Show Notes
Medicine has run rigorous clinical trials since the 1940s. Development economists borrowed the structure of the trials during the credibility revolution. Chris Cotton (Queen's University) argues that they misunderstood an important part of this revolution. One successful study is not a mature evidence base, and policies built on too little evidence tend to disappoint at scale. His answer is a framework of Policy Evidence Readiness Levels, or PERLs, just published in Science. PERLs 1 through 4 categorise the weight of evidence behind an intervention, and are inspired by the scale NASA uses to judge whether a technology is ready for a space mission. He tells Tim Phillips which development programmes have already climbed to the top rung, which were implemented at scale on too little evidence (and what happened when they were), and why his framework, by his own admission, is still a modest PERL level 1. The research behind this episode
Cotton, Christopher. 2026. "Rigor Is Not Readiness: The PERL Framework for Evidence-Based Policy." Science 393 (6810): 463-465. To cite this episode
Phillips, Tim, and Christopher Cotton. 2026. "Evidence-based policy: Why one good trial isn't enough." VoxDev Talks (podcast).
About the guest
Christopher Cotton is Professor of Economics at Queen's University in Kingston, Ontario, where he holds the Jarislowsky-Deutsch Chair in Economic and Financial Policy and directs the John Deutsch Institute for the Study of Economic Policy. He is cross-appointed to the School of Policy Studies and the Department of Medicine. His research spans evidence-based policy, the economics of science, education and public health, and how organisations use expertise when they make decisions. He is a co-owner of and research adviser at Limestone Analytics, a policy advisory firm, and has advised on impact evaluation and evidence-based policy for the UK and US governments, the World Health Organization, and others. Research cited in this episode
Evidence-based medicine. The movement that took hold in the 1990s, decades after the clinical trial became standard. Its classic statement is Sackett, David L., William M. C. Rosenberg, J. A. Muir Gray, R. Brian Haynes, and W. Scott Richardson. 1996. "Evidence Based Medicine: What It Is and What It Isn't." BMJ 312 (7023): 71-72. It set out how clinicians should combine the best research evidence with clinical judgement. Cotton's point is that medicine's evidence hierarchy puts systematic reviews above any single trial; the social sciences adopted the trials but not the hierarchy. Technology Readiness Levels. NASA's nine-level scale for the maturity of a technology, from basic principles observed (TRL 1) to flight proven on a successful mission (TRL 9). It gives engineers a shared vocabulary for readiness without dictating how each component is tested. PERLs borrow the idea and apply it to claims about policy. The four PERLs. PERL 1 is a hypothesis, backed by theory or observational data. PERL 2 is efficacy, shown in controlled trials under favourable conditions. PERL 3 is targeted adoption, with at least one rigorous causal evaluation under real-world implementation. PERL 4 is generalised guidance, built on systematic reviews that address how effects vary across contexts. Cotton's examples of PERL 4 evidence in development include insecticide-treated bed nets for malaria, cash transfers for school enrolment, and iron and folic acid supplements for pregnant women. The science of scaling. A growing literature on why promising pilots disappoint at scale; Cotton cites Rasul, Imran. 2026. "From Field Experiments to Policy Interventions at Scale." Science 391 (6790). Much of this work asks researchers to test programmes under real-world conditions. In PERL terms, that moves evidence from level two to level three; Cotton argues it is necessary but not sufficient. Evidence synthesis organisations. Cochrane produces systematic reviews in health; the Campbell Collaboration does the same fo
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