What have we learned about UBI from recent, large-scale studies? What factors contribute to differential attrition in (especially long-term) studies? How much does it cost to run large UBI studies? Where else in the world have major UBI studies been run? What's the difference between "guaranteed income" and UBI? How do people in cash transfer studies tend to spend their money? Should restrictions be placed on what people can spend their study money on? How long does it take to see various effects of UBI or guaranteed income on a large scale? How does guaranteed income affect the nature of work in recipients' lives? How does guaranteed income affect a person's net worth in the long run? What are the effects on well-being? How does topical knowledge affect prediction accuracy in a given area? How good are subject-matter experts at making predictions about the outcome or utility of a study? How can such predictions in aggregate be used to shape future research? To what extent should reseachers express uncertainty when making proposals to policy-makers? How much of an effect does the publishing of academic papers have on the world? What kind of person should try to build a career in academia? How can non-experts assess the rigor and significance of academic papers?
Eva Vivalt is an Assistant Professor in the Department of Economics at the University of Toronto. Dr. Vivalt's main research interests are in investigating stumbling blocks to evidence-based policy decisions, including methodological issues, how evidence is interpreted, and the use of forecasting. Dr. Vivalt is also a principal investigator on three guaranteed income RCTs and a co-founder of the Social Science Prediction Platform, a platform to coordinate the collection of forecasts of research results. Find out more about her on her website, evavivalt.com.
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