Does better evidence lead to better policies and programs? Massive amounts of reliable evidence, drawing on scientifically strong methods, including randomized controlled trials, mixed-methods approaches, and more, have been generated and disseminated in recent decades. A Nobel Prize has been awarded for that pathbreaking work. Yet the impact of that evidence – on what policymakers and program implementers think and do – has been far below expectations, even pitifully tiny according to some accounts. billion people.
Almost a year ago, we announced in this blog 3ie's collaboration with USAID’s Bureau of Resilience and Food Security (RFS) to map the existing evidence and gaps in four technical areas: agriculture-led growth, resilience, nutrition-sensitive agriculture and water security, sanitation, and hygiene (WASH). While these maps are intended to help guide RFS’ programmatic and strategic investments, they have much broader applications for the international development community as they reveal key insights into priority evidence gaps.
In recent years, international observers such as the V-Dem Institute have highlighted an alarming crisis of democracy with a decline in competitive elections, political participation and public accountability. For the first time in two decades, the Institute’s 2023 Democracy Report found more closed autocracies than liberal democracies in the world.
As we've discussed on this blog before, the development community has made tremendous strides in producing and using rigorous evidence, and it also still has a long way to go to build a strong evidence culture. The closing plenary for USAID's Agency Learning and Evidence Month on 27 April reflected recent years' progress and the remaining challenges.
If economists are the ‘dismal scientists’ always harping on about limited resources, evaluators are often considered the ‘pessimist scientists’ who only see the half-empty glass, rather than the half-full one. The end of the year is, however, a perfect time to break with that tradition. It is a time to reflect and appreciate progress, promising initiatives, and flickers of hope. Evidence suggests that positive reinforcement can be effective in ensuring that positive developments or behaviors are maintained.
Urban waste pickers face several intertwined challenges such as low incomes, limited education, poor health, social marginalization, and domestic violence. In Bengaluru, India, 3ie is currently evaluating an initiative called Saamuhika Shakti, which adopts an innovative ‘Collective Impact’ approach to improving the lives of informal waste pickers. The initiative, just like the problems it looks to address, is complex.
The buzz around this year’s Nobel Prize picks in economics continues to stimulate discussion, not least on “where next in the quest for better evidence?” The groundbreaking research by Laureates David Card, Joshua Angrist and Guido Imbens has substantially improved our ability to answer key causal questions with great benefits to society. But much more needs to be done to get from conceptual advances to improved practice in evidence-informed decision-making by policymakers and program designers around the globe.
Fifteen years ago, the Evaluation Gap Working Group published a report noting the absence of solid evidence on the effectiveness of development programming. This report, and the intellectual community behind it, drove a wave of work on impact evaluations in the development sector. So, did we learn?
The world's development institutions collect lots of data – but do they learn from it? Perhaps not as much as they should. Between the challenges of quick timelines, rigid systems, and disconnects between implementers and evaluators, development agencies do not always walk the talk of evidence-informed decision-making, 3ie's expert panel agreed.
Given the variety of ways in which evidence is taken up and used, we found that ‘you will know evidence uptake and use when you see it’ is not a good enough standard. We are in the business of evidence, not anecdotes. So, we developed a detailed typology of the ways decision-makers take up and use research evidence, particularly findings and lessons from impact evaluations.
