The aim of the course is to introduce students to how economists work with data to answer questions relevant for economic policy and theory. Students will be introduced to all stages of an applied research project, from formulating suitable research questions to presenting the results of an analysis. In doing so we will discuss real world issues on a range of topics relevant for economics, including inequality, health, environment, and labour economics (specific topics may vary from year to year). In particular, the focus will be on how we can combine economic theory with data to investigate each topic empirically using statistical programming.
Course description for study year 2023-2024. Please note that changes may occur.
In a digitized economy in which more data is available than ever before, data literacy is vital to validate and assess policy interventions, for strategic planning and execution in business organisations and for improving our understanding of the intended and unintended effects of human interaction. Avoiding poor understanding of data and improving knowledge of statistical analysis is also important to holding executive power to account and preventing the spread of misinformation.
This course gives students hands-on experience with real-world data in a range of topics of importance to contemporary society, and will help students develop critical thinking to avoid erroneous interpretation of quantitative data. Students will also develop basic knowledge of how to work with data in an empirical research project, including the use of statistical software, data cleaning, data handling, statistical and presentation skills that they can transfer to other courses and eventually to the workplace.
Upon completion of the course, candidates will have knowledge of:
How economists learn from data to analyze important policy problems.
How economists combine theory and empirical evidence in practice.
The importance of the concept of data literacy and critical thinking.
How to organize, structure, and manage data.
Basic knowledge of statistical analysis.
Upon completion of the course, candidates will:
Have hands-on experience with real-world data on topics relevant for economic research.
Have basic skills in using statistical software.
Have a valuable toolkit of data handling, data cleaning, and basic statistical analysis.
Be able to review, evaluate, and ciritically assess empirical evidence.
Be able to communicate results and findings based on empirical evidence.
Have basic data skills transferable to other courses and the workplace.
Required prerequisite knowledge
Experience with basic statistical analysis is an advantage, but not a requirement.
Group term paper and individual exam
Form of assessment
Group term paper
Group assignment 1, Group assignment 2, Group assignment 3, Compulsory attendance at the first lecture
Students must complete three group assignments and be present at the first lecture to be eligible to take the exam.
In this course, you will learn through a combination of traditional lectures, group exercises and individual study. Lectures will be used both for teacher instruction and group work, and you will also work on group projects in between lectures.
There must be an early dialogue between the course coordinator, the student representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.