After the course, you will be able to perform your own economic data analysis based on the understanding of described econometrics tools. You will learn how to apply the indicated tools and methods to various topics of your research and how to prevent and overcome problems, which can arise in real data analysis.
Syllabus
WEEK 1
Ordinary Least Squares
In this week we will learn the core method of regression analysis OLS and practice the main steps of estimating a model. We will consider necessary assumptions, derive and discuss the properties of the estimates.
WEEK 2
Model Specification
This week is devoted to various questions related to model specification. How to choose the functional form? How to account for qualitative characteristics? What are the consequences of errors in the choice of regressors? How to test whether the model specification is correct? These and other questions will be discussed and supported by practice exercises on real data.
WEEK 3
Multicollinearity, Heteroskedasticity and Autocorrelation
Let’s discuss the most popular problems that can arise in regression analysis: multicollinearity, heteroskedasticity and autocorrelation. We will tackle every topic by studying the ways to test the presence of the problem and then by considering possible approaches to correct for it.
WEEK 4
Endogeneity and Instrumental Variables
In this week we will discuss the problem of endogeneity which is an often case in many econometric studies. We will discover the reasons and consequences of it as well as the famous instrumental variables approach which allows to cope with this problem.
WEEK 5
Project Assignment
Tired of derivations and theory? In this week use only learning by doing approach!
The Project Assignment will help you to integrate all the tools and methods discovered through the course. Upgrade your skills through the practice on real data!