Condominium Prices Research Articles

An Investigation of the Impact of Amenities on Condominium Apartment Prices in Colombo, Sri Lanka with Machine Learning

Condominium prices of a location are heavily impacted by the availability of neighbourhood amenities, which attract people to that location. Studies that employ machine learning to evaluate the impacts of amenities on condominium prices are a few, despite indications of increased accuracy. Hedonic models are used in the majority of current studies on housing pricing. Yet, the application of machine learning will improve accuracy and be more effective for the identification of multi-collinearity and non-linear relationships between property prices and the availability of amenities for a wide range of parameters. The aim of this study is to investigate the possible relationship between urban amenities surrounding condominium apartments and their market prices. The study uses data from the Google Maps Platform to examine the link between neighbourhood amenities and the prices of 236 condominiums in Colombo, Sri Lanka. 56 significant amenity characteristics were found using the eXtreme gradient boosting (XGB) algorithm, and the variety of correlations between amenities and condominium prices as restricted positive, accelerated positive, crooked, humped, and negative was explained. Results demonstrated that while a beautiful urban environment requires a variety of facilities, the popularity and other attributes of amenities affect condominium prices in numerous non-linear ways. Therefore, public and private organizations must work together to create integrative strategies that enhance and maintain the variety and accessibility of urban amenities.

Dynamic spatiotemporal ARCH models

ABSTRACT Geo-referenced data are characterised by an inherent spatial dependence due to geographical proximity. In this paper, we introduce a dynamic spatiotemporal autoregressive conditional heteroscedasticity (ARCH) process to describe the effects of (i) the log-squared time-lagged outcome variable, the temporal effect, (ii) the spatial lag of the log-squared outcome variable, the spatial effect, and (iii) the spatiotemporal effect on the volatility of an outcome variable. We derive a generalised method of moments (GMM) estimator based on the linear and quadratic moment conditions. We show the consistency and asymptotic normality of the GMM estimator. After studying the finite-sample performance in simulations, the model is demonstrated by analysing monthly log-returns of condominium prices in Berlin from 1995 to 2015, for which we found significant volatility spillovers.

Does size matter? Is there an optimal size for tenant–owner associations?

PurposeThe authors investigate how prices of condominiums are affected by the size of the tenant-owner associations that they belong to.Design/methodology/approachThe authors use data of sold apartments in the Swedish municipality Malmö 2013–2018 and estimate hedonic price regressions. The authors also perform semi-structured interviews with three senior professionals in real estate companies.FindingsThe authors find significantly negative relationships between the prices of condominiums and the size of tenant-owner associations. Also, regression results indicate that associations should be no smaller than 6–10 apartments. The interviews support that associations should not be too small or too big. The lower and upper limit was suggested by the respondents to 40–50 and 80–150 apartments, respectively. In these ranges, economies of scale can be achieved, and residents will not lose the sense of community and responsibility.Research limitations/implicationsThe authors do not prove causality. Smaller associations may have relatively exclusive common amenities, about which we lack data. The same relationships may not exist in different market conditions.Originality/valueThe authors are not aware of previous studies with the same research question. The size of tenant-owner associations may affect the price through different channels. First, several of the banks in Sweden do not always grant mortgages for condominiums that belong to small associations. Second, larger associations may have better economies of scale and more efficient property management. Third, homeowners may prefer smaller tenant-owned associations, because they may feel less anonymous and provide more influence on common amenities.

Estimation of Building Age Effect on Condominium Price based on the APC Model

재개발‧재건축은 기성시가지에 질적으로 향상된 신축아파트를 공급할 수 있음에도 불구하고 억제되어왔다. 기본적으로 경과연수 제약에 의해, 경과연수 증가에 따른 재건축 가능성의 증가가 아파트 가격에 영향을 주는 것으로 해석되어왔다. 본 연구는 APC모형에 기초해 주택의 질적 수준을 통제할 때 아파트 가격에 대한 건축연령 효과를 추정하였다. 서울을 한강 이북과 한강 이남 지역으로 분리하여 실증분석한 결과, 건축연도코호트 효과가 존재함을 확인하였고, 2000년대 전후로 높아지는 질적 수준에 따른 프리미엄이 발생함을 확인하였다. 이는 높은 질적 수준의 주택에 대한 주택수급의 불균형이 낳은 결과라고 생각된다. 따라서 재건축사업을 통해 질적으로 향상된 주택을 공급함으로서 이러한 양상을 해결할 수 있다고 판단한다. 또한 지역별로 상이하게 도출된 가격반등시점을 통해 경과연수 제약의 탄력적인 적용이 필요할 것으로 생각된다.

マンションの管理費・修繕積立金に対する購入者意識と価格の関係性

This study verified the influence of maintenance costs on condominium’s purchase price through inverse probability weighting. Further, the results stated that condominium buyers identified that management fee payments are necessary to quality of planned repairs and management program, and hence, the market value of well-maintained condominiums are high. Therefore, the purchase prices of well-maintained condominiums are higher than the poorly maintained condominiums by 9.6 precent.

Green building factor in machine learning based condominium price prediction

The negative impact of massive urban development promotes the inclusion of green building aspects in the real estate and property industries. Green building is generally defined as an environmentally friendly building, which rapidly emerged as a national priority in many countries. Acknowledging the benefits of green building, Green Certificate and Green Building Index (GBI) has been used as one of the factors in housing prices valuation. To predict a housing price, a robust approach is crucial, which can be effectively gained from the machine learning technique. As research on green building with machine learning techniques is rarely reported in the literature, this paper presents the fundamental design and the comparison results of three machine learning algorithms namely deep learning (DL), decision tree (DT), and random forest (RF). Besides the performance comparisons, this paper presents the specific weight correlation in each of the machine learning models to describe the importance of the green building to the model. The results indicated that RF has been outperformed others while Green Certificate and GBI have only been slightly important in the DL model.

Determinants of Luxurious Condominium Prices in Bangkok CBD: A Case study of Encouraging Housing Affordability in Bangkok, Thailand

Determinants of Luxurious Condominium Prices in Bangkok CBD: A Case study of Encouraging Housing Affordability in Bangkok, Thailand

Google Maps amenities and condominium prices: Investigating the effects and relationships using machine learning

Neighbourhood amenities significantly impact condominium prices and attract population to the area. Despite evidence of improved accuracy, studies that use machine learning to assess the effects of amenities on condominium prices are limited. The purpose of this research is to investigate the relationship between neighbourhood amenities and the prices of 500 condominiums in Bangkok, Thailand using data from Google Maps. An eXtreme gradient boosting (XGB) algorithm identified 36 important amenity factors, while the multiplicity of relationships between amenities and condominium prices as bounded positive, accelerated positive, limited positive, humped and negative was elucidated. Results showed that the popularity and other features of amenities drive condominium prices in several non-linear ways, while an attractive urban environment requires multiple amenities. Public and private organisations in Bangkok should collaborate to develop integrative plans that improve and sustain the diversity and availability of urban amenities.

Latent Topic Analysis of the Post Property for Sales to Predict a Selling Price of Second-Hand Condominiums

This research objective is to study the latent topics analysis in selling post of real estate of second-hand condominium by using Latent Dirichlet Allocation (LDA) and build a price prediction model of second-hand condominium using multiple linear regression and artificial neural networks by measuring and comparing the performance of the second hand condominium price prediction model with root mean square error (RMSE). This experiment included four variables are room size, number of bathroom, number of bedroom and latent topics from LDA. The result of LDA indicated that selling post of real estate can be separated into 4 topics, in which finding the factors that affect the price use the regression analysis method to get five variables are room size, number of bathroom, floors, topic 2 and topic 4. The RMSE based on the multiple linear regression analysis was 1.349, while the RMSE based on artificial neural network was 1.156. Thus, it can be concluded that the predictive model using the artificial neural networks is superior to multiple linear regression.

The resilience and realignment of house prices in the era of Covid-19*

PurposeThe study aims to analyze the effects of the Covid-19 pandemic on house prices.Design/methodology/approachThe authors start by discussing the possibility that house price indexes may not fully incorporate the effects of the pandemic as of yet. Against the background of the pandemic, the authors then analyze economic and behavioral effects affecting house prices. The authors also discuss how the linkages between tourism and house prices have been affected. The authors further present evidence of an emerging shift in preferences from urban locations to more peripheral ones.FindingsThe authors report variance in the evolution of house prices across countries at the onset of the pandemic, with locations depending heavily on tourism showing slower price appreciation while appreciation has firmed in other places. The authors argue that the resilience of house prices is not only because of the low-interest rate environment and government efforts to support firms and households, but also behavioral factors. In some locations, the price of condominiums has declined relative to the price of detached houses. This could indicate that wealthier households are seeking more space and larger units as a result of the crisis. There is also evidence of a downward pressure on rents, leading to increased price–rent ratios in the USA.Originality/valueBy considering both economic and behavioral factors, this paper provides for a better understanding of the resilience and realignment of house prices at the onset of the Covid-19 pandemic.

The Resilience and Realignment of House Prices in the Era of Covid-19

Purpose:The article analyzes the effects of the COVID-19 pandemic on house prices.Design/Methodology/Approach:We start by discussing the possibility that house price indexes may not fully incorporate the effects of the pandemic as of yet. Against the background of the pandemic, we then analyze economic and behavioral effects affecting house prices. We also discuss how the linkages between tourism and house prices have been affected. We further present evidence of an emerging shift in preferences from urban locations to more peripheral ones.Findings:We report variance in the evolution of house prices across countries at the onset of the pandemic, with locations depending heavily on tourism showing slower price appreciation while appreciation has firmed in other places. We argue that the resilience of house prices is due not only to the low interest rate environment and government efforts to support firms and households, but also behavioral factors. In some locations, the price of condominiums has declined relative to the price of detached houses. This could indicate that wealthier households are seeking more space and larger units as a result of the crisis. There is also evidence of a downward pressure on rents, leading to increased price-rent ratios in the U.S.Originality/Value:By considering both economic and behavioral factors, this paper provides for a better understanding of the resilience and realignment of house prices at the onset of the COVID-19 pandemic.

Developing Land and Structure Price Indices for Ottawa Condominium Apartments

AbstractMeasuring the service flow and the stock value of condominium apartments in Canada and decomposing these values into constant quality price and quantity components is important for many purposes. In addition, the System of National Accounts requires that these service flows and stock values for condos be decomposed into constant quality land and structure components. In Canada and most other countries, such a land and structure decomposition of condominium apartment sale prices does not currently exist. In this article, we provide such a decomposition of condominium apartment sales in Ottawa for the period 1996–2009. Specific attention is paid to the roles of communal land and structure space on condominium apartment unit selling prices. Key findings include methods to allocate land and building space to a single condominium unit, identifying the characteristics that best explain condominium prices, and developing an average depreciation rate for condos for the 14-year time period.

Impacts of shopping malls on apartment prices: the case of Stockholm

Shopping malls, as an important type of commercial facilities, are growing dramatically. They have gradually become one of the most dominant factors that can influence people's daily life as well as a city's economic development. People's willingness to pay for dwellings is also primarily associated with the surrounding commercial layout. Hence, it is of interest to find out more from a quantitative perspective on the relationship between shopping malls and housing prices. This study aims to analyze how the prices of condominiums will be affected by the proximity of shopping malls. Two aspects are considered and examined in the empirical study, namely a proximity to the shopping mall, and the number of shopping malls within 3 kilometers radius. We try to examine if there is any price premium for those apartments near the shopping mall or with more shopping malls in the neighborhood. In this empirical study, 36 shopping malls in different locations in the county of Stockholm, Sweden, is utilized. The sample of transactions consists of 336,914 apartments. By using regression analysis, based on the traditional hedonic model, the results show that there is an inverse relationship between the apartment prices and its distance from the shopping mall while the number of shopping malls is positively correlated with apartment prices. However, the impact has declined over time.

Persistence and Long Memory Behavior in Condominium Prices: Evidence from Major U.S. Metropolitan Areas

This study examines the degree of persistence in the prices, returns, excess returns, and risk-adjusted excess returns in the condominium market for five U.S. metropolitan areas: Boston, Chicago, Los Angeles, New York, and San Francisco, using fractional integration techniques that account for structural breaks and nonlinearity. The results show that the prices, returns, excess returns, and risk-adjusted returns for condominiums across the five metropolitan areas are highly persistent, with orders of integration much greater than one in a vast majority of the cases. Such results challenge the conventional view of market efficiency. The degrees of persistence in West Coast metropolitan areas of Los Angeles and San Francisco are much greater than those of Chicago and the East Coast metropolitan areas of Boston and New York City.

재건축기대에 따른 건축연령효과의 동태적 변화

일반적으로 아파트는 시간이 흐를수록 노후화로 인해 가격이 하락하는 경향이 나타난다. 그러나 여전히 수요가 높은 서울의 강남지역과 같은 경우 일정시간이 지나면 재건축에 대한 기대로 인해 다시 가격이 상승하는 현상이 발생한다. 이와 관련하여 본 연구는 건축연령이 증가할수록 아파트 가격은 하락하다가 재건축 기대효과에 의해 몇 년을 기점으로 반등하는지를 시계열적으로 최저가격 도달 기간을 파악하고자 한다. 이를 위해 한강이남 11개구를 대상으로 주택, 입지, 재건축 관련 특성변수와 아파트 가격의 상관관계를 분석하였다. 추정결과는 예상대로 준공 후 건축연령이 증가하면서 아파트 가격은 점차 하락하다가 다시 상승한다는 것을 검증하였다. 주택이 오래될수록, 즉 건축연령이 오래된 주택일수록, 주거서비스의 질은 낮아지고 가격도 그에 따라 감소되어야하지만 재건축시점이 가까워짐에 따라 재건축 이후 취득될 수 있는 주택 취득에 대한 불확실성이 감소함으로 가격은 오히려 상승함을 알 수 있다. 또한 재건축 기준 연한이 30년으로 완화되었음에도 불구하고 시장에선 변곡점이 빨라지지 않고 있었다. 그 이유는 현 서울시 주택시장의 정비사업 해제, 분양가상한제, 정비사업 규제 등으로 인해 정비사업의 추진 가능성이 낮아지고 있는 현상을 반영하고 있다고 판단된다.

Economic impacts of being close to subway networks: A case study of Korean metropolitan areas

Subway networks are often developed in densely populated metropolitan areas that have enough potential passengers to merit their operation. Once a network has been constructed, it provides mobility to passengers and improves local accessibility to various destinations, thereby having economic, social, and public health impacts. This study aims to examine the economic impacts of subway networks in metropolitan areas among the various, wide-ranging effects of provision of transit networks. The association between actual transaction prices of condominiums and accessibility to subway networks in four metropolitan areas in South Korea is examined. Condominiums make up the dominant housing type in South Korea, so they provide a valid proxy for housing prices. In the modeling process, factors known to have a close relationship with housing prices are integrated along with the accessibility of subway networks, and spatially lagged models are utilized to effectively deal with the spatial patterns. The results of this research show that the expected positive effects of transit accessibility exist in the majority of cases in metropolitan areas, though one metropolis was an exception. These findings enhance our understanding of the economic impacts of public transit systems in relatively small metropolitan areas with less complex subway systems.

Condominium price dynamics in Sri Lanka: correlation with inflation and periods of concern

ABSTRACT This study conducted in Sri Lanka’s commercial capital – Colombo, investigated temporal variation of condominium prices from 1998 to 2018, to identify price – inflation relationships and periods of concern. The price increased non-linearly with time without abnormal trends. Unit root, cointegration and vector error correction method tests showed inflation can explain temporal variation of semi-luxury condominium’s price appreciation, and it showed a statistically significant (P < 0.01) positive impact in the long run. Price appreciation and inflation showed a weak negative, yet statistically significant impact for luxury condominiums. The impact of inflation on price appreciation in the short run was mostly a negative correlation and as per explanatory powers the impact was minor. It seemed that Sri Lankan condominium market would mostly be without any periods of concern considering the increasing presales and the decreasing price to rental ratios. However, there is a continuous increment of the ratio between the price and household annual income, and it was about 5.25 as at 2018 (price bubbles occurred when this ratio is over six). More studies are recommended specially on future periods of concern and studies that incorporate ultra-luxury apartments being developed by international developers.

Can government stabilize the housing market? The evidence from South Korea

This study aims to examine the effectiveness of government policies in stabilizing the housing market in South Korea. Analysis of condominium prices between 2012 and 2019 in conjunction with housing policy and regime changes reveals that: (1) housing policies effectively restrained the rapid increase of housing prices; (2) market efficiency was also improved; and (3) finally, housing prices approached close to long-run equilibrium. Our findings strongly indicate that government policies can be effective tools to stabilize housing prices, as well as improve market conditions.

Convergence in condominium prices of major US metropolitan areas

PurposeThe purpose of the study is to examine the long-run convergence properties of condominium prices based on the ripple effect for five major US metropolitan areas (Boston, Chicago, Los Angeles, New York and San Francisco). Specifically, we test for both overall convergence in condominium prices and the possibility of distinct convergence clubs to ascertain the interdependence of geographically dispersed metropolitan condominium markets.Design/methodology/approachOur analysis uses two approaches to identify the convergence properties of condominium prices: the Lee and Strazicich (2003) unit root test with endogenous structural breaks and the Phillips and Sul (2007, 2009) time-varying nonlinear club convergence tests.FindingsThe Lee and Strazicich (2003) unit root tests identify two structural breaks in 2006 and 2008 with the rejection of the null hypothesis of a unit root and long-run convergence in condominium prices in the cases of Boston and New York. The Phillips and Sul (2007, 2009) club convergence test reveals the absence of overall convergence in condominium prices across all metropolitan areas, but the emergence of two distinct convergence clubs with clear geographical segmentation: on the east coast with Boston and New York and the west coast with Los Angeles and San Francisco while Chicago exhibits a non-converging path.Research limitations/implicationsThe results highlight the distinct geographical segmentation of metropolitan condominium markets, which provides useful information to local policymakers, financial institutions, real estate developers and real estate portfolio managers. The limitations of the research are the identification of the underlying sources for the convergence clubs identified due to the availability of monthly data for a number of potential variables.Practical implicationsThe absence of overall convergence in condominium prices, but the emergence of distinct convergence clubs that reflects the geographical segmentation of metropolitan condominium markets raises the potential for portfolio diversification.Originality/valueUnlike previous studies that have focused on single-family housing, this is the first study to examine the convergence of metropolitan area condominium prices.

Do the rich and poor colocate in large cities?

This paper focuses on colocation rather than segregation in the context of Japanese large cities. Using the time cost of commuting from traditional urban economic theory, we analyze how different income households are sorted according to the distance from the city center. By examining microdata on housing prices and rents in Tokyo metropolitan area, we find that the rich and poor tend to colocate and are sorted by income near the city center for detached-housing prices. This is predicted if the income differential is large enough. We also find that different income groups coexist in the same location for condominium prices. This is predicted if the income elasticity of demand for space is close to one and the pecuniary cost of commuting is zero.