DATA ANALYTICS FOR ECONOMISTS

ECON 315

Introduction to the fundamental concepts of economic data visualization and analysis. Develop a toolkit of skills to visualize, interpret, and communicate data. After examining the fundamentals of data visualization, emphasis is on methods using Tableau to design and develop dashboards, graphs, and charts to ease quick and accurate interpretation of economic relationships. Move beyond tabular results to display and demonstrate the findings of economic research.

ECON 310

Introduction to analysis of economic data. The techniques of descriptive statistics and statistical inference (hypothesis testing and estimation) as directed toward application in economic research.

ECON 725

Introduction to the use of Machine Learning (ML) in economic analysis. Covers basic techniques of ML, much attention will be devoted to evaluating the use of these tools in economics. Learn how economists are integrating the tools of ML with econometric techniques in current empirical research. Gain hands on experience in using these techniques to answer traditional questions of interest to economists. Topics include (i) an in-depth discussion of the differences and similarities in goals, empirical settings and tools between ML and econometrics, (ii) supervised learning methods for regression and classification, unsupervised learning methods, large data analysis and data mining, (iii) recent methods at the intersection of ML and econometrics, designed for causal inference, optimal policy estimation, estimation of counterfactual effects. The methods are taught with an emphasis on practical application.

ECON 570

Introduction to the data that underlies quantitative economic analysis. Learn how to formulate a research question, access economic data sources, conduct preliminary and formal analysis, and report findings in a professional manner.

ECON 695

Various advanced topics on the use of data to answer important economic questions.