scholarly journals Influencing Factors of Housing Prices in Chengdu Based on Hedonic Pricing Theory

2017 ◽  
Vol 07 (06) ◽  
pp. 443-449 ◽  
Author(s):  
霜 周
Keyword(s):  
Influencing Factors ◽  
Housing Prices ◽  
Hedonic Pricing ◽  
Pricing Theory

scholarly journals AN ANALYSIS OF COMMON APPLICATIONS ON HEDONIC PRICING MODEL IN VALUING ECOSYSTEM SERVICES: SIMILARITIES AND DIFFERENCE BETWEEN EUROPE, US, AND CHINA

2021 ◽  
Vol 8 (1) ◽  
pp. 1-11
Author(s):  
Xuanfei Zhang
Keyword(s):  
United States ◽  
Ecosystem Services ◽  
Real World ◽  
Housing Prices ◽  
The United States ◽  
Hedonic Pricing ◽  
Pricing Model ◽  
Hedonic Pricing Model ◽  
Real World Applications ◽  
The Common

The study made a comparison with the common applications on the hedonic pricing model that valuing ecosystem services between Europe, the United States, and China. By analyzing various reasons impacting housing prices, cultural and historical backgrounds played roles in the real-world applications.

scholarly journals The effect of land subsidence on real estate values

2020 ◽  
Vol 382 ◽  
pp. 703-707
Author(s):  
Wouter Willemsen ◽  
Sien Kok ◽  
Onno Kuik
Keyword(s):  
The Netherlands ◽  
Land Subsidence ◽  
Housing Prices ◽  
Property Values ◽  
Research Area ◽  
Hedonic Pricing ◽  
Local Conditions ◽  
Negative Skin Friction ◽  
Timber Piles ◽  
The Impact

Abstract. Land subsidence in the Netherlands, mainly occurring in its western and northern peat and clay soils, causes significant damage to houses and infrastructure, estimated at EUR 17 billion until 2050, through differential settlement of shallow foundations, negative skin friction and fungal decay of timber piles. Various studies and reports both in The Netherlands and abroad have addressed the potential economic impacts of subsidence on houses: yet, these studies lack spatially detailed data and instead rely on generic assumptions on expected damage restoration costs. By using a hedonic pricing model, this study examines the impact of subsidence on housing prices in the Dutch cities of Rotterdam and Gouda. In contrast to earlier studies, subsidence and its impact on property values are examined at house level. We test for the effect of subsidence with data related to (i) general (uniform) subsidence (mm yr−1), (ii) differential subsidence of a building and (iii) subsidence of the surrounding area in relation to the house. Results show that uniform subsidence has the largest impact on property values with approximately −6 %, while “differential” and “surrounding” subsidence show respectively −2 % and no effect. These results could prove useful to policymakers, homeowners and housing corporations by generating a better understanding of the impact of subsidence on property values and subsequently to create awareness and spur investments in measures to mitigate damage. It should be noted that these results are specific to the research area are therefore not immediately scalable to other cities as local conditions differ.

Evaluating the worth of nascent old vine cues for South African wines

2019 ◽  
Vol 32 (2) ◽  
pp. 283-300
Author(s):  
David Priilaid ◽  
Jonathan Steyn
Keyword(s):  
South African ◽  
Hedonic Pricing ◽  
Least Square ◽  
Data Set ◽  
Content Type ◽  
Ordinary Least Square ◽  
Extrinsic Cues ◽  
Pricing Theory ◽  
Grape Varieties ◽  
Marketing Material

Purpose In increasingly competitive markets, opportunities exist to meaningfully differentiate product offerings by cue signalling the claims of emergent categories. Therefore, and within the context of wine sales, the purpose of this study models the supply-led price importance of nascent, extrinsic old vine (OV) cues for South African wines to establish whether to what extent and how producers prioritise such nascent cues relative to more established extrinsic cues of worth. Design/methodology/approach A data set was compiled of 159 South African wines with OV category cues signalled on front labels, back labels or via marketing material. The play of contending cue variables was computed through an ordinary least square hedonic pricing model. Findings In addition to the contribution of established cues such as aggregated critic ratings, grape varieties and area of origin, this study confirms that vineyard age contributes significantly to wine price, particularly when signalled on back labels. Practical implications In price setting and positional models, such as brand extensions, the findings prove useful in understanding the inherent value of nascent cues and specifically vineyard age, relative to competing established wine cues of worth. Originality/value This study extends the wine pricing theory by validating the viability of nascent OV cues in the modelling of a wine’s value.

Comparing Interval Restricted Estimators in Hedonic Pricing / Ein Vergleich intervallrestringierter Schätzverfahren in der hedonischen Preismessung

2000 ◽  
Vol 220 (5) ◽  
Author(s):  
Henning Knautz
Keyword(s):  
Monte Carlo ◽  
Bayesian Approach ◽  
Housing Prices ◽  
Hedonic Pricing ◽  
Monte Carlo Experiment ◽  
Constrained Estimation ◽  
Pricing Models ◽  
Interval Constraints ◽  
Using Data ◽  
Fuzzy Interval

SummaryIn hedonic pricing models there is often prior knowledge available which has the form of interval constraints on the unknown coefficients. These are stemming for example from considerations of submarkets for the characteristics involved. In this article we briefly discuss some well known estimators that allow for incorporation of this knowledge. Additionally we introduce two new promising approaches for the same purpose: a modified Bayesian approach and a method applying fuzzy interval constraints. Using data on housing prices we present the results of a Monte Carlo experiment in which these estimators are compared. It turns out that constrained estimation is promising especially in the situation of high multicollinearity and moderate R2 which is typical for hedonic pricing models. We illustrate that estimates and confidence intervals for the unknown coefficients can be improved substantially compared with the conventional unrestricted estimation.

scholarly journals A model to Estimate the Implicit Values of Housing Attributes by Applying the Hedonic Pricing Method

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
TD Randeniya ◽  
Gayani Ranasinghe ◽  
Susantha Amarawickrama
Keyword(s):  
Sri Lanka ◽  
Housing Prices ◽  
House Price ◽  
Housing Price ◽  
Hedonic Pricing ◽  
Pricing Model ◽  
Urban Neighborhood ◽  
Location Factors ◽  
Property Development ◽  
Housing Attributes

Many scholars focused on the location based attributes rather than the non-location factors in decision making on land prices. Further, new research studies have identified the importance of the non-location attributes with the location factors. Many studies suggest that, many attributes exist which affects the housing price. Since the attributes involved and dominant for a particular case differs from one situation to the other, there cannot be an exact list of attributes. Yet, identification of factors that determine housing price and their relationships and the level of influence have poorly understood in planning and property development in the context of Sri Lanka. This study attempts to address what make householders to decide on housing price and application of hedonic pricing approach to estimate the implicit price of housing attributes in context of Sri Lanka. A sample study of selected fifty (50) single house transactions in Maharagama urban neighborhood area has been utilized to illustrate the applicability of the hedonic pricing model. As a methodology, correlation analysis has been carried out to study the degree of relationship between the housing price and the independent variables. The attributes which correlate with housing prices, the study identified the most significant attributes. A model was developed to estimate the future house price by applying the pricing model which is incorporated with these attributes. A hedonic house price model derived from multiple liner regression analysis was developed for the purpose. The findings reveal that six attributes as design type of the house, distance to the local road, quality of Infrastructure, garden size, number of the bed rooms and property age are contributed to estimate the implicit value of Housing property. The model developed would be used to identify implicit values of houses located in urban neighborhood area of Sri Lanka.

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