Higher Housing Prices Research Articles

How to enter high-opportunity places? The role of social contacts for residential mobility

The aim of this article is to analyze the contribution of social ties to moving to high-opportunity locations and assess whether their effect is more pronounced for low-income individuals as a compensation for economic resources. This is done by utilizing Swedish administrative data and by focusing on a wide range of relationships (observed directly or inferred from the data): close and distant family ties, former co-workers and university peers. For estimating the effect of social ties, we use linear probability models, where observed migration is regressed on individual-specific and target-specific characteristics. To account for the nonrandom sorting of movers between locations, we apply sending municipality–target municipality–occupation fixed effects. Our results suggest that there is a positive relationship between migration and the presence of links at given targets for all the examined contact types. The effects are even stronger if the targets are hard-to-reach municipalities (located in Stockholm County or a municipality with higher housing prices). We also demonstrate that, when moving to such opportunity-rich areas, ties to former co-workers and university peers are even more essential assets for those with limited resources. Furthermore, we show that direct help with housing through contacts is an existing factor that contributes to the effect of social networks on residential mobility. The results reinforce the idea that social ties may be of great help in reducing barriers to mobility and can be used to compensate for limited economic resources. We demonstrate the validity of our fixed-effect estimation strategy using a placebo contact approach.

Impact of proximity to thermal power plants on housing prices: Capitalizing the hidden costs of air pollution

This study explores the impact of the Taichung Thermal Power Plant in Central Taiwan on the housing prices of surrounding houses and employs empirical data to capitalize the hidden costs of air pollution. This power plant is the fourth largest in the world and operates mainly through coal burning, in addition, the power plant is still under expansion. The operation of such a large-scale power plant influences the surrounding environment. To reasonably evaluate the cost of thermal power generation, this study capitalizes the impact of proximity to thermal power plants on housing prices and proposes evidence indicating that proximity to thermal power plants has a significant effect on decreases in housing prices, and the closer the distance to the thermal power plant, the more housing prices fall. Additionally, the impact of proximity to the thermal power plant on housing prices is greater in areas with high housing prices. The presence of the thermal power plant within 15 km resulted in housing prices dropping by approximately 25%. This study proposes including negative externalities in the costs of thermal power generation to accurately reflect in the power generation costs and energy prices. This would incentivize power plant operators to invest in more environmentally friendly power generation methods and relieve the burden shared by residents living in proximity to the power plant.

Public Education Inequality and Intergenerational Mobility

Public school funding depends heavily on local property tax revenue. Consequently, low-income households have limited access to quality education in neighborhoods with high house prices. In a dynamic life-cycle model with neighborhood choice and endogenous local school quality, we show that this property tax funding mechanism reduces intergenerational mobility and accounts for the spatial correlation between house prices and mobility. A housing voucher experiment improves access to schools, with benefits that can last for multiple generations. Additionally, a policy that redistributes property tax revenues equally across schools improves mobility and welfare. However, the benefits can take generations to be realized. (JEL H71, H75, I21, I22, J62, R23, R31)

Overheated behaviours and spread effects: an analysis of London’s housing market

ABSTRACT This paper takes the London housing market as an example to discuss whether housing markets with more significant overheating effects have a greater influence on other housing markets. The spillover effect of London’s housing market has been the subject of much literature, but the empirical results of the relevant literature are inconsistent. This paper proposed a new perspective to explain these inconsistent conclusions: Whether the housing market is overheated or not can affect the spread effect of a regional housing market. The paper estimated the indicators of real estate overheated behaviours and market connectedness. Further, it revealed that when real estate overheated behaviours became more severe, the irrationally high house prices resulted in spread effects. The empirical results also showed that when the overheating effect occurred in London’s housing market, the rental yield of its adjacent regions significantly increased; specifically, the rental yield of a region increased with its closeness to London. The results of this study provide an explanation for the variation in spread effects. This study also indicated that when studying the influence of the relatively booming housing markets on other regions, it is necessary to test the prosperity status of these housing markets to more accurately estimate the spread effects of these markets.

What attracts young talents? Understanding the migration intention of university students to first-tier cities in China

In recent years, China has witnessed fierce competition for talents among cities. There is evidence that China's first-tier cities are losing their appeal for young talents due to the soaring housing prices and high living costs in first-tier cities, as well as the catch-up of next-tier cities. Therefore, uncovering what factors drive young talents to develop in first-tier cities is important for policymakers to maintain and enhance the attractiveness of first-tier cities. Most previous research on talent migration has focused on demographic and socioeconomic factors, while little research has examined the influence of psychological factors. By adopting the Theory of Planned Behavior (TPB), this paper aims to explore what beliefs and background factors influence university students' intention to develop in first-tier cities after graduation. Using the data we collected from 1242 university students across China, we found that two-thirds of university students have the intention to develop in a first-tier city after graduation. The Structural Equation Modeling (SEM) results show that students' migration intentions were most influenced by their attitudes, followed by subjective norms and perceived behavioral control (PBC). Specifically, beliefs such as realizing future dreams, better job opportunities, and higher wages shape students' positive attitudes towards developing in first-tier cities. The supports from family, friends, teachers, and classmates contribute to positive subjective norms of developing in first-tier cities. In contrast, perceptions of high housing prices, high living costs, and family ties discourage students from developing in first-tier cities. Furthermore, being male, being a non-only child, studying in first-tier cities, and attending higher-ranking universities have positive influences on migration intention through the mediating effects of the TPB constructs. Policy implications were discussed to help first-tier cities attract graduates.

The relationship between residential development land prices and house prices

There exists apparent disagreement between two areas of literature regarding the relationship between house prices and land prices. In the professional literature it is argued that high house prices cause high residential development land prices. In some of the policy literature it is argued that it is land-price increases that are behind increasing house prices. We argue that this is a rather artificial dichotomy and arises from two different ways of thinking about the relationship between land and house prices. To demonstrate this we explore how housing and residential land markets work and how their price responses are interrelated. Published open access under a CC BY licence. https://creativecommons.org/licences/by/4.0/

Spatial-Temporal Change Trend Analysis of Second-Hand House Price in Hefei Based on Spatial Network.

Spatial Markov chain can effectively explore the spatial evolution trend of housing price under the influence of lag factor. This paper uses spatial autocorrelation and spatial Markov to study 353 second-hand houses in Hefei. The results show that (1) the housing price of Hefei urban area presents a situation of “two points and one side,” the high housing price is concentrated in the south and southwest of the urban area, and the price level gradually weakens from south to north, and the housing development shows a north-south differentiation. (2) There is a significant spatial autocorrelation between second-hand housing prices in Hefei. The “high-high” residential price clusters are mainly distributed in Shushan District and Binhu New Area, while the “low-low” residential price clusters are mostly in Yaohai district and its surrounding areas. The number of “low-high” agglomeration and “high-low” agglomeration is small, and the degree of change is not big. (3) Under the influence of different neighborhood environments, the housing prices in urban Area of Hefei show club convergence overall. At the same time, under the short-term influence of the policy, the housing prices of low level and middle and low level are promoted in the same neighborhood environment, while the housing prices of high level and middle and high level are negatively affected.

Assessing the Equity of Accessibility to Urban Green Space: A Study of 254 Cities in China.

Urban green space has environmental benefits of purifying the air, reducing the heat island effect and providing the social and economic benefits of rest places and social platforms. An integrated and organized green space system is important for fully realizing the positive functions of an urban ecosystem. Previous studies have considered green space supply and demand, but few studies have examined large-scale, diverse and small-scale systems, making it difficult to conduct a comparative study of urban green space accessibility and equity under the same conditions (such as data sources and calculation methods). Using the two-step floating catchment area method, this study evaluates the equity of 254 urban green spaces in China within four ranges of accessibility: 1 km, 2.5 km, 5 km and 10 km. The study also considers urban house price in the research. The results show the following: (1) There are large differences in the accessibility of green space between different cities in China. Within the accessibility threshold of 10 km, the city with the most accessible urban green spaces has an accessibility level that is 27,813 times that of the city with the lowest accessibility. (2) Within the range of walking/cycling, there are significant inequalities in green space access in the 254 cities; the inequality of green space accessibility in most of the studied cities is at the “dangerous” level. (3) The two-step floating catchment area method indicates that the social superiority (high social class) represented by high housing prices is associated with a greater opportunity to access urban green space services. This paper highlights the main problems associated with the accessibility of urban green space in China and proposes targeted development recommendations. These recommendations provide a reference for urban managers to develop effective green space development policies and realize the optimal allocation of urban green space.

Spatial-temporal effects of urban housing prices on job location choice of college graduates: Evidence from urban China

Attracting college graduates is crucial for the local government to (re)drive socioeconomic development. Location choice is subject to a variety of factors and the influence of housing prices is usually considered. Soaring housing prices would have a dual effect on the willingness to work and live in a particular city. Using multinomial logit models based on the China Labor-force Dynamics Survey (CLDS), this study examines the spatial-temporal influence of housing prices on college graduates' job city selection. It concludes that while housing costs in the workplace can have an attractive effect, these intentions to work in large cities will wane as long as housing costs remain high. Before the tipping point of housing prices, cities with higher housing prices, which are considered to offer better employment and public service prospects, might draw considerable inflows of graduates. After exceeding the tipping point, rising housing prices gradually stifled college students' influx. Hometown housing prices serve as an essential benchmark for college graduates' city choices. This study emphasizes the critical need for housing price stabilization and inclusive housing policies such as the provision of affordable housing and subsidized talent housing to attract and retain talent groups.

Revisiting Hukou Transfer Intentions Among Floating Population in Chinese Cities: Spatial Differences and Multi-Level Determinants

The hukou transfer intentions (HTI), as an essential indicator of migration behaviors, is of great significance to the urbanization development and the citizenization process of China’s floating migrants. Although extant studies have devoted extensively to the influence factors of HTI, their spatial differences and multi-level determinants are comparatively under-researched. Based on the China Migrants Dynamic Survey (CMDS) data in 2016, we employed the spatial analysis method to discover a remarkable spatial disparity of HTI among cities of different sizes and found that HTI is affected by individual-level and city-level factors using a multilevel model. Besides city sizes and economic development levels, city amenity factors and housing prices also positively impact HTI. The cross-level interactions also indicate the greater preference of older, higher-educated, and wealthier floating migrants for larger cities than their counterparts, and the greater preference of older, higher-educated, and longer-term floating migrants for cities with higher housing prices than their counterparts, implying an accelerated agglomeration of talent with more social capital in leading cities. Several policy implications can be drawn from the discoveries of this study.

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.

Short-Term Property Rental Platforms and the Housing Market: House Prices and Liquidity

This article examines how the short-term peer-to-peer rental market impacts the housing market. Instead of examining premier tourist destinations, our analysis is in a typical state within the United States – Wisconsin (ranked about 20th in terms of population and output). Our results indicate that a doubling of Airbnb properties in a neighborhood increases the price of housing by approximately 11%. However, the impact is heterogeneous. For example, the impact of Airbnb is largest in less dense neighborhoods with high house prices. By contrast, there is no price impact at all in the most urban and dense neighborhoods. We found no consistent evidence that the presence of Airbnb effects liquidity.

2021 KLEIN LECTURE: AMERICAN DREAM DELAYED: SHIFTING DETERMINANTS OF HOMEOWNERSHIP

AbstractWe develop and estimate a dynamic model of female labor supply, fertility, and transition from renting to first homeownership with panel data, to investigate declining U.S. homeownership over the past decades. Higher house prices and increased female wage rates (that is the opportunity cost of leisure) cause households to postpone their first‐home purchase, because leisure and fertility are complementary to homeownership. Education and female workforce participation are reinforcing factors that raise the value of owning a home. Our estimates show the effects of rising house prices and wage rates more than offset the effects of greater education and workforce participation.

City Size and Permanent Settlement Intention: Evidence from Rural-Urban Migrants in China.

The location choice and livelihoods of rural-urban migrants are critical to the sustainable development of cities. By using data from the China Migrants Dynamic Survey (CMDS) in 2017, this paper extant the Rosen–Roback’s model by adding factors of urban social network and air pollution to the function of the individual utility of migrants. Both the Probit Model and IV estimates imply evidence of an inverse U-shaped pattern of city size and migrants’ permanent settlement in urban China. This view proves that Chinese migrants like to settle permanently in large cities, but not mega-cities, such as Beijing and Shanghai. The internal mechanism is explained by the agglomeration economies and the crowing effect brought by city size. In mega-cities, the attractiveness of the city caused by wage premium cannot offset the combined repulsive force caused by the high housing price, bad urban social network, air pollution, and health deterioration. It is worth noting that air pollution has a significant negative impact on the settlement intention of migrants, such as health conditions and precipitation. Besides, there is heterogeneity among high-skilled migrants and low-skilled migrants in different city sizes. Our findings enhance the understanding of “Escape from megacities” in China and have implications for the reform of the housing security system and the exploration of the urbanization path.

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.

Empirical study on the influencing factors of housing price –––Based on cross-section data of 31 provinces and cities in China

Using Eviews software, this paper makes an empirical analysis on the two kinds of factors that affect the housing price of 31 key cities in China: internal direct factors and external indirect factors, in order to reveal the reasons for the high housing price. A multivariate linear regression model was established in which the explanatory variables were land purchase price and residents’ disposable income, and the explanatory variables were the average selling price of residential commercial housing. The research shows that the land purchase price has a greater positive impact on the average selling price of residential commercial housing, compared with residents’ disposable income although also a positive impact but less impact.

China’s Housing Provision System: Evolution, Purchase–Rental Gap Measurement, and Optimization Strategy

Abstract Continuously high housing prices in large and medium-sized cities in China indicate that the urban housing provision system (HPS) has some drawbacks. One reason is that the housing rental ...

Urbanization path, housing price and land finance: International experience and China’s facts

Urban development rules are examined in this paper from macroscopic and microscopic perspective. At the macro level, 99 global economies from 1991 to 2018 were selected and divided into two sub-samples of developed and developing economies to study the historical rule of urbanization. As urbanization level progresses, there is an inverted U-shaped relationship between the population proportion of large cities and degree of urbanization; population mobility experiences a process of first concentration and then dispersion. Based on the full sample, when the average urbanization rate reaches about 75.94%, the population-carrying capacity of large cities approaches the saturation value. In sub-samples, the turning point of the urbanization rate is about 56% for developing economies and 87% for developed economies. At the micro level, an agent-based model was adopted to simulate urbanization. Using China’s data to set the parameters, the results show that the evolution of urbanization follows a general rule of prioritizing the development of large cities. The local government’s dependence on “land finance” and consequently high housing prices will restrict urbanization development, which hinders population growth in large cities. These findings may prove helpful to government in urbanization related policy-making, especially land system and related policies.

Housing prices, migration, and self-selection of migrants in China

The relationship between housing prices and population migration is a crucial and heated topic worldwide. However, few studies discussed how housing price influences the skill composition of migrants. This paper aims to bridge this knowledge gap to investigate China's internal migration, theoretically and empirically. The research question is: Has a higher price crowded out low-skilled migrants and thus led to a positive selection of migrants? To address it, this study introduces housing costs into the self-selection model of migration to conduct a theoretical analysis. Then, this study develops an empirical model that estimates the effect of housing prices on migrants' skill levels, utilizing the China Migrants Dynamic Survey (CMDS) data in 2017 and other relevant data sources. Our analysis demonstrates that a 1% increase in housing prices gives rise to an extra 0.297 years of schooling among migrants. This implies that a higher housing price has significantly discouraged low-educated migrants. Such education selection is more significant among young migrants who live in rental or self-purchased accommodation and work with private enterprises. Also notable is the severer positive selection of migrants who intends to settle in the migrant cities. This study has shed light on the uneven conditions of migrants under the influence of housing unaffordability with policy implications.

Strategies of Residential Area Regeneration and Urban Development in China from the Perspective of Mismatch between Population Mobility and Land Supply: Take Shenzhen as Example

Objectives: After the global financial crisis in 2008, the housing price in cities of China turned from comprehensive prosperity to regional differentiation, and the phenomenon of coexistence of “high housing price” in some cities and “high inventory” in some other cities appeared. The problem of mismatch of land resources and population mobility in China has generated superimposed effect on the high housing price and high inventory in different areas, and the outbreak of COVID-19 in the world has also brought new challenges to the urban development modes; thus, how to develop mega-cities to guarantee the residents’ welfare has become an important academic issue and practical issue. In this paper, with Shenzhen, the most representative city in China, as an example, typical characteristics of real estate market in cities are analyzed, and the methods such as field investigation, questionnaire survey and behavior observation are adopted to analyze the conflicts between the spatial environment of the old residential areas and the demands of residents from the perspective of man-land mismatch. On the basis of expounding the corresponding relationship between the residents’ actual demands and the space, the intergeneration-integrated age-appropriate community regeneration strategy is proposed, and the corresponding suggestions on improving the residents’ welfare are proposed from the perspectives of aging of population, architectural space and urban development. This paper concretely reflects the real estate policy of “one policy for one city”, and proposes new thinking for the development of resilient cities in the post-epidemic era.