Determinants of House Prices in Dublin: A Quantile Regression Approach

Sousa, Carlos José Silva

Publication

Determinants of House Prices in Dublin: A Quantile Regression Approach

2025-05-29Master thesis

datacite.subject.fos	Ciências Sociais::Economia e Gestão
dc.contributor.advisor	Jorge, Maria João da Silva
dc.contributor.advisor	Horrigan, Matthew
dc.contributor.author	Sousa, Carlos José Silva
dc.date.accessioned	2025-08-05T11:07:25Z
dc.date.available	2025-08-05T11:07:25Z
dc.date.issued	2025-05-29
dc.description.abstract	Today's property market is more competitive than ever, making accurate property valuation essential for ensuring fair transactions for both buyers and sellers. Historically, the Irish have shown a strong preference for homeownership over renting, with the homeownership rate reaching 69.4% in 2023 (Eurostat, 2023). This research underscores the significance of identifying key factors that influence housing prices in the Dublin market. Over time, researchers have developed various methods to achieve the most rigorous results in real estate valuation. As in many previous studies, the hedonic price model was employed, as it is widely regarded as one of the most effective approaches for property valuation. To conduct the empirical analysis, different forms of the hedonic price model were tested on a sample of 5,091 houses in Dublin, with the double logarithmic form proving to yield the most accurate results. To enhance performance, the study applied quantile regression, a technique that provides a more comprehensive view of price variations across the housing market. This approach allowed for the identification of attributes that significantly influence price fluctuations in both lower- and higher-priced properties. Our findings reveal that location and house size exert the strongest positive influence on property prices, consistently driving price variations across all market segments. Additionally, property type plays a crucial role in determining house values. However, factors such as usage status, the number of bedrooms, and the availability of gardens or terraces primarily impact lower- and mid-priced houses. Furthermore, Building Energy Rating (BER) significantly affects prices, but mainly in cases of lower ratings, which lead to price reductions, particularly in the lower-priced segment. Lastly, proximity to the sea enhances house values, especially for high-priced houses.	eng
dc.identifier.tid	203980182
dc.identifier.uri	http://hdl.handle.net/10400.8/13869
dc.language.iso	eng
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject	Real estate valuation
dc.subject	House prices
dc.subject	Hedonic price model
dc.subject	Quantile regression
dc.subject	Dubli
dc.subject
dc.subject	House market
dc.title	Determinants of House Prices in Dublin: A Quantile Regression Approach
dc.type	master thesis
dspace.entity.type	Publication
thesis.degree.name	Master´s Degree in Corporate Finance