Abstract Textual information contained in online property listings has become an increasingly important source of market signals, yet the economic value of linguistic features remains insufficiently understood. This study examines whether sentiment expressed in residential property descriptions is associated with asking prices and whether this relationship depends on the informational context of the listing. Drawing on signalling theory and information asymmetry, the study argues that sentiment should be viewed as a conditional signal rather than a universal price premium. The paper analyzes residential property listings from Krakow, Poland, and applies hedonic pricing models incorporating textual sentiment measures and interaction terms. The results show that the relationship between sentiment and price is heterogeneous rather than uniform. Positive sentiment is associated with higher asking prices particularly in contexts characterized by greater information uncertainty, including tenement buildings. The findings further indicate that seller type influences the level of sentiment expressed in listings but does not significantly moderate its price effect. Overall, the study contributes to the literature by showing that textual sentiment functions as a context-dependent market signal, with its value determined by the informational characteristics of the property and listing environment.
Abstract As China’s urbanization enters a more localized and intensive phase, the real estate sector is increasingly facing unique structural challenges in lower-tier markets, where capacity is limited, and sales pressure is high. This research investigates the risk landscape of market competition, marketing, and sales in apartment development projects within China’s third-tier cities to support strategic decision-making and project optimization. The study employs the Analytic Hierarchy Process (AHP) to analyze survey data from a panel of real estate experts, focusing on identifying critical risk factors across various development stages. The results show that the planning and sales stages receive relatively higher risk weights, indicating that early-stage market identification and subsequent sales performance are important components of the overall risk structure. Specifically, competition and market analysis and marketing appropriateness receive the highest composite weights, whereas broader macroeconomic factors do not dominate the overall risk structure. The findings suggest that accurate market positioning and effective marketing practices represent important risk-management priorities for apartment development projects in third-tier cities. These findings provide developers with an empirical basis for optimizing project positioning and sales strategies amid intense competition and limited market absorption.
Abstract Climate change increasingly affects real estate markets because property assets are location-specific and directly exposed to environmental conditions. This study examines whether physical climate risks influence volatility in South African listed property markets. Using a GARCH–MIDAS framework, daily returns from five property indices are linked to monthly indicators of drought, extreme precipitation, and temperature extremes derived from the Actuarial Society of South Africa Climate Index. Results show that physical climate conditions contribute to persistent market volatility. Short-run volatility persistence is strong across all indices. Drought consistently increases long-run volatility, particularly in segmented indices, while broader indices show weaker effects. Temperature extremes exert the greatest influence, with minimum temperatures affecting most indices. Precipitation effects vary with flood exposure and infrastructure resilience, reducing volatility where rainfall alleviates drought stress and increasing it where flood risk dominates. These findings highlight the importance of incorporating physical climate risks into portfolio risk assessment, volatility forecasting, and long-term investment decisions in climate-exposed real estate markets.
Abstract National aggregate measures of housing shortages often obscure local disequilibrium, bundling heterogeneous markets and masking the coexistence of severe deficits and excess stock. Furthermore, the housing gap is affected by demographic and cultural changes, which need to be factored into any projection of it. To address these limitations, this article proposes a novel, empirically grounded framework for calculating and projecting the housing gap at the regional level. The model accounts for local demographic projections, immigration trends, and the adaptive responses of real estate developers. We apply this framework to Poland. Our analysis reveals that, as household growth reverses, market adjustment transitions from a return to equilibrium through new supply toward a rapid accumulation of uninhabited dwellings. Consequently, the resolution of the aggregate national housing gap is likely to coincide with widening spatial divergence between local markets. Rather than producing a deterministic forecast, this framework serves as a robust tool for structured conditional forecasting. By identifying where shortages are likely to persist and where oversaturation may emerge, it offers a comprehensive analytical foundation for examining market adjustment, development pressures, vacancy formation, and future house price developments.
