Housing Market Prices Research Articles

Analysis of the Combined Impact of Socio-Economic Factors on House Price Volatility in the Housing Market

As an important variable in China’s economic system, real estate price is a key point closely linked to the country’s economy and people’s livelihood. It is of great practical significance to study the impact of socio-economic factors in the housing market on China’s house prices and its transmission mechanism, so as to put forward corresponding policy recommendations for stabilizing house prices and preventing real estate market and financial risks. Taking China’s time series data from 2014 to 2023 as a sample, this paper empirically investigates the law of the relationship between socio-economic factors in the housing market and house price fluctuations by constructing a structural vector autoregressive model, and employs impulse response function and variance decomposition to analyze the relationship between the two dynamically. The study shows that the 15-period variance decomposition effect of itself and residents’ disposable income are the main influencing factors of house price fluctuation, and the degree of explanation of its fluctuation is 55.5% and 23.2% respectively. In a market economy, real estate prices fluctuate up and down around their value due to the law of value. Therefore, real estate prices cannot rise indefinitely, and the final result should be stabilized within a reasonable level.

Institutions' dynamics and homeownership aspirations in Ethiopia

The desire to own a home is a common aspiration amongst many. The role of institutions either by enabling or constraining the achievement of the aspirations is very crucial. Unfortunately, the study investigating the impact of these institutional factors on homeownership aspirations was not adequately adequate. Thus, the researchers motivated to analyze the role of institutions for homeownership aspirations. Researchers used qualitative and quantitative data analysis methods to explore the relationship between mortgage access, housing market prices, and homeownership in Sheger City, Ethiopia. The study involved 384 participants, and the results were analyzed using descriptive statistics and multinomial regression. The findings suggest that mortgage access and housing prices play a significant role in shaping homeownership aspirations. However, it was apparent that banks prioritize the wealthy, resulting in the housing market neglecting the needs of low-income individuals and families, leading to unaffordable housing options and findings revealed institutions’ dynamics are accompanied by dysfunctions. The multinomial regression analysis revealed that the likelihood of owning a home over renting one increases when housing becomes more affordable which shows market dysfunctions affect aspirations to homeownership. Obtaining a mortgage is also critical, as it significantly improves the chances of aspiring to own a home. The authors suggest that the Municipality reconsider the affordability of mortgage services and housing prices to ensure that homeownership opportunities are distributed fairly.

시계열모형에 의한 서울 아파트시장 가격예측 분석

The purpose of this study is to make a model to forecasting apartment trade price and household rent price in apartment housing market using ARIMA model. On the basis of those models, I tried to forecast the fluctuations of short-term apartment trade price and household rent price in Seoul apartment market. To analyze the ARIMA model, quarterly data during 2011 1/4∼2023 4/4 are used for identification, estimation, diagnosis, and prediction of the ARIMA model. Using ARIMA model, the outcome ARIMA(1,1,0) model is applied to Sepol apartment trade price in the rate of apartment trade price forecasting model, and ARIMA(1,1,1) model is applied to Seoul apartment household rent price in the rate of apartment rent price. According to the forecast results of Seoul apartment trade price and apartment household rent price in the ARIMA model, looking at the quarterly rate of change in Seoul apartment sales prices, it appears that they will continue to go up the 2024 1/4, and will continue to rise but without significant fluctuations. Looking at the quarterly trend of Seoul apartment rental prices on the 2024 1/4 and continue until the 2024 4/4, and the upward trend will be larger than Seoul apt sale price. While the government's housing policy is sluggish, Seoul apartment sales prices and Jeonse prices are expected to be affected by a decrease in apartment supply and interest rates due to a decrease in permits and occupancy this year.

임대주택의 공급 주체 ‧ 방식별 주택시장 안정화 효과 비교 분석

This study conducted a panel analysis to examine the impact of rental housing supply by type (public/private, built/purchased) on housing market price stabilization at the level of metropolitan city and province level. This study used data from the National Survey of House Price Trends (Korea Real Estate Board) and MOLIT Statistics System (Ministry of Land, Infrastructure, and Transport) for the period 2013–2021. The main findings of the analysis are as follows. In terms of a provider, publicly rented housings contribute more to price stabilization than privately rented, and in terms of a supply method, purchased-rented housings are better in price stabilization than constructed-rented housings. In terms of renting types, price stabilization effect is strongest in public purchase followed by public construction and private purchase. However, private construction is more likely to drive up prices. This suggests that rather than focusing solely on increasing inventory, rental housing supply policies should include both legal and institutional support and regulation.

Recommended Strategies Based on The Capability And Purchasing Power of Low-Income Communities (MBR) In Providing MBR Houses In Kartamantul

The housing needs that shape urban spatial structures or the relationships between the three cannot be fully understood without considering the state of housing market prices. The reason is that changes in urban housing market prices no longer depend on the city level, but over time begin to be characterized by urban agglomeration processes. Furthermore, agglomeration dynamics that change urban spatial structure and housing market prices will have an impact on socio-economic disparities and challenges in providing affordable housing for people with low incomes in densely populated urban areas. The aim of this research is to find out whether the MBR housing allocated by the regional government is appropriately located in low-income areas/zones in KARTAMANTUL. The research methods used are web scrapping, mapping and comparative evaluation of housing locations with the distribution of MBR in KARTAMANTUL. The results obtained were to simplify the simulation of affordability and household purchasing power regarding home ownership, the researchers tried to average the income of the two categories of low-income households. Therefore, with an average MBR income limit of Rp. 3,900,000 in DIY, then the ability to repay the house in installments is IDR. 1,170,000/month. Furthermore, regarding house buildings, the criteria for a habitable house is a per capita area of at least 9 m2 per person. With the average number of family members in DIY being 4 people, the house area required per household is 36 m2. The recommendations given are a) 25 year house installments are a payment option that can be used for low-income households in KARTAMANTUL, b) the choice of house locations for MBR is mostly in Bantul Regency and Sleman Regency, both of which have urban status. fringe and urban shadow.

THE EFFECTS OF TRANSACTION HOTSPOTS AND FLIPPING HOTSPOTS ON HOUSING PRICES

In contrast to much of the literature that focuses on the issue of spatial dependence in housing price research, this study addresses the spatial aggregation of housing transactions and analyzes the effects of transaction hotspots and short-term flipping hotspots on housing prices by using real housing transaction data in Taipei City, Taiwan. The empirical results show that after controlling for the effects of spatial dependence and individual housing attributes, the impact of transaction hotspot areas on housing prices is significantly negative, while the impact of flipping hotspot areas on housing prices is significantly positive. The results verify that the key to driving up housing prices lies in flipping activities. Furthermore, the results of the spatial quantile regression model show that low-priced residential properties are more sensitive to the spatial concentration of housing transactions and flipping transactions in the housing market. Our results have implications for the government’s policy intending to control hot trade volumes to cool skyrocketing housing prices in a booming housing market. It is suggested that the government should pay attention to restraining short-term flipping activities in the housing market rather than setting constrains on housing transactions.

Housing market, oil prices, and macroeconomic volatility in the G7

AbstractIn this paper, we investigate house price shocks on the macroeconomic variables (financial market, inflation, and real sector) of the G7 economies. We use the GVAR to capture the spillover effects from the U.S. housing market and oil prices on these economies from 1991M3–2022M10. We identify the U.S. house price shock using the Structural Generalized Impulse Response Function, house supply and demand variables, and regional divergence. We find that the domestic stock markets and industrial production are the most sensitive to house price shocks. We further compare the importance of house and oil prices on domestic fluctuations. The estimates reinforce the previous findings: U.S. house prices are responsible for a quarter of the domestic volatility of the stock markets and industrial production. In the other macroeconomic segments, the effects of house prices are present, but in lower values. Our results show that house prices provoke more domestic fluctuations than oil prices. Finally, we also found that short and long‐term credit markets, as well as stock markets, transmit the house price shock to industrial production. Consequently, we provide potential channels to comprehend the spillover effect of U.S. house prices on international markets.

Assessing Dubai’s housing market price cycles and bubble risk

ABSTRACT This study investigates the presence of a real estate bubble in Dubai’s housing market, considering the recent surge in prices. Using monthly city-level housing price data and a recursive unit root test designed for real-time bubble detection, the study covers the period from 2008 to the second half of 2023. The findings reveal that, despite the recent price increases, there is no significant evidence of a real estate bubble in Dubai’s property market. This suggests that no substantial price correction is expected in the near term, which is crucial given the heightened financing costs and potential impact of rising interest rates.

ARIMA 모형을 이용한 전국 아파트시장 가격 예측

The purpose of this study is to make a model to forecasting apartment trade price and household rent price in apartment housing market using ARIMA model. On the basis of those models, I tried to forecast the fluctuations of short-term apartment trade price and household rent price in national apartment market.
 To analyze the ARIMA model, quarterly data during 2011 1/4∼2023 3/4 are used for identification, estimation, diagnosis, and prediction of the ARIMA model. Using ARIMA model, the outcome ARIMA(2,1,1) model is applied to nationwide apartment trade price in the rate of apartment trade price forecasting model, and ARIMA(1,1,1) model is applied to nationwide apartment household rent price in the rate of apartment rent price.
 According to the forecast results of nationwide apartment trade price and apartment household rent price in the ARIMA model, looking at the quarterly rate of change in national apartment sales prices, it appears that they will continue to fall in the 2023 4/4, but will turn to an upward trend starting in the 2024 3/4, and will continue to rise slightly but without significant fluctuations. Looking at the quarterly trend of national apartment rental prices, the downward trend is expected to turn into an upward trend in the 2023 4/4 and continue until the 2024 4/4, but the upward trend will not be large.
 While the government's housing policy is sluggish, national apartment sales prices and Jeonse prices are expected to be affected by a decrease in apartment supply and interest rates due to a decrease in permits and occupancy next year.

Relationship between housing, oil, gold and stock markets: evidence from UK and Norway

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.

Effects of House Flips on Local Housing Transactions

This study explores the possible impacts of short-term house trades, often called “house flips,” on local housing markets. Using nationally representative data across multiple U.S. housing markets during 2000–2013, we test the Spillover Hypothesis and the alternative Competition Hypothesis for the influences of flips on the neighborhood non-flip house transactions. We find that the local flip tendency, our measurement for local flip activity, is negatively associated with the holding durations of neighborhood houses experiencing non-flip resales, and positively associated with their resale prices, after we control for market conditions that affect both flip and non-flip transactions as well as other potential determinants for holding duration and price. The effects are generally more prominent when the local flip tendency is measured for a longer run, supporting the Spillover Hypothesis. These effects are also persistent regardless of whether the local flip tendency is defined as the proportion of flips in the local resales by transaction number or by transaction volume, or whether it is measured continuously or discretely. The results also hold when we endogenize the local flip tendency, or when we change the neighborhood size. These findings demonstrate the substantial influences of flip activities to the local housing market turnover and price movements.

Research on Influencing Factors of Second-Hand Housing Price in Haidian District, Beijing

The housing issue is an economic issue as well as an issue of people's livelihood, especially in megacities like Beijing, where housing prices in the second-hand housing market fluctuate greatly, so its influencing factors have become the focus of attention. Studying the influencing factors of housing prices in the second-hand housing market can provide reference for the government to formulate appropriate real estate regulation policies and predict the development trend of housing prices in the future. This article collects nearly 3,000 groups of public second-hand housing individual transaction data from the Lianjia website in the domestic second-hand housing market. The time span of the data is from June 2020 to June 2021. After data cleaning and descriptive statistical analysis of the acquired data, we set the total price of the house as the explained variable, and the number of rooms, the area of the house, the decoration, the floor, and the unit price of the house are used as the explanatory variables. We establish a multiple linear regression model, then test and optimize it. The results are as follows: in the second-hand housing market of Haidian District, if the second-hand house has a large construction area, a large number of rooms, a high unit price and has been renovated, the total price of the house will be high.

Rational housing demand bubble

We provide a unified framework with demand for housing over the life cycle and financial frictions to analyze the existence and macroeconomic effects of rational housing bubbles. We distinguish a housing price bubble, defined as the difference between the housing market price and its fundamental value, from a housing demand bubble, which corresponds to a situation where a pure speculative housing demand exists. In an overlapping generation exchange economy, we show that no housing price bubble occurs. However, a housing demand bubble may occur, generating a boom in housing prices and a drop in the interest rate, when households face a binding borrowing constraint. The multiplicity of steady states and endogenous fluctuations can occur when credit market imperfections are moderate. These fluctuations involve transitions between equilibria with and without a housing demand bubble that generate large fluctuations in housing prices consistent with observed patterns. We finally extend the basic framework to a production economy and we show that a housing demand bubble increases housing prices, which can still be characterized by large fluctuations.

Oil prices and gold prices on housing market in China: novel findings from the bootstrap approach

PurposeThis study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.Design/methodology/approachThis study uses a novel bootstrap autoregressive distributed lag (ARDL) testing to empirically analyze the short and long links among the tested variables.FindingsThe ARDL estimations demonstrate a positive impact of oil price shocks and real income on housing market prices in both the phrases of the short and long run. Furthermore, the results reveal that gold price shocks negatively affect housing prices both in the short and long run. The result can be attributed to China’s housing market and advanced infrastructure, resulting in a drop in housing prices as gold prices increase. Additionally, the prediction of housing market prices will provide a base and direction for housing market investors to forecast housing prices and avoid losses.Originality/valueTo the best of the authors’ knowledge, this is the first attempt to analyze the effect of gold price shocks on housing market prices in China.

A Housing Market with Cournot Competition and a Third Housing Sector

This paper integrates a non-profit third-housing sector (THS) into a housing market with Cournot competition. The paper analyses the indirect effects of a THS on the aggregate housing market, on a commercial housing supplier and on the market adaption of households not embraced by the THS. While beneficial for households included in the THS, a question arises related to the indirect effects of a THS. The paper argues for crowding-out and higher house prices in the commercial housing market in response to a THS expansion. In addition, a THS also affects the strategic behaviour of the commercial housing supplier. Compared to a conventional Cournot housing market, a fixed THS housing supply changes the market structure from one where the housing supply of different housing providers are alternative to one-another, to a market structure where housing supply is complementary.

The social construction of touristification. Residents’ perspectives on mobilities and moorings

One of the last decade’s major challenges faced by tourist cities has been dominated by the increasing tourism flows that have harmed the quality of life of residents, the neighbourhood’s sense of belonging, and the stakeholders’ concerns regarding reliance on tourism. However, tourism mobilities are not the only drivers of structural change in cities. The advent of temporary residents, digital nomads, international students, short-stay expats, and creative workers have shaped the way cities have evolved together with tourism mobilities. This paper will present research conducted in the Vila de Gràcia neighbourhood in Barcelona, which has undergone a thoughtful transformation in terms of tourism-oriented businesses specialisation, housing market prices, sociodemographic changes, the use of public space and nightlife leisure. Gradually, the Vila de Gràcia neighbourhood has become an emblematic area of leisure and tourism consumption experience in Barcelona. Based on ethnographic fieldwork begun in 2017 and in-depth semi-structured interviews with lifelong and new residents, the research analyses residents’ attitude toward touristification processes related to social discontent, nightlife noise, the rise in housing market prices and overcrowding.

Kindergarten Proximity and the Housing Market Price in Italy

This paper investigates the impact of kindergarten proximity on housing market prices in the eleven major Italian Municipalities over the period 2004–2017. For this purpose, we employ a hedonic property price model. We also differentiate the impact of kindergarten proximity on houses’ market price between state and non-state premises. The findings highlight that (i) the level of housing price depends on kindergarten proximity; (ii) some quality school characteristics played a crucial role and (iii) the distinction between public and non-state kindergartens shows that the vicinity of the latter generates a more significant capitalization effect. Finally, the empirical evidence could be useful to several actors involved in urban planning when developing plans for the construction of new kindergartens in order to create a more homogeneous city.

THE INFLUENCE OF MONETARY POLICY ON HOUSING MARKET: EVIDENCES FROM TURKEY

Purpose: Nowadays, the changes in the level of economic activities in the housing market are accepted as the most important signal of macroeconomic performance. This situation brings about the need to give importance to the investigation of policy implementations that affect economic activity in the housing market. So, this study aims to find out the effects of changes in the monetary policy on housing prices in Turkey as a sample of developing country. Design/methodology/approach: This study employed Augmented Vector Autoregression (VAR) analysis. For housing prices; the Housing Unit price series, calculated by the Central Bank, spanning 2010M1-2016M3 are used. Housing unit price is calculated by Housing price per square meter. To represent production volume, the index of total industrial production has been used. To represent inflation series, CPU (Consumer Price Index) series have been used. The data has been taken from CBRT (the Central Bank of the Republic of Turkey) and TUIK (Turkish Statistical Institute). Findings: Results show that policy interest rates are important indicators for the related term?s housing prices and it can also be said that the housing price channel has partially been effective. Accordingly, results determined that monetary policy had a significant effect on housing prices in Turkish housing market. Originality/value: This study supports the argument that monetary policy has a significant effect on housing prices in developing countries like Turkey.

Planning for active aging: exploring housing preferences of elderly populations in the United States

Increases in the elderly population (defined as people aged 65 years old and above by the United States Census Bureau) in the United States (U.S.) have reached an inflection point. This demographic shift fundamentally reshapes the magnitude of housing needs in U.S. communities. Planning housing markets for active aging, our study (1) examines how the overall housing market in the U.S. responds to increases in the elderly population, (2) identifies housing preferences of elderly populations by exploring the heterogeneous effects of increasing elderly populations on different types/sizes of houses. Our results suggest that increases in the elderly population are associated with a slight rise in prices in the overall housing market. It points towards the role of increasing elderly populations in shaping the housing market, bringing both opportunities and challenges in reframing urban and housing policy. The study also shows that increases in the elderly population have significant and positive effects on single-family homes and small homes, but no impact on condominiums and large homes. The heterogeneous effects on different types/sizes of housing represent the preferences of elderly populations to single-family homes and small homes. Given the increasing size and share of elderly populations and severe shortages in affordable elderly housing, our study suggests that a strong commitment to reframing urban policy and housing programs targeting assistance and support toward elderly populations such as the Sect. 202 Supportive Housing for the Elderly Program, is in great need of federal and local governments’ interventions.

The COVID-19 Housing Boom: Is a 2007–2009-Type Crisis on the Horizon?

While the current housing market remains relatively strong, with housing prices setting records, concerns are growing of a potential housing bubble similar to that of 2007–2009; this paper compares the current housing market environment with that of 2007–2009 and concludes that the many of the factors that caused the 2007–2009 crisis do not exist today. Factors associated with subprime mortgages, poor and non-existent underwriting loan requirements, weak regulatory oversight, exaggerated credit ratings, under-capitalization in the banking sector and excessive speculative activity in the housing market have been addressed by regulation, which is aimed at preventing another financial crisis similar to 2007–2009. Equally important, major fundamental factors affecting real estate valuation are providing support for the housing market and housing prices; these factors are impacting both the demand and supply side of the housing market. The factors include the lack of inventories of homes available for sale, the underproduction of housing, decreased household mobility limiting supply and the increase in housing demand from millennials and institutional investors; these fundamental factors were not evident during the 2007–2009 period. Despite a number of indicators signaling a potential topping out and overvaluation of housing prices, the authors conclude that the fundamental factors will limit the extent that the housing market weakens over the next few years.