Applied Econometrics in R
This course combines both analytical and computer-based (data) methods to enable you to gain practical experience in analyzing a wide variety of econometrics problems. You will explore how modern data science approaches can be used to answer important economic and business questions, which will help you build a solid foundation to develop econometric models to answer important economic and business questions based on the data. The topics include analysis of cross-sectional, time series, and panel data models using the econometrics approaches.
This course covers essential econometrics techniques with an emphasis on intuition and applications.
Every topic covers a brief introduction and provides plenty of examples for greater understanding.
The course uses programming language R to show several examples.
No prior knowledge of R is required. The codes are written in a simple way and explained clearly.
The course is divided in several parts for better understanding.
Syllabus
Introduction to the course and R
Introduction to the Course
How to install R and the Rstudio
Introduction to R: R environment, Working with the Rstudio IDE, Importing data in the Rstudio, Installing R packages, Using help, etc.
Part 1: Cross-sectional data
Steps to complete computer exercises (R codes)
Ch 5: Multiple regression analysis: OLS Asymptotics (R codes)
Ch 6: Multiple regression analysis: Further Issues (R codes)
Ch 7: Multiple regression analysis with qualitative information (R codes)