Calendar & Readings

Readings must be done before the date listed, so that you arrive prepared to discuss them. Required readings are marked in red with three stars (***) – students should be prepared to discuss the minutiae of these papers, and to provide critical commentary on the design and execution of the study. Recommended readings are marked by a single star (*) – students should skim these articles, to the point that they could summarize the data, methods, and key results. Other readings are optional.

Jan 28: Introduction and Overview

Required for those who are less familiar with Python:
Optional (skim a few!)

February 4: Methodological primer: Econometrics & Machine Learning

Required readings
Recommended reading for those less familiar with machine learning:
Recommended reading for those less familiar with development economics:
Optional readings

February 11: Data Sources: Traditional Data & Satellite Imagery

Required readings
Optional readings

February 18: No Class (President’s Day)

February 25: Data Sources: Mobile phones

Required readings
Optional readings

March 4: Data Sources: Internet and social media

Required readings
Optional readings

March 11: Data Sources: New forms of instrumentation and intervention

Required readings
Optional readings

March 18: Applications: Mobility, Migration, Health, and Epidemiology

Required readings
Optional readings

March 25: No Class (Spring Break)

April 1: No Class (Josh travel)

April 8: Applications: Disasters, Displacement, Crime, and Civil Unrest

Required readings
Optional readings

April 15: Applications: Financial Inclusion

Required readings
Optional readings

April 22: Ethics and privacy

Required readings
Optional readings

April 29: Final presentations


Optional: Applications: Social networks

  • Alatas, V., Banerjee, A., Chandrasekhar, A.G., Hanna, R., Olken, B.A., 2016. Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia. American Economic Review 106, 1663–1704. doi:10.1257/aer.20140705
  • Aral, S., Walker, D., 2012. Identifying Influential and Susceptible Members of Social Networks. Science 337, 337–341. doi:10.1126/science.1215842
  • Banerjee, A., Chandrasekhar, A.G., Duflo, E., Jackson, M.O., 2014. Gossip: Identifying Central Individuals in a Social Network (Working Paper No. 20422). National Bureau of Economic Research.
  • Björkegren, D., 2019. The Adoption of Network Goods: Evidence from the Spread of Mobile Phones in Rwanda. Rev Econ Stud. https://doi.org/10.1093/restud/rdy024
  • Chuang, Y., Schechter, L., 2015. Social Networks in Developing Countries. Annu. Rev. Resour. Econ. 7, 451–472.
  • Ferraz, Claudio, and Frederico Finan. “Exposing Corrupt Politicians: The Effects of Brazil’s Publicly Released Audits on Electoral Outcomes.” The Quarterly Journal of Economics 123, no. 2 (May 1, 2008): 703–45. doi:10.1162/qjec.2008.123.2.703.
  • Khwaja, Asim Ijaz, and Atif Mian, 2005. “Do Lenders Favor Politically Connected Firms? Rent Provision in an Emerging Financial Market.” The Quarterly Journal of Economics 120, no. 4: 1371–1411. doi:10.1162/003355305775097524.
  • Palla, G., Barabási, A.-L., Vicsek, T., 2007. Quantifying social group evolution. Nature 446, 664–667. https://doi.org/10.1038/nature05670
  • Ugander, J., Backstrom, L., Marlow, C., Kleinberg, J., 2012. Structural diversity in social contagion. Proceedings of the National Academy of Sciences 201116502.

Optional: Applications: Agriculture, Environment & Sustainability