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

2018 ◽  
Vol 11 (3) ◽  
pp. 573-585 ◽  
Author(s):  
Rotimi Boluwatife Abidoye ◽  
Albert P.C. Chan
Keyword(s):  
Real Estate ◽  
Data Bank ◽  
Developing Nations ◽  
Selling Price ◽  
Property Market ◽  
Data Set ◽  
Content Type ◽  
Transaction Data ◽  
Property Valuation ◽  
Property Markets

PurposeThe 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/approachThis 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.FindingsIt 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 implicationsThe 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/valueThis 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.

An analysis of auction strategies in apartment sales

2018 ◽  
Vol 11 (2) ◽  
pp. 202-223 ◽  
Author(s):  
Rosane Hungria-Gunnelin
Keyword(s):  
Real Estate ◽  
List Price ◽  
Selling Price ◽  
Residential Real Estate ◽  
Data Set ◽  
Content Type ◽  
Bidding Strategies ◽  
Ascending Auctions ◽  
Jump Bidding ◽  
Positive Effect

Purpose This paper aims to empirically test the effect of list price and bidding strategies in ascending auctions of residential real estate. Design/methodology/approach Three regression models are estimated, using a unique data set from 629 condominium apartments in the inner-city of Stockholm, Sweden, sold between January 2010 and December 2011. Findings The results show that jump bidding has the predicted effect of reducing competition by scaring off bidders. However, a higher average bid increment leads to a higher selling price. Furthermore, results show that a fast auction in terms of average time between bids acts to increase the probability of so-called auction fever as both the number of bidders and the selling price are positively correlated with the speed of the auction. While the average behavior of all auction participants, in terms of jump bidding and time between bids, significantly affects auction outcomes, differences in strategies applied by winners and losers show mixed results. The results of this study with respect to sellers’ list price strategy show that underpricing is an ineffective strategy in terms of enticing more bidders to participate in the auction. Furthermore, underpricing is not sufficient to have a positive effect on the selling price. Originality/value This paper is one of the first papers to empirically analyze how different bidding strategies affect the outcome of residential real estate auctions in terms of competition and the final selling price.

Artificial neural network in property valuation: application framework and research trend

2017 ◽  
Vol 35 (5) ◽  
pp. 554-571 ◽  
Author(s):  
Rotimi Boluwatife Abidoye ◽  
Albert P.C. Chan
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Real Estate ◽  
Search Engines ◽  
Predictive Accuracy ◽  
Research Area ◽  
Research Trend ◽  
Content Type ◽  
Property Valuation ◽  
Property Markets

Purpose The predictive accuracy and reliability of artificial intelligence models, such as the artificial neural network (ANN), has led to its application in property valuation studies. However, a large percentage of such previous studies have focused on the property markets in developed economies, and at the same time, effort has not been put into documenting its research trend in the real estate domain. The purpose of this paper is to critically review the studies that adopted ANN for property valuation in order to present an application guide for researchers and practitioners, and also establish the trend in this research area. Design/methodology/approach Relevant articles were retrieved from online databases and search engines and were systematically analyzed. First, the background, the construction and the strengths and weaknesses of the technique were highlighted. In addition, the trend in this research area was established in terms of the country of origin of the articles, the year of publication, the affiliations of the authors, the sample size of the data, the number of the variables used to develop the models, the training and testing ratio, the model architecture and the software used to develop the models. Findings The analysis of the retrieved articles shows that the first study that applied ANN in property valuation was published in 1991. Thereafter, the technique received more attention from 2000. While a quarter of the articles reviewed emanated from the USA, the rest were conducted in mostly developed countries. Most of the studies were conducted by universities scholars, while very few industry practitioners participated in the research works. Also, the predictive accuracy of the ANN technique was reported in most of the papers reviewed, but a few reported otherwise. Research limitations/implications The articles that are not indexed in the search engines and databases searched and also not available in the public domain might not have been captured in this study. Practical implications The findings of this study reveal a gap between the valuation practice in developed and developing property markets and also the contributions of real estate practitioners and universities scholars to real estate research. A paradigm shift in the valuation practice in developing nations could lead to achieving a sustainable international valuation practice. Originality/value This paper presents the trend in this research area that could be useful to real estate researchers and practitioners in different property markets around the world. The findings of this study could also encourage collaboration between industry professionals and researchers domiciled in both developed and developing countries.

Real estate development in the city of Athens during the financial crisis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maria Nikitidou ◽  
Fragiskos Archontakis ◽  
Athanasios Tagkalakis
Keyword(s):  
Financial Crisis ◽  
Real Estate ◽  
Structural Characteristics ◽  
House Prices ◽  
Real Estate Market ◽  
Structural Factors ◽  
Data Set ◽  
Content Type ◽  
Capital Financing ◽  
The City

Purpose This study aims to determine how the prices of residential properties in the Greek real estate sector are affected by their structural characteristics and by the prevailing economic factors during recession. Design/methodology/approach Based on 13,835 valuation reports for the city of Athens, covering a period of 11 years (2006–2016), this study develops a series of econometric models, taking into account both structural characteristics of the property market and the macroeconomic relevant variables. Finally, the city of Athens is divided into sub-regions and the different effects of the structural factors in each area are investigated via spatial analysis confirming the validity of the baseline model. Findings Findings show that the size, age, level, parking and storage space can explain the property price movements. Moreover, the authors find evidence that it is primarily house demand variables (e.g. the annual average wage, the unemployment rate, the user cost of capital, financing constraints and expectations about the future course of the house market) that affect house prices in a statistically significant manner and with the correct sign. Finally, using a difference-in-differences approach, this study finds that an increase in house demand (on account of net migration) led to higher house prices in smaller and older than in larger and younger apartments in areas with high concentration of immigrants. Originality/value This study uses a novel data set to help entities, individuals and policy-makers to understand how the recent economic and financial crisis has affected the real estate market in Athens.

DEMATEL method of analysing the factors influencing the decision to adopt virtual reality technology by real estate firms in Lagos property market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ayodele Samuel Adegoke ◽  
Timothy Tunde Oladokun ◽  
Timothy Oluwafemi Ayodele ◽  
Samson Efuwape Agbato ◽  
Ahmed Ademola Jinadu
Keyword(s):  
Virtual Reality ◽  
Real Estate ◽  
Social Influence ◽  
Property Market ◽  
Content Type ◽  
Performance Expectancy ◽  
Factors Influencing ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Estate Agency

PurposeThe study analysed the factors influencing real estate firms' (REFs) decision to adopt virtual reality (VR) technology using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. This was done to enhance the practice of real estate agency in Nigeria.Design/methodology/approachData were elicited from eight real estate experts. These experts were heads of the agency department of firms that had been in existence for a minimum of five years in the Lagos property market. The data analysed in this study were collected with the aid of a questionnaire.FindingsThe result revealed that use intention was influenced by performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value and UB. Also, facilitating conditions, habit and use intention did not influence use behaviour. Overall, six constructs, which include price value (Ri − Cj value = 0.1284), use behaviour (Ri − Cj value = 0.0666), social influence (Ri − Cj value = 0.0583), facilitating conditions (Ri − Cj value = 0.0323), performance expectancy (Ri − Cj value = 0.0196) and effort expectancy (Ri − Cj value = 0.0116), were significant predictors of the factors influencing the decision of REFs to adopt VR. Of these constructs, the Ri − Cj values indicated that price value had the highest causative influence.Practical implicationsThe result of this study will bring REFs to the consciousness of the factors that could affect their adoption of VR technology. This study will also assist the Nigerian Institution of Estate Surveyors and Valuers in appropriately enlightening REFs on the integration of VR technology into the agency practice especially at this time when all health protocols and guidelines need to be observed to help flatten the curve of the Covid-19 pandemic.Originality/valueThis study is the first to have an insight into the analysis of the factors influencing REFs' decision to adopt VR technology using the DEMATEL method.

House price index (HPI) and Covid-19 pandemic shocks: evidence from Turkey and Kazakhstan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yeşim Aliefendioğlu ◽  
Harun Tanrivermis ◽  
Monsurat Ayojimi Salami
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Housing Prices ◽  
House Price ◽  
Monthly Basis ◽  
Data Set ◽  
House Price Index ◽  
Content Type ◽  
Asymmetric Pricing ◽  
Long Run

Purpose This paper aims to investigate asymmetric pricing behaviour and impact of coronavirus (Covid-19) pandemic shocks on house price index (HPI) of Turkey and Kazakhstan. Design/methodology/approach Monthly HPIs and consumer price index (CPI) data ranges from 2010M1 to 2020M5 are used. This study uses a nonlinear autoregressive distributed lag model for empirical analysis. Findings The findings of this study reveal that the Covid-19 pandemic exerted both long-run and short-run asymmetric relationship on HPI of Turkey while in Kazakhstan, the long-run impact of Covid-19 pandemic shock is symmetrical long-run positive effect is similar in both HPI markets. Research limitations/implications The main limitations of this study are the study scope and data set due to data constraint. Several other macroeconomic variables may affect housing prices; however, variables used in this study satisfy the focus of this study in the presence of data constraint. HPI and CPI variables were made available on monthly basis for a considerably longer period which guaranteed the ranges of data set used in this study. Practical implications Despite the limitation, this study provides necessary information for authorities and prospective investors in HPI to make a sound investment decision. Originality/value This is the first study that rigorously and simultaneously examines the pricing behaviour of Turkey and Kazakhstan HPIs in relation to the Covid-19 pandemic shocks at the regional level. HPI of Kazakhstan is recognized in the global real estate transparency index but the study is rare. The study contributes to regional studies on housing price by bridging this gap in the real estate literature.

Residential property market determinants: evidence from the 2018 Australian market downturn

2019 ◽  
Vol 38 (2) ◽  
pp. 157-175
Author(s):  
Peng Yew Wong ◽  
Woon-Weng Wong ◽  
Kwabena Mintah
Keyword(s):  
Housing Market ◽  
Economic Conditions ◽  
Residential Property ◽  
Investment Fund ◽  
Property Market ◽  
Data Set ◽  
Content Type ◽  
Econometric Methods ◽  
Residential Market ◽  
Australian Bureau Of Statistics

Purpose The purpose of this paper is to validate and uncover the key determinants revolving around the Australian residential market downturn towards the 2020s. Design/methodology/approach Applying well-established time series econometric methods over a decade of data set provided by Australian Bureau of Statistics, Reserve Bank of Australia and Real Capital Analytics, the significant and emerging drivers impacting the Australian residential property market performance are explored. Findings Besides changes in the significant levels of some key traditional market drivers, housing market capital liquidity and cross-border investment fund were found to significantly impact the Australian residential property market between 2017 and 2019. The presence of some major positive economic conditions such as low interest rate, sustainable employment and population growth was perceived inadequate to uplift the Australian residential property market. The Australian housing market has performed negatively during this period mainly due to diminishing capital liquidity, excess housing supplies and retreating foreign investors. Practical implications A better understanding of the leading and emerging determinants of the residential property market will assist the policy makers to make sound decisions and effective policy changes based on the latest development in the Australian housing market. The results also provide a meaningful path for future property investments and investigations that explore country-specific effects through a comparative analysis. Originality/value The housing market determinants examined in this study revolve around the wider economic conditions in Australia that are not new. However, the coalesce analysis on the statistical results and the current housing market trends revealed some distinguishing characteristics and developments towards the 2020s Australian residential property market downturn.

scholarly journals Tax increment financing and major league venues

2020 ◽  
Vol 10 (4) ◽  
pp. 495-517
Author(s):  
Robert Sroka
Keyword(s):  
Real Estate ◽  
Future Research ◽  
Real Estate Development ◽  
Tax Increment Financing ◽  
General Reference ◽  
Data Set ◽  
Content Type ◽  
Capital Costs ◽  
Major League ◽  
Sports Venues

PurposeThis article intends to shine a light on venue-related tax increment financing (TIF) through the first comprehensive inventory of its use at the major league level.Design/methodology/approachFor each 2018 venue in the five North American major leagues, data was collected on TIF contributions to direct venue capital costs as well as to projects using TIF to enable real estate development ancillary to a venue. Neighborhoods surrounding a venue were also assessed for the presence of a TIF district. With both the direct and ancillary elements, data was collected from government, industry, academic, mapping and media sources. A review of this data set and findings are followed by a discussion of implications and directions for future work.FindingsOver one-third of the TIF eligible permanent stadiums and arenas studied in the five major leagues have a direct or strong TIF connection. Direct TIF contributions to sports venues, as well as TIF use intended to generate real estate development around these venues, are most frequent and financially significant in arenas and soccer-specific stadiums. Additionally, arena and stadium projects using TIF often accompany ancillary real estate development.Originality/valueA primary purpose of this article is to provide a previously missing general reference resource to governments and citizens of jurisdictions considering facility TIF use on the scope, nature, extent and identity of TIF projects related to major league sports venues. More generally, the inventory and assessment of TIF use in professional sports venues offered by this article sets the stage for future research on associative relationships between TIF contributions and facility finance outcomes as well as the normative value of venue-related TIF.

Spatial effects and non-linearity in hedonic modeling

2018 ◽  
Vol 36 (1) ◽  
pp. 32-49 ◽  
Author(s):  
Marcelo Cajias ◽  
Sebastian Ertl
Keyword(s):  
Real Estate ◽  
Functional Form ◽  
Asymptotic Properties ◽  
Additive Model ◽  
Percentage Error ◽  
Spatial Effects ◽  
Hedonic Models ◽  
Data Set ◽  
Content Type ◽  
Out Of Sample

Purpose The purpose of this paper is to test the asymptotic properties and prediction accuracy of two innovative methods proposed along the hedonic debate: the geographically weighted regression (GWR) and the generalized additive model (GAM). Design/methodology/approach The authors assess the asymptotic properties of linear, spatial and non-linear hedonic models based on a very large data set in Germany. The employed functional form is based on the OLS, GWR and the GAM, while the estimation methodology was chosen to be iterative in forecasting, the fitted rents for each quarter based on their 1-quarter-prior functional form. The performance accuracy is measured by traditional indicators such as the error variance and the mean squared (percentage) error. Findings The results provide evidence for a clear disadvantage of the GWR model in out-of-sample forecasts. There exists a strong out-of-sample discrepancy between the GWR and the GAM models, whereas the simplicity of the OLS approach is not substantially outperformed by the GAM approach. Practical implications For policymakers, a more accurate knowledge on market dynamics via hedonic models leads to a more precise market control and to a better understanding of the local factors affecting current and future rents. For institutional researchers, instead, the findings are essential and might be used as a guide when valuing residential portfolios and forecasting cashflows. Even though this study analyses residential real estate, the results should be of interest to all forms of real estate investments. Originality/value Sample size is essential when deriving the asymptotic properties of hedonic models. Whit this study covering more than 570,000 observations, this study constitutes – to the authors’ knowledge – one of the largest data sets used for spatial real estate analysis.

An analysis of operating expense control within US multifamily properties

2017 ◽  
Vol 35 (1) ◽  
pp. 48-66 ◽  
Author(s):  
Andrew Carswell
Keyword(s):  
Explanatory Variable ◽  
Rental Housing ◽  
Positive Association ◽  
Individual Investors ◽  
Property Management ◽  
Property Market ◽  
Data Set ◽  
Content Type ◽  
Operating Income ◽  
The Usa

Purpose The purpose of this paper is to determine the effect that ownership and management structures have on ability to control operating expenses. For individual investors, intensity of management experience is also explored as a possible explanatory variable for operating expenses. For property management services that are contracted out, the level of the fee is investigated as a possible cause for movements in operating expenses as well. Finally, operating expenses are used as a possible explanatory variable for a property’s lease-up performance during the year. Design/methodology/approach The analysis consists of a series of regression models performed on data provided by the 2012 Rental Housing Finance Survey (RHFS) in the USA. The RHFS is a unique data set that covers a wide degree of information on multifamily properties. The RHFS represents 2,260 properties in total, and covers various aspects of the apartment industry, including financing and operational cost measures. Control variables used as independent variables include number of units, year of property acquisition, and age of building. Findings Individual ownership and self-management proved to be statistically significant drivers in driving down log operating expenses. Hours spent by individuals performing property management roles on their own properties had a slightly positive association with operating expenses. For professional managers, the fees devoted solely to the manager or management company had a highly significant and positive effect on other operating costs. Finally, when separating out the individual components of operating expenses, only two variables had significant effects on tenant lease-ups: management expenses (positive) and security expenses (negative). Research limitations/implications The data set is potentially biased toward those properties with less than 100 units, and thus it would be problematic to assume that these findings are generalizable to the population at large. There are also no geographic coding indicators within the RHFS data set, which eliminates the potential to control for various market factors and rural/urban differences. Practical implications The research provides an understanding of some of the basic factors behind increases in operating expenses, which ultimately has implications for performance benchmarks such as net operating income and property market value. Social implications The reasonable controlling of operating expenses ultimately has potentially positive implications for low- to moderate-income populations, who would ultimately experience lower rents as a result. Originality/value This research represents one of the first known uses of the RHFS database.

scholarly journals Modelling the drivers of the UK multi-let industrial property market: an exploratory study

2020 ◽  
Vol 38 (4) ◽  
pp. 585-596
Author(s):  
David Higgins ◽  
Tsvetomira Vincent ◽  
Peter Wood
Keyword(s):  
Real Estate ◽  
Hedonic Pricing ◽  
Valuable Insight ◽  
Pricing Model ◽  
Property Market ◽  
Industrial Property ◽  
Content Type ◽  
Hedonic Pricing Model ◽  
Significant Difference ◽  
Asset Class

PurposeMulti-let industrial (MLI) estates are an emerging £15 billion UK real estate asset class that can offer attractive returns, a diversified income base, constrained supply and extensive management opportunities to add value within an operational platform. This investment appeal is supported by the evolving MLI occupier market with the growth of small to medium enterprises (SME) requiring modern urban business space driven in part by technology advances offering new streams of supply chain connectivity between businesses and potential clients at a local level.Design/methodology/approachTo understand more about MLI properties, this study utilises a hedonic pricing model to quantify property values as a function of defined variables. The dataset used for this research is a sample portfolio of 26 multi-let industrial properties. The dataset was analysed alongside eleven physical, financial and locational factors. Interestingly, the hedonic pricing model results showed that only four characteristics are value-affecting across the selected properties: namely (1) Granularity of the property income, (2) Distance from the nearest motorway, (3) Distance to the nearest town centre and (4) Gross internal floor area. A chi–test confirmed that there was no significant difference between the modelled values and the supplied property valuations.FindingsThis preliminary study offers valuable insight into MLI property market drivers and could easily form a simple decision-making tool to examine potential MLI opportunities in this developing real estate asset class.Originality/valueIn detailing these key MLI property features, current research is limited and focused primarily on market commentary. New knowledge on the MLI property market can provide a platform creating interesting opportunities for fund managers with an intensive management engagement strategy.

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