PDS bolsters consumption of rice (30g/day) and sugar (7/day), but has no effects on child nutrition. And in China, a paper by Cameron et al shows that 61 million children remain in rural villages as their parents migrate to cities. When reaching adulthood, those “left behind” children are more likely to commit crimes (h/t Elena Glinskaya).
“Accelerator” vs “Fund”: a blog by Cichon clarifies differences and commonalities between two initiatives, the “Global Fund for Social Protection” and the “Global Accelerator for Jobs and Social Protection”. The price tags are non-trivial: the Accelerator would cost low- and middle-income countries about of $2.2 trillion (982 billion for jobs, $1.2 trillion for social protection floors). An initial investment of $600 million would be needed to finance a “technical support facility for the implementation of Accelerator projects on a country level”. The Global Fund, largely funded by donors, would be of smaller size, or about 0.5-0.8% of the Accelerator’s budget. In other words, “… [t]his is roughly equivalent to saying that 99% of all resources to close the estimated global social protection floor gap will have to be coming from national resources”. (For more details, see also a full paper by Cichon and Lanz on “creating fiscal and policy space”).
Kiosk announcement: GiveDirectly has opened up seven roles in its Growth Team, including External Communications Manager; Front-End Developer; Marketing Manager, Growth; Senior Manager, Acquisition and Community; Software Engineer; VP, Business Development; and VP, Growth (h/t Cristina Sharpe)
Finally, as anticipated in early February here is the downloadable Excel database with all data from our tracker of nearly 4,000 social protection responses to the pandemic. Hope it’s useful for your research and analysis!