Real Estate

19 pages, 1000 KB

Open AccessArticle

Transactional (Case–Shiller) vs. Hedonic (Zillow) Housing Price Indices (HPI): Different Construction, Same Conclusions?

by Mark Rzepczynski and Wei Feng

Real Estate 2025, 2(4), 19; https://doi.org/10.3390/realestate2040019 - 5 Nov 2025

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Abstract

Housing price indices (HPIs) are employed to assess the impact of the business cycle, monetary policy, housing policies, and local market dynamics. However, comparative empirical analysis of different HPI methodologies has not been conducted to measure why or when they may diverge and whether these differences are meaningful. Two leading US HPI choices, the repeat-sale transactional (S&P Case–Shiller) and characteristic-based hedonic (Zillow) indices, although highly correlated, generate different distributions and time-series properties primarily at the city level. The spread between these two HPI choices measures the difference between housing market transaction intensity and a willingness-to-pay characteristic valuation. We find that transactional indices are more volatile, with HPI spreads associated with both macro and local drivers. The transactional index will rise more rapidly in a market with increased buying (positive macro and local market conditions) and fall further in a market with increased selling (negative macro and local market conditions) relative to a hedonic index. A buyer- or seller-biased spread between a transactional and hedonic housing price index (HPI) may impact policy judgments during housing market extremes. Full article

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26 pages, 5171 KB

Open AccessArticle

A Method to Measure Neighborhood Quality with Hedonic Price Models in Three Latin American Cities

by Marco Aurélio Stumpf González and Diego Alfonso Erba

Real Estate 2025, 2(4), 18; https://doi.org/10.3390/realestate2040018 - 3 Nov 2025

Viewed by 147

Abstract

Location effects play a crucial role in the real estate market, encompassing aspects of accessibility and neighborhood quality. While traditional measures exist for accessibility, evaluating neighborhood quality can be a complex task. Understanding these elements is essential for accurately estimating property values, whether for commercial or tax purposes. Recently developed methods based on web scraping and automatic detection using artificial intelligence have proven effective but require substantial human and financial resources, often unavailable in small cities. As a solution, this study proposes and evaluates a simpler mechanism for assessing neighborhood quality using Google Street View images and a scoring system in a human-centered approach. Based on image interpretation, a set of weights is assigned to each point, resulting in a micro-neighborhood quality assessment. This study was conducted in three Latin American cities, and the resulting variable was integrated into hedonic price models. The findings demonstrate the feasibility and effectiveness of the proposed approach. The novelty of this study lies in applying a method based on quasi-objective criteria and adapted to cities with limited technological resources. Full article

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22 pages, 1356 KB

Open AccessArticle

A Holistic Sustainability Evaluation for Heritage Upcycling vs. Building Construction Projects

by Elena Fregonara, Chiara Senatore, Cristina Coscia and Francesca Pasquino

Real Estate 2025, 2(4), 17; https://doi.org/10.3390/realestate2040017 - 8 Oct 2025

Viewed by 588

Abstract

The paper contributes to the debate on the holistic sustainability assessment of real estate projects, integrating economic, financial, environmental, and social aspects. A methodological study is presented to support decision-making processes involving the preferability ranking of alternative investment scenarios: new building production vs. retrofitting the existing stock, in the context of urban transformation interventions. The study integrates life cycle approaches by introducing the social components besides the economic and environmental ones. Firstly, a composite unidimensional (monetary) indicator calculation is illustrated. The sustainability components are internalized in the NPV calculation through a Discounted Cash-Flow Analysis (DCFA). Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) are suggested to assess the economic and environmental impacts, and the Social Return on Investment (SROI) to assess the intervention’s extra-financial value. Secondly, a methodology based on multicriteria techniques is proposed. The Hierarchical Analytical Process (AHP) model is suggested to harmonize various performance indicators. Focus is placed on the criticalities emerging in both the methodological approaches, while highlighting the relevance of multidimensional approaches in decision-making processes and for supporting urban policies and urban resilience. Full article

(This article belongs to the Topic Improving Nature-Smart Policies through Innovative Resilient Evaluations)

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18 pages, 1257 KB

Open AccessArticle

Forecasting the Housing Market Sales in Italy: An MLP Neural Network Model

by Paolo Rosato and Matteo Galante

Real Estate 2025, 2(4), 16; https://doi.org/10.3390/realestate2040016 - 2 Oct 2025

Viewed by 881

Abstract

Using panel data on 99 Italian provinces in the period between 2005 and 2020, the research investigates the effects of fundamental economic factors on the home sales at the provincial level, in order to build a forecasting model using a non-linear artificial intelligence approach (MLP-Multiple Linear Perceptron neural network). There are multiple objectives to this: (a) to test the hypothesis that national, regional and local fundamentals such as interest rates, income, inflation rate, unemployment and demography affect the activity’s degree of the housing market; (b) to verify the effectiveness of a neural network in describing the dynamics of the real estate market; (c) to build a simulation model capable of predicting the effect of changes in fundamentals, also due to economic policy measures, on the market. Empirical results show that neural networks offer better capabilities than linear models in representing the complex relationships between the economic situation and the real estate market. The study provides useful information for regulators to improve the effectiveness of monetary policy to stabilize real estate markets as well as for stakeholders to draw up scenarios of market development. Full article

(This article belongs to the Topic Improving Nature-Smart Policies through Innovative Resilient Evaluations)

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Real Estate, Volume 2, Issue 4 (December 2025) – 4 articles

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