Much recent innovative research in development and agricultural economics has been driven by the application of field experiments to economic questions.  The popularity of these methods originate from a fundamental concern among empirical economists in identifying and attributing causality to key variables in social contexts where individuals and households make simultaneous decisions and the exogeneity of choice variables is often questionable.  Advances in methodology have created a lively debate about when experimental and nonexperimental methods should be used, what can be learned from studies that use these methods, and what types of biases different methods may introduce in parameter estimates.  

The course I teach, AEC 874:  Field Data Collection and Analysis in Developing Countries, focuses on prominent microeconometric research methods including randomized control trials, propensity score matching, and regression discontinuity.  The course does not cover panel data econometric methods (LATE) or IV methods which are extensively covered in other econometrics courses, although we do discuss when it may be more appropriate to use these types of methods throughout the course.  Familiarity with these types of methods from previous course work is a prerequisite.    

A major emphasis of the course is to help students develop clear research hypotheses that are derived from economic theory.  With these hypotheses, we review the development literature to see how these hypotheses have been empirically tested using different experimental and nonexperimental methods.  At the end of the course, students should be able to identify research questions and a research design using experimental or nonexperimental methods where they might make a contribution through their master’s or dissertation research.  As such, the course is targeted to advanced master’s students and Ph.D. students.