2025/2026 BA-BHAAV1016U Quantitative Methods
English Title | |
Quantitative Methods |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Elective |
Level | Bachelor |
Duration | One Semester |
Start time of the course | Autumn |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Max. participants | 200 |
Study board |
Study Board of General Management
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Course coordinator | |
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Main academic disciplines | |
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Teaching methods | |
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Last updated on 30-01-2025 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||
The course will provide students with a practical
understanding of basic statistical models and methods in data
analysis. To obtain a top grade, students are required to have a
good understanding of the main concepts and models in applied
econometrics that are covered in the course. This includes the
ability to:
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Examination | ||||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||
In economics and finance there are three important factors that affect people’s choices in reation to saving and investment: How people like or dislike risk and uncertainty, how patient they are and their expectations of future events. Understanding how to measure and estimate these three behavioral factors can 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 risk taking in financial decisions than men which could translate into a wealth gap? Are men more or less confident 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 students with the necessary statistical tools to answer these types of questions. The course will focus on applied aspects of econometrics, as opposed to theoretical aspects. We will use data from surveys, experiments in economics and finance, 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 be using applications that are relevant to popular topics in behavioral economics and finance. |
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Research-based teaching | ||||||||||||||||||||||||
CBS’ programmes and teaching are research-based. The following
types of research-based knowledge and research-like activities are
included in this course:
Research-based knowledge
Research-like activities
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Description of the teaching methods | ||||||||||||||||||||||||
There is an even split between lectures and exercise classes, and all teaching activities take place in computer rooms on campus. Students will learn to program statistical models in Stata, and there is an applied approach in all lectures and exercise classes where students first are introduced to a specific topic followed by exercises and practical examples. There is much emphasis on learning by doing and practical aspects of statistical programming and use of statistical models. | ||||||||||||||||||||||||
Feedback during the teaching period | ||||||||||||||||||||||||
The course offers continuous feedback to students during lectures and exercise classes as well as office hours. Feedback includes discussions of topics and empirical examples in class, and lectures and exercise classes provide plenty of opportunities for questions and discussions. Continuous feedback is a key component of teaching and learning activities in the course. | ||||||||||||||||||||||||
Student workload | ||||||||||||||||||||||||
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Expected literature | ||||||||||||||||||||||||
Stock, J. H. and Watson, M., Introduction to Econometrics, Global Edition, 4th edition (Pearson Education, 2019); and academic papers relevant to the various topics in the course. |