Why homebuyers have a high housing affordability problem: Quantile regression analysis

Lin, Yu‐Ju; Chang, Chin‐Oh; Chen, Chien Liang

doi:10.1016/j.habitatint.2014.01.013

Cited by 34 publications

(19 citation statements)

References 18 publications

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“…As proposed by the United Nations Human Settlement Programme (UNHSP) and the World Bank, the PIR was considered the best assessment criterion for evaluating housing affordability. “It is the ratio of the median free-market price of a dwelling unit to the median annual household income” (Lin et al , 2014, p. 42). High PIR indicates housing affordability crisis while low PIR, below 3.0, indicates improved housing affordability.…”

Section: Literature Reviewmentioning

confidence: 99%

Towards a sustainability assessment model for affordable housing projects: the perspective of professionals in Ghana

Adabre

Chan

2020

ECAM

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PurposeThis paper presents a sustainability assessment model to holistically guide sustainable construction and green retrofitting of affordable housing from the Ghanaian perspective.Design/methodology/approachA comprehensive review was carried out, which yielded 16 sustainability indicators. Then, a questionnaire survey was conducted among respondents in the Ghanaian housing sector. Forty-seven valid responses were received and analysed using fuzzy synthetic evaluation (FSE) technique.FindingsA four-index model was developed that includes: Housing and Transportation (H + T) index, household-satisfaction index, efficient stakeholder-management index and quality-related index. These indices account for 25.3%, 26.3%, 23.6% and 24.9% of sustainability attainment in affordable housing, respectively. Accordingly, household-satisfaction has the greatest contribution to sustainability attainment in affordable housing.Research limitations/implicationsDue to challenges in obtaining responses to the questionnaire, the study was conducted with relatively small number of responses.Originality/valueThe model serves as a tool that could be used to objectively and comprehensively assess sustainability performance in affordable housing. Besides, it could be used as a baseline to calibrate future projects and for benchmarking success levels of comparable housing projects. Finally, the estimated indices are applicable in decision making for optimum resource allocation for sustainable low-cost housing in the Ghanaian perspective.

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Section: Literature Reviewmentioning

confidence: 99%

Towards a sustainability assessment model for affordable housing projects: the perspective of professionals in Ghana

Adabre

Chan

2020

ECAM

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“…Therefore, exploring the housing price-to-income ratio of microscopic regions inside cities may still reflect more accurately the real housing purchasing ability of families with different incomes and have more social practical significance. The formula of housing price-toincome ratio is [11,37] AI AF AR n AI n AF AR HI…”

Section: Housing Price-to-income Ratio Modelmentioning

confidence: 99%

Spatial Justice of a Chinese Metropolis: A Perspective on Housing Price-to-Income Ratios in Nanjing, China

Yin

Song

et al. 2019

Sustainability

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The housing price-to-income ratio is an important index for measuring the health of real estate, as well as detecting residents’ housing affordability and regional spatial justice. This paper considers 1833 residential districts in one main urban area and three secondary urban areas in Nanjing during the period 2009–2017 as research units. It also simulates and estimates the spatial distribution of the housing price-to-income ratio with the kriging interpolation method of geographic information system (GIS) geostatistical analysis and constructs a housing spatial justice model by using housing price, income, and housing price-to-income ratio. The research results prove that in the one main urban area and the three secondary urban areas considered, the housing price-to-income ratio tended on the whole to rise, presenting a core edge model of a progressive decrease from the Main Urban Area to the secondary urban areas spatially, with high-value areas centered around famous school districts and new town centers. The housing spatial justice degree presented a trend opposite to that of the housing price-to-income ratio pattern; it progressively decreased from the secondary urban areas to the Main Urban Area. Furthermore, the spatial justice degree tended to decrease in the new towns, in the periphery of the Main Urban Area, and in the secondary urban areas, and it tended to rise, relatively, in the inner urban areas. The enhancement of the housing price-to-income ratio has caused the urban housing spatial justice degree to become gradually imbalanced, gradually squeezing out the poor and vulnerable groups to urban fringe areas and leading to a phenomenon of middle class stratification. This has thus aroused social problems such as housing differentiation and class solidification, etc., and has caused inequality in social spaces. Tt is therefore urgently necessary to reflect on urban space production with the value and principle of spatial justice, which is also the only way to obtain urban sustainable development, in mind.

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“…As a useful supplement to OLS regression, quantile regression produces a complete description of the impact across the entire distribution of housing prices and is robust to non-normal random errors [59,60]. This method has been widely used in the field of social sciences and some scholars have recently tried introducing it into the field of real estate [61][62][63][64][65]. For example, Kang and Liu [66] investigated the influence of the 2008 financial crisis on housing prices at different quantiles of the price distribution in Taiwan.…”

Section: Of 23mentioning

confidence: 99%

Subway Opening, Traffic Accessibility, and Housing Prices: A Quantile Hedonic Analysis in Hangzhou, China

et al. 2018

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Most existing studies empirically investigated the impact of rail transit on housing prices using the traditional hedonic price model, which is based on ordinary least squares (OLS). This method can estimate only the average implicit prices of housing characteristics and may ignore possible heterogeneous impacts of rail transit at different housing price levels. As a useful supplement to OLS regression, quantile regression can measure how implicit prices of explanatory variables vary across different price levels, thereby providing a comprehensive picture of the relationship between housing characteristics and prices. By using Hangzhou, China as an example, this study adopts the traditional hedonic price model and quantile regression model to investigate the capitalization effect of a new subway line on housing prices. Empirical results suggest the significant impacts of accessibility to subway stations. The average housing price within 2 km of the station is 2.1% to 6.1% higher than those outside. We also find that the impacts of the subway differ significantly across the distribution of housing prices, wherein the absolute value of estimated coefficients increased from 0.023 for the 15th quantile to 0.086 for the 95th quantile. The subway opening strengthens the capitalization effect of traffic accessibility. The absolute value of price elasticity increases from 0.044 to 0.053, and the range of influence is expanded from 1500 m to 2000 m.

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Why homebuyers have a high housing affordability problem: Quantile regression analysis

Cited by 34 publications

References 18 publications

Towards a sustainability assessment model for affordable housing projects: the perspective of professionals in Ghana

Towards a sustainability assessment model for affordable housing projects: the perspective of professionals in Ghana

Spatial Justice of a Chinese Metropolis: A Perspective on Housing Price-to-Income Ratios in Nanjing, China

Subway Opening, Traffic Accessibility, and Housing Prices: A Quantile Hedonic Analysis in Hangzhou, China

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