Increase In House Prices Research Articles

An Analysis of Factors Affecting the Housing Market of San Jose Using MLR Model

This article seeks to explain the unstable curve of housing prices in San Jose by analyzing the data of factors that may affect the housing market. By previous research conducted by other scholars, we believe there were five major factors which cause the housing prices to fluctuate, which are construction costs, total population, median income, mortgage rates and crime rates. Introducing multiple linear regression (MLR) as an approach to analyze and based on the monthly data of five-years period, from 2015 to 2019, we find an increase of mortgage rates and construction costs can lead to an increase in housing prices and other factors may not affect the housing prices as expected. However, due to lacking monthly data of certain factors like total population, we use other information associated with the factors to find an approximation of the real monthly data. Hence, while the conclusion provides certain explanations of housing prices for the buyers, it is built on many assumptions and may not perfectly fit the real behaviour of the housing market of San Jose.

ANALISIS PERHITUNGAN ESTIMASI BIAYA PADA RUMAH TINGGAL 2 LANTAI MENGGUNAKAN MATERIAL KONTAINER

The dwindling availability of land has resulted in an increase in the price of residential houses every year, moreover cities with relatively denser populations have an increase in house prices of more than 20% each year. The design of residential houses by utilizing used containers will save material, transportation, and construction costs, so it is hoped that this alternative can be developed to become a sustainable solution. The research was conducted by designing a 2-storey container house with a building area of 172.8 m2 using the SketchUp2022 software and then calculating the estimation cost analysis. The results of the estimation costs show that conatainer house needs cost of IDR 565,476,007.90 or IDR 2,827,380.04/m2 included tax. So that container house can savings of 19.22% - 43.45% when compared to the average price of conventional houses in Indonesia of IDR 4,500,000.00 - IDR 6,000,000.00 per m2 .

부동산학 연구에서 근린의 보행친화성(Walkability)은 중요한가?

This study examines previous studies on the relationship between neighborhood walkability and the real estate to find out what academic discussions have been made between these two issues, and to explore the implications of walkable environments in the real estate studies. For systematic literature review, a selection process was conducted using PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) guideline, and a total of 23 academic papers were selected. According to the citation report, articles related to walkability in the real estate studies began to appear more than a decade ago, and the number of publications and citations has tended to increase in recent years. In addition, the issue of walkable environment, which was mainly dealt with in the urban planning studies, was also being discussed in the fields of economics and business finance. The 23 articles were largely divided into three thematic groups: walkability and housing prices, walkable and property values, and making walkable environment projects and housing prices. In these three topics, it was found that the walkable environment plays a positive role in increasing housing prices and property values. This study is meaningful in that it comprehensively reviewed previous studies that discussed neighborhood walkability and real estate, which have not been reviewed much from the academic perspective. Based on this study, it is expected that making walkable environment will emerge in the field of real estate industry.

가구수 변화가 주택가격에 미치는 영향에 관한 연구

This paper empirically investigates the effect of the number of households on housing sales prices from a long-run perspective using the DOLS(Dynamic Ordinary Least Squares) model. Estimation results show that most of the variable estimators included in the DOLS model are consistent with the theoretical sign and are statistically significant at the 1% significance level. First, it is found that a cointegration relationship exists between housing prices, the number of households, the population, the average wage of regular workers, and the interest rate of mortgage loans. Second, the growth rate coefficient of the number of households representing the number of households showed a positive(+) value, and the t-value was greater than 2, so it was statistically significant at the 1% significance level. This means that a 1% increase in the number of households will increase housing prices by 0.18% in the long run. Therefore, for housing policies to show significant effectiveness in stabilizing housing prices, It is necessary to proactively implement housing policies by developing a prediction and evaluation simulation model based on close monitoring of the trend of growth rate of households.

Unleashing the Casual Impact of House Prices on Air Quality: Evidence from Chinese Cities

With the rapid development of the real estate industry in China, urban air quality is inevitably affected. By using data of Chinese cities located in the Yangtze River Delta from 2009 to 2018, this paper is aim at examining the casual impact of house prices on air quality. By considering the endogenous problems, in this study, first, the birth rate of the previous six years and the area of state-owned land supply per capita in the previous year are taken as instrumental variables of house price. Second, the two-stage least squares method is used to assess the causal impact of house price on air quality. The findings of this study show that there is no significant relationship between urban house prices and air quality, and these results are obtained without considering the endogenous problem. While, after considering the endogenous problem, urban house prices showed a significant negative effect on overall air quality, especially for low administrative level cities. The increase in house prices has hindered the improvement of air quality mainly through the blind-scale expansion of real estate development investments and the inhibitory effect of innovation.

MORTGAGE LENDING MARKET IN EUROPE: DYNAMICS AND FEATURES

The housing market is an important part of any country's economy. The article analyses the main trends in the development of the mortgage lending market in Europe: general dynamics, development of individual segments, lending volumes, interest rates, construction volumes, resource prices, etc. The purpose of this article is to analyse current trends in the development of the housing market. Graphical and statistical analysis methods are used to visualise the trends in investment in residential construction in Europe in 2020-2022, to identify the main external and internal factors behind the market's decline, and to outline development prospects for the coming years. practical implications. Practical implications. The housing investment market is under the influence of new external destabilising factors (pandemic, military aggression), as well as the pressure of factors such as the economic crisis, widespread digitalisation, the fight against black markets, etc. The results of the analysis have identified the main factors currently affecting the European property market: the aftermath of the invasion of Ukraine, a sharp rise in energy prices, rising inflation and interest rates, a slowdown in economic activity and political uncertainty at global, regional and national level. In general, the development of the housing investment market is characterised by the following trends: high interest rates on mortgage loans; tightening of financing conditions and bank standards, reducing the availability of mortgage loans; slowdown in economic growth and rapid inflation; higher prices for energy and building materials, construction costs and, as a result, an increase in house prices; slowdown in bank lending to households buying houses. Value/originality. An urgent task of modern economic science and practice is the search for ways to attract additional financial resources, mechanisms to ease the financial burden of payments for investors, to reduce and distribute investment risks. It is these circumstances that have determined the growth of the housing investment market segment associated with such innovative forms of investment as digital lending and crowdfunding. According to forecasts, the global digital lending market will grow by up to 12% per year until 2026.

Determinants of housing affordability in the USA

Purpose This study aims to identify the determinants of housing affordability in an effort to inform policy. Design/methodology/approach The authors use econometric analysis to determine variables that impact housing affordability in the USA. Findings The authors find that affordability depends on a number of demographic factors as well as physical characteristics of properties, including average age of homeowner, family size and average dwelling square footage. The authors also find that vacancy rates, increase in house price and median family income also have a significant impact on housing affordability. Additionally, the authors find that households with high-cost burdens are more vulnerable to mortgage rates and property taxes than those with moderate-cost burdens. As a result, changes in economic or policy variables tend to have a disproportionate impact on high-cost-burdened households, and they are more vulnerable to economic and policy shocks. Originality/value To date, the literature has not done a systematic investigation of housing affordability using detailed census data.

The housing status and two-child fertility willingness of floating population: Evidence from the Chinese General Social Survey

In recent years, China’s fertility rate shows a declining trend with rapid urbanization and increasing housing prices. Based on the China General Social Survey (CGSS) data, for the first time, this paper investigates the effect of housing status on the two-child fertility willingness of China’s floating population using a Probit model combined with the propensity score matching method and the instrumental variable method. The results show that the floating population with self-owned housing has a significantly lower two-child fertility willingness than those living in rented housing. This finding remains robust after addressing the potential endogeneity problem. Moreover, the effect of housing status on the two-child fertility willingness of floating population varies with demographic characteristics. Furthermore, the heterogeneous analysis indicates that the floating population with two or more self-owned housings have higher two-child fertility willingness than those who have only one self-owned housing or who live in rented housing. The married without children and living in self-owned housing have lower two-child fertility willingness than the married with one or more children and living in self-owned housing.

House Bubbles, global imbalances and monetary policy in the US

This paper examines the factors driving housing price exuberance in the United States, specifically the influence of expansionary monetary policies and the global saving glut. We employ medium scale Bayesian VAR and time-varying VAR models to estimate the effects of monetary policy and global saving glut shocks on US housing bubbles. We find that, prior to the Global Financial Crisis, the impact of the saving glut shock is more enduring, powerful, and rapid in generating housing bubbles compared to monetary policy shocks. However, the recent housing boom that commenced in 2019 demonstrates a different pattern. Our results suggest that both monetary policy and the global saving glut contribute to the increase in house prices. Counterfactual policy experiments validate this conclusion.

Impacts of monetary policy on housing prices in five emerging economies during the Covid-19 pandemic

Purpose This paper aims to examine the dynamic impacts of the COVID-19 pandemic and government policy on real house price indices in five emerging economies, namely, Brazil, China, Thailand, Turkey and South Africa. Design/methodology/approach The authors use the local projection method with a panel data set of these countries spanning from January 2020 to July 2021. Findings The number of COVID-19 confirmed positive cases raised housing prices, whereas government containment measures reduced them. Both conventional and unconventional monetary policy implemented by central banks to cope with the COVID-19 helped increase housing prices. These effects were strengthened by the US monetary policy via globalized financial markets. Originality/value First, while previous researches typically concentrated on developed countries, the authors investigate emerging economies where proportionally more people were badly affected by the pandemic. Second, a panel data set of five emerging economies enabled the authors to examine the dynamic effects of the COVID-19 crisis on housing prices. Third, to the best of the authors’ knowledge, this is the first study evaluating the influences of easing monetary policy on housing prices in emerging economies during the pandemic.

Cost of credit, mortgage demand and house prices

This paper studies the relationship between mortgage rates and house prices. We exploit a subsidized mortgage program that reduced the mortgage rates of state-owned banks in Turkey during the summer of 2020 as an exogenous shock to provide causal estimates of a decrease in the cost of credit on mortgage demand and house prices. The effects are estimated using a detailed dataset on all house sales with mortgages. We find that a 1 percentage point decrease in annual mortgage rates led to an increase in individual mortgage loans by 3.3% and an increase in house prices by 1.6%.

주택은 인플레이션을 헷지 할 수 있는가?

This paper examines the inflation hedging capacity of Korea’s housing return from January 1987 to December 2022. The exponential generalized autoregressive conditiuonal heteroskedasticity(EGARCH) model and a dynamic ordinary least squares (DOLS) regression were employed to study the hedging capacity of Korea’s housing return against expected and unexpected inflation over the short run and long run. The results that could be obtained through this paper is as follows. First, The empirical results show a hedge effect on expected inflation only in housing return excluding gold over the short term, but not in unexpected inflation. Second, Over the long run, housing and gold returns provide a positive inflation hedge against expected inflation only. Third, it is found that the price volatility of housing and gold have both a positive asymmetric effect on news shocks. Over the long run, an increase in wages is found to increase housing prices by promoting housing demand, While no similar evidence is found in money supply.Therefore, there is a need to implement a stable wage policy to stabilize the housing market.

Australian housing markets, the COVID-19 pandemic and black swan events

PurposeThis study aims to examine the impact of lending liquidity on house prices especially during black swan events such as the Global Financial Crisis of 2007–08 and COVID-19. Homeownership is an important goal for many, and house prices are a significant driver of household wealth and the wider economy. This study argues that excessive liquidity from central banks may be driving house price increases, despite negative changes to fundamental drivers. This study contributes to the literature by examining lending liquidity as a driver of house prices and evaluating the efficacy of fiscal policies aimed at boosting liquidity during black swan events.Design/methodology/approachThis study aims to examine the impact of quantitative easing on Australian house prices during back swan events using data from 2004 to 2021. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation's Central Bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration among some of the I(1) variables, the auto-regressive distributed lag model was selected given its flexibility and relative lack of assumptions.FindingsThe Australian housing market continued to perform well during the COVID-19 pandemic, with the house price index reaching an unprecedented high towards the end of 2021. Research using data from 2004 to 2021 found a consistent positive relationship between house prices and housing finance, as well as population growth and the value of work commenced on residential properties. Other traditional drivers such as the unemployment rate, economic activity, stock prices and income levels were found to be less significant. This study suggests that quantitative easing implemented during the pandemic played a significant role in the housing market's performance.Originality/valueGiven the severity of COVID-19, policymakers have responded with fiscal and monetary measures that are unprecedented in scale and scope. The full implications of these responses are yet to be completely understood. In Australia, the policy interest rate was reduced to a historic low of 0.1%. In the following periods house prices appreciated by over 20%. The efficacy of quantitative easing and associated fiscal policies aimed at boosting liquidity to mitigate the impact of black swan events such as the pandemic has yet to be tested empirically. This study aims to address that paucity in literature by providing such evidence.

Impact of decentralized long-term rental apartments on the value of community housing--taking Tianjin, China, as an example

Purpose This study aims to explore the impact of decentralized long-term rental apartments on the value of in-community housing from two perspectives of housing price and rent. Design/methodology/approach This study uses the hedonic model to identify the factors affecting the housing value, and the influence of distributed long-rented apartments on the housing value in the community is analyzed from two aspects of housing price and rent by using the ordinary least square method and propensity score matching method. Findings The primary finding indicates that decentralized long-term rental apartments increase housing prices while decreasing general rental housing rents in the community, with the average degree of increase ranging from 0.93% to 2.59% and the average degree of decrease ranging from 2.23% to 4.34%. According to additional research, the prices of houses within communities rise by 0.042% for every 1% increase in the share of decentralized long-term rentals, while the rents for other types of rental property fall by 0.162%. Practical implications The government can regulate the housing market by regulating the access and layout of distributed long-rent apartments. Originality/value The findings of this study indicate that the existence and share of distributed long-rent apartments have a heterogeneous impact on the housing price and rent in the community, respectively.

Structural transformation, urbanization, and remittances in developing countries: A panel VAR analysis

Structural transformation and urbanization have increased greatly in developing countries over the last few decades. Migrant remittances—private external financial flows—have also grown phenomenally during this period. The literature reveals a significant causal relationship between urbanization and economic growth and considers urban cities to be the engines of growth. However, investigation into the link between structural transformation, urbanization, and remittances is missing in the literature. This study aims to fill that gap by investigating the relationship between structural transformation, urbanization, remittances, and GDP growth in developing countries. After finding no long-run relationship between the respective variables, this study applies vector autoregressive modelling to determine their short-run dynamic causal relationship, using panel data from 95 developing countries for the period 1980–2018. Its findings suggest that there is a two-way (bi-directional) causal relationship between structural transformation and urbanization, structural transformation and GDP growth, urbanization and GDP growth, and urbanization and remittances. Rapid urbanization can increase housing prices and overall urban living costs, which may increase remittance flows that support consumption. Likewise, increased urban infrastructure development may also attract remittances to real-estate investment, leading to further urbanization.

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.

Rural and Alpine Gentrification Impact on Lifestyle Mobilities During Covid-19: The Yayla Experience at the Taurus Mountains in Turkey

Abstract COVID-19 has had significant impacts on social and economic sectors worldwide. International travel and tourism are restricted as preventive measures to combat the disease. However, it is clearly visible that the mobility from urban to rural areas continues within the borders of the countries during the pandemic. Mobility to the countryside is named as lifestyle mobility. It varies significantly in motivations, frequency, push and pull factors, and duration of stay. It is also considered an essential agent of change that causes gentrification in rural vicinities regarding economic structure, real estate market, and sociocultural life. The recent spread of COVID-19 has also been deemed a vital push for urban-rural mobility. The present study is aimed to explore the gentrification of lifestyle mobilities in the Yaylas of the Taurus Mountains during the pandemic. A mixed-method approach using questionnaire and interview techniques was applied. Results revealed that the duration and frequency of seasonal mobility towards second homes in Turkey have changed with the spread of COVID-19. Moreover, it is found that the selected mountain areas confront the impacts of urbanization, increase in housing prices, and commercial occupation of land. The research concludes that such changes are augmented due to the increased mobility of urbanites belonging to the new middle class of Mersin and Adana metropolitan cities to rural areas to escape COVID-19. Due to the increase in lifestyle mobility, gentrification takes place in rural and mountainous areas, and accordingly, rural residents tend to move to the city.

Introduction

Home ownership—the great Australian dream—seems to be increasingly out of reach for many Australians. Increasing house prices, especially in relation to wages, have long been on the front pages of newspapers and at the centre of policy debates about affordable housing. A host of policy measures—from shared equity schemes over government-backed loan guarantees for selected demographics to tax incentives for rent-to-buy schemes—aim to make it achievable for first-home buyers to purchase a home. And yet, home ownership rates over the life course have consistently dropped for successive generations since the 1970s (Australian Institute of Health and Welfare 2023). Long-term renting thus becomes a more and more common experience among younger Australians. But can the private rental market offer the security, stability and quality of living space that long-term renters need? If buying affordable housing is out of reach for many, are affordable rental properties available as an alternative? After a drop in rents in the first half of 2020, weekly rents have begun to increase again over the last two years; in particular rents paid by new tenants increased by 14 per cent over the year to February 2023 (Australian Bureau of Statistics 2023). This increase far exceeds overall inflation and is at least partially driven by a decrease in household size in the wake of the COVID-19 pandemic. With vacancy rates also at a historic low (Australian Bureau of Statistics 2023), renters with little protection against eviction or rent increases during a tenancy are left in a very vulnerable position. At the same time, given general increases in the cost of living and stagnant wages, particularly renters in low-income groups have few resources to deal with increasing rents or to compete for a new home in a tight market. Kath Hulse and Zoë Goodall argue that better protection against no grounds eviction, well-designed rent controls and minimum standards for habitability of a property are sorely needed—and their research shows that these do not lead to substantial disinvestment by property owners. Bruce Bradbury reviews the arguments for and against the Commonwealth Rent Assistance, and proposes that the maximum rent assistance payment should increase by a lot more than the most recently announced increase of 15 per cent, to support adequate housing consumption and to reduce the net cost of housing for low-income groups. The articles in this policy forum outline clear steps for reform and contribute important thoughts on a long-term, sustainable private rental sector. I believe our readership will benefit from and enjoythese insightful pieces.

Effects of the Implementation of the Broadband China Policy (BCP) on House Prices: Evidence from a Quasi-Natural Experiment in China

With the rapid development of digital finance, the implementation of digital infrastructure is becoming increasingly significant. Broadband construction is an important part of the communication network, and can promote urban infrastructure in cities. However, whether the development of broadband can affect housing prices by affecting the urban infrastructure and the convenience of residents is a question worth addressing. In this study, using panel data regarding cities in China, we used the spatial multi-period difference-in-differences (SDID) model to investigate the utility of the Broadband China Policy (BCP) on urban house prices and the mechanism of impact. We found that the BCP can increase house prices, and that this impact has a positive spatial spillover effect. This conclusion still held after a series of tests such as parallel trend tests, placebo tests, and the exclusion of other policy effects. The BCP can increase house prices by improving urban infrastructure, promoting urbanization, and optimizing urban industrial structure. In addition, we conducted a heterogeneity analysis by taking into consideration the administrative level, economic development level, and location of cities. The findings of this paper not only enrich the research on the BCP and housing prices, they also provide policy recommendations in terms of urban land use and sustainable development.

Impact of house prices on household carbon emissions

Carbon emissions generated by household activities are an important factor in climate change; reducing household carbon emissions (HCEs) will be an essential part of future energy conservation and sustainability initiatives. Housing prices have a crucial impact on residents’ consumption, and the increase of consumption level is the main reason for the rise of household carbon emissions. Therefore, studying the impact of housing prices on HCEs not only provides guidance on expanding domestic demand and increasing consumption from the perspective of housing prices but also provides construction advice on curbing global warming and is more conducive to the development of building sustainable consumption. Taking household consumption as a starting point, this study investigates the impact of house prices on HCE in China based on the 2018 Chinese Household Tracking Survey (CFPS) and the China Energy Statistics Yearbook, using the carbon emission factor method to measure carbon emissions. It was found that increased house prices had a significant positive effect on HCEs. There is a clear wealth effect of rising house prices among homeowners, while the substitution effect also increases consumption among non-homeowners (by reducing attempts to save). Furthermore, rising house prices have a varied effect on different types of HCEs. The impact on emissions from everyday necessities such as clothing and housing is greater, and the impact on entertainment-related carbon emissions is small. In addition, rising house prices had the strongest effect on HCEs in central China. Homeowners in the east responded more to increased house prices than in the west, while the inverse effect was observed among non-homeowners. Urban homeowners and rural non-homeowners were also more sensitive to rising house prices. Policy recommendations are made based on the findings.