· On VoxDev, Alix Bonargent summarizes her work looking at IGC projects to see what features of projects are associated with them having more policy impact. “he final dataset consists of over 500 research projects initiated between 2009 and 2018…The primary measure of policy impact captures any instances of change in programmatic or operational decisions by local policymakers after project completion, as well as the decision to commission additional research….Designing and implementing a research project with a policymaker increases the likelihood of policy change by 17 to 20 percentage points. This magnitude is substantial when compared to the mere 3% of non-partnership projects that resulted in evidence uptake…The election cycle also affects the policy outcomes of co-created projects: these projects are 15 percentage points less likely to result in policy change when initiated in the two years prior to an election compared to those started earlier in the term”
· On the Agency Fund blog, Paul Wang and Richard Sedlmayr note that many evidence-oriented implementors seem really wedded to ideas they have tried which have proven successful in a small-scale trial – what they term the “nail it and scale it” paradigm – “This is the idea that translating evidence into change involves 1) tinkering with an innovation, then 2) demonstrating cost-effectiveness by conducting a rigorous evaluation, and finally 3) scaling the program for widespread impact. With NITSI, most improvement occurs when a given program is small; at scale, learning and innovation focuses on the nuances of implementation, while the core intervention remains unchanged.” – they contrast this with a continual learning or “shed your skin” paradigm and notes that microentrepreneurship is one such space where this is needed: “it is not yet time for the research community to “mic drop” and for implementers to simply “scale up”. A long list of challenging questions remain – about suitable contexts, heterogeneity, implementation modalities, spillovers, and so on – and findings will continue to evolve as programs are adapted in the face of emerging lessons and technological change. In the future, the most cost-effective approaches to stimulating entrepreneurship – and countless other complex and hard-to-measure challenges – may end up looking quite different.”
· In Foreign Affairs - A requiem for hyperglobalization – Dev Patel, Justin Sandefur, and Arvind Subramanian on the period between 1990 and 2020 when the developing world was converging towards rich countries. “Hyperglobalization is simply globalization on steroids. Beginning in the late 1980s, three critical factors drove a truly exponential rise in these flows: a rapid decline in the cost of transporting goods and communicating across borders; political leaders’ embrace of more globalization-friendly policies; and perhaps most fundamentally, the end of the Cold War….this convergence reflected three distinct and related phenomena: faster growth in poorer countries; less volatility in domestic countries’ economic growth rates, suggesting that poor nations were becoming less vulnerable to economic shocks; and particularly stellar and steady growth by middle-income countries, belying the assumption that such countries would struggle to grow once they crossed a certain income-per-capita threshold”
· Oliver Kim on the research so far on the desirability of jobs in Ethiopian factories and whether manufacturing will be a source of lots of jobs growth: “this points to a central tension in Ethiopia’s strategy—the situation could reasonably be described as a pernicious low-wage, low-productivity equilibrium. From the workers’ point of view, low wages make an already intolerable work environment unacceptable. The resulting attrition erodes efficiency—every new worker who has to be recruited, trained, brought up to speed is a cost to the firm. And yet, with chronically low productivity, Ethiopia only has one carrot with which to draw international investors: low labor costs.”
· A reminder that slides and videos are up now for most lectures in STEG’s course on Data in Macro Development, including recent lectures on Climate and Weather Data, Cellphone data, and primary data collection. In her lecture on primary data collection, Meredith Startz addresses the idea that administrative data are more objective and more representative, noting that this is often not the case – as well as the advice “LOOK AT YOUR DATA. LOOK AT YOUR DATA. LOOK AT YOUR DATA. (Before it’s too late.)” The last lecture is next week, on Time use data.
· Dave Evans and Pam Jakiela have a post up for father’s day on the IDB blog which give 5 findings about the role of fathers in early childhood development. Must also be time for me to relink to my 2012 post on dads and development. Happy (US) Father’s Day!
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