Unraveling the Role Played by Energy Rating Bands in Shaping Property Prices Using a Multi-criteria Optimization Approach: The Case Study of Padua’s Housing Market

Copiello, Sergio; Donati, Edda

doi:10.1007/978-3-031-10562-3_42

Cited by 1 publication

(1 citation statement)

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“…Below is a description of the methodological steps we take to that end. An early draft of this multi-criteria optimization approach has been tested on very few properties and discussed at a recent conference [101]. To the best of the authors' knowledge, no other use of the approach to estimating the price premium of energy efficiency can be found in the literature.…”

Section: Multi-criteria Optimization Approachmentioning

confidence: 99%

The Price Premium in Green Buildings: A Spatial Autoregressive Model and a Multi-Criteria Optimization Approach

Copiello

Coletto

2023

Buildings

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The energy issue has given rise to a prolific research field, which branches into several strands. One of these strands focuses on the role played by building energy features in shaping property prices. Indeed, market players are expected to show a higher willingness to pay for building units characterized by higher energy performance. The study of the so-called price premium for building energy efficiency has flourished in the last decade or so; plenty of evidence is now available concerning its occurrence, although its magnitude is still debated. The literature relies on the methodological frameworks of statistical modeling and multiple regression, primarily employing hedonic price models. Lately, spatial autoregressive models have also been adopted. Here, we propose to deal with estimation of the price premium by adopting an innovative perspective. In particular, we use a methodological framework in which regression models are complemented with a multi-criteria optimization approach. Using a spatial autoregressive model first, and with D as the reference energy rating band, we find the following price premiums: 55% for A4, 42% for A3 to A, 20% for B or C, −14% for F, and −29% for G. The multi-criteria optimization approach proves efficient in estimating the price premium. The estimates above are essentially confirmed: the results converge for all the energy rating bands except for G.

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Section: Multi-criteria Optimization Approachmentioning

confidence: 99%