House Price Changes Research Articles

개별 주택가격 데이터를 이용한 주택가격 변동률 분포의 특성 분석*

This study departs from the convention of using only the house price index when analyzing the housing market price change, and examines the market through the lens of house price change distribution. By using a panel data of individual house prices, I find the following. First, house price change distribution has a positive skewness; so, the median is smaller than the mean. Second, when the price index falls, the individual price also falls; however, when the price index rises, the deviation between individual price change increases. Third, even when the price index rises by 10%~20%, 5.2% of the individual houses experience a price fall. Last, the large, high price houses in the capital area shows high price volatility; so, when the price index rises, their price rises more than the average houses, and when the price index falls, their price falls more than the average houses. The results of this study can be utilized in risk management in financial institutions.

An Empirical Analysis of the Benefits of Opening a Highway in Terms of Changes in Housing Prices

This study empirically analyzes the social benefits of opening a highway by assessing the increase in housing prices in two surrounding regions: one defined as the treatment group and the other defined as the control group. Although the two regions are geographically adjacent, they belong to different administrative districts and are physically separated by natural topographical features such as mountain ranges. Both aspects make it so that the interaction or influence between the two regions is limited, which raises the probability that the control group will show a trend similar to that of the treatment group under the influence of economic factors but will not be affected by the opening of the highway. With this in mind, the benefits of accessibility improvement due to the opening of the highway are estimated by using the difference-in-differences framework, i.e., the relative change in housing prices in the treatment group compared to the control group. In addition, the corresponding highway route is analyzed by dividing it into three sections according to their opening times and locations. The findings suggest that the estimated benefits are not fictional but robust. The increase in housing prices due to the opening of a highway is estimated to be, on average, 586 to 3075 dollars per apartment (equivalently, USD 10 to 53 per square meter). These benefits are worthy of being reflected upon, complementary to a traditional cost-benefit analysis.

COVID-19 and entrepreneurial processes in US equity crowdfunding

ABSTRACT The COVID-19 pandemic brought about a shift in entrepreneurial opportunities in the United States. In this paper, we proxy entrepreneurial processes by examining housing prices in different regions of the United States. Housing prices capture the movement in people, tax dynamics, and behavioral preferences for equity ownership in different regions and over time, all of which were drastically impacted by COVID-19. We examine all US equity crowdfunding offerings starting with the very first offerings in 2016 Q2 until 2021 Q1 based on data from the Securities and Exchange Commission. The data indicate that regional housing prices post-COVID-19 are a strong predictor of the number of equity crowdfunding campaigns and the amount of capital raised. Moreover, the impact of housing price changes on crowdfunding is more pronounced among more prosperous regions. The housing price effect is robust to numerous controls and consideration of outliers.

서울 아파트 가격은 거품인가?*

This study analyzed whether the rise in apartment prices in Seoul could be interpreted as a housing bubble since 2017. In terms of the fact that the housing price bubble was difficult to be explained by observable changes in the market environment, this study examined the explanatory power of the endogenous relationship between the change in housing prices and economic variables in the pertinent period. To do so, this study set a model which interpreted how far the rate of change in actual housing prices deviated from the explainable change in basic market environments and applied the model to housing bubbles right before the U.S. subprime crisis (the early and mid 2000’s) and to apartment markets in Seoul after 2017. According to the result, the increase of housing prices in the U.S. markets in the mid 2000’s significantly exceeded the rise anticipated by the change in markets, while the change in apartment prices in Seoul was not considerably different from the conditions that were explained by the change in market circumstances. This suggested that the rise in housing prices in Seoul was caused not by bubbles from excessive expectations or self-realizing predictions but by factors affecting changes in the fundamental values for housing, such as government interventions or monetary policies.

Are The Effect of Housing Prices on Bank Performance Different Among Korean Commercial, Regional and Specialized Banks?

Abstract This study analyzes the effect of housing prices on banking performance in Korea. The findings of the study reveal that the impact of housing price changes on banking performance was different in the commercial banks, regional banks and specialized banks. This seems to be due to the different characteristics of each bank. The three types of banks in Korea have different functions, and thus the impact of changes in housing prices on their respective banking performance is different. Therefore, it would be desirable for Korea’s financial regulatory authorities to draw up policies and perform its supervisory functions in consideration of these points.

지역별 주택 공급과 시장가격 변화는 신혼부부 증감에 영향을 미치는가?

This study aimed to identify the effects of housing supply and price changes by regions for the increase and decrease in newlyweds and spatial causation with demographic-sociological factors for the quality of life and to present implications. To do so, this study used the ordinary least squares regression (OLS) and geographic weighted regression (GWR) models. The main results are as follows. First, the variables in housing markets significantly affected the increase and decrease in newlyweds

Housing Wealth, Fertility, and Child Quality

We use changes in wealth due to house price changes to test the effect of wealth on fertility and child quality in the context of Chinese fertility policies. We find, even in those situations where the one-child policy is not in effect, that wealth increases do not lead to increased fertility in urban areas, and have only a minuscule effect in the rural areas. However, a rise in housing wealth leads to increased expenditure on the education of children for households in both rural and urban areas (although different types of expenditure) and increased height of children in rural areas. Following Becker (1960), increased wealth shifts the tradeoff between child quality and quantity in favor of the former.

Effects of planning regulations on housing and land markets: A system dynamics modeling approach

The effect of planning regulations on housing and land markets has been a long-lasting concern. The inherent complexities of incorporating regulations into models, including the heterogeneity of regulations and their temporal effect, have resulted in different approaches, and consensus has been elusive. Few studies have addressed the effect of regulations in a dynamic framework of the housing and land markets. In these studies, different regulations or the indices capturing their restrictiveness are assumed to have a linear additive effect along with the other factors. The results have been contradictory. This paper aims to model the dynamic effect of regulations by incorporating them in a causal rather than correlational form of relationships. To this end, we adopted the system dynamics approach to model the individual effect of three important types of regulation widely used in urban planning systems: maximum building density, minimum lot size, and urban growth boundary. We use the concept of optimum building density to integrate the housing market and the land market through the construction sector, providing clearer causal links among the related markets. To our knowledge this is the first use of this concept in a dynamic model. We ran the simulations (using hypothetical parameters) to analyze the effect of each regulation on housing and land price changes. The simulation results show that by imposing more restrictive UGBs, housing and land prices increase. A more restrictive MBD first results in a decrease in the land price and, then, due to its effect on the whole housing market, increases both housing and land prices. A more restrictive MLS has a short-term impact on land and housing prices, but it does not change long-run price levels. The common feature of the market under more restrictive forms of all three regulations is lower volatility.

Effects of Urban Expressways on Housing Prices: A Case Study of Qiushi Highway, Hangzhou, China

This paper discusses the effects of the construction of urban expressway on accessibility and further investigates the relationship between changes in accessibility and house prices caused by expressway construction. Taking the Qiushi Highway Phase III project in China as an example, a hedonic price model and difference-in-difference method are used to analyze the impact. The main innovation of the study is how it considers the improvement of the overall traffic conditions brought about by the construction of the expressway. In addition, three distance impedance parameters—namely Euclidean distance, road network distance, and actual transit time—are used to estimate the value of traffic accessibility during the process. The main research conclusions are as follows: (1) The opening of the Qiushi Highway Phase III project can significantly improve the accessibility of the surrounding areas to the city center. Additionally, this improvement can be extended to further sites through the urban expressway network; (2) The results of the difference-in-difference method show that the premium effect of the city expressway on house prices will not be directly generated by the expressway’s geographical proximity to the project. In fact, the expressway will increase accessibility in some related areas and will also have a further positive impact on housing prices; (3) Among the three types of traffic impedance parameters, accessibility calculated on the basis of actual transit time has the strongest connection to house prices.

New housing construction and market signals in urban China: a tale of 35 metropolitan areas.

This paper investigates the equilibrium adjustment mechanism of new housing construction in urban China after the 1998 housing market reform. This analysis is based on a panel of 35 metropolitan areas over the period 2001–2015. The new housing supply function is specified in terms of changes rather than levels to capture the disequilibrium state of the Chinese housing market. In addition, current, one-year and two-year lags of the controls are used to capture the impact of the state control of construction land permits (Land Regulation Act). The main outcome is that new housing construction in the metropolitan areas under study responded to market signals but with relatively long time lags. In particular, during the period 2007–2015, new housing construction positively responded to the one-year and two-year lagged changes in housing prices and construction land supply, negatively responded to the current, one-year and two-year lagged changes in the interest rate, and negatively responded to the one-year lagged changes in construction material costs. The main conclusion is that China’s housing marketization has started to work, although it is still subject to its historical footprints and typical Chinese characteristics, notably state control of the construction land supply.

Spatial Analysis and Modeling of the Housing Value Changes in the U.S. during the COVID-19 Pandemic

COVID-19 has affected almost all sectors of the economy, including the real estate markets across different countries in the world. A rich body of literature has emerged in analyzing real estate market trends and revealing important information. However, few studies have used a spatial perspective to investigate the impact of COVID-19 on property values. The main purposes of this study are as follows: (1) to explore the spatial distribution and spatial patterns of housing price changes during the COVID-19 pandemic crisis in the U.S. real estate market and (2) to model the spatially nonstationary relationships between the housing price change and COVID-19 characteristics. We find that housing price changes differ across space and appear associated with the spatial distribution of the COVID-19 case rates. The housing market volatility is amplified by the uneven distribution of some socioeconomic factors. The spatially uneven housing price changes may bring an uneven spillover effect to the rest of the economy and lead to divergence in economic growth across different areas.

Housing Rental Scheme Based on Redactable Blockchain

With the increase of the housing population, it is very important for renters to find credible housing information through rental platforms. However, due to the imperfection of relevant laws and insufficient supervision of the housing rental market, problems have emerged one after another. In this article, we propose a housing rental scheme based on redactable blockchain, introducing a trusted third party to verify the homeowner rental listings, and fundamentally preventing false listings from flowing into the housing rental market. Specifically, a trusted third party similar to the housing authority will issue a verifiable claim for the homeowners listing, and then the accounting node of the consortium blockchain will publish the verified listing information on the blockchain so as tenants to make inquiries according to their needs. At the same time, we use the new chameleon hash to build a redactable blockchain. After the homeowner proposes to change the housing price or housing information, the content of the historical block is modified as required. Thus, to a certain extent, the changes in housing prices can be monitored to curb chaos in the housing rental market.

United Kingdom general elections and the impact on house prices

PurposeThe paper considers if house price movements in the United Kingdom (UK) can be linked to the political cycle as governments realise homeowners represent a large portion of the voter base and their voting decisions could be influenced by the magnitude and direction of house price changes. Specifically, this paper aims to investigate whether house prices behave differently before and after elections and under different political regimes.Design/methodology/approachThe paper analyses quarterly house price data from 1960 to 2018 together with data on UK parliamentary elections for the same period. Descriptive statistics and significance tests are used to analyse the impact of the political cycle on house price movements in the UK.FindingsWhile there is no evidence that house prices in the UK performed significantly differently under different political parties, the authors observed that house prices performed much better in the last year before an election compared to the first year after an election. On average, house prices increased by 5.3% per annum in the last year before an election compared to 1.3% per annum in the first year following an election.Research limitations/implicationsThe study highlights significant variations in the performance of UK house prices around election times.Practical implicationsIt is imperative that the political cycle is given adequate consideration when making residential property investment decisions.Social implicationsHouse buyers and investors in the residential property market could include the election timings as part of their decision-making process.Originality/valueThis paper represents a unique systematic examination of the influence of the political cycle on residential houses prices in the UK.

COVID-19 and the Mortgage Market in Luxembourg

With a ratio of household debt to gross disposable income above 150%, households in Luxembourg are among the most indebted in Europe. A high level of debt exacerbates the sensitivity of household net worth to changes in house prices, which can increase the severity of economic downturns. In this note, we evaluate the implications of the COVID-19 crisis for the mortgage market in Luxembourg using data on the labour market and government interventions, as well as surveys of consumer finances (HFCS). Our conclusions are twofold. At the aggregate level, the Luxembourg mortgage market is relatively well placed to weather the shock, because a large share of residents work in sectors that are less affected by the crisis such as the financial or government sectors. However, our analysis of micro-level survey data suggests that some segments of the population may be financially vulnerable to the COVID-19 shock.

A New angle on excess consumption volatility in emerging countries: Does house price matter?

This paper focuses on house prices in order to explain excess consumption volatility, which is one of the stylized facts of the business cycle observed in emerging countries. The relative consumption volatility compared to output volatility is higher in emerging countries than in rich countries. Because house prices in emerging countries are more volatile than in advanced countries, this paper suggests a new angle focusing on relationship between house price fluctuation and excess consumption volatility. To begin, I construct a cross-country dataset, and suggest new evidence that house prices are more correlated with consumption in the case of emerging countries compared to rich countries while the correlation between house prices and output are similar between two country groups. Then, I build business cycle models given exogenous house price and output processes in order to explain excess consumption volatility puzzle. The results of the models suggest that high house price volatility in emerging countries causes their excess consumption volatility and that the mechanisms behind it are housing collateral effects and rental price pass-through. The former is related to the borrowing capacity affected by house price changes, and the latter is related to the link between house prices and housing consumption volatility.

Health Crisis and Housing Market Effects - Evidence from the U.S. Opioid Epidemic

We present evidence on the effect of a public health crisis on housing markets through the lens of the recent opioid crisis in the U.S. Using data on opioid prescriptions and repeat sales in Ohio, we find that house price changes around opioid dispensaries are negatively associated with the quantity of opioids dispensed. To explore a causal inference, we use a potentially cleaner measure of supply that is based on vertical integration. We estimate that a one standard deviation increase in the standardized number of pills dispensed by vertically integrated pharmacies is associated with a 5.8% decrease in house price appreciation. Our work informs the broader policy discussion on economic costs resulting from health crises.

Research on the Impact of Market Concern for Real Estate Policy on Housing Prices: Evidence from Internet Search and Hedonic Price Theory

To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price, the Chinese government has been exploring the most effective policies for regulating the housing market. Measuring the effect of real estate regulation policies has been a challenge for present studies. This study innovatively employs big data technology to obtain Internet search data (ISD) and construct market concern index (MCI) of policy, and hedonic price theory to construct hedonic price index (HPI) based on building area, age, ring number, and other hedonic variables. Then, the impact of market concerns for restrictive policy, monetary policy, fiscal policy, security policy, and administrative supervision policy on housing prices is evaluated. Moreover, compared with the common housing price index, the hedonic price index considers the heterogeneity of houses and could better reflect the changes in housing prices caused by market supply and demand. The results indicate that (1) a long-term interaction relationship exists between housing prices and market concerns for policy (MCP); (2) market concerns for restrictive policy and administrative supervision policy effectively restrain rising housing prices while those for monetary and fiscal policy have the opposite effect. The results could serve as a useful reference for governments aiming to stabilize their real estate markets.

The effect of COVID-19 on the USA house market

The purpose of this study was to understand the varying effects of COVID-19 on the median house price in metropolitan areas in the USA. Recently, the demand for houses has increased due to the COVID-19 pandemic. The pandemic increased the desire to stay indoors and introduced working from home. Four different factors were tested for their impact on the housing market: number of COVID-19 deaths, number of available houses for sale, unemployment rate, and mortgage interest rates. The control in this study was 2018-2019 house price data. We hypothesized that the house supply would cause the greatest change in house prices. Ckmean clustering method was applied to separate 93 metropolitan areas of the USA into three groups with different median house price levels. We then conducted linear regression modeling for each group to determine the varying level of effect each of the variables had. The results suggested that unemployment rate had the largest correlation with house prices, especially for metropolitan areas with extremely high house prices. This result did not support the research hypothesis. Further research could clarify the findings of our study by using fine-turned modeling techniques and including more economic factors like immigration or tourism. Additionally, we can research the effect of COVID-19 on house prices globally.

Gulf property damage, housing price trends and US bankruptcy filings

PurposeThis paper aims to examine potential causes of bankruptcy as they relate to hurricane damage. Investigate whether hurricanes result in personal bankruptcy filings due to real property damages. Strengthen existing descriptive results by using fully modified ordinary least squares (FMOLS).Design/methodology/approachLagged FMOLS model is used with data from states that suffered hurricane damage between 2000 through 2020. FMOLS controls for various financial distresses that can cause bankruptcy filings.FindingsBankruptcy is usually filed for within one year of a hurricane. Changes in house prices and hurricane severity were significant indicators of bankruptcy filings. However, the divorce rate, commonly thought of as a primary reason for bankruptcy, is insignificant.Research limitations/implicationsData was available on a state level for the independent variables. Hurricane damage needed to be financially significant enough for inland flooding to be measurable and influential.Practical implicationsEstablishes that financial distress comes from several sources, not just home damage. Financial distress is highly correlated with whether a home was insured. Divorce does not cause bankruptcy filings.Social implicationsFederal flood insurance programs should be reexamined. Having a broader all-risk homeowner policy could reduce the number of households that file for bankruptcy after a hurricane.Originality/valueExisting research uses descriptive statistics and obtains mixed findings regarding the association between hurricane damage and bankruptcy filings. The FMOLS approach provides clarity about this association.

Housing wealth shocks, home equity withdrawal, and the claiming of Social Security retirement benefits

AbstractThis paper examines the impact of changes in house prices on when eligible individuals start receiving Social Security benefits. If house prices appreciate, financially constrained households may draw upon the additional home equity and delay receipt of Social Security. To address concerns that house price changes are correlated with unobserved local demand shocks, we use a control function approach and two different instrumental variables. We find that individuals delay Social Security claiming when house prices increase during the housing boom period. We also find that the total home loan amount increases, indicating households are drawing upon their home equity.