Assessing housing market dynamics across a sample of European cities

Union Jack
Dannebrog

Assessing housing market dynamics across a sample of European cities

Show full item record

Title: Assessing housing market dynamics across a sample of European cities
A Random Forest Machine Learning Approach
Author: Begatti, Luca; Mauceri, Corrado
Abstract: This paper studies the housing market across European cities by combining regression analysis with a machine learning process. We identify that despite the limited data availability, there are time, national and local effects associated with real housing returns. According to our choice of explanatory variables, we document that mortgage rate, GDP per capita and unemployment rate are important determinants of housing returns. Generally speaking, we can infer that the European housing market does not show evidence of bubbles but there are some markets which deserve particular attention. We witness the presence of Shiller's Irrational Exuberance only with respect to the city of Nurnberg, Germany. We further witness in some cities a substantial adjustment rate suggesting market efficiency as well as strong mean reversion effects. Collectively, these results support the view that most of the European cities are not currently experiencing a bubble but in some instances the foundation for such inexplicable behaviour have been building up following the recent financial downturn.
URI: http://hdl.handle.net/10417/6309
Date: 2018-09-28
Pages: 105 s.
Files Size Format View
Luca Begatti og Corrado Mauceri.pdf 741.9Kb PDF View/Open

The following license files are associated with this item:

This item appears in the following Collection(s)

Show full item record