The pace and extent of economic development in a country depends on many factors. The type and scope of corruption, the rule of law and the protection of property rights, the levels of trust in a society can all influence the success of reforms and the extent to which different sectors of society will benefit. Can these factors be changed with specific economic policies? If so, what are they and how are they best implemented? Are there country-specific characteristics such as history and culture that determine economic fate? We will consider these questions and more in this class.
This class will have three goals. First, students will be introduced to the most recent research on the aforementioned topics in development economics and political economy. Second, students will learn to use quasi-experimental methods - such as regression discontinuity designs and difference-in-difference designs - to analyze non-experimental data that are often used to generate causal policy evidence for topics that are difficult to study with experimental methods. Finally, students will learn basic R programming skills so that they can analyze data sets, create data visualizations, and apply these quasi-experimental methods. No prior knowledge of R is required.
The course is aimed at MPP, MAE, and other masters' or Ph.D. students who are interested in economic development, or who may wish to use these tools in program design or evaluation. PubPol 639: Program Evaluation or familiarity with (specific techniques) is highly recommended. Assignments will alternate between short memos discussing assigned development economics papers and short R assignments aimed at developing simple programming skills and analyzing development datasets.