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Advanced Quantitative Methods for Economists


Course Description

Aims to advance econometric and quantitative skills for applied data analysis. Focus on data processing and visualization using R, use of conventional (array) and unconventional (spatial, text) data types, econometrics for causal inference, and essential machine learning applications.


Athena Title

Adv Quant Meth Econ


Prerequisite

ECON 8080


Semester Course Offered

Offered spring


Grading System

A - F (Traditional)


Course Objectives

1) Manipulate, visualize, and summarize data effectively using R (or similar software), including web, text, or spatial data. 2) Choose, utilize, and assess the strength of various econometric models, with a focus on causal inference applications. 3) Understand and apply machine learning models for prediction.


Topical Outline

1) Using R for research (Basics, Data Manipulations, Visualization) 2) Econometrics for causal inference (Randomization, OLS, IV, RDD, TWFE, Event Study) 3) Working with varied data sources (Web Scraping, GIS, Text Mining) 4) Essentials of machine learning (LASSO, Random Forests, SVMs, Neural Nets)