Quant­it­at­ive Meth­ods

Course content

In economics and finance there are three important factors that affect people’s choices: How people like or dislike risks, how patient they are and what expectations they have about the future. Understanding how to measure and estimate these three factors help us answer practical and relevant questions such as:

How do you measure and elicit individual attitudes to financial risk and time delay of income that help explain why people save or don’t save for later consumption? Are women more patient and more averse to taking risk in financial decisions than men which could translate into a wealth gap? Are men more overconfident than women in investment decisions? Do people over- or underinvest in companies that score highly on environmental and societal responsibility (ESG) metrics?

The objective of the course is to provide bachelor students with the necessary statistical tools to answer such type of questions. The course will focus on applied aspects of econometrics, as opposed to theoretical aspects. We will use data from surveys, experiments and market data to develop students’ competences in quantitative methods. The course is designed to target students who intend to conduct empirical analysis during their undergraduate and graduate study programs, and in their professions.

The course will focus on various applications of basic statistical models. Throughout the course emphasis will be placed on the qualitative and quantitative understanding of statistical models. That is, how can you translate a qualitative research question into a quantitative model and make inferences? A recurring theme during the course is the distinction between correlation and causation. Despite this simple distinction much of the difficulty in econometrics stems from the desire to make causal inferences from observational data. 

To illustrate the statistical models, we will also be using applications that are relevant to popular topics in Behavioral Economics and Finance. The course will thus provide students with statistical models to understand behavioral biases in conjunction with asset valuation, among other things.