14.32 Econometric Data Science

Class Info

Introduces multiple regression methods for causal inference and descriptive analysis in economics and related disciplines. Extensions include instrumental variables methods, analysis of randomized experiments and quasi-experimental research designs, and regression with time series data. Develops the skills needed to conduct - and critique - empirical studies in economics and related fields. Students complete an empirical project with a written description and interpretation of results; this may involve original data collection or use of existing data sets. Applications drawn from real-world examples and frontier research. Familiarity with statistical programming languages is helpful. Students taking graduate version complete additional assignments.

This class has 14.30 as a prerequisite.

14.32 will be offered this semester (Fall 2019). It is instructed by A. Mikusheva and B. Frandsen.

Lecture occurs 1:00 PM to 2:30 PM on Tuesdays and Thursdays in E52-164.

This class counts for a total of 12 credits.

You can find more information on MIT OpenCourseWare at the Econometrics site or on the 14.32 Stellar site.

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MIT 14.32 Econometric Data Science On The Web
statistical methods econometrics

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