Pedro Bessone Tepedino is currently a data scientist at Uber who just completed his PhD in economics at MIT. His research interests are at the intersection of development, labor, and behavioral economics. His primary research agenda explores how machine learning algorithms can be used to increase the allocative efficiency of workers to tasks, studying the case of financial advisors to clients in brazil and tax collectors to properties in the D.R. Congo. His second agenda focuses on the impact of new technologies by studying the impact of the expansion of broadband internet on political accountability and education in Brazil. He holds a BA and an MA in economics from PUC-Rio.
Recent work by Pedro Bessone Tepedino
Improving state effectiveness through bureaucrat assignment: Evidence from the Democratic Republic of Congo
Optimising the assignment of tax collectors significantly increases tax revenue and compliance at little or no added cost