Modern societies are composed of complex systems in which large groups of people routinely interact to produce sophisticated collective outcomes, ranging from innovation and economic activity to crime and disease. These social phenomena involve differentiated inputs or “capabilities” that are first distributed across agents and groups of agents through division of labor and then recombined through organizational forms like firms and government organizations or by leveraging spatial configurations such as cities and clusters. Up to recently, the social sciences have studied these phenomena by aggregating information on capabilities and the agents that carry them into broad concepts, such as political participation, public health and crime rates or factors of production, like labor, land and capital. In doing so, valuable information that help understand the laws of motion of these social systems is lost. This course will provide an alternative way to studying social phenomena by introducing students to a set of tools that have been developed to analyze these complex structures in a disciplined way. It will focus on complex network analysis and other data dimensionality reduction techniques that form the core of Economic Complexity Analysis. It will apply these tools to explore a variety of issues at the core of economic development such as economic stagnation and growth, skills and labor markets, crime and disease, migration and FDI, the production of scientific and technological knowledge, and industrial clusters and cities. The course is hands-on: students will work on real-word data taken from large-scale databases that contain, for instance, patents and academic publications, skill surveys, and trade and FDI records. Through these exercises, students will acquire skills to analyze and visualize large data sets, as well as learn how to interpret their findings through an Economic Complexity lens.
This course is designed for students who want to learn how to extract valuable information from the expanding administrative and unstructured data sets that are becoming increasingly available to governments and firms across the globe. It presumes previous exposure to linear algebra, econometrics, and basic programming.