Search results

1 – 10 of over 50000
To view the access options for this content please click here
Article
Publication date: 1 June 2012

Hassan Gholipour Fereidouni

In recent years, housing prices and rents have recorded impressive growth in Iran. Several observers believe that real estate agents have had a significant effect on this…

Downloads
1208

Abstract

Purpose

In recent years, housing prices and rents have recorded impressive growth in Iran. Several observers believe that real estate agents have had a significant effect on this phenomenon. However, some do not agree with this viewpoint and argue that the role of real estate agents is not that much and housing prices and rents are affected by macroeconomic factors. The purpose of this paper is to investigate whether real estate agents can influence housing prices and rents across provinces of Iran.

Design/methodology/approach

Applying panel data technique, this paper uses observations from 28 provinces of Iran covering 2000 and 2003 to examine the role of real estate agents on housing prices and rents.

Findings

The empirical results indicate that the increased number of real estate agents and their activities positively significantly stimulate housing prices and rents.

Research limitations/implications

To the author's knowledge, most studies in this area cover the US and European real estate markets. Since findings for developed countries might not be directly transferable to emerging market economies such as Iran, more work is necessary to obtain a clearer picture of the role of real estate agents on housing prices and rents in emerging economies.

Originality/value

Although there has been a series of cross‐sectional studies published in this area, few empirical works have examined the effects of real estate agents on housing prices and rents by applying panel data set. The paper begins to fill this gap by analyzing a data sample of 28 provinces of Iran covering 2000 and 2003.

Details

International Journal of Housing Markets and Analysis, vol. 5 no. 2
Type: Research Article
ISSN: 1753-8270

Keywords

To view the access options for this content please click here
Article
Publication date: 1 August 2006

Ming‐Long Lee and R. Kelley Pace

The purpose of this paper is to provide additional evidence that housing prices significantly impact aggregate refinancing and thus directly influence mortgage termination.

Downloads
1460

Abstract

Purpose

The purpose of this paper is to provide additional evidence that housing prices significantly impact aggregate refinancing and thus directly influence mortgage termination.

Design/methodology/approach

Regression analysis is applied to examine refinancing activity in US cities.

Findings

The evidence shows that positive appreciation in housing prices provides the borrower with positive incentives to refinance in response to the associated increased borrowing capacity when mortgage rates have declined. On the other hand, depreciation in housing prices may depress refinancing.

Research limitations/implications

Housing price movements, not only collateral constraints on refinancing but also the disincentive to engage in cash‐out refinancing caused by depreciation as well as the incentive for cash‐out refinancing brought by appreciation, should be included in modeling total termination risks of mortgage‐backed securities.

Originality/value

In contrast to previous studies, this paper provides empirical support for both the incentive and the disincentive to engage in cash‐out refinancing produced by housing price changes, in addition to support for the traditional collateral constraint effect of housing prices on refinancing.

Details

Property Management, vol. 24 no. 4
Type: Research Article
ISSN: 0263-7472

Keywords

To view the access options for this content please click here
Article
Publication date: 29 May 2009

Onur Özsoy and Hasan Şahin

The purpose of this paper is to analyze empirically major factors that affect housing prices in Istanbul, Turkey using the classification and regression tree (CART) approach.

Downloads
1201

Abstract

Purpose

The purpose of this paper is to analyze empirically major factors that affect housing prices in Istanbul, Turkey using the classification and regression tree (CART) approach.

Design/methodology/approach

The data set was collected from various internet pages of real estate agencies during June 2007. The CART approach was then applied to derive main results and to make implications with regard to the housing market in Istanbul, Turkey.

Findings

The CART results indicate that sizes, elavators, existance of security, existance of central heating units and existance of view are the most important variables crucially affecting housing prices in Istanbul. The average price of houses in Istanbul was found to be 373,372.36 New Turkish Liras. The average size of a house was 138.37 m2. The average age of houses is 15.07 years old with the average number of rooms being 3.11. The average number of baths is 1.43 and average number of toilets is 1.22. Only 5 percent of homes have storage space, 45 percent of homes have parking space, 64 percent of homes are heated with furnace, whereas only 29 percent of homes are used central heating system. Among the 31 variables employed in this study, it was concluded size, elavator, security, central heating unit and view are the most important factors that have impact on housing prices in housing market in Istanbul.

Practical implications

Future research and analysis of housing market in Istanbul and in Turkey can benefit from the method used in this study and findings derived from this research to come up with more general model(s) to include more houses in a wide range of regions in Turkey to analyze the determinants of housing prices in Turkey in general.

Originality/value

Examining housing prices using the CART model is relatively new in the field of housing economics. Additionally, this study is the first to use the CART model to analyze housing market in Istanbul and in Turkey and derive valuable housing policies to be used by the authorities.

Details

International Journal of Housing Markets and Analysis, vol. 2 no. 2
Type: Research Article
ISSN: 1753-8270

Keywords

Content available
Article
Publication date: 8 October 2021

Xiuzhi Zhang, Zhijie Lin and Junghyun Maeng

The sharing economy has enjoyed rapid growth in recent years, and entered many traditional industries such as accommodation, transportation and lending. Although…

Abstract

Purpose

The sharing economy has enjoyed rapid growth in recent years, and entered many traditional industries such as accommodation, transportation and lending. Although researchers in information systems and marketing have attempted to examine the impacts of the sharing economy on traditional businesses, they have not yet studied the rental housing market. Thus, this research aims to investigate the impact of the sharing economy (i.e. home-sharing) on traditional businesses (i.e. rental housing market).

Design/methodology/approach

The authors assemble rich data from multiple sources about the entry of a leading Chinese home-sharing platform (i.e. Xiaozhu.com) and local housing rental price index. Then, econometric models (i.e. linear panel-level data models) are employed for empirical investigation. Instrumental variables are used to account for potential endogeneity issues. Various robustness checks are adopted to establish the consistency of the findings.

Findings

Overall, the estimation results show that the entry of a home-sharing platform will decrease the local housing rental price. Moreover, this impact would be strengthened in a more developed city. Additionally, this impact would be strengthened with higher prices of new houses or second-hand houses.

Originality/value

First, this research is one of the first to study the impact of the sharing economy (i.e. home-sharing) on traditional markets (i.e. housing rentals). Second, it contributes to the relevant literature by documenting that the impact of a platform's entry is not uniform but contingent on city and housing market characteristics. Third, practically, the findings also offer important implications for platform operators and policy makers.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

Keywords

To view the access options for this content please click here
Article
Publication date: 16 August 2021

Le-Vinh-Lam Doan and Adipandang Yudono

This paper aims to bring together research on housing market area, submarket and household migration into a systems approach that helps us gain a better understanding of…

Abstract

Purpose

This paper aims to bring together research on housing market area, submarket and household migration into a systems approach that helps us gain a better understanding of the structure and dynamics of a housing market and identify housing problems for a large metropolitan area.

Design/methodology/approach

The paper uses a geographic information system (GIS)-based method with simple quantitative techniques, including spatial analysis, location analysis, house price clustering and cross-tabulation. The analysis is based on migration data from the 2011 Census, house price data from the Land Registry in 2011 for Greater Manchester at the ward level and the output areas level.

Findings

The results show that different submarkets and housing market areas had different patterns of spatial migration and connections with other areas. Through a systematic analysis of migration and house price in combination, it also found a close connection between destination submarkets and the ages of migrants and identified specific problematic patterns for a large metropolitan area.

Research limitations/implications

The interactions between the owner-occupied sector and the social and private rented sectors are arguably an important omission from the analysis. Also, it is acknowledged that clustering ward units based on price differentials is subject to distortions in terms of specification, size and shape. Moreover, the use of the large samples may result in very small p-values, leading to the problem of the rejection of the predefined hypothesis.

Practical implications

A systematic analysis of migration and house price in combination may be used to gain a better understanding of the housing market dynamics and identify housing problems systematically for a large metropolitan. It may help to identify low-demand areas, high-demand areas and assist planners with decisions in allocating suitable land for new housing constructions.

Social implications

The GIS-based method introduced in the paper could be considered as an effective approach to provide a better basis for determining policy interventions and public investment designed to allocate land resources effectively and improve transport systems to change existing problematic migration patterns.

Originality/value

This paper fills a gap in the international literature in relation to adopting a systems approach that analyses migration and house price data sets in combination to systematically explore migration patterns and linkages and identify housing problems for a large metropolitan area. This systems approach can be applied in any metropolitan area where migration and house price data are available.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

Content available
Article
Publication date: 16 August 2021

Mats Wilhelmsson, Mohammad Ismail and Abukar Warsame

This study aims to measure the occurrence of gentrification and to relate gentrification with housing values.

Abstract

Purpose

This study aims to measure the occurrence of gentrification and to relate gentrification with housing values.

Design/methodology/approach

The authors have used Getis-Ord statistics to identify and quantify gentrification in different residential areas in a case study of Stockholm, Sweden. Gentrification will be measured in two dimensions, namely, income and population. In step two, this measure is included in a traditional hedonic pricing model where the intention is to explain future housing prices.

Findings

The results indicate that the parameter estimate is statistically significant, suggesting that gentrification contributes to higher housing values in gentrified areas and near gentrified neighbourhoods. This latter possible spillover effect of house prices due to gentrification by income and population was similar in both the hedonic price and treatment effect models. According to the hedonic price model, proximity to the gentrified area increases housing value by around 6%–8%. The spillover effect on price distribution seems to be consistent and stable in gentrified areas.

Originality/value

A few studies estimate the effect of gentrification on property values. Those studies focussed on analysing the impacts of gentrification in higher rents and increasing house prices within the gentrifying areas, not gentrification on property prices in neighbouring areas. Hence, one of the paper’s contributions is to bridge the gap in previous studies by measuring gentrification’s impact on neighbouring housing prices.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

To view the access options for this content please click here
Article
Publication date: 7 August 2021

Philip Inyeob Ji and Seema Bogati Bhandari

The aim of this paper is to examine dynamic linkages between price and rent and between property types. Intuition suggests that housing market segments experience…

Abstract

Purpose

The aim of this paper is to examine dynamic linkages between price and rent and between property types. Intuition suggests that housing market segments experience different market cycles in response to macroeconomic shocks. However, they may be dynamically interlinked in urban areas because of substitutability. The linkage may even change, if preference weakens for multiple occupancies. A sudden reduction in apartment demand may create repercussions to other housing segments. Past analyses, despite their contributions, are static and do not consider possible linkages between property types. To fill this void, this paper investigates the price-rent dynamics for urban homes by adopting the case of Singapore.

Design/methodology/approach

This paper applies a methodology from Phillips et al. (2015) to Singaporean housing (price and rent) data. Phillips et al. (2015) recently proposed a test for an explosive root in time series data and has spurred several empirical applications in the bubble literature.

Findings

This paper finds for Singapore that the markets were subjected to explosive growth (where rents grew at a higher rate than prices did) during the Global Financial Crisis. Also, the results suggest that rent drives price and that non-landed housing (offices in central areas) leads to other residential housing (non-residential housing) in both price and rent.

Practical implications

Overall, the present findings suggest that rent drives price, while property types are interlinked. Non-landed homes and offices in central areas are the sources of repercussions. Under normal circumstances, rental shocks may be propagated positively from nonlanded housing (central offices) to the other residential (non-residential) property types as the present findings suggest, which enables us to infer that a decrease in non-landed housing (central offices) rent may lead to an increase in rent on other property types because pandemic shocks only shift demand fromone property type to another, unlike typical macroeconomic shocks.

Originality/value

Urban homes are faced with uncertainty arising from the COVID-19 outbreak for which city residents have a stronger incentive to exile to suburbs. Urban life may no longer be attractive because of social distancing and work from home policy. This has implications for urban home demands that are closely linked to urban house price and rent. In the present study, the paper set out to investigate the price-rent and property-type dynamics for urban homes in Singapore.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

To view the access options for this content please click here
Article
Publication date: 14 August 2021

Pham Phuong Nam and Tran Trong Phuong

The study aims to identify the affecting factors and their impact rates on the commercial housing prices. The study also aims to suggest implications related to commercial…

Abstract

Purpose

The study aims to identify the affecting factors and their impact rates on the commercial housing prices. The study also aims to suggest implications related to commercial housing prices to develop the commercial housing market.

Design/methodology/approach

The study investigates housing investors, real estate agents and buyers to identify factors that might affect commercial housing prices. The proposed research model has 7 latent factors and is tested by Cronbach' alpha and exploratory factor analysis by SPSS20.0 software.

Findings

There are 7 groups with 24 factors affecting commercial housing prices. The neighboring factor group has the greatest impact rate (18.54%); the housing service group has the lowest impact rate (11.48%).

Research limitations/implications

The study has only determined the affecting factors and their impact rates on commercial housing prices in Bac Ninh city. Therefore, it is necessary to conduct research on factors affecting commercial housing prices in other provinces and cities of Vietnam in the coming time. In addition, the proposed research method can also be consulted when it is necessary to determine the factors affecting commercial housing prices in other countries around the world.

Practical implications

The study proposes some implications related to commercial housing prices such as commercial housing valuation; housing selection with suitable prices for people intending to buy houses; state support policies for commercial housing investors to develop commercial housing with reasonable prices.

Social implications

The implementing the implications proposed in the study will facilitate people's easier access to commercial housing; real estate investors do business more efficiently.

Originality/value

To the best of the authors’ knowledge, this paper presents for the first time a method to determine the affecting factors and their impact rates on commercial housing prices in Vietnam. The paper also points out a number of specific factors affecting commercial housing prices that are different from those shown in previous studies.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

To view the access options for this content please click here
Article
Publication date: 6 August 2021

Zhijiang Wu, Yongxiang Wang and Wei Liu

Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed…

Abstract

Purpose

Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces.

Design/methodology/approach

This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang.

Findings

This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price.

Research limitations/implications

The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang.

Originality/value

This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

To view the access options for this content please click here
Article
Publication date: 9 September 2021

Narvada Gopy-Ramdhany and Boopen Seetanah

This study aims to investigate the effect of immigration on housing prices in Australia both at the national and regional levels.

Downloads
29

Abstract

Purpose

This study aims to investigate the effect of immigration on housing prices in Australia both at the national and regional levels.

Design/methodology/approach

Data for eight Australian states on a quarterly basis from 2004–2017 is used. To study the possible dynamic and endogenous relationship between housing prices and immigration, a panel vector autoregressive error correction model (PVECM) is adopted.

Findings

Analysis of the results indicates that in the short run immigration positively and significantly affects housing prices, whereas in the long run no significant relationship was observed between the two variables. From the regional breakdown and analysis, it is discerned that in some states there is a significant and positive effect of immigration on residential real estate prices in the long run. Causality analysis confirms that the direction of causation is from immigration to housing prices.

Practical implications

The study illustrates that immigration and interstate migration, as well as high salaries, have been causing a rise in housing demand and subsequently housing prices. To monitor exceedingly high housing prices, local authorities should be controlling migration and salary levels.

Originality/value

Past research studies had highlighted the importance of native interstate migration in explaining the nexus between immigration – housing prices. In this study, it has been empirically verified how immigration has been affecting the locational decisions of natives and subsequently how this has been affecting housing prices.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

1 – 10 of over 50000