Residential Housing Prices Research Articles

Factors influencing the price of housing in Indonesia

Purpose– This study aims to address the factors or attributes that would influence the price of residential products in Jakarta Metropolitan Region.Design/methodology/approach– In total, 202 respondents from all across Jakarta Metropolitan Region participated in the questionnaire for this study. Demographic questions are categorized into age, gender and preferences for real estate locations. The questionnaire was made based on the author’s previous studies. Of the total respondents, 127 were males and 75 were females with age ranging from 18 to 56 years old. For data analysis, the authors utilized factor analysis, Cronbach’ α test and analysis of correlation to reach the conclusion of this study.Findings– The findings suggested that from the initial three factors groups, there are five new groups that emerge as influencing factors for housing prices. Cronbach’ α score were verified (α = 0.906). Correlation study result suggested that the initial three factors groups produce a significant correlation between each of them, except for the factor of “overall location” and “located near family.” After factor analysis, the research results show that there are two new additional groups of factors that emerge as influences to housing prices. There are significant scores of differences between gender and real estate location preference toward the groups of factors.Research limitations/implications– This study shows how physical qualities, concept and location factors influence the housing price perception of their consumers. The result shows to be relatively reliable and valid.Originality/value– The study is the first to analyze the relationship between the factors for preferences on residential products and housing price in Indonesia. This paper is also intended to be the first to pioneer the study on factors of preferences on residential products in Indonesia. The findings will be useful to develop pricing models for housing product in Indonesia.

Homeownership and Financial Strain Following the Collapse of the Housing Market: A Comparative Study on Loan Delinquencies Between Black and White Households

The objectives of this study were to evaluate the extent to which homeownership contributed to household financial strain as measured by loan delinquency after the onset of the recent housing market crash, and to examine if the impact of homeownership on household financial strain differed for Black and White households. Using data from the 2010 Survey of Consumer Finances, we found that, after controlling for other factors, a household's housing preferences had a potential effect on the likelihood of experiencing financial strain following the collapse of residential housing prices. In addition, Black homeowners were more likely to have experienced financial strain following the housing collapse than were White homeowners, regardless of the time period in which the home was purchased. The implications of the findings for public policy, personal financial planning and education, and further research are presented.

Housing Prices in Urban China as Determined by Demand and Supply

AbstractThis paper studies the demand for and supply of residential housing in urban China since the late 1980s when the urban housing market became commercialized. Using aggregated annual data from 1987 to 2012 in a simultaneous equations framework we show that the rapid increase in the urban residential housing price can be well explained by the forces of demand and supply, with income determining demand and cost of construction affecting supply. We find the income elasticity of demand for urban housing to be approximately 1, the price elasticity of demand to be approximately −1.1 and the price elasticity of supply of the total housing stock to be approximately 0.5. The resulting long‐run effect of income on urban housing prices in elasticity terms is approximately 0.7, because the increase in income has shifted the demand curve outward more rapidly than the supply curve.

The Economic Benefits of New York City's Public School Reforms, 2002-2013

This study examines some of the economic consequences associated with the public school reforms introduced in New York City (NYC) by Mayor Michael Bloomberg, including their impact on housing values. The reforms focused primarily on increasing the autonomy and accountability of a school’s principal and teachers, and expanding school choice and charter schools. We found that those reforms have been followed by substantial improvements in a number of key measures of student performance, including Math and English test scores, high school graduation rates, and college enrollment rates. From 2006 to 2009, for example, the four-year graduation rate of NYC high school students increased from 49.1 percent to 60.4 percent, improvements driven mainly by the progress of African-American and Hispanic students. We estimate that from 2008 to 2012, 41,000 more NYC public high school students earned diplomas than would have occurred assuming the graduation rates for NYC students in 2006; and the net present value of the additional income that these additional high school graduates should earn over their lifetimes is $8.9 billion. Similarly, from 2008 to 2012, 30,900 more NYC public high school students enrolled in institutions of higher learning than would have occurred assuming the college enrollment rates of NYC students in 2006; and the net present value of the additional income that these additional NYC college attendees should earn over their lifetimes is $6.4 billion. Our analysis further found that rising high school graduation rates increase housing demand in the neighborhoods where those graduation rates rose, which in turn has led to increased residential property values. We estimate that increasing NYC graduation rates by 1 percentage point in a zip code leads to an increase in residential property prices of 0.54 percent in that zip code. On this basis, we estimate that NYC’s rising graduation rates added as much as $37.1 billion to NYC residential housing prices or values. Finally, the number of NYC charter schools climbed from 14 in 2001 to 183 in 2013, an average increase of 0.96 charter schools per zip code. We found that adding one new NYC charter school in a zip code increased residential property prices there by an estimated 3.69 percent. On this basis, the expansion of charter schools in NYC may have added as much as $22.45 billion to NYC residential property prices or values.

Understanding House Price Index Revisions

Residential house price indexes (HPI) are used for a large variety of macroeconomic and microeconomic research and policy purposes, as well as for automated valuation models. As is well known, these indexes are subject to substantial revisions in the months following the initial release, both because transaction data can be slow to come in, and as a consequence of the repeat sales methodology, which interpolates the effect of sales over the entire period since the house last changed hands. We study the properties of the revisions to the CoreLogic House Price Index. This index is used both by researchers and in the Financial Accounts of the United States to compute the value of residential real estate. We show that the magnitude of revisions to this index can be significant: At the national level, the ratio of standard deviation of monthly revisions to the growth rate of the index, relative to the standard deviation of the growth rate in the index, is 29%, which is comparable to the relative ratio for other macroeconomic series. The revisions are also economically significant and impact measures used by policymakers: Revisions over the first 12 releases of the index reduce estimates of the fraction of borrowers nationwide with negative equity by 4.3%, corresponding to 423,000 households. Lastly, we find that revisions are ex-ante predictable: Both past revisions and past house price appreciation are negatively correlated with future revisions.

Study on Commodity Residential House Price Volatility of the Guanzhong Urban Agglomeration Using Spatial Econometric Analysis

This paper was based on the theory of spatial econometric model. It selected the panel datas of the guanzhong urban agglomeration of five core cities from 1998 to 2012, and inspected the commodity residential house price if there is a space dependency relationship between the two cities. On the basis to analyze the main factors influencing the commodity residential house price volatility and research on the influence of the housing price direction. Results show that the sample is significant spatial correlation between urban housing prices. Xi 'an have great influence on regional cities housing price. The urban population, household disposable income, land acquisition costs, sales area are the main influence factors affecting housing price volatility.

Impact of Urban Green Space on Residential Housing Prices: Case Study in Shenzhen

AbstractPublic resources such as transportation, hospitals, parks, and schools are important factors in housing prices. However, studies on property value have mainly concentrated on transportation, and few studies have focused on the effect that green space has on property values. Researchers have mainly focused on specific parks within different communities rather than parks (on a larger scale) to study the average impact of green space on housing prices. Therefore, the objective of this research is to quantify the effect of public resources on property value, especially green space, using the hedonic pricing method (HPM). This paper focuses on 71 parks within Shenzhen to make results universal. Transaction price data and the structural attributes of 6,473 dwelling units were collected. This paper looks at HPM from three dimensions: structural attributes, location variables, and environmental variables. The results showed that (1) proximity to a central business district (CBD) produced the greatest effe...

Hedonic Valuation of Land Protection Methods: Implications for Cluster Development

This study estimates a generalized spatial hedonic pricing model to assess how residential property values are impacted by inclusion within cluster developments and by proximity to various types of protected land. The estimated model simultaneously controls for the spatial dependence of residential housing prices and for the presence of spatial autocorrelation. The sample includes 4,008 single-family housing sales transactions within the non-urban portions of Larimer County in northern Colorado. The empirical framework accounts for topographical diversity across the study region, as well as distinguishing between several distinct types of publicly and privately protected land. The key findings of the study are: (i) proximity to national or state park land and to city or county open space has a significant positive impact on property values, while proximity to national forest land or to privately conserved land exhibits no significant effects; and, (ii) inclusion of a property within a cluster development decreases its value by 17 to 26 percent. These findings are robust to different estimation techniques and model specifications, which suggests important considerations for policymakers who design development rules and alternative land protection measures aimed at preserving open space in non-urban areas.

Hedonic valuation of land protection methods: implications for cluster development

This study estimates a generalized spatial hedonic pricing model to assess how residential property values are impacted by inclusion within cluster developments and by proximity to various types of protected land. The estimated model simultaneously controls for the spatial dependence of residential housing prices and for the presence of spatial autocorrelation. The sample includes 4,008 single-family housing sales transactions within the non-urban portions of Larimer County in northern Colorado. The empirical framework accounts for topographical diversity across the study region, as well as distinguishing between several distinct types of publicly and privately protected land. The key findings of the study are: (i) proximity to national or state park land and to city or county open space has a significant positive impact on property values, while proximity to national forest land or to privately conserved land exhibits no significant effects; and, (ii) inclusion of a property within a cluster development decreases its value by 17 to 26 %. These findings are robust to different estimation techniques and model specifications, which suggests important considerations for policymakers who design development rules and alternative land protection measures aimed at preserving open space in non-urban areas.

Fundamental factors in the housing markets of China

This paper seeks to understand the importance of changes in the fundamental factors of demand and supply, such as the urban hukou population, wage income, urban land supply, and construction costs, in explaining the rising residential housing prices in major Chinese cities between 2002 and 2008. We propose an empirical approach that uses both city-level and residential development project-level data. Results suggest that, for most of the cities in our sample, changes in fundamental factors can account for a major proportion of the actual housing price appreciation. However, in several coastal cities, the actual increase in housing prices deviates largely from what can be predicted from fundamental changes.

Subsidized mortgage loans and housing affordability in Poland

While a couple of decades ago homeownership used to be a privilege of the few, nowadays most households in developed countries are living in their own four walls. One of the reasons behind this shift are government policies aimed at promoting homeownership and making it more financially feasible. Among these policies, there is a wide range of instruments reducing the costs of mortgage loan interest. Recently, the promotion of homeownership has also become an important issue in some of the former socialist countries. An example of that is a policy of the Polish government called “Family’s own home”. The aim of this policy was to provide financial support for young households who are particularly vulnerable to the difficult housing situation in Poland. Due to huge price increases between 2006 and 2008, and in connection with a short supply of rental housing, many households have been unable to find an affordable dwelling in recent years. The “Family’s own home” policy, initiated in 2007, was the government’s response to this problem. The purpose of this paper is to investigate the outcomes of this policy, which was terminated at the end of 2012 because of a public finance crisis. Three research questions are addressed: (1) what was the relationship between government support and residential construction, housing prices, and mortgage loan interest rate, (2) what was the spatial distribution of government support, and (3) how was it related to the spatial distribution of housing prices, incomes, and housing affordability?

The Influence of Demographic Structure on Housing Price: An Empirical Analysis of Chongqing

Residential housing price affects life of tens of thousands of families. Based on the relevant data of Chongqing’s reports from 2003 to 2012, this paper studies the influence of population structure on residential housing price from the perspective of demand comprehensively. It comes up with the report that the population bring-up ratio and sex ratio have a negative influence on housing price, while sex ratio’s influence is much bigger than the population bring-up ratio. In a word, the demographic structure will cause certain influence to the residential housing price of Chongqing.

Commodity Residential House Price Volatility Spillover Effects of Study — To Zhengzhou City Circle as an Example

With the overall urban scale and the constant improvement of the level of economic development and regional urban cluster gradually formed, the interactive relationship between urban residential market is increasingly significant.Based on building the VAR model, this paper using Johansen cointegration relationship test, Granger causality test based on VEC model and variance decomposition method of the nine cities of zhengzhou city circle commodity residential house price volatility spillover effect carries on the empirical analysis, the results showed that: each city commodity housing prices keep long-term stable equilibrium relationship between, and has obvious effect, the interaction of zhengzhou and luoyang to other urban commodity residential house price fluctuation has significant guiding role.

Evidence of a Housing Bubble in Beijing

The price of residential housing in Beijing has increased at an annual nominal rate of 20 percent for the past decade. This rapid growth has happened in a period of rapid urbanization where rural people have moved to cities and towns and there is a rapid and sustained growth in per capita income. This paper reports on the findings from a purpose-designed survey administered to a total of 420 households in 16 districts in Beijing on the determinants of house prices. Our analysis reveals that housing prices in Beijing have deviated above the norms in terms of expectation and affordability. Economic fundamentals in the form of income growth and low interest rates on home-loans are able to explain just 12 percent of the inflation in house prices. The remainder is due to speculation which is another reason for the bubble in house prices. Policies, in the form of interest rate hikes, reduced loans to purchase second and third homes, and limits on the purchase of additional homes have been introduced to slow the growth of the bubble. Respondents to the survey doubt the effectiveness of these policies in slowing the growth of price bubble, both in the short and the long term. DOI: 10.5901/ajis.2013.v2n8p627

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.

Dual-market Equilibrium of China’s Residential Housing Price

This paper constructs a structural dynamic equilibrium model based on a dual market system, which includes China’s residential housing market and the property rental market in China’s first-tier urban cities. The paper analyzes dual-market general equilibria under different scenarios as perceived since 2004. An open-economy Gordon growth model is also introduced to examine fair housing prices based on the assumption of no arbitrage. Empirical results indicate significant (but time-varying) price deviations from the equilibrium level since 2005 which are mostly driven by contingent demand and property investors. The paper concludes that the contingent purchasing demand supports China’s recent residential price hike and that speculation does not dominate the price boom. The recent quota policy has a theoretical downward pressure on the housing price in the short run but it also lifts property rents dramatically in the middle and long run.

The Potential Impact of an Anthrax Attack on Real Estate Prices and Foreclosures in Seattle

This article provides a methodology for the economic analysis of the potential consequences of a simulated anthrax terrorism attack on real estate within the Seattle metropolitan area. We estimate spatially disaggregated impacts on median sales price of residential housing within the Seattle metro area following an attack on the central business district (CBD). Using a combination of longitudinal panel regression and GIS analysis, we find that the median sales price in the CBD could decline by as much as $280,000, and by nearly $100,000 in nearby communities. These results indicate that total residential property values could decrease by over $50 billion for Seattle, or a 33% overall decline. We combine these estimates with HUD's 2009 American Housing Survey (AHS) to further predict 70,000 foreclosures in Seattle spatial zones following the terrorism event.

Research on House Price Prediction Based on Gray Markov Model

The paper mainly studies the house price prediction problem. Recently, with the rapid growth of domestic house price, it becomes conducive for the government to issue policy to regulate the house price in a visionary way to select a proper method to predict the price. At the same time, it is also very important to stabilize the domestic real estate market and promote the sound national economic development. The commercial residential housing price has the largest contribution rate among all the housing prices. Although commercial residential house price is featured with fluctuations, it basically shows the increasing tendency. Therefore, according to the existing tendency of the commercial residential house price, the paper uses the gray Markov Model for prediction. Gray GM (1,1)model will well simulate the long-term development tendency of the house price. In addition, Markov Model could remove the fluctuation of the house price data to increase the prediction accuracy.

HOUSING FINANCE AND MONETARY POLICY

We document three facts concerning how the structure of housing finance affects the monetary transmission mechanism: first, the characteristics of residential mortgage markets differ markedly across industrialized countries; second, the impact of monetary policy shocks to residential investment and house prices is significantly stronger in those countries with larger flexibility/development of mortgage markets; third, the transmission to consumption is stronger only in those countries where mortgage equity release is common and mortgage contracts are predominantly of the variable-rate type. We then build a two-sector DSGE model with financial constraints to rationalize those facts.

Extending the Scope of Highway Planning: Accessibility, Negative Externalities and the Residential Context

The objectives of this review-based paper were twofold. Firstly, we aimed to explore the need and possibilities for broadening the scope of highway planning by taking account of the residential context, including residential satisfaction. Satisfaction appears to be an interesting, and in our opinion, valuable mediating planning concept between road infrastructure planning and the accompanying external effects on the one hand and household coping strategies on the other. Households living near highway infrastructure are influenced by both positive (i.e. accessibility gains) and negative road-related factors (e.g. noise nuisance and air pollution). Changes in these factors may trigger people to accept the new situation, adjust preferences, try to influence plans and/or even relocate. The second aim was to gain a greater understanding of the influence of both accessibility characteristics and negative externalities on the residential context of households. With respect to context, we make a distinction between residential satisfaction, housing prices and residential relocation. We see changes in residential satisfaction as a potential early predictor of opposition to plans, not only from active opposers but also from the more ‘silent majority’, and as a predictor of housing price changes and residential migration. Insights into residential satisfaction around highways may help transportation planners to relieve locational stress and may also prevent protests and relocations. Our literature review indicated that households prefer to live close to highways to benefit from high regional accessibility, but do not want to contend with the nuisances. This is also reflected in property values. However, the literature appears to put more emphasis on studying the impact of (regional) accessibility and externalities on location behaviour than on residential satisfaction. Because of the added value that the concept of residential satisfaction may provide in road planning, and the limited scientific insights, it is important to gain greater insight into how residential satisfaction is influenced by negative and positive externalities and into how residential satisfaction changes over time—from the stage when new road projects are discussed through to concrete planning, realization and the period after completion. Moreover, it would be worthwhile to gain a deeper understanding of the extent to which house prices, location behaviour and residential satisfaction near highways interrelate.