The Effect of Listing Price Changes on the Selling Price of Single-Family Residential Homes

Gordon, Bruce; Winkler, Daniel T.

doi:10.1007/s11146-016-9558-z

Cited by 10 publications

(19 citation statements)

References 28 publications

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“…As generally referred to in the literature, listing price is the price of a property that is put up for sale by a property owner or the agent(s), whereas selling price is the amount a property is sold or purchased when been exchanged (Knight, 2002; Yavas and Yang, 1995). The studies of Pozo (2009); Hayunga and Pace (2016) and Gordon and Winkler (2016), among other studies, used property listing prices collected from real estate companies in property price modelling. Also, information of sold and purchased properties collected from real estate companies was used for property price modelling by scholars including McGreal et al (1998); Bourassa et al (2006); Choy et al (2007) and Owusu-Ansah (2012).…”

Section: Literature Reviewmentioning

confidence: 99%

Achieving property valuation accuracy in developing countries: the implication of data source

Abidoye

Chan

2018

IJHMA

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Purpose The demand for accurate property value estimation by valuation report end users has led to a shift towards advanced property valuation modelling techniques in some property markets and these require a sizeable number of data set to function. In a situation where there is a lack of a centralised transaction data bank, scholars and practitioners usually collect data from different sources for analysis, which could affect the accuracy of property valuation estimates. This study aims to establish the suitability of different data sources that are reliable for estimating accurate property values. Design/methodology/approach This study adopts the Lagos metropolis property market, Nigeria, as the study area. Transaction data of residential properties are collected from two sources, i.e. from real estate firms (selling price) and listing prices from an online real estate company. A portion of the collected data is fitted into the artificial neural network (ANN) model, which is used to predict the remaining property prices. The holdout sample data are predicted with the developed ANN models. Thereafter, the predicted prices and the actual prices are compared so as to establish which data set generates the most accurate property valuation estimates. Findings It is found that the listing data (listing prices) produced an encouraging mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) values compared with the firms’ data (selling prices). An MAPE value of 26.93 and 29.96 per cent was generated from the listing and firms’ data, respectively. A larger proportion of the predicted listing prices had property valuation error of margin that is within the industry acceptable standard of between ±0 and 10 per cent, compared with the predicted selling prices. Also, a higher valuation accuracy was recorded in properties with lower values, compared with expensive properties. Practical implications The opaqueness in real estate transactions consummated in developing nations could be attributed to why selling prices (data) could not produce more accurate valuation estimates in this study than listing prices. Despite the encouraging results produced using listing prices, there is still an urgent need to maintain a robust and quality property data bank in developing nations, as obtainable in most developed nations, so as to achieve a sustainable global property valuation practice. Originality/value This study does not investigate the relationship between listing prices and selling prices, which has been conducted in previous studies, but examines their suitability to improve property valuation accuracy in an emerging property market. The findings of this study would be useful in property markets where property transaction data bank is not available.

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Section: Literature Reviewmentioning

confidence: 99%

Achieving property valuation accuracy in developing countries: the implication of data source

Abidoye

Chan

2018

IJHMA

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“…The main pricing strategies used in practice by the developers (Smith et al, 2016;Rattermann, 2007;Cupal, 2017;Gordon and Winkler, 2017) include:…”

Section: Literature Reviewmentioning

confidence: 99%

The Functioning of the Real Estate Market: Dynamics of Price Formation and the Sale of Apartments

Wolniak¹,

Szymczewska²,

Olkiewicz³

2020

ERSJ

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The aim of this publication is to analyse how the dynamics of apartments' price formation correlates with the development of the apartment market. Design/Methodology/Approach: We analysed data about real estate markets of Polish communes located in Central Pomerania. The values of the analysed indicators were calculated using Excel program and the results were presented in the form of Tables and Figures in Microsoft Excel and ArcMap. Findings: This publication focuses on issues related to price formation on the housing market with the objective to illustrate a correlation between the dynamics of price formation of apartments and the development of the apartment market. This study concentrates on the pricing behaviour of transactions in the primary and secondary real estate markets of apartments. Research results indicate that there is a relationship between the dynamics of price formation and the development of the apartment market in both the primary and secondary markets. The hypotheses have been positively verified. The analysis of the obtained data does not indicate the same tendencies in the transaction prices of the apartment properties in the researched seaside communes in the years 2014-2018. Practical Implications: The most important practical implication is that the analyzed seaside areas still have a large investment space for newer, more expensive and larger apartments. Originality/Value: Research analysis of the two markets shows that the primary market is characterised by a much greater volatility of the average transaction price per sqm of apartment's usable floor area, while the secondary market is much more stable in terms of the average transaction price. There is also a very large variation in the average price per sqm between the surveyed municipalities.

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“…Pro statisticky významné hodnocení je však nutné zvětšit rozsah datového souboru realizovaných cen. [5]…”

Section: Výsledky Pozorováníunclassified

Vývoj cen nemovitostí od nabídky do uskutečnění transakce

Opalkova¹,

Cupal²

2019

Soudní Inženýrství

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Článek se zabývá sledováním nabídkových cen až do realizace tržní transakce jako ukazatele efektivity trhu. Tento mikroekonomický výzkum by měl určovat jak cenové rozdíly mezi nabídkovými a realizovanými cenami, tak i dobu trvání prodeje každé entity vybraného trhu a segmentu. Výzkum zahrnuje dva segmenty trhu s nemovitostmi v České republice: rodinné domy a zemědělské pozemky. Data jsou kontinuálně shromažďována od března 2017. Aktualizována jsou jednou týdně, aby bylo možné určit dobu trvání nabídky, nabídkovou cenu a realizovanou (tržní) cenu. Údaje o realizovaných cenách byly získány z katastru nemovitostí. Dílčí výsledky tohoto výzkumu jsou uplatnitelné jako vstupy do komparativní metody ocenění.

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The Effect of Listing Price Changes on the Selling Price of Single-Family Residential Homes

Cited by 10 publications

References 28 publications

Achieving property valuation accuracy in developing countries: the implication of data source

Achieving property valuation accuracy in developing countries: the implication of data source

The Functioning of the Real Estate Market: Dynamics of Price Formation and the Sale of Apartments

Vývoj cen nemovitostí od nabídky do uskutečnění transakce

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