Quantitative Research Methods III - Economics and Finance

COURSE OBJECTIVE
After successfully completing this course you can:
- design a research set-up with a quantitative model to investigate a financial research question
- work with univariate and multivariate regression models, probit and logit models, interpret their outcomes using the software package Stata.
- recognize and create solutions to cases when the underlying assumptions of the linear regression model fail (such as omitted variables, heteroskedasticity, endogeneity and multicollinearity)
- report the results of your analysis clearly according to the academic standards

COURSE CONTENT
First of all, students get to know and learn about different data sources to summarise data in a number of descriptive statistics.
Second, they learn how to work with univariate and multivariate linear regression models. We also pay attention to situations when the
classical assumptions of the linear regression model do not hold: think about problems such as multicollinearity, omitted variable
bias, heteroskedasticity and endogeneiy.
Third, you will learn to work with Probit and Logit models. (in case the outcome variable is binary) and you get to know the basics of time series and panel data models.
Finally, students will apply the mentioned techniques on empirical data using Stata.

TEACHING METHODS
Lectures
Tutorials
Computerlab sessions

TYPE OF ASSESSMENT
Written exam – Individual assessment
Case 1 – Assessment in groups of 2
Case 2 – Assessment in groups of 2

ADDITIONAL INFORMATION
Students who completed the complete minor 'Applied Econometrics: A Big Data Experience for All' may choose a different course from the curriculum of BSc Economics and Business Economics instead of QRM III.

RECOMMENDED BACKGROUND KNOWLEDGE
Quantitative Research Methods I and II.