The Market Valuation of Interior Design and Developers Strategies: A Simple Theory and Some Evidence

Leung, Charles Ka Yui; Yip, Wai-Hing; Zhang, Jun

doi:10.2139/ssrn.2203647

Cited by 8 publications

(8 citation statements)

References 42 publications

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“…Compared to Table A3, the goodness of fit was improved (measured by Adj. R 2 ), while the signs of the metro index were back to positive and 10% significant for both clusters as required by the constraint (8), which reflects the positive relation between commuting time saving and land value [70].…”

Section: Regression By Clustersmentioning

confidence: 88%

“…If were revisit Constraint (8), it is clear that the coefficient of the metro index not only depends on the value of the metro index, but also on all the other covariate variables, because the OLS estimator for every single coefficient is essentially a function of the full input data matrix. Therefore, apart from the housing market, many important pieces of information regarding urban structure are also encoded by this constraint, such as the relative position between the living zone and CBD, education centers, industrial centers, and so on.…”

Section: Implication For Urban Structurementioning

confidence: 99%

“…Most studies demonstrated positive price premiums and a decreasing effect with distance [3,4]. For Chinese cities, some research on Beijing, Shanghai, Shenzhen, and Hong Kong confirm this pattern [5][6][7][8][9]. Despite this, some studies report little or negative effects of subway transit on housing prices, due to noise and crime rates nearby.…”

Section: Introductionmentioning

confidence: 99%

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Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

et al. 2019

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Using housing market data of Beijing and Hangzhou, China, we conduct a case study to detect how the difference of urban structure can affect the relationship between the subway system and housing prices. To quantify the characteristics of urban structure, we propose a constrained clustering method, which can not only reveal the spatial heterogeneity of the housing market, but also provides a link between heterogeneity and the underlying urban structure. Applying constrained clustering to Beijing and Hangzhou, we find that the relationship between accessibility to metro stations and housing prices is weak and vulnerable, while the improvement of commuting efficiency, measured by a key variable, the metro index, does have a robust connection to metro premium on housing units. In particular, only a large metro index can be associated with a positive metro premium. Structural features, such as the size of urban core and the existence of multiple sub-centers, influence the metro premium by affecting the value and spatial distribution of the metro index. The evidence from Beijing and Hangzhou supports that in a mono-centric city, the size of the urban core is positively associated with the metro index and the metro premium, while in a poly-centric city with a small urban core, the metro index tends to be lower in the core region and higher in the satellite regions, which enforces the metro premium to be negative in the core while positive outside of the core.

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Section: Regression By Clustersmentioning

confidence: 88%

Section: Implication For Urban Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

et al. 2019

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“…To mitigate the potential competitive pressure from other developers, a developer has incentives to shape a real estate development (RED) to make it even more differentiated from those produced by the competitors and to increase her market power (Gnagey, 2012;Leung et al, 2014;Somervile, 1999). Also, a developer can adjust the prices and the timing mechanism to maximize her profit.…”

Section: Introductionmentioning

confidence: 99%

Financial conditions, local competition, and local market leaders: The case of real estate developers

Fan

Leung

Yang

2021

Pacific Economic Review

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This paper studies whether (and how) corporate decisions are affected by internal factors (such as the financial conditions of own company) and external factors (such as the actions of local competitors) in an imperfectly competitive environment. We study the listed real estate developers in Beijing as a case study. Our hand-collected dataset includes transaction-level information booked indicators (such as profitability, liability, and liquidity) and un-booked financial indicators (political connections). Our multi-step empirical model shows that both the firm's financial conditions and her competitors' counterparts are essential but play different roles in the output design, pricing, and the time-on-the-market (TOM). Internal versus external factors' relative importance relates to the degrees of market concentration in a nonlinear manner. Local market leaders' existence alters the small firms' strategy and leads to higher selling prices and slower selling pace in the local market. Our findings survive various robust checks.

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“…The next influencing factor for housing product is the physical qualities of the product being offered to consumers. This factor includes façade characteristics (Cetintahra and Cubukcu, 2014), infrastructure condition (Kwanda et al (2001); Famuyiwa & Babawale (2014), product specifications (Kwanda et al, (2001) and Epple et al,(2013), and floor plan design (Xie et al (2013), Aulia & Ismail (2013) and Leung et al (2013).…”

mentioning

confidence: 99%

Factors Affecting Housing Products Price in Jakarta Metropolitan Region

Rahadi

Wiryono

Koesrindartoto

et al. 2016

IJPS

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This study addresses the issue of factors affecting housing products price in Indonesia, particularly in Jakarta Metropolitan Region. Based on a conceptual model conceived in the study, this preliminary study aims to validate the conceptual model and influencing factors for housing products price.Through a specially designed questionnaire, responses from housing consumers in late 2014 were used to analyse the current housing market products in Jakarta Metropolitan Region. Factors from the conceptual model and information about current housing products in Jakarta Metropolitan Region were combined to produce the questionnaire items. Eleven housing products from various areas and various segmentations in Jakarta Metropolitan Region were applied into the questionnaire. The findings suggested different preference factors for each of the housing development. They also confirm the current housing market conditions in Indonesia are facing overpriced situation. The responses indicate that consumers cannot afford the housing products offered at their current prices. This condition applies for most of the socio-economic and demographics attributes including the housing market segmentation, housing market locations and gender.

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The Market Valuation of Interior Design and Developers Strategies: A Simple Theory and Some Evidence

Cited by 8 publications

References 42 publications

Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

Financial conditions, local competition, and local market leaders: The case of real estate developers

Factors Affecting Housing Products Price in Jakarta Metropolitan Region

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