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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…

1423

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

Book part
Publication date: 8 April 2024

Daniel Pakši and Aleš Melecký

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three…

Abstract

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three distinct periods of excessive growth of regional Czech housing prices, identified through the formation of large positive GAPs – (1) before the entrance of Czechia to the European Union (EU), (2) at the onset of the Global Financial Crisis GFC, (3) in 2021. In all these periods, we identify significant differences among regions. We find that GAPs above 15% may be considered an indication of unsustainable long-term housing price growth that will be followed by a correction.

We then employ fixed effect panel data model to determine the drivers of flat and house prices in 14 Czech regions. Our results show that wage growth, migration and crime rate are significant factors affecting the prices of both flats and houses. Nevertheless, the impact of GDP per capita and job market indicators differs between flats and houses. Moreover, we find that higher migration into the region increases the difference between the prices of houses and flats, while increasing GDP per capita growth and crime rate mitigate this difference significantly.

Details

Modeling Economic Growth in Contemporary Czechia
Type: Book
ISBN: 978-1-83753-841-6

Keywords

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.

1537

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

Article
Publication date: 31 May 2011

Eric J. Levin, Alberto Montagnoli and Gwilym Pryce

Downward movements in house prices can exacerbate bank crises if mark‐to‐market methods of asset valuation are used by lenders to assess their current balance sheet exposure…

Abstract

Purpose

Downward movements in house prices can exacerbate bank crises if mark‐to‐market methods of asset valuation are used by lenders to assess their current balance sheet exposure. There is an imperative to find methods of house price index calculation that reflect equilibrium prices rather than temporary undershoots. The purpose of this paper is to propose a new methodology in order to evaluate whether market house prices are different from their fundamental asset prices.

Design/methodology/approach

This paper proposes a method for house asset valuation that incorporates expected house price appreciation as an endogenous variable. This avoids the necessity to make conjectures about expected future house price appreciation when applying Poterba's user‐cost method of house asset valuation. The methodological extension to Poterba's user‐cost method of house asset valuation endogenises expected house price appreciation as the no‐arbitrage expected price appreciation consistent with the term structure of real interest rates. A benchmark equilibrium house valuation can be calculated because the term structure of real forward interest rates is observable in financial markets. This enables market house prices to be compared with the benchmark equilibrium valuation in order to determine if house prices are overvalued or undervalued.

Findings

The paper presents the results of a worked example to illustrate how this approach could be applied in practice.

Research limitations/implications

There are a number of issues associated with the measurement of user cost which we do not address here and which the authors hope will provide fruitful avenues for future research. There are also issues regarding the impact of tax frameworks on the returns to housing, particularly the taxation of mortgage interest and imputed income. More work also needs to be done in comparing the performance of the extended Poterba model against alternative approaches, such as those that use expected inflation and/or long‐run average house price appreciation, or the real interest rate spread to proxy for expected capital appreciation, and how these different approaches compare in different institutional and socio‐economic contexts.

Practical implications

The authors' results underscore the rationale for mortgage banks to use marking to model instead of marking to market, and this in turn should reduce unnecessary macroeconomic instability when the market prices of houses undershoot fundamental value.

Originality/value

The paper shows how the term structure of real forward interest rates, observable in financial markets, can be used to extend the Poterba model.

Details

International Journal of Housing Markets and Analysis, vol. 4 no. 2
Type: Research Article
ISSN: 1753-8270

Keywords

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.

1415

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

Article
Publication date: 9 April 2024

Amanda Dian Widyasti Kusumawardani and Muhammad Halley Yudhistira

The purpose of this study is to examine the effects of the Odd-Even Road Rationing Policy (RRP) on housing prices in Jakarta, Indonesia. It aims to evaluate the net effect of the…

Abstract

Purpose

The purpose of this study is to examine the effects of the Odd-Even Road Rationing Policy (RRP) on housing prices in Jakarta, Indonesia. It aims to evaluate the net effect of the RRP on housing prices.

Design/methodology/approach

The study uses the monocentric model and employs the difference-in-differences (DD) method. Annual neighborhood-level housing price data is analyzed to assess the impact of the RRP on housing prices. Additionally, propensity score matching is used to address potential biases resulting from non-random policy assignments.

Findings

The results demonstrate that houses located within the RRP-restricted area experience a decrease in price that is relative to those in the control group. The findings indicate a decrease in housing prices ranging from 7.59% to 14.7% within the RRP-restricted area. This suggests that the positive impacts resulting from the RRP have not fully compensated for the restricted accessibility experienced by individuals who have limited behavioral changes. The study also confirms the significance of commuting costs in individuals' location decisions, aligning with predictions from urban economics models.

Originality/value

This study contributes to the literature by providing insights into the effects of a RRP on housing prices. It expands understanding beyond the immediate effects on traffic conditions and air pollution, which previous studies have primarily focused on. Furthermore, to the best of the authors’ knowledge, this research will be the first conducted to identify the impacts of RRP on housing prices in Indonesia.

Details

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

Keywords

Article
Publication date: 18 April 2024

Anton Salov

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

Abstract

Purpose

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

Design/methodology/approach

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Findings

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

Originality/value

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

Details

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

Keywords

Article
Publication date: 11 January 2024

Siti Hafsah Zulkarnain, Abdol Samad Nawi, Miguel Angel Esquivias and Anuar Husin

The purpose of this study is designed to achieve the learning process in producing studies involving economic issues and scenarios in business management in Malaysia. In addition…

Abstract

Purpose

The purpose of this study is designed to achieve the learning process in producing studies involving economic issues and scenarios in business management in Malaysia. In addition, this study will provide exposure to the integration of managerial skills by using both microeconomics and macroeconomics concepts and theories to aid decision-making in a business environment.

Design/methodology/approach

The research method comprised qualitative methodology of literature review, case study and quantitative methodology of multiple linear regression (MLR). In this case, seven microeconomics and macroeconomics factors which are believed to significantly affect house price index (HPI) are taken into consideration which includes gross domestic product, consumer price index (CPI), government tax and subsidy on housing, overnight policy rate, unemployment rate (UNEMP), the median income (INC) and cost of production index.

Findings

This research has resulted in three significant factors affecting HPI from MLR, which include CPI, UNEMP and INC where the increase of these factors will cause a high increment of HPI. The other four factors are not significant.

Originality/value

Malaysia has been facing the stagnancy in house market these recent years due to issues such as massive oversupply, impacting Malaysia’s economy specifically focusing on domestic direct investment. To avoid oversupply issues, the vitality of future house demand and pricing forecast should be comprehended by involved bodies for more effective planning for the house development industry. To make a better and bigger impact, this research is intended to analyse the microeconomic and macroeconomic factors affecting the HPI to better understand the significance of each of these factors to the changes of HPI to resolve these economic issues.

Details

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

Keywords

Abstract

Details

The Corporate, Real Estate, Household, Government and Non-Bank Financial Sectors Under Financial Stability
Type: Book
ISBN: 978-1-78756-837-2

Article
Publication date: 6 December 2023

Z. Göknur Büyükkara, İsmail Cem Özgüler and Ali Hepsen

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both…

Abstract

Purpose

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

Design/methodology/approach

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

Findings

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

Research limitations/implications

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

Practical implications

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

Social implications

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Originality/value

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

Details

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

Keywords

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