This advanced econometrics course, ECON 222: Statistical Methods II extends foundational topics from ECON 221, focusing on hypothesis testing and the classical linear regression model. The course examines the model’s key assumptions, the properties of estimates derived from it, and methods for interpreting results. Emphasis is placed on understanding the effects of violating model assumptions and exploring corrective measures. Main topics to be covered include model specification, heteroscedasticity, multicollinearity, indicator variables, time series, and forecasting.

Upon completion, you will be adept at testing various hypotheses and applying statistical inference to make data-driven conclusions. You will also acquire a technical understanding of regression theory, enabling them to compute, interpret, and communicate results effectively. The course aims to develop both computational competence and the capacity to clearly explain the ideas behind regression analysis and forecasting, preparing you for complex statistical challenges in research and applied econometrics.

Prerequisites include ECON 221 and either MATH 203 or MATH 209, or an equivalent course.