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Models for Simulating the Impact of Accessibility on Real Estate Prices
Published in Rubén Cordera, Ángel Ibeas, Luigi dell’Olio, Borja Alonso, Land Use–Transport Interaction Models, 2017
Rubén Cordera, Ángel Ibeas, Luigi dell’Olio
The characteristics zn can be classified into three main types: environmental/social, structural characteristics and transport/accessibility to opportunities. This kind of model has been used in studies over many years (Court 1939) even though it was Rosen (1974) who formulised the supply and demand equilibrium model for heterogeneous goods. This chapter will only refer to the hedonic model estimated during a first phase, in other words, the implicit prices model based on market equilibrium, that is able to provide the willingness to pay for marginal increases in any of the specified attributes. Estimating the second phase of a hedonic model also allows the researcher to calculate the structural parameters of the supply and demand curves for the market of the heterogeneous product (Malpezzi 2008). Therefore, the hedonic function becomes conceptualised as the envelope function of the supply and demand functions of producers and consumers, respectively. The hedonic pricing function on its own does not reveal information about the preferences of the producers and consumers that generated it. Nevertheless, McFadden (2013) has highlighted that under certain conditions, the preferences of the consumers can be recovered directly from the hedonic function. These conditions are as follows: (1) consider that all consumers have identical preferences and (2) consider that all consumers have identical perceptions about the unobservable attributes. Under these hypotheses, the market prices are determined independently from the market and production structures, so the parameters of the hedonic regression directly represent the consumers’ preferences.
The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images
Published in Journal of Asian Architecture and Building Engineering, 2023
Masatomo Suzuki, Junichiro Mori, Takashi Nicholas Maeda, Jun Ikeda
The quality of surrounding landscapes has a potential impact on real estate price formation because landscapes represent elements that make up the quality of the surrounding neighborhood. There are many factors forming property prices, including building characteristics (e.g., property age and floor area), land characteristics (e.g., land area and walking time to nearest station), and land use around the properties. The hedonic regression analysis separates the contribution of each component to property prices. The economic value of a landscape is captured using a landscape index, which provides additional explanatory variables to the basic characteristics. The landscape index has traditionally been created through a field survey, whereby criteria are set and scored by a researcher (Gao and Asami 2007). Alternatively, researchers collect detailed land use information (Gao and Asami 2001), advertising information or 3D geographical information on whether a property offers a scenic view, such as of the ocean (Jim and Chen 2009; Yamagata et al. 2016), to create the landscape index.
The impact of Energy Performance Certificates on building deep energy renovation targets
Published in International Journal of Sustainable Energy, 2019
Alexandros G. Charalambides, Christos N. Maxoulis, Orestis Kyriacou, Erik Blakeley, Laura Soto Frances
Typically, hedonic regression models are used to calculate the effect of factors such as EPC ratings on property prices and rental returns. Fuerst et al. (2013) used such a method to investigate the effect of EPC ratings on house prices in the UK. Their research indicated significant effects, and although it is logical that the building condition is important when considering deep energy renovation, they were unable to capture the contribution of building condition or general renovation needs in their analysis due to lack of data. In their research, they took into account the age of the building and used prices per square metre to allow for the contribution of size of property. They estimate that compared to dwellings rated G, dwellings rated F sell for nearly 6% more, dwellings rated D and E sell for approximately 6% and 8% more, C rated dwellings sell for around 10% more and dwellings rated A or B sell for approximately 14% more.Brounen and Kok (2011) carried out similar work in the Netherlands. Using data from 2008 and 2009 and a D rating as their reference point they suggest prices higher by 10%, 5.5% and 2% for A, B and C EPC ratings, respectively, and reduction of 0.5%, 2.5% and 5% for E, F and G rated properties, respectively. Hyland, Lyons, and Lyons (2013) also concluded similar findings from work on the housing market in Ireland although there were a limited number of properties in possession of an EPC rating at the time of their studies (2008–2012).