scholarly journals Data Selection as the Basis for Better Value Modelling

2019 ◽  
Vol 27 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Jacek Zyga
Keyword(s):  
Real Estate ◽  
Statistical Methods ◽  
Data Selection ◽  
Property Value ◽  
Price Model ◽  
Real Estate Appraisal ◽  
Property Prices ◽  
Property Price ◽  
Specific Object ◽  
Selection Of

Abstract The article is a voice in the debate on the scope of the application of statistical methods in real estate appraisal, written from the comparative perspective. It presents the results of an illustrative valuation of housing units with the use of databases of various sizes, constructed on the basis of publicly available data from the register of property prices and values. Against this background, the article presents an analysis of differences between the objectives and published results of valuations, which exemplify broadly understood property price modelling or property value modelling, as well as of activities focused around appraising a specific object. The conducted experiments demonstrated that, for the purposes of real estate appraisal itself, the selection of data is more useful than searching for a price model.

scholarly journals Housing Vulnerability and Property Prices: Spatial Analyses in the Turin Real Estate Market

2018 ◽  
Vol 10 (9) ◽  
pp. 3068 ◽  
Author(s):  
Alice Barreca ◽  
Rocco Curto ◽  
Diana Rolando
Keyword(s):  
Real Estate ◽  
Social Vulnerability ◽  
Real Estate Market ◽  
Spatial Analyses ◽  
Price Determination ◽  
Spatially Correlated ◽  
Property Prices ◽  
Vulnerability Indicators ◽  
Property Price ◽  
Physical Features

In the literature, several vulnerability/resilience indicators and indexes are based and assessed by taking into account and combining different dimensions. Housing vulnerability is one of these dimensions and is strictly related to the buildings’ physical features and to the socio-economic condition of their occupants. This research aims to study housing vulnerability in relation to the real estate market by identifying possible indicators and spatially analyzing their influence on property prices. Assuming the city of Turin and its territorial segmentation as a case study, spatial analyses were performed to take into account the presence of spatial dependence and to identify the variables that significantly influence the process of property price determination. The results of this study highlighted the fact that two housing vulnerability indicators, representative of fragile buildings’ physical features, were spatially correlated with property prices and had a significant and negative influence on them. In addition, their comparison with two social vulnerability indicators demonstrated that the presence of economical buildings and council houses was spatially correlated with the presence of people with a low education level. The results of the spatial regression model also confirmed that one of the social vulnerability indicators had the highest and most negative explanatory power in the property price determination process.

scholarly journals International Real Estate Review

2013 ◽  
Vol 16 (3) ◽  
pp. 296-322
Author(s):  
Damrongsak Rinchumphu ◽  
◽  
Chris Eves ◽  
Connie Susilawati ◽  
◽  
...  
Keyword(s):  
Negative Impact ◽  
Positive Impact ◽  
Explanatory Power ◽  
Metropolitan Region ◽  
Hedonic Price ◽  
Price Model ◽  
Lot Size ◽  
Price Increases ◽  
Property Prices ◽  
Property Price

This paper aims to evaluate the brand value of property in subdivision developments in the Bangkok Metropolitan Region (BMR), Thailand. The result has been determined by the application of a hedonic price model. The development of the model is developed based on a sample of 1,755 property sales during the period of 1992-2010 in eight zones of the BMR. The results indicate that the use of a semi-logarithmic model has stronger explanatory power and is more reliable. Property price increases 12.90% from the branding. Meanwhile, the price annually increases 2.96%; lot size and dwelling area have positive impacts on the price. In contrast, duplexes and townhouses have a negative impact on the price compared to single detached houses. Moreover, the price of properties which are located outside the Bangkok inner city area is reduced by 21.26% to 43.19%. These findings also contribute towards a new understanding of the positive impact of branding on the property price in the BMR. The result is useful for setting selling prices for branded and unbranded properties, and the model could provide a reference for setting property prices in subdivision developments in the BMR.

Predicting property price index using artificial intelligence techniques

2019 ◽  
Vol 12 (6) ◽  
pp. 1072-1092 ◽  
Author(s):  
Rotimi Boluwatife Abidoye ◽  
Albert P.C. Chan ◽  
Funmilayo Adenike Abidoye ◽  
Olalekan Shamsideen Oshodi
Keyword(s):  
Artificial Intelligence ◽  
Real Estate ◽  
Price Index ◽  
Policy Formation ◽  
Support Vector ◽  
Ann Model ◽  
Property Market ◽  
Content Type ◽  
Property Prices ◽  
Property Price

Purpose Booms and bubbles are inevitable in the real estate industry. Loss of profits, bankruptcy and economic slowdown are indicators of the adverse effects of fluctuations in property prices. Models providing a reliable forecast of property prices are vital for mitigating the effects of these variations. Hence, this study aims to investigate the use of artificial intelligence (AI) for the prediction of property price index (PPI). Design/methodology/approach Information on the variables that influence property prices was collected from reliable sources in Hong Kong. The data were fitted to an autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and support vector machine (SVM) models. Subsequently, the developed models were used to generate out-of-sample predictions of property prices. Findings Based on the prediction evaluation metrics, it was revealed that the ANN model outperformed the SVM and ARIMA models. It was also found that interest rate, unemployment rate and household size are the three most significant variables that could influence the prices of properties in the study area. Practical implications The findings of this study provide useful information to stakeholders for policy formation and strategies for real estate investments and sustained growth of the property market. Originality/value The application of the SVM model in the prediction of PPI in the study area is lacking. This study evaluates its performance in relation to ANN and ARIMA.

scholarly journals A DYNAMIC RELATIONSHIP BETWEEN CONSUMER CONFIDENCE AND RESIDENTIAL PROPERTY PRICE: EMPIRICAL EVIDENCE FOR MALAYSIA

2021 ◽  
Vol 11 (1) ◽  
pp. 16-34
Author(s):  
Nur Hafizah Ismail ◽  
Sabri Nayan
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Consumer Confidence ◽  
Residential Property ◽  
The Real ◽  
The Real Estate ◽  
Property Prices ◽  
The Real Estate Market ◽  
Property Price ◽  
Housing Industry

In recent years, the real estate market has become a major interest for economists and researchers. In general, property prices are influenced by the supply and demand of the real estate market. In addition to the individual's positive expectation of the real estate market would raise the demand for housing and hence, house price indexes would increase. This study provides new knowledge on how consumer confidence in the housing industry affects residential property prices in Malaysia. Previous studies on the effect of consumer perception towards residential property in Malaysia are scarce. Therefore, the objective of this study is to determine how consumer confidence affect residential property price in Malaysia. Our study differs by focusing on the effect of consumer confidence on the housing industry and macroeconomic drivers toward residential property prices in Malaysia over the period 2004:Q1 to 2018:Q4. By using the autoregressive distributed lag (ARDL) test, the empirical results have shown the presence of long-run adjustment and indicate that consumer confidence towards the housing industry and many macroeconomic variables significantly affect residential property prices. From this finding, we have suggested that government and policymakers should be able to understand consumer confidence in the housing industry to increase consumer satisfaction and to improve consumer sentiment towards the residential property market in Malaysia.

scholarly journals Municipal assessments versus actual sales prices in hedonic price studies

2015 ◽  
Vol 8 (1) ◽  
pp. 35-46
Author(s):  
Mario Du Preez ◽  
Michael Sale
Keyword(s):  
Seemingly Unrelated Regression ◽  
Hedonic Price ◽  
Property Value ◽  
Market Prices ◽  
Sales Price ◽  
Model Studies ◽  
Hedonic Price Models ◽  
Property Prices ◽  
Unrelated Regression ◽  
Property Price

In most hedonic price model studies, the actual sales price of a property is employed as the dependent variable in the parametric regression analysis. Although the use of this price is pervasive, alternatives to it do exist. One such alternative is the assessed property value, which is more readily available than the actual property price. The aim of this study is to compare implicit price estimates of property characteristics (both structural and locational) based on actual sales price data and assessed property values. To this end, a seemingly unrelated regression with two hedonic price equations is used, one which employs actual market prices as the dependent variable and the other which employs assessed values. The results show that the hypothesised influence of structural and locational housing characteristics on residential property prices is the same for assessed values, and actual market prices cannot be accepted. This finding should act as a caution for hedonic practitioners not to base their conclusions and recommendations solely on the use of assessed values in hedonic price models.

scholarly journals The Use of Statistical Methods for Determining Attribute Weights and the Influence of Attributes on Property Value

2020 ◽  
Vol 28 (4) ◽  
pp. 33-47
Author(s):  
Anna Gdakowicz ◽  
Ewa Putek-Szeląg
Keyword(s):  
Real Estate ◽  
Statistical Methods ◽  
Correlation Coefficients ◽  
Business Practice ◽  
Property Value ◽  
Attribute Weights ◽  
Methods Of Calculation ◽  
The Individual ◽  
The Impact ◽  
Calculation Procedures

AbstractDetermining the impact of individual attributes on the value or price of real estate in business practice poses many problems. One of the solutions to this problem is the use of statistical methods. The article proposes correlation coefficients (and their partial modifications) that can be used to determine the impact of selected features on the value of real estate. In addition, several procedures were taken into account for the factors in further calculations, using different methods for determining weights. Empirical verification of the proposed solutions was based on the mass valuation of land properties. The obtained results were compared with valuations developed by property appraisers and valuation errors were calculated. Based on valuation errors, the proposed methods of calculation procedures were ranged, indicating those which provide results closest to the individual valuations carried out by property appraisers.

METHODOLOGY FOR REAL ESTATE APPRAISAL OF GREEN VALUE

2009 ◽  
Vol 8 (3) ◽  
pp. 601-606 ◽  
Author(s):  
Daniela Popescu ◽  
Emilia Cerna Mladin ◽  
Rodica Boazu ◽  
Sven Bienert
Keyword(s):  
Real Estate ◽  
Real Estate Appraisal

Assessing Impact of Freshwater Lake Ecosystem on Residential Property Prices using Hedonic Property Pricing approach: Evidence from Vellayanilake of Kerala

2020 ◽  
pp. 125-130
Keyword(s):  
Economic Effect ◽  
Lake Ecosystem ◽  
Aesthetic Value ◽  
Market Prices ◽  
Scenic Beauty ◽  
Property Prices ◽  
Property Price ◽  
Valuation Technique ◽  
Hedonic Property ◽  
The Impact

ABSTRACT The ecosystem services provided by wetlands can be direct or indirect. The direct services can be mostly valued through market prices, but the indirect service like aesthetic beauty and its impact on property prices surrounding the natural resource cannot be directly measured. To single out the economic effect of particular amenity which influenced the land property prices, the advanced valuation technique Hedonic property pricing was most popularly used. In this study, it was attempted to assess using the hedonic property pricing technique, the impact of the presence of the freshwater body, the Vellayani Lake on land property prices surrounding it. The results revealed that the marginal implicit price of getting one cent of land with lake view evaluated at mean property price of Rs. 2,44250 was Rs.79171. The total aesthetic value of land with the scenic beauty of the lake was Rs. 275.92 crores.

CRITICAL DETERMINANTS OF HERITAGE PROPERTY VALUE: A CONCEPTUAL FRAMEWORK

2019 ◽  
Vol 17 (9) ◽  
Author(s):  
Normayuni Mat Zin ◽  
Suriatini Ismail ◽  
Junainah Mohamad ◽  
Nurul Hana Adi Maimun ◽  
Fatin Afiqah Md. Azmi
Keyword(s):  
Real Estate ◽  
Conceptual Framework ◽  
Structural Characteristics ◽  
Property Values ◽  
Property Value ◽  
Architectural Styles ◽  
Online Databases ◽  
The Status ◽  
Conference Papers ◽  
Published Research

Real estate is complex in nature, whereby its value is determined by many characteristics. Heritage property is different as compared with non-heritage property, thus; it is essential to identify the heritage property value determinants due to limited published research about it. This paper closes the gap by reviewing the literature to identify the determinants. To achieve this, academic journals and conference papers in online databases from 1974 to 2017 have been reviewed. The results indicated that there are four groups of heritage property value determinants namely; i) transaction characteristics, ii) structural characteristics, iii) spatial characteristics, and iv) historical characteristics. It can be concluded that heritage property values are differentiated by historical characteristics notably on their architectural styles or design and the status of the heritage property itself. This finding should be a useful guidance for the valuers in valuation practice.

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