Willingness to accept and willingness to pay for residential properties: a hedonic model approach

Abstract

The world over is becoming urbanized, and people are migrating to cities in large numbers in search of opportunities. The increased urbanization has posed challenges such as congestion, rising crime, and growing urban poverty. The governments respond by providing amenities such as schools, hospitals, and housing to meet to increase in demand for these facilities. However, there is a need for the provision of facilities that meets the expectations of the people, particularly on the proximity of amenities and bundles of utility-bearing housing characteristics. In an attempt to address the challenge mentioned, the study estimated the hedonic characteristics influencing the willingness to accept and willingness to pay for housing facilities in the Eastern Cape Province, South Africa. Using a multiple linear regression model and artificial neural network, the study found out that properties with a bathroom, garage and large floor size have a higher value compared to properties without these facilities.When making decisions to acquire a property, buyers consider the availability of discounts and the prevailing property price. Overall, willingness to pay and accept decisions are mainly determined by location and the price at which homogeneous neighborhood properties were sold. Therefore, the study recommends that urban town planners and other housing authorities prioritize the construction of properties with larger floor areas, parking bays, and bathrooms using a cost-effective mechanism that makes the properties affordable to residents.

Endowment Effect, Information Asymmetry, and Real Estate Market Decisions: Willingness to Pay and Willingness to Accept Disparities

“…The consumer chooses the combination of attributes that provides the highest level of utility given the affordability constraint. The study asked buyers and sellers whether or not they prefer a property close to urban amenities such as schools, shopping malls, and their workplaces over environmental amenities such as a beachfront (Mishi & Mwanyepedza, 2023). The effects of structural features of properties that were included in the survey, which includei the number of bedrooms, bathrooms, floor size, parking spaces available, and whether the property is a townhouse or an apartment, on the endowment effect were estimated as well.…”

“…However, buyers compare homogenous properties in terms of structural features, making buyers willing to pay less than the property's actual value when public amenities have been included. While some buyers may view schools as an amenity, others may view them as "not in my backyard" (NMBY) due to the negative externalities generated, which include noise and congestion (Mishi & Mwanyepedza, 2023).…”

“…The study further used ordinary least squares and quantile regressions to estimate the effect of the involvement of agents and affordability on the endowment effect with demographic, structural, and neighborhood variables as dummies. According to McCord et al (2018) ordinary least squares regression has been the most extensively utilized strategy in property forecasting due to its well-established methodology, extensive history of usage, and universal support among practitioners and academics (Can, 1992;Mishi & Mwanyepedza, 2023;Zhou et al, 2013). However, the ordinary least square's inability to handle intervariable relationships, nonlinearity, and multicollinearity well has resulted in researchers adopting other non-parametric models in estimating regressions (Abidoye & Chan, 2018).…”

“…The application of the endowment effect to the real estate sector got the attention of scholars due to valuation inconsistencies, where buyers and sellers do not value properties to the same market price (Gong et al, 2019;Paraschiv & Chenavaz, 2011). Gong et al, (2019) discovered that sellers tend to attach emotions when valuing properties, which result in overvaluations, whereas buyers are reluctant to pay the market price for a property when its desired amenities do not meet their needs (Mishi & Mwanyepedza, 2023) and simply because they do not own the property (Yan et al, 2021). The overvaluation by sellers and undervaluation by buyers creates a disparity between WTA and WTP.…”