Why do we observe enormous differences in incomes per capita across countries, but also across regions within countries, i.e. across regions that share the same institutions, macro-environment, and cost of capital, for example? Why do production technologies that are in principle obsolete continue to exist in parts of the world and are not pushed out of the market by more advanced technologies?

In this course, we will argue that this is partly because modern production is complex and requires the combination of many different capabilities such as know-how, tools, inputs, regulations, etc. Students will be introduced to basic concepts of economic complexity, their analysis and policy implications.

Starting from a definition of technology, we will develop a simple combinatorial (‘scrabble’) theory of production in a complex world and discuss its implications and empirical support. We will show how we can derive from the theory measures of country and product complexity and how these measures can inform our understanding of economic development.

We will then consider network analysis: Using the ‘product space’, a network that connects products with similar capability requirements, as our guiding example, we will argue that networks are powerful tools to visualize and analyze complex systems. We will introduce students to basic concepts in data visualization and dimensionality reduction and their implementations in Python.

The course will conclude with giving an overview of advanced topics and discussing policy implications for economic development as well as open research questions in these areas.

The course will be taught by the academic research team of the Harvard Growth Lab: https://growthlab.cid.harvard.edu/academic-research

Students will get an overview of the economic complexity paradigm, the related literature, and open research questions. They will get acquainted with basic concepts and analytical tools and will learn how to apply them in different contexts.

The course is interdisciplinary and open to PhD and advanced Master Students from public policy, economics, and related fields. The concepts taught in this course will be developed from the ground up, but basic knowledge of linear algebra, econometrics, international trade theory, and Python are a plus.

Access to Python will be provided using cloud services. Alternative Stata modules will be offered for students not using Python.

The application is closed.

Find all the information about the program here(PDF 70,3 KB).