Terms Of Housing Price Research Articles

Is housing price distribution across cities, scale invariant? Fractal distribution of settlements' house prices as signature of self-organized complexity

Locations and sizes of settlements within regions often exhibit a self-organized central place pattern, where larger settlements are encircled by smaller ones, with the former more set apart. This hierarchical spatial pattern is displayed by the fractal signature of the power law typical of the rank-size distribution of settlements. Is a similar pattern also revealed in the housing prices across settlements? An empirical analysis on the almost 8000 Italian municipalities, whose residential population varies between 33 and ∼3 million, shows that, for 15 out of 20 regions, the upper tails rank-house price distribution of settlements is plausibly following a power law. This result discloses a universality in the function behaviour: a scale invariance. The average scaling parameters have been estimated via Maximum Likelihood Estimator and Kolmogorov–Smirnov statistics, and the goodness-of-fit assessed via bootstrapping. Ordinary Least Squares regressions have also been used for comparative purposes. In average, Maximum Likelihood Estimator found a scaling parameter of 4.4. Namely, doubling the rank of the settlement (in terms of housing price), its housing price decreases by 15 %: between the settlement with the highest average house prices (ranked 1), and the settlement with the second highest average house prices (ranked 2), there is a 15 % difference in the average house prices. Idem between the ranked 5 and 10, 10 and 20 … it does not matter; it is a universal behavioural pattern whose scale invariance suggests a self-organized complexity in the phenomena behind it.

Spatial analysis of housing prices in Tehran city

PurposeThe purpose of this study is to identify the situation of spatial inequality in the residential system of Tehran city in terms of housing prices in the year 2021 and to examine its changes over time (1991–2021).Design/methodology/approachIn terms of purpose, this study is applied research and has used a descriptive-analytical method. The statistical population of this research is the residential units in Tehran city 2021. The average per square meter of a residential unit in the level of city neighborhoods was entered in the geographical information system (GIS) in 2021. Moran’s spatial autocorrelation method, map cluster analysis (hot and cold spots) and Kriging interpolation have been used for spatial analysis of points. Then, the change in spatial inequality in the residential system of Tehran city has been studied and measured based on the price per square meter of a residential unit for 30 years in the 22 districts of Tehran by using statistical clustering based on distance with standard deviation.FindingsThe result of spatial autocorrelation analysis with a score of 0.873872 and a p-value equal to 0.000000 indicates a cluster distribution of housing prices throughout the city. The results of hot spots show that the highest concentration of hot spots (the highest price) is in the northern part of the city, and the highest concentration of cold spots (the lowest price) is in the southern part of Tehran city. Calculating the area and estimating the quantitative values of data-free points by the use of the Kriging interpolation method indicates that 9.95% of Tehran’s area has a price of less than US$800, 17.68% of it has a price of US$800 to US$1,200, 25.40% has the price of US$1,200 to US$1,600, 17.61% has the price of US$1,600 to US$2,000, 9.54% has the price of US$2,000 to US$2,200, 6.69% has the price of US$2,200 to US$2,600, 5.38% has the price of US$2,600 to US$2,800, 4.59% has the price of US$2,800 to US$3,200 and finally, the 3.16% has a price more than US$3,200. The highest price concentration (above US$3,200) is in five neighborhoods (Zafaranieh, Mahmoudieh, Tajrish, Bagh-Ferdows and Hesar Bou-Ali). The findings from the study of changes in housing prices in the period (1991–2021) indicate that the southern part of Tehran has grown slightly compared to the average range, and the western part of Tehran, which includes the 21st and 22nd regions with much more growth than the average price.Originality/valueThere is massive inequality in housing prices in different areas and neighborhoods of Tehran city in 2021. In the period under study, spatial inequality in the residential system of Tehran intensified. The considerable increase in housing prices in the housing market of Tehran has made this sector a commodity, intensifying the inequality between owners and non-owners. This increase in housing price inequality has caused an increase in the informal living for the population of the southern part. This population is experiencing a living situation that contrasts with the urban plans and policies.

A CONCEPTUAL FRAMEWORK FOR MINIMISING MIDDLE-INCOME HOUSING MISMATCH

The housing demand of the middle-income group cannot be ignored as they are the majority of the population in Malaysia which is about 40% out of the population. However, there is a mismatch between the supply and middle-income housing demand. The developer has always been eager to develop high-end products instead of affordable housing. This circumstance leads to the insufficient supply of middle-income housing. The mismatch is not only in terms of housing price, but also does not meet their housing preferences towards other housing attributes. Accordingly, this paper attempts to develop a conceptual framework for minimising middle-income housing mismatch. Thus, this paper reviewed the existing literature on the housing mismatch occurrences and the strategies to overcome this situation through government intervention. Almost all evidences from the studies indicate government, developer behaviour and buyer preferences have contributed to the middle-income housing mismatch occurrences. The findings were compiled through the creation of a conceptual model. Government intervention, developer behaviour and buyer preferences are included in the model as aspects that cause the housing mismatch occurrences. Significantly all these three aspects should interrelate with each other so that the potential of housing mismatch occurrences is low.

Online property brokerage platform and prices of second-hand houses: Evidence from Lianjia’s entry

Despite the popular emergence of online property brokerage platforms in the second-hand housing market, little is known about whether and how these platforms would influence the market, especially in terms of housing price. We thus assemble and analyze data from multiple sources about the entry of a representative Chinese platform (Lianjia.com) and local housing market for empirical validation. Our analysis found that platform entry may decrease the price of second-hand houses, and the impact would be weakened with the increase in new house price and total households. Moreover, platform entry eventually may boost the sales of second-hand houses. These notable findings offer several important contributions. First, our research is one of the first to explore the intricate impact of online property brokerage platforms on housing price. Second, our research is one of the few to study the impact of online intermediaries on the sales price of large consumer goods. Third, we further uncover some contingent factors and subsequent downstream outcome of this impact. Practically, our findings also offer important implications to practitioners and policy makers.

THE IMPLICATIONS OF GUARDED NEIGHBORHOOD ON HOUSING PRICES IN URBAN MALAYSIA

The research on gated communities has drawn considerable attention over the last three decades as researchers identify why certain social groups of people choose to live in a fortified neighborhood. Many scholars ranging from urban geographers, urban planning, anthropologist, urban economists, sociologists to urban politics have attempted to explore the reasons behind the proliferation of gated communities throughout the world. However, less research talked about the impacts of enclosure developments on housing prices, especially in developing countries like Malaysia. Therefore, this article will examine the various actors' perceptions of guarded neighborhoods' implications towards housing prices in urban Malaysia. This article found that various actors interviewed believe that guarded neighborhoods can improve the housing prices in Malaysia. This article contributes to the general understanding of Malaysia's guarded neighborhood and has multiple implications in terms of housing prices in enclosure developments.

Forecasting house prices in Iran using GMDH

Purpose An accurate predictive model for forecasting urban housing price in Isfahan can be useful for sellers and owners to take more appropriate actions about housing supplying. Also, it can help urban housing planners and policymakers in managing of the housing market and preventing an urban housing crisis in Isfahan. The purpose of this paper is forecasting housing price in Isfahan city of Iran until 2022 using group method of data handling (GMDH). Design/methodology/approach This paper presents an accurate predictive model by applying the GMDH algorithm by using GMDH-Shell software for forecasting housing price in municipal boroughs of Isfahan city till the second half of 2022 based on creating time series and existing data. Alongside housing price, some other affecting factors have been also considered to control the forecasting process and make it more accurate. Furthermore, this research shows the housing price changes of boroughs on map using ArcMap. Findings Based on forecasting results, the housing price will increase at all boroughs of Isfahan till second half of the year 2022. Amongst them, Borough 15 will have the highest percentage of the price increasing (28.27%) to year 2022 and Borough 6 will have the lowest percentage of the price increasing (8.34%) to the year 2022. About ranking of the boroughs in terms of housing price, Borough number 6 and 3 will keep their current position at the top and Borough number 15 will stay at the bottom. Research limitations/implications In this research, just few factors have been selected alongside housing price to control the forecasting process owing to limitation of reliable data availability about affecting factors. Originality/value The most remarkable point of this paper is reaching to a mathematical formula that can accurately forecast housing price in Isfahan city which has been rarely investigated in former studies, especially in simplified form. The technique used in this paper to forecast housing price in Isfahan city of Iran can be useful for other cities too.

HOUSING AFFORDABILITY IN THE STATE OF JOHOR

The Malaysian property market has been facing significant changes in terms of housing price since a decade ago and these changes are different between states. The changes in housing prices are being supported by the economic theories of demand and supply as well as the regional economic and demographic factors such as income level, housing supply stock, speculative buying and population changes. This paper provides an overview of the affordable housing policy and elaborates on the housing affordability index for the districts in the State of Johor. Using datasets for year 2012 and 2014 in order to determine the median multiple of price-income ratio, this paper found that housing in all the districts were generally unaffordable. Some districts recorded HAI of severely unaffordable, while others in the seriously and moderately unaffordable index categories.

HOUSING AFFORDABILITY IN THE STATE OF JOHOR

The Malaysian property market has been facing significant changes in terms of housing price since a decade ago and these changes are different between states. The changes in housing prices are being supported by the economic theories of demand and supply as well as the regional economic and demographic factors such as income level, housing supply stock, speculative buying and population changes. This paper provides an overview of the affordable housing policy and elaborates on the housing affordability index for the districts in the State of Johor. Using datasets for year 2012 and 2014 in order to determine the median multiple of price-income ratio, this paper found that housing in all the districts were generally unaffordable. Some districts recorded HAI of severely unaffordable, while others in the seriously and moderately unaffordable index categories.

Tradable location tax credit scheme for balancing traffic congestion and environmental externalities

ABSTRACTThis article proposes a novel urban system equilibrium model for design of a tradable location tax credit scheme to balance traffic congestion and environmental externalities. In the proposed model, the interaction between the location tax credit scheme and households' residential location choices is explicitly considered. It is assumed that the authority initially allocates the credits to all households in a uniform way, and the households pay a certain amount of credits for housing consumptions, relying on the traffic congestion and environmental externalities that they cause. The credits are traded among households through a free market, and the tax revenue due to credit trading is considered as a part of household's income to be redistributed through household's income budget constraint. For a given credit scheme, households' residential location choices and housing market structure in terms of housing prices and space can be endogenously determined by the urban system equilibrium and the price per unit of credit is governed by the credit market equilibrium. A social welfare maximization model is presented to determine the total amount of credits issued. The results show that implementation of the tradable location tax credit scheme can rationalize the urban residential density and promote the efficiency of the urban system in terms of social welfare.

Spatiotemporal Analysis of Housing Prices in China: A Big Data Perspective

Due to the rapid economic growth and urbanization, China’s real estate industry has been undergoing a fast-paced development in recent decades. However, the spatial imbalance between the economic growth in urban and that in rural areas and the excessive growth and fluctuations of house prices in both areas had quickly caught public’s attention. Not surprisingly, these issues had become a focus of urban and regional economic research. Efficient and accurate prediction of housing prices remains a much needed but disputable topic. Currently, based on the trends and changes in the financial market, population migration and urbanization processes, numerous case studies have been developed to evaluate the mechanism of real estate’s price fluctuations. However, few studies were conducted to examine the space-time dynamics of how housing prices fluctuated from a big data perspective. Using data from China’s leading online real estate platform {sofang.com}, we investigated the spatiotemporal trends of the fluctuations of housing prices in the context of big data. This paper uses spatial data analytics and modeling techniques to: first, identify the spatial distribution of housing prices at micro level; second, explore the space-time dynamics of residential properties in the market; and third, detect if there exist geographic disparity in terms of housing prices. Results from our analysis revealed the space-time patterns of the housing prices in a large metropolitan area, demonstrating the utility of big data and means of analyzing big data.

Optimal time for implementing cordon toll pricing scheme in a monocentric city

AbstractThis paper proposes an analytical model to address the timing issue of cordon toll pricing in a monocentric city. The proposed model allows an explicit consideration of the interactions among three types of agents in the urban system: (i) the local authority who aims to jointly determine the optimal time for introducing cordon toll pricing scheme, cordon toll location and toll level to maximize social welfare of the urban system; (ii) property developers who seek to determine the intensity of their capital investment in the land market to maximize their own net profit generated from the housing supply; and (iii) households who choose residential locations that maximize their own utility within a budget constraint. The effects of the cordon toll pricing scheme on household's residential location choice and housing market structure in terms of housing price and space are explicitly considered. A comparison of the toll pricing schemes with a fixed and a mobile cordon location over time and the no toll case is carried out. The proposed model is also illustrated in several Chinese cities. Insightful findings are reported on the interactions among cordon toll pricing scheme, urban population size, household income level, toll collection cost, and urban development.

Optimal density of radial major roads in a two-dimensional monocentric city with endogenous residential distribution and housing prices

This paper proposes an analytical urban system equilibrium model for optimizing the density of radial major roads in a two-dimensional monocentric city. The proposed model involves four types of agents: local authorities, property developers, households and household workers (i.e. commuters). The local authorities aim to maximize the total social welfare of the urban system by determining the optimal density of radial major roads in the city. The property developers seek to determine the intensity of their capital investment in the land market to maximize the net profit generated from the housing supply. The households choose residential locations that maximize their utility within a budget constraint, and the commuters choose the radial major roads that minimize their individual costs of travel between home and workplace. A heuristic solution procedure is developed to find the urban system equilibrium solution. A system optimum model is also proposed to optimize the density of radial major roads that maximizes the social welfare of the urban system. The proposed model can endogenously determine household residential distribution and land values across the city, along with the housing market structure in terms of housing prices and space. Numerical comparative static analyses of congestion pricing and road infrastructure investment (adding a new radial major road) are carried out together with evaluation of the effects of the service level of radial major roads, urban population size, and household income level on the urban economy.

Defining Housing Market Areas Using Commuting and Migration Algorithms: Catalonia (Spain) as a Case Study

In the literature on housing market areas, different approaches can be found to defining them—for example, using travel-to-work areas and, more recently, making use of migration data. This paper proposes a simple exercise to shed light on which approach performs better. Using regional data for Catalonia, in Spain, housing market areas are computed with both commuting data and migration data. In order to decide which procedure shows superior performance, the uniformity of prices within areas is examined. The main finding is that commuting algorithms present more homogeneous areas in terms of housing prices.