Examining the spatial and non-spatial linkages between suburban housing markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Morteza Moallemi ◽  
Daniel Melser ◽  
Ashton de Silva ◽  
Xiaoyan Chen
Keyword(s):  
House Prices ◽  
Housing Prices ◽  
Housing Markets ◽  
Geographic Proximity ◽  
Content Type ◽  
Spatial Weights ◽  
Spatial Weights Matrix ◽  
Sar Model ◽  
Spatial Linkages ◽  
The City

Purpose The purpose of this paper is on developing and implementing a model which provides a fuller and more comprehensive reflection of the interaction of house prices at the suburb level. Design/methodology/approach The authors examine how changes in housing prices evolve across space within the suburban context. In doing so, the authors developed a model which allows for suburbs to be connected both because of their geographic proximity but also by non-spatial factors, such as similarities in socioeconomic or demographic characteristics. This approach is applied to modelling home price dynamics in Melbourne, Australia, from 2007 to 2018. Findings The authors found that including both spatial and non-spatial linkages between suburbs provides a better representation of the data. It also provides new insights into the way spatial shocks are transmitted around the city and how suburban housing markets are clustered. Originality/value The authors have generalized the widely used SAR model and advocated building a spatial weights matrix that allows for both geographic and socioeconomic linkages between suburbs within the HOSAR framework. As the authors outlined, such a model can be easily estimated using maximum likelihood. The benefits of such a model are that it yields an improved fit to the data and more accurate spatial spill-over estimates.

Dynamic effects and spatial heterogeneity of land supply on housing price: evidence from Nanchang, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhijiang Wu ◽  
Yongxiang Wang ◽  
Wei Liu
Keyword(s):  
Spatial Heterogeneity ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Dynamic Effects ◽  
Negative Effects ◽  
Land Supply ◽  
Content Type ◽  
Major Factors ◽  
The City

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.

scholarly journals A dynamic model for housing price spillovers with an evidence from the US and the UK markets

2018 ◽  
Vol 2 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Alper Ozun ◽  
Hasan Murat Ertugrul ◽  
Yener Coskun
Keyword(s):  
New York ◽  
Real Estate ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Housing Markets ◽  
Content Type ◽  
Real Estate Markets ◽  
Country Level ◽  
The Us

Purpose The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies. Design/methodology/approach The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method. Findings The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach. Research limitations/implications One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets. Practical implications The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City. Social implications The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice. Originality/value The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.

Housing markets’ linkage between China and Taiwan

2019 ◽  
Vol 12 (5) ◽  
pp. 826-848 ◽  
Author(s):  
Mei-Se Chien ◽  
Neng-Huei Lee ◽  
Chih-Yang Cheng
Keyword(s):  
Economic Integration ◽  
House Prices ◽  
Housing Prices ◽  
Housing Markets ◽  
Wealth Effects ◽  
Time Varying ◽  
Consumer Expenditure ◽  
Content Type ◽  
Cross Border ◽  
Cointegration Tests

Purpose This paper aims to examine the linkage of regional housing markets between Taiwan and China as increasing economic integration. Design/methodology/approach Two time-varying estimations of cointegration tests, Gregory and Hansen (1996) cointegration test with structural break and the recursive coefficients of cointegration (Hansen and Johansen, 1993) are applied to trace the possible dynamic linkage of cross-border regional housing prices between Taiwan and China. Findings First, the estimating results of the long-run relationships show that increasing housing prices in Beijing and Shanghai decrease Taipei’s house prices, while Shenzhen and Chengdu have converse effects. The technologies’ levels of Taiwanese industries surrounding the cities in China will affect the direction of the linkage of regional housing prices between the two economies. Second, in light of causalities of these five housing prices’ changes, Beijing and Shanghai lead Taipei and Shanghai leads Chengdu, which, in turn, leads Shenzhen. Finally, the results of time-varying cointegration tests show that some critical economic and political incidents changed the linkages of housing prices between Taipei and the four cities in China. Originality/value Although some empirical works examined the linkages between cross-border house prices in Europe and the USA, study has looked at the linkages of cross-border housing prices between Taiwan and China. This is an interesting topic insofar as house price integration has implications for wealth effects that feed into consumer expenditure in both Taiwan and China. The empirical evidence overall displays the existence of the integration of regional housing markets between Taiwan and China. For the longer-term future, increasing economic integration between China and other Asia countries will result in greater and more diversified cross-border housing markets and pools of investors.

The effect of school performance on property values: a literature review and a case study

2017 ◽  
Vol 10 (3) ◽  
pp. 277-302 ◽  
Author(s):  
Larisa Fleishman ◽  
Nir Fogel ◽  
Israela Fridman ◽  
Yaffa Shif
Keyword(s):  
School Performance ◽  
House Prices ◽  
Housing Prices ◽  
Property Values ◽  
Housing Price ◽  
Housing Markets ◽  
Socioeconomic Background ◽  
Content Type ◽  
State Education ◽  
Student Achievements

Purpose This paper, a pioneering one in the Israeli context, aims to augment the research literature on school quality and housing prices by examining the effect of primary-school performance on local property values. It focuses on the main question whether the release of students’ test scores offered households a new source of information with which they could evaluate the quality of schools, thereby affecting local housing markets. Design/methodology/approach Several models that examine a variety of transactions, schools and locality characteristics that affect house prices are estimated. Using different administrative sources of information, a wide array of socioeconomic characteristics of students, parents and homebuyers, as well as locality features, is constructed and merged. This information, combined with students’ scores on Meitzav exams (standardized student achievement tests) in 2009-2012 and house prices, illuminates the relationship between student achievements and the prices of houses purchased within the defined attendance zones. Findings Student achievements, mainly in the state education system, are found to have a positive and statistically significant effect on housing prices. Accurate information published about a certain school that showed much stronger achievements than those yielded by information attainable about the same school before school-level publication, does contribute to boost house prices in the post-publication period. The socioeconomic background of the students’ parents was found to have a significant effect on house prices. The premium for housing value is much higher in the most prestigious, prime demand districts, in which the housing supply is limited and the housing price level is higher than in that the peripheral districts. Originality/value This study not only breaks new ground in the Israeli context but also contributes to the existing literature, by investigating the relation between publishing students’ scores and property values near the same schools, on a national scale. Given that the housing price dynamics and the spatial differentiation of housing stock are extremely hot issues in many European cities, the results of this study could serve as an important tool for better understanding the housing price responses to market incentives, resulting in specific patterns in local housing markets. This paper could be thus applicable in housing policy outline, urban design and planning.

scholarly journals Liquidity, interest rates and house prices in the euro area: a DSGE analysis

2016 ◽  
Vol 9 (1) ◽  
pp. 4-25 ◽  
Author(s):  
Margarita Rubio ◽  
José A. Carrasco-Gallego
Keyword(s):  
Interest Rates ◽  
Monetary Union ◽  
Euro Area ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Dsge Model ◽  
Content Type ◽  
The Core ◽  
Dynamic Stochastic

Purpose This study aims to build a two-country monetary union dynamic stochastic general equilibrium (DSGE) model with housing to assess how different shocks contributed to the increase in housing prices and credit in the European Economic and Monetary Union. One of the countries is calibrated to represent the core group in the euro area, while the other one corresponds to the periphery. Design/methodology/approach In this paper, the authors explore how a liquidity shock (or a decrease in the interest rate) affects house prices and the real economy through the asset price and the collateral channel. Then, they analyze how a house price shock in the periphery and a technology shock in the core countries are transmitted to both economies. Findings The authors find that a combination of an increase in liquidity in the euro area coming from the common monetary policy, together with asymmetric house price and technology shocks, contributed to an increase in house prices in the euro area and a stronger credit growth in the peripheral economies. Originality/value This paper represents the theoretical counterpart to empirical studies that show, through macroeconometric models, the interrelation between liquidity and other shocks with house prices. Using a DSGE model with housing, the authors disentangle the mechanisms behind these empirical findings.

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.

Are regional house prices stationary in Iran? New evidence using Fourier quantile unit root test

2019 ◽  
Vol 12 (5) ◽  
pp. 849-864
Author(s):  
Arash Hadizadeh
Keyword(s):  
Interest Rates ◽  
Housing Market ◽  
Unit Root ◽  
House Prices ◽  
Housing Prices ◽  
Unit Root Test ◽  
Generalized Least Squares ◽  
Main Concern ◽  
Content Type ◽  
Positive Effects

Purpose In the Iranian economy, investing in the housing market has been very important and beneficial for investors and households, because of inflationary environment, low real interest rates, underdeveloped financial and tax systems and economic sanctions. Hence, prediction of house prices is the main concern of housing market agents in the economy. The purpose of this paper is to test the stationary properties of Iran's provinces to improve the prediction of future housing prices. Design/methodology/approach In this paper, the authors have tested the stationary properties of 20 Iran’s province centers over the period from 1993 to 2017 using a novel Fourier quantile unit root test and conventional ordinary/generalized least squares (O/GLS) linear unit root/stationary tests. Findings According to conventional O/GLS linear unit root/stationary tests, most of the house prices series exhibit random walk behavior, whereas by applying the Fourier quantile unit root test, the null hypothesis of unit root is rejected for 15 out of 20 series. Other results indicated that house prices of cities responded differently to positive and negative shocks. Originality/value Previous studies only addressed conventional OLS or GLS linear unit root or stationary tests, but novel Fourier quantile unit root test was not used. New results were obtained based on this unit root test, that, as a priori knowledge, will help benefiting from the positive effects, or avoiding being victimized by the negative effects.

Testing for bubbles in housing markets: some evidence for Brazil

2018 ◽  
Vol 11 (5) ◽  
pp. 754-770 ◽  
Author(s):  
Cássio da Nóbrega Besarria ◽  
Nelson Leitão Paes ◽  
Marcelo Eduardo Alves Silva
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Housing Prices ◽  
Market Price ◽  
Housing Markets ◽  
Cointegration Analysis ◽  
Small Samples ◽  
Content Type ◽  
Long Run ◽  
Cointegration Tests

Purpose Housing prices in Brazil have displayed an impressive growth in recent years, raising some concerns about the existence of a bubble in housing markets. In this paper, the authors implement an empirical methodology to identify whether or not there is a bubble in housing markets in Brazil. Design/methodology/approach Based on a theoretical model that establish that, in the absence of a bubble, a long-run equilibrium relationship should be observed between the market price of an asset and its dividends. The authors implement two methodologies. First, the authors assess whether there is a cointegration relationship between housing prices and housing rental prices. Second, the authors test whether the price-to-rent ratio is stationary. Findings The authors’ results show that there is evidence of a bubble in housing prices in Brazil. However, given the short span of the data, the authors perform a Monte Carlo simulation and show that the cointegration tests may be biased in small samples. Therefore, the authors should be caution when assessing the results. Research limitations/implications The results obtained from the cointegration analysis can be biased for small samples. Practical implications The information on the excessive increase of the prices of the properties in relation to their fundamental value can help in the decision-making on investment of the economic agents. Social implications These results corroborate the hypothesis that Brazil has an excessive appreciation in housing prices, and, as Silva and Besarria (2018) have suggested, this behavior explains, in part, the fact that the central bank has taken this issue into account when deciding about the stance of monetary policy of Brazil. Originality/value The originality is linked to the use of the Gregory-Hansen method of cointegration in the identification of bubbles and discussion of the limitations of the research through Monte Carlo simulation.

The effects of network hospitality on women empowerment

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sonia Ern Yi Lim ◽  
Frederic Bouchon
Keyword(s):  
Developing Economies ◽  
Housing Markets ◽  
Women Empowerment ◽  
Kuala Lumpur ◽  
Content Type ◽  
Cultural Expectations ◽  
The Social ◽  
Worldwide Network ◽  
The Impact ◽  
The City

Purpose This concept paper aims to discuss the effects of network hospitality on women empowerment in the city of Kuala Lumpur. Design/methodology/approach This paper uses a qualitative approach to analyse women engaged in Airbnb activity as hosts or guests. Findings Findings show new types of entrepreneurs, hospitality services, and socio-cultural expectations under this change. Originality/value The recent growth of Network Hospitality platforms such as Airbnb around the world has generated multiple impacts on urban destinations worldwide. Network hospitality is transforming the way tourism is produced and consumed. Several studies have analysed the impact of network hospitality on destinations’ accommodation and housing markets, the gentrification effects and users’ experience. However, studies on the social impacts of Airbnb in developing economies remain scarce. Network hospitality is creating entrepreneurship and mobility opportunities for women. In the case of Malaysia, there is a noticeable empowerment trend of women through network hospitality.

scholarly journals Untangling the nonlinear “knots” of UK’s housing prices

2019 ◽  
Vol 46 (5) ◽  
pp. 1083-1103
Author(s):  
Constantinos Alexiou ◽  
Sofoklis Vogiazas
Keyword(s):  
Housing Market ◽  
House Prices ◽  
Housing Prices ◽  
Positive Association ◽  
Research Area ◽  
Content Type ◽  
Nonlinear Ardl ◽  
Long Run ◽  
Short Run ◽  
The Uk

Purpose Housing prices in the UK offer an inspiring, yet a complex and under-explored research area. The purpose of this paper is to investigate the critical factors that affect UK’s housing prices. Design/methodology/approach The authors utilize the recently developed nonlinear ARDL approach of Shin et al. (2014) over the period 1969–2016. Findings The authors find that both the long-run and short-run impact of the price-to-rent (PTR) ratio and credit-to-GDP ratio on house prices (HP) is asymmetric whilst ambiguous results are established for mortgage rates, industrial production and equities. Apart from the novel framework of analysis, this study also establishes a positive association between HP and the PTR ratio which suggests a speculative behaviour and could imply the formation of a housing bubble. Originality/value It is the first study for the UK housing market that explores the underlying fundamental relationships by looking at nonlinearities hence, allowing HP to be tied by asymmetric relationships in the long as well as in the short run. Modelling the inherent nonlinearities enhances significantly the understanding of UK housing market which can prove useful for policymaking and forecasting purposes.

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