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Econometrics II (ECON 326)

This section contains material to support UBC’s ECON 326 Methods of Empirical Research in Economics. This course is a second course in econometrics, and focuses on econometric modeling - specifically using regression-based models

These modules in particular are designed to be used in 1 or 2 one-hour long lab environments, with TA or Instructor supervision, or in a flipped classroom setting (i.e. as a lecture)
They include a number of exercises which are intended to be formative (i.e. not graded) in nature, and can be addressed during the lab
They can also be used for self-study, with some additional effort

Modules

1.0.1 - Beginner - Introduction to Statistics using R

This notebook is an introduction to basic statistics using Jupyter and R, and some fundamental data analysis. It is a high-level review of the most important applied tools…

2.1 - Intermediate - Introduction to Regression

An introduction to simple regression using Jupyter and R, with an emphasis on understanding what regression models are actually doing. Computation is using OLS.

2.2 - Intermediate - Multiple Regression

An introduction to multiple regression using Jupyter and R, connecting simple to multiple regression. We also discuss some important concepts, including control variables.

2.4 - Intermediate - Issues in Regression

What are the key issues with a regression model? This notebook discusses collinearity, heteroskedasticity, and model specification.

2.5 - Intermediate - Interactions and Non-linear Terms

How do we specific non-linear models? Why would we want to do so? This notebook covers non-linear and interaction models, including marginal effects and related issues.

Projects - Example Project for ECON 326

Let’s put it all together! This notebook is an example of what a “final project” might look like in ECON 326. It summarizes and uses all many of the empirical skills and R…