PDRI-DevLab affiliates work on projects focused on various aspects of international development including migration and forced displacement, land and the environment, education, health, governance, gender, poverty reduction, and economic growth. Through regular seminars, conferences, collaborative research projects, and dissemination activities, PDRI-DevLab makes it possible for faculty and graduate students at Penn to expand their efforts to conduct research that advances science and policymaking, and contributes to the improvement of well-being in developing countries.
Connecting international development researchers at Penn. While many international development researchers are trained to use theory to formulate potential solutions to complex problems and test those solutions in real-world settings, individual disciplinary perspectives are rarely sufficient for solving complex problems. Addressing these challenges requires joining forces with researchers from multiple disciplines. PDRI-DevLab helps to facilitate such collaboration across the Penn campus.
Connecting researchers at Penn to the world. Even the best research can be inadequate for solving problems if it is isolated from the world of practice. Local and international practitioners and various government agencies have valuable platforms for learning and critical expertise in implementing and scaling potential solutions. PDRI-DevLab focuses on connecting social scientists at Penn who work in international development with the community of development practitioners to create rigorous programming, collect monitoring and evaluation data, and conduct impact evaluations of development projects. We bring together scholars and students attuned to the research frontier and with advanced capabilities in experimental and quasi-experimental impact evaluation designs, survey design and other data collection tools, and data analytics, including web scraping and geospatial analysis.
As established social scientists, we are adept at identifying opportunities for knowledge generation that will benefit the Penn community of scholars and the scientific community more broadly. As academics trained in applied statistics, we are well-positioned to offer advice on best practices for cutting-edge program evaluation to practitioners. Our setting also gives us access to a range of experts on the frontier of technology relevant to program evaluation.
The purpose of the RESTORE Activity is to demonstrate a scalable and regionally replicable model for community-led governance, natural resource management, and biodiversity conservation that aligns with regional and government priorities in cocoa production landscapes in the Guinean forests of Ghana and Cote d'Ivoire. The RESTORE Activity envisions that in partnership with multinational chocolate companies, farmer cooperatives, and local partners, it will establish the technical capacity, policy implementation approaches and economic incentives to bring cocoa producing families, governments and private sector together in a joint endeavour to secure improved livelihoods from cocoa farming, socially inclusive additional economic opportunities, increased tree cover and a scalable contribution to national and corporate emission reductions targets. The activity works at both farm and landscape scales, and seeks to support an inclusive landscape management governance body in selected target areas to drive resilient economic growth, with expanded opportunities for women and youth based on sustainable resource use.
RESTORE's specific objectives include increasing tree cover on and off farm in the cocoa production in four landscapes in the Guinean forest in Ghana and Cote d'Ivoire). At present, the conservation and biodiversity indicators for the off-farm forest restoration activity are anticipated to be amenable to evaluation through a a quasi-experimental difference-in-difference (DiD) approach.
Baseline data - including qualitative and quantitative data - will be collected January - March 2024. Baseline data analysis will take place April 2024 - August/September 2024. This capstone will support baseline data analysis, including the analysis of qualitative data from interviews and focus group discussions, secondary data from implementing partners, and quantitative data from farmers, households, and community leaders.
For this capstone, the student will be focused on analyzing a set of baseline data sources - ideally a mix of qualitative and quantitative sources and generating a report (no more than 20 pages) to synthesize findings about the baseline context and present analysis tables. As this is a baseline, the analysis will mostly rely on descriptive statistics and qualitative analysis. If the student has training with regression analysis, the capstone can also include some additional cross-sectional regression analysis to explore various trends, although this is not required. A highly successful product will highlight any differences between the baseline context and the program's assumptions about the baseline context - and - if needed, recommend adaptations in program design.
