Forecast-based instruments are increasingly central to the ‘adaptive’ social protection agenda. These are a somewhat an extension of early warning systems, and incorporate protocols for implementation and finance in areas facing humanitarian and disaster risks. A super-interesting ODI report by Wilkinson et al identifies the core features of over two-dozen forecast-based programs and examine the full application, i.e., the choices about forecast and monitoring data, selection of triggers and thresholds (and methods for integrating bio-physical and socio-economic impact data), protocols for delivery, and the financing mechanisms.
From natural disasters to a specific form of forced displacement. When constructing a huge Dam in India’s Gujarat state, over a 100,000 tribal people were displaced. The Gujarat government promised to offer each male adult five acres of land, plus additional compensation for loss of houses and livestock. An NBER paper by Ajar and Khaushal presents an experiment investigating whether resettled populations were better off in 2017, approximately three decades after resettlement, than comparable neighbors who were not ousted. They found that the displaced were far better off than their former forest neighbors in ownership of a range of assets (e.g., TVs, cellphones, vehicles, and access to services/markets). However, despite enhanced economic wellbeing about half (54%) of displaced folk wished to return to their old habitat. Nearby undisplaced forest dwellers were asked if they would like to be “forcibly” resettled with the full compensation package. Of two forest groups, 31% and 52% responded favorably.
Speaking of moving, Pritchett weighs in (again) on the ‘graduation’ or assets transfer model: in a new CGD paper, he estimates that gains in such interventions are about 40 times smaller than letting people migrate to a high-productivity destination. His second-best option? Broad-based domestic economic growth, which he argues is “many-fold” larger in impact on poverty than direct individual interventions.
Back to transfers, a new evaluation by Courtin et al investigate the impact of the old CCT in New York City (h/t Dave Evans). The program, called Family Rewards, supported 2,377 families between 2007-2010 and led to overall modest effects. Specially, it helped improve in health insurance coverage, increased the use of preventive dental care, and enhanced parents’ qualitative perception of their own health and levels of hope. However, the program was consequently phased out, although a new experiment was eventually set up in Memphis.
Goldstein and Evans have a great round-up of papers from Oxford’s CSAE conference on economic development in Africa. Among the social protection-related materials: a secondary school stipend (with a condition on not being married) in Bangladesh led to higher education and no change in fertility or female labor force participation (Tanaka and Otzuka) is it better to get cash transfers quarterly or monthly? In Nigeria it doesn’t matter for nutrition, consumption or investment outcomes (Bastian et al); and bank cards for cash grants in South Africa increase women’s autonomy, which in turn augments female labor force participation by 62% (Biljon et al).
What’s the latest on public works? Gehrke and Hartwig’s review of the evidence suggests that PW programs can induce productive investments via income and insurance effects when the program is sufficiently reliable and long-term. These can also have positive welfare effects by raising wages, but also potential adverse effects on labor markets. Implicit or explicit training components of PW programs do not seem to increase the employability or business earnings of participants. Finally, there is only scant empirical evidence on the productive effects of the public infrastructure generated by PW programs. The paper concludes that PW programs are only preferable over alternative interventions if they generate substantial investments among the target group, if there is clear evidence that private-sector wages are below equilibrium wages, or if the public infrastructure generated in PW programs has substantial growth effects. Bonus: Karlan et al illustrate the competing productivity-equity objectives of a program: the authors ran an RCT on a microcredit organization in the Philippines which tried to hand out loans on poverty-based targeting criteria. While well-intended, the program ended up confusing and overworking loan officers, with no additional poor applicants and lower-performing loans.
Can a social protection system be at the same time inequality-reducing and poverty-augmenting? Yes it can. A new working paper by Davalos et al examines the redistributive effect of fiscal policy on income distribution and poverty in Albania. Based on the CEQ methodology, the authors found that the fiscal system played a positive role in reducing inequality. Yet, taxes and contributions had a moderate poverty-increasing effect, particularly VAT taxes. This effect is somewhat compensated by direct pro-poor government transfers (e.g., Ndihma Ekonomike program), but which are not large enough to offset fully the negative impact on the taxation side. More on fiscal transfers: in a thought-provoking, forthcoming WD article Masaki finds that in rural Tanzania, intergovernmental transfers facilitate local revenue mobilization instead of undermining it. This is because financial transfers from the central government for public services seems to generate further local revenues by promoting voluntary tax compliance. Bonus: Kanbur et al. have an elegant technical article on optimal taxation.
Final assortment: a cautionary tale by Courtemanche et al illustrates how administrative and survey-based measure can lead to profoundly different results in SNAP, the US food voucher programs; and Tyler Cowen interviews Chris Blattman on array of issues, such as cash transfers, conflicts, industrialization, and technological change.