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Description
Given the primary role that real estate plays in all aspects of our society, analysing the economics of real estate markets is as relevant as it is interesting. Additionally, the ability to handle real estate data is a fundamental asset to any professional. By combining real estate assets' physical and locational characteristics with their transactions and investment conditions, real estate data works as a bridge between people's decisions, preferences, and the value of properties and their surroundings. In this course, we will dive into real estate data analysis and learn which questions to answer by employing causal inference methods and, more importantly, how to apply these methods.
Students will be provided with:
- Introduction to current issues in empirical research
- Examples of solutions to these issues in state-of-the-art research
- R coding with applications of these solutions
- Data sources and tools to replicate published research
- Tools for creating convincing visualisations
At the end of the module, students will be able to:
- Remember the basic principles of how to interpret data.听
- Understand the challenges of drawing conclusions from data.听
- Apply the basic econometric concepts to data analysis.听
- Analyse real estate data using R.听
- Evaluate what data can tell us and what it is not suitable for.
- Create visualisations adapted to their objectives.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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