Director of the Certificate in Spatial Analysis program and Director of Online Education at GPS
Microeconomics for Policy and Management
This course introduces microeconomics, emphasizing applications to public policy. We examine tools such as marginal analysis and game theory to understand markets, the behavior of individuals and firms and what role policy plays when markets fail to maximize social welfare. Throughout the course we will supplement theory with real-world examples from newspaper and magazine articles.
Geographic Information Systems (GIS) and Spatial Data Analysis
This course provides an introduction to GIS and spatial data analysis for applied social science research. Students will work in ArcGIS to manipulate different types of georeferenced data, visualize data, import/export data from Excel and Stata, and conduct spatial analysis (for example clustering analysis, interpolation, kernel densities, and geographically weighted regression). Basic knowledge of statistics and regression (ordinary least squares) is assumed, as is familiarity with Stata software. The course will also look to motivate geography as an important lens through which to study society and invite guest lecturers to present different kinds of research that employ GIS.
Spatial Analysis for Sustainable Development (not currently offered)
This course focuses on the challenges of sustainable development through the lens of spatial analysis. Organized thematically by individual Sustainable Development Goals (SDGs), the course surveys the latest literature employing spatial data or remote sensing to improve SDG monitoring or policy design. As a culminating exercise for the three-course Spatial Analysis sequence, students will produce a policy advising report for a country government, using spatial analysis to propose a public investment plan to put the country on track to meet an SDG.
Integrated Development Practice (not currently offered)
This course complements the concepts taught in Economic Development (GPEC 451) by introducing students to the basic competencies and practical skills of a development practitioner. Lectures will be grounded in a practical, multi-sectorial approach that will focus on the inter-relationship of the social sciences, health sciences and natural sciences (agronomy, engineering). Lectures outside the social sciences will be led where possible by guests who are development practitioners in their field. In parallel to lectures, the course will emphasize the idea of a “differential diagnosis for development” through case studies of developing countries. Students will work in teams and focus on one developing country, tasked with diagnosing obstacles to sustained economic development and poverty reduction. These case studies will rely heavily on both policy documents and data-driven approaches. Students will be asked to manipulate data in Stata & GIS formats to identify poverty hotspots and use household survey data to characterize poor households and poverty traps. Issues around scaling up best practices from pilots to national level will be emphasized. Students will be asked to put forward policy recommendations to government based on their analysis of existing national policy frameworks & data.