Housing Price Level Research Articles

An Approach to Analyzing Migration Flow and House Price Data: Exploring Spatial Linkages between Flow, Price, Distance, Age at the Local Level

This paper is intended to elucidate the efficacy of employing a Geographic Information Systems (GIS) methodology to investigate the spatial interrelations among migration flows, housing prices, age demographics, and geographical distances. Utilizing data on migration flows and housing prices from Greater Manchester, UK, in 2011, in this study, we performed statistical analyses and generated a suite of visual mappings to illustrate the spatial dynamics between migration patterns, distances, age brackets, and the segmentation of migration destinations by housing price tiers. The findings reveal pronounced spatial associations among migration destinations, underscored by the interplay of housing price levels with age categories, distance intervals, or the origination points tied to specific housing price ranges. This GIS-based analytical framework offers policy-makers and urban planners a powerful tool for discerning distinct migration trends and locales, thereby facilitating more informed decision-making processes.

Industrial robot applications and individual migration decision: evidence from households in China

The integration of industrial robot application (IRA) into various sectors has catalyzed significant transformations in the labor market, reshaping the dynamics of individual migration decision (IMD). As industries increasingly adopt automation, the implications for workforce distribution and migration patterns become critical areas of study. Based on the conditional logit model and using CMDS data, this paper explores the relationship between IRA and IMD, as well as the heterogeneity effect and influencing mechanism. The findings indicate that IRA reduces the probability of the floating population choosing the city, and the results are robust after considering endogeneity and further robustness test. The impact of IRA on IMD is heterogeneous. Relatively speaking, the floating population with high education levels, health, younger, unmarried, female, agricultural household registration, state-owned enterprises, and non-routine task work does not over-think the impact of IRA during the migration process. In addition, the floating population also considers geographical location, city size, marketization level, wage level, and environmental quality when making migration decisions. the mechanism test shows that IRA attracts or suppresses the floating population through factors such as wage levels, housing price level, difficulty in finding a job, etc., depending on the result of individual utility maximization. These insights reveal the complex interplay between technological advancements in robotics and labor migration, emphasizing the need for comprehensive policy frameworks to manage these transformations effectively.

Geographic Information System-Based Approach and Analysis of Housing Mismatches in Searches during Housing Selection

This study aimed to explore the spatial interaction between search flow and house price levels. It utilized migration flow data from 2011 and house price data from the same year in Greater Manchester, United Kingdom. The methodology included Chi-square tests and a series of visual maps to explore and visualize the relationship between current areas and search areas. The study examined five house price ranges with matches and mismatches between search patterns and current patterns and tried to illuminate the underlying causes. The research results could prove beneficial for policymakers and planners in discerning distinct migratory patterns and geographical regions, thereby facilitating the formulation of well-informed decisions.

Estimating regional house price levels

While quality‐adjusted indices tracing the evolutions of regional house prices are increasingly available, this is less the case for data on regional house price levels. Yet, such information is fundamental to assess housing affordability and barriers to labour mobility. This article puts forward a method to compile regional house price levels that are consistent with the evolutions given by house price indices, representative of the underlying stock of dwellings, and based on the information on house price levels that is available at all dates rather than in a single reference period. Results for Spain show that the decline in house prices following the 2008–2009 crisis initially reduced the dispersion in house prices across Spanish regions, but this dispersion has increased again afterwards. Moreover, the relative housing affordability of Madrid deteriorated compared to all other Spanish regions in the last decade. Monitoring whether COVID‐19 will reverse this trend will be key.

Revisiting international house price convergence using house price level data

The literature on house price convergence largely relies on house price indices, based in an arbitrary year, rather than on actual price levels. This is essentially due to the scarcity of comparable house price level data. However, this severely constrains the analysis. In particular, it often forces to discard a large part of the data sample, which leads to a great loss of information and hampers analysis on sub-periods. In this paper, we combine the price level estimates produced by Bricongne et al. (2019) with long OECD house price series to analyse long-run house price convergence across 18 OECD countries. Applying the Phillips and Sul (2007) procedure, we find convergence in OECD nominal house prices, but two separate convergence clubs in real house prices. We find some convergence in euro area real house prices, but no evidence of strengthening after the introduction of the euro. β-convergence regressions (linking changes in house prices to their initial levels) point to conditional convergence, related to the evolution of gaps in real GDP per capita, long-term interest rates and population growth across countries.

House price, gender spatial allocation, and the change of marriage matching

<abstract> <p>We investigated the relationship between changes in housing prices and marriage patterns among Chinese residents, considering the evolving real estate market and increasing prevalence of homogamous marriages. Using microdata from the China Household Income Project (CHIP) and urban housing price data, our results showed the following: First, housing price levels significantly decreased the likelihood of residents engaging in hypergamous mating and marrying individuals from lower social strata. Second, regional fluctuations in housing prices could influence residents' marital matches by affecting the spatial distribution of genders. Specifically, the higher the level of urban house prices, the greater the crowding out effect on marriageable men, and the less likely men in that area were to match downwards and marry women from lower social classes. Third, heterogeneity analysis indicated that residents in the eastern regions, younger populations, and migrants faced greater housing price pressures in the process of marital matching, resulting in a more substantial impact on these groups. The study contributes to marriage matching theories and offers policy insights for real estate reforms.</p> </abstract>

A Study on the Correlation Between School District Housing Price and Birth Rate in Beijing and Kunming

In China, under the influence of traditional thinking, peoples enthusiasm for buying houses is constantly rising, and the real estate market has always been enthusiastically sought after in China. On this basis, with the development of the economy, it has slowly evolved into school district housing, central business district housing, new city housing and other room types. School district housing has become a hot topic of concern in the whole society. Some researchers believe that fluctuations in the freshman population affect school district housing prices, but there is still a lot of room for research on this view. Therefore, this paper analyzes the correlation between the new population and the housing prices of school districts in representative cities in China by collecting the data of Chinas new population in the past decade, as well as the highest transaction price and average annual transaction price of school districts in China. The study found no correlation between birth rates and house price levels. There is a positive correlation between the birth rate and the growth rate of house prices.

Credit supply shocks, home purchase volume, and borrowing behavior

AbstractWe exploit the 2007 private label securitization (PLS) freeze as a quasi‐experiment to study the impact of a negative credit supply shock on home purchases and borrowing behavior. Using a difference‐in‐differences estimator, we show that a negative supply shock to first‐lien mortgages has little impact on the volume of purchases financed with a mortgage, but significantly reduces the average first‐lien loan balance. Much of this reduction in loan balances is the result of increased bunching at the conforming loan limit that is achieved through a combination of greater second mortgage utilization and larger downpayments. Importantly, we find significant heterogeneity in the response to the mortgage supply shock across borrower characteristics and house price levels. Home purchase volume does decline after the shock for less creditworthy borrowers and in expensive locations. The reduction in first‐lien balances is fairly uniform across borrower types, however, the effect is slightly more acute in less expensive areas. Our results suggest that financial market frictions (e.g., downpayment constraints, imperfect credit) play an important role in determining how credit supply shocks impact housing purchases and borrowing behavior.

Tracking Home-Owners’ Sentiments: Subjective Indices and Convergent Validity

Abstract Surveys regularly ask home-owners to guess what their property might be worth in the current housing market. We develop suitable statistical techniques to construct hedonic and repeat-sales style house price indices from these owner-estimated values (OEVs). The resulting series are then linked to a large set of quality-adjusted residential property price indices estimated from transaction data allowing us to perform a variety of convergent validity tests. Based on results for 20 countries, several decades and different OEV elicitation techniques, we conclude that the “wisdom of the home-owner crowd” is sufficient to study objective house price dynamics. Yet, surveys fail to accurately measure house price levels.

서울 주택구매력지수의 변화가 지방거점도시 주택시장에 미치는 영향에 관한 연구

This study attempted to derive the effect of changes in the Seoul Housing Purchasing Power Index on apartment prices in Jeonju, one of the representative non-metropolitan base cities, and to understand its meaning. The analysis method used VECM in consideration of the characteristics of the variables measured in time series. The summary and implications of the results of this study are as follows.
 First, the change in housing purchasing power in Seoul was found to be one of the main variables affecting apartment prices in Jeonju, a local hub city, and in particular, it was found to have a significant impact on the lag behind. In other words, if housing prices in the Seoul metropolitan area soar and housing investors' ability to invest in the Seoul metropolitan housing market decreases, it is interpreted that they are interested in the apartment market in local hub cities with relatively high price advantages over some time difference. Second, it was found that the change in the population had the greatest effect on apartment prices in Jeonju. Finally, unlike research results on housing prices in Seoul and the metropolitan area, changes in major macroeconomic environments such as total currency, economic growth, and consumer price index did not significantly affect housing prices in Jeonju. This result is judged to be because the level of housing prices is very low compared to the metropolitan area, and the merit as an investment good or an inflation hedge is not high.

Modelling Household Mortgage Debt: the case of the Czech Republic

This paper deals with Czech household mortgage debt and its determinants in the period 1Q2005-2Q2021. Our analysis focuses on the variables determining the level of mortgage debt from both short- and long-term perspectives. Our contribution is two-fold. Firstly, we examine the relationship between the selected variables within a cross-correlation analysis. The results confirm the positive dependency of household mortgage debt and real GDP, real gross average income and the level of house prices. By contrast, a negative relationship was identified for real interest rates, the unemployment rate and the inflation rate. Secondly, we explore the ARDL and EC models and identify one cointegration relationship. Our results confirm that house prices and real wages are determinants of household mortgage debt in the long-term perspective. However, a wider range of variables plays a role in the short run, including house prices, real gross average income, inflation and long-term interest rates. Moreover, our model indicates the insignificance of unemployment in both the short and long run.

Migration, the Quality of Life, and Economic Opportunities in the U.S. Revisited: Impacts of Round-Trip Work Commute Time and Rent or Single-Family Housing Prices

Given the importance to businesses of having a better understanding of factors that influence migration, this study argues that there are two dimensions of the quality of life and economic opportunities that have largely been ignored in previously published studies of migration patterns in the U.S.: the impacts of (1) the costs of commuting between one’s residence and one’s place of employment and (2) apartment rent-levels and single-family housing price levels. It is hypothesized here that the greater the commute time between one’s prospective place of residence and one’s prospective place of employment, the greater the costs associated with in-migration to that potential residence in terms not only of the value of time expended round-trip in commuting but also the opportunity costs and mental health costs (stress) of that time along with the greater pecuniary costs that accompany longer commutes. Therefore, it is hypothesized that in-migration to an area is a decreasing function of commute time associated with that area. A second hypothesis proffered here is that greater housing-cost levels reduce disposable real income and hence utility. More specifically, we argue that either higher apartment rent levels or higher prices on single family homes reduce disposable real income and thereby reduce household well-being; hence, in-migration to an area is hypothesized to be a decreasing function of those higher rent levels and higher home prices. Based upon panel 2SLS estimates, where net in-migration and gross in-migration over the 2010-2017 period are separately considered, there is strong initial empirical support for both hypotheses.

Intensi Generasi Milenial Kota Banda Aceh terhadap Produk KPR Syariah

Fulfilling basic needs in the form of houses (boards) is different from meeting the needs of clothing (clothing) or food (food) because the minimum level of house prices is far above the wage level (UMR/UMP/UMK). Mortgage is one way to get housing, in the midst of rising house prices today. The millennial generation (born 1981-1996) is the largest composition of the Indonesian population today, in Banda Aceh the number reaches 25.87%. The digitally oriented millennial life affects the way they shop. This study aims to analyze the intentions of the millennial generation towards Islamic mortgage financing products in fulfilling their maqasid sharia. The sample was selected randomly from 76 respondents from the millennial generation population in Banda Aceh. Quantitative research using primary data (online questionnaire) results that of the four background factor variables studied, only the income level is effective separately in influencing the millennial generation's intention to get a Sharia mortgage. While other factors, age, level of education, and reasons for not being effective enough did not have a significant effect. However, when taken together, the four variables have a significant influence with a contribution of only 0.205, so that it is still inadequate in predicting the intention of the millennial generation towards Sharia mortgage financing products.

Air quality affects house prices — Analysis based on RD of the Huai River policy

Based on the quasi-natural experiment of the Huai River policy in China, this research attempts to demonstrate the causal relationship between the Huai River policy, air quality and house prices, as well as the underlying logical mechanism. This paper's findings suggest that the Huai River policy leads to higher concentrations of air pollutants such as PM10, SO2and PM2.5 in cities north of the Huai River than in the south, and lower real estate prices in cities north of the Huai River than in the south. Secondly, air quality significantly affects house prices.For every 1 unit increase in PM10 concentration, house prices will decrease by 0.24%; for every 1 unit increase in PM2.5 concentration, house prices will decrease by 0.37%; and for every 1 unit increase in SO2 concentration, house prices will decrease by 0.24%. Finally, by tracing the potential mechanisms, the results SO2 show that the Huai River policy reduces the air quality in the northern region, and then has a restraining effect on the northern housing price level, and there is no alternative path for the Huai River policy to affect house prices.

Value capitalization effects of green buildings: A new insight through time trends and differences in various price levels

While many studies have explored green buildings, there remain many unsolved questions about how to expand this section of the housing market, such as how the capitalization effect of green buildings varies across time and location. This study investigates the price premiums of green buildings in Taipei City, the largest metropolis in Taiwan, to examine how they have changed over time, and assesses the magnitude of the capitalization effects under varying housing price levels. The empirical results indicate that Taipei residents are willing to pay higher prices for houses with green-label certification. The higher the certification level, the higher the price that residents are willing to pay. This study additionally identifies two characteristics of the capitalization effects in this market. The first is that the price premiums vary with the market condition. For example, during housing market downturns (e.g., 2014–2015), building green premiums may be unremarkable or non-existent. The second effect identified is that green buildings tend to exhibit an ‘aristocratic trend.’ This means that high-priced houses (i.e., houses priced above the 80% quantile) in the high-end label category attract the highest premiums, implying that the willingness to pay for green features tends to only exist among wealthy buyers. The result of this paper provides evidence to explain the heterogeneity of green build premiums. Regarding the specificity of these premiums, this paper provides recommendations for builders and managers.

How is housing purchase intention related to consumption? The role of market sentiment

Recent literature has widely discussed how housing price is linked to consumption and tenure choices, while tended to ignore that consumption and tenure choices are inter-correlated. This study employs the simultaneous equation model to explore how the housing purchase intention affects the non-housing consumption, considering the role of housing market sentiment. The result shows, on average, the housing purchase intention is associated with higher non-housing consumption, and a higher sentiment magnifies this positive relationship. Housing price level and growth decrease the household’s enthusiasm of purchasing a new house, while sentiment is positively related to the housing purchase intention. Renters’ behavior is less likely be affected by sentiment. In addition, the heterogeneous analysis indicates that households face a trade-off between housing and certain kinds of commodities. This study has some significant, practical implications on optimizing households’ wealth allocation, implementing housing policy and improving the social welfare.

Characteristics of Single-person Households Affecting the Use of Housing Support Programs: Focus on Demographics characteristics, Socio-economics characteristics, and Residential Characteristics, Housing Perception

In order to improve the effectiveness of the housing support program, this study analyzed the characteristics of single-person households that influence the use of the program and suggested policy. It was found that single-person households have relatively lower educational levels and housing price level than multi-person households, and notably have low-income. As a result of analyzing the characteristics of single-person households that use the housing supply program, the utilization rate of single-person households willing to buy their own homes and households willing to move into public housing was low. It is noteworthy that the utilization rate of households living in the metropolitan area and self-owned households is low, and the utilization rate of the elderly is higher than that of other age groups. The housing needs of single-person households are different according to each regional situation, and this response can be used to establish appropriate housing policies when cooperation between the central and local governments is achieved. In addition to the policies currently in operation, we hope that this study will serve as a starting point for establishing measures to improve the effectiveness of the housing support program for single-person households in the future.

The housing cycle as shaped by prices and transactions: a tentative application of the honeycomb approach for Italy (1927–2019)

PurposeThe purpose of this paper is to provide a dating system for the Italian residential real estate market from 1927 to 2019 and investigate its interaction with credit and business cycles.Design/methodology/approachTo detect the local turning point of the Italian residential real estate market, the authors apply the honeycomb cycle developed by Janssen et al. (1994) based on the joint analysis of house prices and the number of transactions. To this end, the authors use a unique historical reconstruction of house price levels by Baffigi and Piselli (2019) in addition to data on transactions.FindingsThis study confirms the validity of the honeycomb model for the last four decades of the Italian housing market. In addition, the results show that the severe downsizing of the housing market is largely associated with business and credit contraction, certainly contributing to exacerbating the severity of the recession. Finally, preliminary evidence suggests that whenever a price bubble occurs, it is coincident with the start of phase 2 of the honeycomb cycle.Originality/valueTo the best of the authors’ knowledge, this is the first time that the honeycomb approach has been tested over such a long historical period and compared to the cyclic features of financial and real aggregates. In addition, even if the honeycomb cycle is not a model for detecting booms and busts in the housing market, the preliminary evidence might suggest a role for volume/transactions in detecting housing market bubbles.

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.

Boon or Burden? Evaluating the Competing Effects of House-Price Shocks on Regional Entrepreneurship

This paper examines the impact of changes in housing affordability on regional entrepreneurship. Two-way fixed-effects estimates suggest an increase in the level of house prices in a commuting zone results in a decline in establishment openings as a share of existing establishments—consistent with a crowding-out effect. In contrast, an increase in the growth rate of house prices results in a small (although not always statistically significant) increase in establishment openings—consistent with a positive wealth effect from capital gains. To address endogeneity concerns, the authors adopt two alternative instruments for commuting zone house-price growth: a measure of local real estate lending and a geography-based measure of the elasticity of local housing supply. They extend the analysis using restricted-use establishment-level microdata from the Quarterly Census of Employment and Wages (QCEW) for the state of Colorado. Results from the QCEW data are consistent with those from the commuting zone sample.