House Prices Research Articles

Has Cross-City Commuting Promoted Housing Purchases among the Workforce within Metropolitan Areas?—An Empirical Analysis from Micro Survey Data from China’s Three Major Metropolitan Areas

The ability of the cross-city commuting labor force to obtain housing has a profound impact on the development of the housing market and the enhancement of social welfare, but whether cross-city commuting has facilitated housing purchases remains to be verified However, the research on whether cross-city commuting behavior promotes labor force housing purchase in metropolitan areas is still lacking, especially in China, where the culture of buying houses is relatively special. This article used field survey data from the 2023 China Metropolitan Area Occupation and Housing Status Sampling Survey to empirically analyze whether cross-city commuting has facilitated housing purchases within metropolitan areas. The analysis was conducted by constructing a baseline model, a mediation effect model, and a subsample regression model. The results show that the cross-city commuting facilitated housing purchase within metropolitan areas, and the location preference is to purchase a house with a distance of 20–40 km from the workplace, but the contribution of the cross-city commuting to multi-suite purchases is relatively low. Mechanism analysis shows that compared to the workers who work and live in peripheral areas or the workers who work and live in cores, intercity commuters are promoted to purchase housing by relatively higher income and inducement of the housing price gap. The above conclusions still hold after controlling potential endogeneity issues and in robustness tests. The research of this paper can provide a new perspective for alleviating the housing inequality in the metropolitan area.

The relationship between accessibility and land prices: A focus on accessibility to transit in the 15-min city

In the context of local residents’ travel activities, access to transportation facilities is crucial and a key factor in achieving the goals of a 15-min city. However, current research on accessibility and land prices seldom fully considers the exploration of the relationship between the two using machine learning models. In this study, we conduct an analysis based on land price and accessibility in Beijing. Firstly, factors such as accessibility, population density, land use types, the number of Points of Interest (POI), and housing prices are selected as independent variables for the model, with land price as the dependent variable. Secondly, the CatBoost model is employed to investigate the complex relationship between accessibility to transit and land prices. Finally, the study introduces the XGBoost model and the ordinary least squares (OLS) method for comparison, validating the effectiveness of the CatBoost model in studying the complex relationship between accessibility and land prices through the comparison of model performance evaluation metrics. A clear nonlinear relationship exists between public transportation accessibility and land prices. Accessibility to bus within a 15-min bicycle is positively associated with land price; its trend shows a sharp increase followed by a gradual increase, and then another sharp increase. Accessibility to metro within the multistage distance threshold walk has a roughly positive association with land price within a certain range. While accessibility to bus within a 15-min walk and accessibility to bus within the multistage distance threshold walk have a negative association with land price. The nonlinear patterns between the four accessibility variables and land prices differ and exhibit significant spatial heterogeneity. Both housing prices and population density positively correlate with land prices. Housing prices sharply increase, then gradually, while population density gradually rises, then sharply. This paper explores the relationship between the two, reinforcing research on the mutual influence of public transportation facilities and surrounding environmental elements. It provides a theoretical basis for promoting transit-oriented development (TOD) and city planning.

Stimulus Policy in Uncertain Times: Evidence on the Impact in Real Estate Markets

The COVID-19 pandemic introduced historic high levels of economic and policy uncertainty alongside historic accommodative monetary and fiscal policy. Economists have theorized that uncertainty can inhibit market participants’ response to policy stimulus. We empirically tested whether the behavior of house prices following the COVID-19 pandemic is associated with changes in policy and economic uncertainty by examining a sample of 111 housing markets in the United States. We found that while accommodative monetary policy and several rounds of fiscal policy providing direct payments to households were made throughout the pandemic, house prices increased most significantly only after the uncertainty had resolved, nearly a year after the first policy moves. These effects were strongest in higher quantiles of the house price distribution and uncorrelated with the level of cash transfers received in the local housing market.

A Critical Analysis on the Low Birth Rate Problem and the Effectiveness of Relevant Policy

This paper discusses the importance of the birth rate problem and the effectiveness of Chinas Three-Child policy. In order to efficiently elaborate problems, this paper analyses the issue from several perspectives. Firstly, a declining birth rate will have a negative impact on the global and domestic economic development due to the decrease in labour force. Secondly, this paper suggests that the key reason for this declining birth rate is the rising economic pressure on young people. This paper finds that China, Japan, and South Korea face the same low birth rate problem. Hence, this paper investigates the different wage levels and house prices among these East Asian countries and elaborates on the relationship associated with declining birth rates. Furthermore, this paper also discusses how to ensure the successful implementation of the Three-Child policy, and what effect the social welfare and the Three-Child policy can bring to help the society and the economy.

Entrance opportunity vs. academic performance: unpacking the nonlinear capitalization effects of multidimensional school qualities on housing sales and rental prices

It is widely documented that school quality has a capitalization effect on housing prices. However, existing literature has commonly reported a linear relationship between housing sales prices and the academic performance of nearby schools. This study challenges this prevalent understanding by examining how the entrance opportunity as an integral part of school quality affects both housing sales prices and housing rental prices, in response to the newly adopted point-based school enrolment policy in China whereby tenants are allowed to access local public schools but with fewer opportunities compared to homeowners. Employing machine learning algorithms, this study identifies which key school indicators and what ranges of these indicators have significant impacts on different housing sales and rental price segments in Shenzhen, China. Our results reveal that housing rental prices, particularly in the lower-priced segment, are more determined by the entrance opportunity than the academic performance, while the latter is the most important factor influencing housing sales prices. The nonlinear capitalization effect suggests that tenants and homebuyers are willing to pay more for school quality increases only within specific ranges, namely, from median to a relatively high level of school quality. These findings contribute to a more nuanced and updated understanding of the education capitalization effect and thus inform more inclusive and equitable urban planning and governance.

Spillovers of U.S. monetary policy shocks on housing prices in nine emerging economies and their stabilizing capital controls

Spillovers of U.S. monetary policy shocks on housing prices in nine emerging economies and their stabilizing capital controls

Does the size of the housing rental market stabilize regional economic fluctuations? Evidence from China's large- and medium-sized cities

The influence of the housing rental market on economic operations is a significant concern. Particularly in China, the rental market has been undergoing a transition from being disregarded to being valued. Based on an analytical framework referencing the three-sector theory of metropolitan economic growth, this study explores the impact of rental market size on regional economic fluctuations and its influence channels using a panel of 69 large and medium-sized cities from 2010 to 2019. The results indicate that increased rental market size is significantly correlated with decreased regional economic fluctuations through housing sales and labor market channels. Specifically, house price depression, house investment stability, labor allocation, and employment stability effects are crucial channels through which the size of the rental market influences regional economic fluctuations. In addition, the marginal effect of rental market size on regional economic fluctuations is smaller in cities with higher economic development. The conclusions imply that policymakers should not focus on how to unilaterally expand the housing rental market, but should strategically compensate for the defects of regional housing rental–related institutional systems.

Factors influencing housing prices: A case study of Shanghai

Housing is a major consumer good for residents, and housing prices affect people's quality of life and happiness. This paper analyzes the factors influencing housing prices based on the housing price dataset for Shanghai in 2023-2024. Comparison is made via multiple linear regression model to discover the difference between with and without considering interaction terms, assessing the importance and accuracy of the two models' results, and optimizing the model. According to the analysis, living area, decoration type, and building usage are the factors most positively correlated with housing prices. The number of bathrooms, living rooms, and bedrooms also shows a significant positive correlation with housing prices. Additionally, building type and the construction age of the house are negatively correlated with housing prices, and this correlation is very significant. Finally, the housing area weakens the positive impact of the number of bathrooms and bedrooms on housing prices.

Research on house price prediction in UK based on linear regression model

This paper aims to analyze the factors that affect housing prices and predict the trend of housing prices through a linear regression model. This article will use a linear regression model to analyze data on UK house prices from 1952 to 2022. And selected 12 different factors that affect housing prices, using a linear regression model to predict the fluctuations of housing prices. At the same time, a multiple prior regression model was used to explore the importance of each factor in affecting house prices. And the significance of these variables was also compared. The results show that the location of the house, per capita income, housing environment, immigration rate, actual deposit rate and actual loan rate have a significant linear relationship with house price changes, while per capita productivity and house type after the epidemic do not have a significant linear relationship with house price changes. Therefore, UK house prices can be predicted based on the above factors.

House prices and ultra-low interest rates: exploring the nonlinear nexus

House prices and ultra-low interest rates: exploring the nonlinear nexus

Residents’ willingness to pay to avoid crime

How much is a resident willing to pay to avoid a crime in the neighborhood? House price changes following a crime do not fully reflect the willingness to pay to avoid crime. Besides prices the market’s liquidity needs to be taken into account in this context. We detect market freezes following shootings, assaults, robberies, and burglaries. We propose a model, supported by empirical evidence, that combines the price and quantity dimensions into a single measure: economic welfare. The willingness to pay depends on the type of crime and averages between 7% and 18% of house valuations. These predictions are manifolds of the effect on prices estimated in this paper (0%–10%) and documented in the literature. Overall, our findings highlight the importance of considering market liquidity when examining the impact of crime on the real estate market.

Parameters and barriers affecting the marketability of energy efficient residential buildings: a case study in Turkey

ABSTRACT The data indicate that merely improving energy efficiency within energy-efficient buildings (EEBs) is insufficient to significantly reduce the energy demand of the building sector. To achieve substantial reductions, strategies must also focus on increasing the number of EEBs within the existing building stock. However, research in this area remains limited. Therefore, this study aims to explore the current market demand and barriers for EEBs, examine the impact of various design decisions on housing prices, identify the factors influencing the marketability of residential buildings, and analyze customer purchasing decisions in Turkey (Türkiye). For this purpose, a comprehensive literature review was first made. It was observed that factors such as macroeconomic conditions, sales price, housing opportunities, location, brand, customer demographics, energy efficiency, housing features, and aesthetics were frequently discussed in the literature. Based on the literature review and preliminary study results, among other factors, aesthetic appreciation is considered the most applicable design strategy, and windows and balconies are identified as building components that can simultaneously affect energy efficiency, marketability, and aesthetics. Then, as a preliminary study to determine major marketing strategies, the housing marketing strategies were surveyed and analyzed from the real estate sector in different cities as provided in the advertisements posted on their websites. Furthermore, a comprehensive e-mail survey was conducted with 351 different real estate companies amongst 22 cities of Türkiye. Based on the findings, enhancing architectural designs could potentially elevate the perceived value of energy-efficient homes by up to 18% among consumers and this can increase the marketability.

Private school admission policy and the choice of public schools: Evidence from the housing market

The Ministry of Education of China started to introduce “simultaneous admission of both public and private schools” in 2018. Using housing transaction data from 2017 to 2020, we investigate the policy effects on residential properties in Hangzhou. We find increased housing price premiums for public school quality following the introduction of the new policy. The increase in the housing price premium for top-tier public schools was mainly driven by price gains for smaller, simple- and fancy-decorated, and older or quasi-new properties. In addition, we found a relative increase in the transaction volume of properties bundled with the second-best public schools versus those in the top-tier schools. It suggests that the increased price premium have led parents to choose a sub-optimal school quality, which might result in a widening inequality to be enrolled in top tier public schools.

House prices, financing mode and economic growth

This study delves into the intricate relationship between house prices and the economy, using a combined dataset of 287 Chinese cities and incorporating urban investment bonds, local government financing platforms, and land resources statistics. Key findings indicate that rising house prices boosted per capita gross domestic product before the financial crisis, but this effect diminished after the crisis. Although rising prices increased total output, they also heightened local debt risks, resulting in a double-edged impact. The study also found that government policies that caused a rapid increase in house prices disrupted resource allocation, jeopardizing urban sustainability. Research emphasizes the importance of carefully designed policies to ensure the balanced development of the real estate market, which is conducive to long-term economic health.

Unpacking the relation between media sentiment and house prices: A topic modeling approach

This study uses a topic modeling approach to investigate the relation between news media sentiment and house price movements. By examining real estate related articles published in local newspapers of 16 major cities in Canada and Australia, we find that housing media sentiment has significant relation with future house price movements in the Canadian market but not in the Australian market. We identify the specific topics discussed in news media related to the housing market and report differences in their themes and media sentiment's predictive power between Canada and Australia. This analysis presents novel inferences of qualitative and hard-to-quantify information related to the housing market in two different countries.

Performance evaluation of housing price index prediction model using DNN and SVR

This study used the base interest rate, mortgage interest rate, deposit interest rate, consumer price index, exchange rate, and composite stock price index as variables to predict the housing price index. The variables were normalized using the min-max normalization method. Machine learning methods, Deep Neural Networks (DNN) and Support Vector Regression (SVR), were employed to construct a prediction model, and the fit of the model was evaluated using the Root Mean Square Error (RMSE). The analysis results of the DNN model indicated that when applying the softplus activation function, the RMSE was 0.1298, resulting in the smallest prediction error, and the correlation coefficient between the predicted and actual values was highest at 0.9342. The analysis results of the SVR model using the Gaussian RBF kernel showed that the RMSE was smallest at 0.2781 when the parameters were set to C=100 and Gamma=0.1. Therefore, the DNN model was found to be more fit for predicting the housing price index. Additionally, it was confirmed that the consumer price index had a non-linear effect with a positive relationship, and the base interest rate had a linear effect with a negative relationship.

Pricing strategies in the Silicon Valley housing market: an update on TOM and recent events

Purpose This study aims to explore the relationship between house prices and time-on-market (TOM) in Silicon Valley. Previous findings have been inconclusive due to variations in property characteristics. This paper highlights the discrepancy between listing and selling prices and identifies differences among housing types such as condominiums, detached houses and townhouses based on housing orientations and customer groups. Additionally, this study considers the impact of the COVID-19 pandemic and the Fed’s interest rate policies on the housing market. Design/methodology/approach The authors analyze 63,853 transactions from the Bay East Board of Realtors’ Multiple Listing Service during 2018 to 2022. The study uses a multiple-stage methodology, including a nonlinear hedonic pricing model, search theory and two-stage least squares method to address concerns relating to endogeneity. Findings The Silicon Valley housing market shows resilience, with low-end properties giving buyers more bargaining power without significant price drops. High-end properties, on the other hand, attract more attention over time, leading to aggressive bidding and higher final sale prices. The pandemic, despite reducing housing supply, did not dampen demand, leading to price surges. Post-COVID, price correlations with TOM changed, indicating a more cautious buyer approach toward high premiums. The Fed’s stringent monetary policies post-2022 intensified these effects, with longer listing times leading to greater price disparities due to financial pressures on buyers and shifting dynamics in buyer interest. Practical implications Results reveal a nonlinear positive correlation between TOM and the price formation process, indicating that the longer a listed property is on the market, the greater the price changes. For low-end properties, TOM becomes significantly negative, while for high-end properties, the coefficient becomes significantly positive, with effects and magnitudes varying by type of dwelling. Moreover, external environmental factors, especially those leading to financial strain, can significantly impact the housing market. Originality/value The experience of Silicon Valley is valuable for cities using it as a development model. The demand for talent in the tech industry will stimulate the housing market, especially as the housing supply will not improve in the short term. It is important for government entities to plan for this proactively.

Radial analysis and scaling of housing prices in French urban areas

Urban scaling laws summarize how attributes evolve with city size. However, one limitation concerns the aggregate view of this approach, which leads to neglecting the internal structure of cities. This is an important issue regarding housing prices, given their significant variations across space. Based on a dataset compiling millions of real estate transactions over the period 2017–2021, we investigate the regularities of the radial (center-periphery) profiles of housing prices across cities, with respect to their size. Results are threefold. First, they corroborate prior findings in the urban scaling literature stating that largest cities agglomerate higher housing prices. Second, we find that housing price radial profiles scale in three dimensions with the power 1/5 of city population. After rescaling, great regularities between radial profiles can be observed, although some locational amenities have a significant impact on prices. Third, it appears that our approach with rescaled profiles fails to explain housing price variations in the city center across cities. In fact, prices near the city center rise much faster with city size than in the periphery. This has strong implications for low-income households seeking homeownership because prohibitive prices in the center may contribute to pushing them out into peripheral locations, especially in large cities.

Balancing education and real estate: The impact of the teacher rotation policy on school district housing prices

In this study, we use Shanghai as a case study, leveraging extensive housing transaction data from its pilot areas to analyze the impact of the teacher rotation policy on the differentiation of school district housing prices within the city. Our findings reveal that the policy significantly reduces housing prices in high-quality school districts, with the most pronounced effect observed in dual school districts. This suggests that the teacher rotation policy not only promotes a more equitable distribution of educational resources but also curbs the excessive and irrational inflation of school district housing prices in major cities.

The ‘Airbnbisation’ of European cities: legislation for collaborative accommodations

ABSTRACT This study examines ‘Airbnbisation’ in tourist destinations, where professionally-managed properties have surged, affecting housing availability, prices, and community well-being, along with concerns about tax evasion. Despite platforms like Airbnb intending to support the sharing economy, short-term rental regulations struggle to differentiate between collaborative and professional lodgings, complicating oversight. To address this issue, the study examines regulations in 37 cities and evaluates their effectiveness in differentiating between collaborative and professional accommodations. The research proposes new short-term rental legislation using the results of three quantitative techniques. Data on short-term rental regulations, property locations, features, and host profiles were analyzed. Results show that regulations limiting annual rental days and properties per host encourage collaborative accommodations. However, rules controlling guest numbers, requiring licenses (among others) are not adequate to reduce professionalized lodgings. Collaborative accommodations are often found over 5 km from the cathedral, suggesting they aren't primary contributors to city ‘Airbnbisation’. This research aids policymakers in balancing residents' needs and short-term rental interests.