Validating spatial dynamics for energy efficiency in the Belgian residential rent market

Alesia Gerassimenko (), Ian Lenaers () and Lieven De Moor ()
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Alesia Gerassimenko: Vrije Universiteit Brussels
Ian Lenaers: Vrije Universiteit Brussels
Lieven De Moor: Vrije Universiteit Brussels

Review of Regional Research: Jahrbuch für Regionalwissenschaft, 2025, vol. 45, issue 2, No 4, 299-325

Abstract: Abstract Growing concerns about climate change have led policymakers to adopt measures to promote an energy-efficient building sector, making energy improvements a key driver of housing renovation. The role of energy efficiency in the residential market has already been studied extensively, but results vary greatly. This variation can in part be attributed to location differences, but also to the selection of variables and the use of diverse models. In fact, the choice of methodology often appears somewhat arbitrary, mainly driven by what has been done in previous literature. A dataset of 22,834 listed Belgian rental properties in Belgium is analysed to examine the relationship between energy efficiency and rental prices, using the four most commonly applied econometric models: Ordinary Least Squares (OLS) model, Generalized Additive Model (GAM), Spatial Durbin Model (SDM) and Geographically Weighted Regression (GWR) model. are analysed. While the study offers insights into the complex interplay between energy efficiency, housing characteristics, location factors and rent prices, its primary contribution lies in the methodology, emphasizing the critical importance of accurate model selection. The traditional OLS captures linear relationships, but fails to capture nuanced relations and neglects spatial dynamics. GAM introduces non-linear relationships and provides a more refined understanding, but ignores spatial variations. The SDM, which takes spatial influences into account, provides a more accurate reflection of rental price dependencies across regions. However, its assumption of geographic stationarity leads to the adoption of the GWR model, which effectively captures spatial heterogeneity and outperforms other models in terms of explanatory power and fit. While this study underscores the importance of selecting the appropriate research strategy in general, it specifically highlights the importance of incorporating geographical information into the methodology of energy efficiency studies.

Keywords: Energy efficiency; Residential real estate; Rental market; Spatial dynamics; Econometric models (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10037-025-00227-1

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