Skip to main content Skip to secondary navigation
Main content start
Postdoctoral Fellow | 2023–2024

Binta Zahra Diop

Postdoctoral Fellow | 2023–2024
King Center on Global Development

Binta Zahra Diop was a Postdoctoral Fellow at the King Center on Global Development. Her work aims to understand migration and location choices of people under constraints, both positive (driven by central policy choices) and normative (from fairness principles). Diop received her PhD in economics at the University of Oxford and she will be joining Boston College as an assistant professor in 2025.

Innovations in Methods and Data

King Center Supported Research

2023 - 2024 Academic Year | Global Development Research Funding

Positive and Normative Determinants of Labor Allocation 
 

Exploring Tradeoffs in Algorithmic Fairness: An Experimental Investigation of Preferences Policymakers face crucial choice when weighing the risk of social protection policies failing to assist some individuals living in extreme poverty -- false negatives -- against the possibility of inadvertently providing benefits to wealthier individuals -- false positives. This project aims to uncover the preferences of individual affected by these decisions regarding various algorithmic approaches to managing false positives and false negatives. The relevance of this project grows alongside the increasing integration of machine learning and artificial intelligence in policy decision-making contexts.

Productivity and Allocation of Labor in Ghana Healthcare System: Studying the productivity of healthcare labor in Ghana with a unique administrative panel of over 9,000 health facilities, and 100,000 workers from 2014 to 2019. Focus on understanding the impact of nurse staffing on healthcare outcomes in rural facilities and estimating elasticities of healthcare outputs. Then plan to estimate improvements in health outcomes, and fairness that the system could make by merely reallocating labor across facilities.

Productivity and Allocation of Tax Collectors in Kananga (DRC): The assignment of workers to tasks and teams is a key margin of firm productivity and a potential source of state effectiveness. In this project, we aim investigates whether a low-capacity state can increase its tax revenue by varying the way it assign assigns its tax collectors.