Mentor Areas
Dr. Heather Huntington is a Professor of Practice in the Department of Political Science at the University of Pennsylvania. She serves as Executive Director of PDRI-DevLab at Penn. Her research expertise includes land tenure, land administration, natural resource governance, and environmental conservation. She teaches courses on survey methodology and impact evaluations. Dr. Huntington has served as the technical lead on impact and performance evaluations across Africa, Asia, and Latin America. She holds a PhD in Political Science and Public Policy from the University of Michigan.
Description:
For AY 2025/2026, PDRI-DevLab has research opportunities for students across the following portfolio of three projects:
- Climate change and big data analytics: Climate change has moved from a future threat to a present catastrophe. Extreme weather now routinely overwhelms public services and turns local disasters into regional emergencies, especially in countries with the least capacity to respond. Despite growing recognition of these risks, leaders still lack timely, usable information about how individuals, communities, and governments respond when climate shocks hit. Our team of political scientists, climate scientists, and data scientists have combined mass scraping and a machine classifier to produce the first monthly, sub-national data on 14 dimensions of climate-related adaptation and stress across 66 developing countries. We will combine our original environmental event data with climate data and original geolocated microdata from the Lloyd's Register Foundation World Risk Poll and World Bank Survey data to do research on the impact of climate change on citizen attitudes, community adaptations, and migration across a wide range of contexts. Depending on technical skills, fellows will help validate the environmental event data, provide descriptions on merged data, do desk research on different regional contexts, etc.
- Continued collaboration with the United Nation’s International Office of Migration: This research would explore the role of social media in facilitating, shaping, and potentially disrupting trafficking and smuggling networks. As a first step, the project would identify which sources of data are realistically available—for example, digital trace data from platforms such as Facebook, WhatsApp, or TikTok; monitoring reports from NGOs; or interviews with law enforcement and survivor support organizations. Depending on the availability and reliability of these sources, we would then collaborate with the UN’s International Organization for Migration (IOM) to produce a short research brief. The study would adopt a mixed-methods design, combining quantitative analysis of social media and network data with qualitative approaches such as key informant interviews and content analysis, to better understand how trafficking and smuggling actors use digital platforms and how interventions might disrupt these practices.
- Continued collaboration with the World Bank on land administration and property rights: The proposed research will address two interrelated questions on land administration. Task A involves a desk-based literature review to map the full range of cost factors associated with delivering a land record through a land administration system. This will require systematically identifying all relevant components—such as field survey work, data processing, staffing, technology infrastructure, overhead, and administrative expenses—and synthesizing available evidence on their cost magnitudes. Where possible, the review will provide cost estimates per hectare, distinguishing between precise figures and broader ranges depending on the source. This task will require strong desk research, synthesis, and comparative analysis skills. Task B will conduct a simple correlation analysis to assess whether stronger land administration systems are associated with improved revenue generation, particularly property tax collection. Using publicly available cross-country datasets—including the BeReady index and related World Bank and international statistical sources—the analysis will test associations between land system strength and fiscal outcomes (e.g., property tax as a share of GDP). This task will require statistical analysis skills, familiarity with cross-country datasets, and capacity to clean and harmonize data with non-standardized years. Together, the two tasks will generate a comprehensive overview of land administration costs and provide initial evidence on the fiscal benefits of more robust systems.
Interested students should submit an application HERE. If you have any questions about the application, please reach out to sandrafa@sas.upenn.edu. We will review applications on a rolling basis.
Preferred Qualifications
This portfolio has a variety of quantitative and qualitative research tasks and can accommodate students with a range of skills and qualifications. Quantitative research tasks focus on big data analytics, survey data analysis, and the analysis of GIS data. For quantitative research tasks, we are especially interested in students who are proficient in R or Stata for data analytics, and experience with GIS and applied econometrics for social science research is highly preferred. Qualitative research tasks focus on the analysis of interviews and focus group transcripts, along with in-depth literature reviews.
Project Website
Learn more about the researcher and/or the project here. Research Website
Details:
Preferred Student Year
First-year, Second-Year, Junior, Senior
Academic Term
Fall, Spring, Summer
I prefer to have students start during the above term(s).Volunteer
Yes
Yes indicates that faculty are open to volunteers.Paid
Yes
Yes indicates that faculty are open to paying students they engage in their research, regardless of their work-study eligibility.Work Study
Yes
Yes indicates that faculty are open to hiring work-study-eligible students.