In this course we will discuss emerging topics in econometrics. Possible topics include reanalyses of widely used econometric methods in more challenging settings (e.g., negative weights of two-way-fixed-effect regression), partial identification, design of randomized experiments, empirical Bayes methods, shrinkage estimators and regularized regression (e.g., LASSO), matrix completion methods for panel and network data, adversarial methods, interference and peer effects, randomization inference, regression adjustment techniques in experiments, sensitivity analysis, and decision making under ambiguity. Students are expected to read recent research papers, write short summaries and discussions of them, and work on a final research project that has the potential to be developed into a full-blown paper.
3 units · GSB Student Option LTR/PF
In this course we will discuss emerging topics in econometrics. Possible topics include reanalyses of widely used econometric methods in more challenging settings (e.g., negative weights of two-way-fixed-effect regression), partial identification, design of randomized experiments, empirical Bayes methods, shrinkage estimators and regularized regression (e.g., LASSO), matrix completion methods for panel and network data, adversarial methods, interference and peer effects, randomization inference, regression adjustment techniques in experiments, sensitivity analysis, and decision making under ambiguity. Students are expected to read recent research papers, write short summaries and discussions of them, and work on a final research project that has the potential to be developed into a full-blown paper.