scholarly journals School Desegregation and Urban Change: Evidence from City Boundaries

2012 ◽  
Vol 4 (1) ◽  
pp. 85-108 ◽  
Author(s):  
Leah Platt Boustan
Keyword(s):  
Public Schools ◽  
Metropolitan Areas ◽  
Housing Prices ◽  
Housing Price ◽  
Urban Housing ◽  
Urban Residents ◽  
Urban Residence ◽  
Tax Base ◽  
Central Cities ◽  
The City

I examine changes in the city-suburban housing price gap in metropolitan areas with and without court-ordered desegregation plans over the 1970s, narrowing my comparison to housing units on opposite sides of district boundaries. Desegregation of public schools in central cities reduced the demand for urban residence, leading urban housing prices and rents to decline by 6 percent relative to neighboring suburbs. Aversion to integration was due both to changes in peer composition and to student reassignment to nonneighborhood schools. The associated reduction in the urban tax base imposed a fiscal externality on remaining urban residents. (JEL H75, I21, I28, J15, R23, R31)

Dynamic effects and spatial heterogeneity of land supply on housing price: evidence from Nanchang, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhijiang Wu ◽  
Yongxiang Wang ◽  
Wei Liu
Keyword(s):  
Spatial Heterogeneity ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Dynamic Effects ◽  
Negative Effects ◽  
Land Supply ◽  
Content Type ◽  
Major Factors ◽  
The City

Purpose Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces. Design/methodology/approach This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang. Findings This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price. Research limitations/implications The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang. Originality/value This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.

scholarly journals ARE HOUSING PRICE CYCLES ASYMMETRIC? EVIDENCE FROM THE US STATES AND METROPOLITAN AREAS

2018 ◽  
Vol 23 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Christophe André ◽  
Rangan Gupta ◽  
John W. Muteba Mwamba
Keyword(s):  
Loss Aversion ◽  
Linear Models ◽  
Metropolitan Areas ◽  
Housing Prices ◽  
District Of Columbia ◽  
Housing Price ◽  
Metropolitan Statistical Area ◽  
The Us ◽  
Housing Price Dynamics ◽  
Statistical Area

This paper investigates asymmetry in US housing price cycles at the state and metropolitan statistical area (MSA) level, using the Triples test (Randles, Flinger, Policello, & Wolfe, 1980) and the Entropy test of Racine and Maasoumi (2007). Several reasons may account for asymmetry in housing prices, including non-linearity in their determinants and in behavioural responses, in particular linked to equity constraints and loss aversion. However, few studies have formally tested the symmetry of housing price cycles. We find that housing prices are asymmetric in the vast majority of cases. Taking into account the results of the two tests, deepness asymmetry, which represents differences in the magnitude of upswings and downturns, is found in 39 out of the 51 states (including the District of Columbia) and 238 out of the 381 MSAs. Steepness asymmetry, which measures differences in the speed of price changes during upswings and downturns, is found in 40 states and 257 MSAs. These results imply that linear models are in most cases insufficient to capture housing price dynamics.

The Last Mile Matters: Impact of Dockless Bike Sharing on Subway Housing Price Premium

2020 ◽  
Author(s):  
Junhong Chu ◽  
Yige Duan ◽  
Xianling Yang ◽  
Li Wang
Keyword(s):  
Housing Price ◽  
Relative Increase ◽  
Price Premium ◽  
Urban Residents ◽  
Difference In Differences ◽  
Last Mile ◽  
Bike Sharing ◽  
Subway Stations ◽  
The Relationship ◽  
The City

Dockless bike sharing provides a convenient and affordable means of transport for urban residents. It solves the “last-mile problem” in public transport by reducing the travel cost between home and subway stations and thus increasing the attractiveness of distant apartments. This may affect the relationship between housing price and distance to subway and reduce the price premium enjoyed by proximate apartments. Using resale apartment data in 10 major cities in China, a difference-in-differences approach at the apartment level, and a two-step estimator at the city-month level, we find that the entry of bike sharing reduces the housing price premium by 29% per km away from a subway station. The effect is equivalent to a reduction of 1,893–2,127 CNY (282–317 USD) in commuting costs per household per annum over 30 years. The effect is driven by a relative increase in the listing price of, and in the demand for, apartments distant from vis-à-vis proximate to subway stations. This paper was accepted by Juanjuan Zhang, marketing.

scholarly journals Economic Impact of the High-Speed Railway on Housing Prices in China

2018 ◽  
Vol 10 (12) ◽  
pp. 4799 ◽  
Author(s):  
Yuxiang Wang ◽  
Xueli Liu ◽  
Feng Wang
Keyword(s):  
High Speed ◽  
Synergistic Effects ◽  
Housing Prices ◽  
Housing Price ◽  
Quantitative Relationship ◽  
Economic Effects ◽  
High Speed Railway ◽  
Central Cities ◽  
Price Growth ◽  
Regional Imbalance

This study investigated whether and to what extent does the High-Speed Railway (HSR) affect city-level housing prices. With the data of HSR operation and housing prices from 285 cities from 2009 to 2017, the paper aimed to estimate the quantitative relationship between HSR and city-level housing prices and exploited city and regional dummy variables to assess the disparities between regions, followed by the economic effects between typical city pairs. Our findings were as follows: (1) The introduction of HSR leads to a 13.9% increase in city-level housing prices, and the figures for national central cities and regional central cities were 31.7% and 19.6%, respectively; (2) regional imbalance was mitigated with the development of the HSR, and some central cities in underdeveloped regions were stimulated with regard to housing price growth; (3) siphon effects and diffusion effects were observed in megacity–small city pairs, while synergistic effects often lay in megacity–megacity pairs, and such effects all tended to be more significant with increases in the number of HSR lines and a drop in the travel time.

scholarly journals Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 879
Author(s):  
Leeyoung Kim ◽  
Wonseok Seo
Keyword(s):  
Housing Market ◽  
Metropolitan Area ◽  
Mutual Influence ◽  
Housing Prices ◽  
Spillover Effect ◽  
Housing Price ◽  
Sales Price ◽  
Seoul Metropolitan Area ◽  
Housing Submarkets ◽  
The City

This study examined the price spillover effect of housing submarkets in cities in the Seoul metropolitan area in South Korea by using the Granger causality test and vector autoregressive model (VAR). We found that housing prices showed a higher spillover effect within regions with similar housing market characteristics. Additionally, the spatial spillover of housing prices revealed a difference between sales price and jeonse price. The spillover of jeonse price was characterized by mutual influence among neighboring cities, while that of sales price was characterized by the influence being transferred in one direction hierarchically. Furthermore, the effects of housing price indicated a slight difference between sales price and jeonse price. Although jeonse price was mainly affected by a neighboring area (geographic boundary), sales price was more influenced by the city with the highest housing prices. Lastly, the housing price spillover tended to be expansive around the city with the highest price. These results suggest that housing price policies targeting specific regions or areas in Korea must be differentiated according to the type of occupancy (jeonse or sales), and it is essential to consider the externalities when promoting policies in the housing market wherein externalities may be significant.

Study on Commodity Residential House Price Volatility of the Guanzhong Urban Agglomeration Using Spatial Econometric Analysis

2014 ◽  
Vol 638-640 ◽  
pp. 2436-2441
Author(s):  
Feng Lan ◽  
Ying Tian
Keyword(s):  
Housing Prices ◽  
House Price ◽  
Great Influence ◽  
Housing Price ◽  
Price Volatility ◽  
Urban Housing ◽  
Urban Agglomeration ◽  
Spatial Econometric ◽  
Residential House ◽  
House Price Volatility

This paper was based on the theory of spatial econometric model. It selected the panel datas of the guanzhong urban agglomeration of five core cities from 1998 to 2012, and inspected the commodity residential house price if there is a space dependency relationship between the two cities. On the basis to analyze the main factors influencing the commodity residential house price volatility and research on the influence of the housing price direction. Results show that the sample is significant spatial correlation between urban housing prices. Xi 'an have great influence on regional cities housing price. The urban population, household disposable income, land acquisition costs, sales area are the main influence factors affecting housing price volatility.

scholarly journals Housing Booms and City Centers

2012 ◽  
Vol 102 (3) ◽  
pp. 127-133 ◽  
Author(s):  
Edward L Glaeser ◽  
Joshua D Gottlieb ◽  
Kristina Tobio
Keyword(s):  
Metropolitan Areas ◽  
Public Transit ◽  
Initial Density ◽  
Housing Values ◽  
City Center ◽  
Central Cities ◽  
Housing Boom ◽  
Price Growth ◽  
The City ◽  
As If

Popular discussions often treat the great housing boom of the 1996-2006 period as if it were a national phenomenon with similar impacts across locales, but across metropolitan areas, price growth was dramatically higher in warmer, less educated cities with less initial density and higher initial housing values. Within metropolitan areas, price growth was faster in neighborhoods closer to the city center. The centralization of price growth during the boom was particularly dramatic in those metropolitan areas where income is higher away from the city center. We consider a number of different explanations for this connection, and find that the connection between centralized price growth and decentralized income seems to be most explained by the faster price growth in central cities that use relatively more public transit.

scholarly journals Temporal and Spatial Effects of Urban Center on Housing Price — A Case Study on Hangzhou, China

2018 ◽  
Vol 5 (1) ◽  
pp. 89 ◽  
Author(s):  
Luhong Chu ◽  
Haizhen Wen
Keyword(s):  
Rapid Development ◽  
Housing Prices ◽  
Housing Price ◽  
Urban Land ◽  
Urban Housing ◽  
Spatial Effects ◽  
Hedonic Price ◽  
Urban Center ◽  
Center City ◽  
The Impact

<em>With the acceleration of urbanization and the rapid development of real estate, people pay more and more attention to the change of urban housing prices. Over time, the change of city center will inevitably affect the urban land or housing prices, which is reflected in the spatial distribution of urban land or housing prices. Therefore, this article attempts to explore the impact of urban center on housing prices from the perspective of multi-center city and study separately from two aspects of time and space. This paper takes the six main urban districts of Hangzhou as the research scope. At the time level, we select the residential data from 2007 to 2015 to construct models respectively based on the hedonic price theory and find that the influence of different urban center on housing price shows a certain change with time. On the spatial level, this paper choses the residential data in 2012 to construct geographic weighted regression model and the result shows that the impact of three centers on housing prices shows a certain degree of spatial heterogeneity.</em>

scholarly journals Urban Housing Price Fluctuations and Regional Systemic Financial Risks: Panel Spatial Economic Models in Jiangsu, China

2018 ◽  
Vol 10 (10) ◽  
pp. 3452
Author(s):  
Fengyun Liu ◽  
Chuanzhe Liu ◽  
Honghao Ren
Keyword(s):  
Real Estate ◽  
Local Governments ◽  
Financial Risk ◽  
Housing Prices ◽  
Housing Price ◽  
Economic Models ◽  
Urban Housing ◽  
Financial Risks ◽  
Price Fluctuations ◽  
Contagion Effects

The regional systemic financial risks driven by escalating urban housing prices have been of great concern recently. Based on the theoretical analyses on the mechanism of formation of regional systemic financial risk driven by urban housing price fluctuations, this paper builds panel spatial economic models to empirically analyze the relationship between urban housing price fluctuations and regional systemic financial risks, in addition to their spatial linkages, in 13 cities in Jiangsu, a representative province of China. The empirical results show the following. (1) The excessive investment or speculation of local governments, banks, real estate developers, individuals, and families on the housing market stimulate the escalation in urban housing prices, leading to the systemic financial risks; (2) Urban housing prices and the land supply price of local governments have strong spatial contagion effects among cities, which will diffuse risks to adjacent cities, causing regional systemic financial risk; (3) Compared with North Jiangsu, South Jiangsu has more serious investment expansion from real estate developers and stronger spatial contagion effects, suggesting the existence of heavier regional systemic financial risks derived from housing price fluctuations; (4) North Jiangsu has slightly stronger “imitative behavior” among local governments, and fewer “substitution effects” of central cities’ demand to adjacent cities’ demand than does South Jiangsu.

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