Measuring Structural, Location and Environmental Effects: A Hedonic Analysis of Housing Market in Wroclaw, Poland

Ligus, Magdalena; Peternek, Piotr

doi:10.1016/j.sbspro.2016.05.497

Cited by 18 publications

(9 citation statements)

References 15 publications

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“…There are many aspects that contribute to environmental attributes, for instance air quality [30]. The author made an attempt to value air quality in Poland with the use of HPM [31][32][33]. However, the limitation in applicability of this method is the requirement of developed and effective residential property market.…”

Section: Methods For Valuing Environmental Costs and Benefitsmentioning

confidence: 99%

Measuring the Willingness to Pay for Improved Air Quality: A Contingent Valuation Survey

Ligus¹

2018

Pol. J. Environ. Stud.

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Section: Methods For Valuing Environmental Costs and Benefitsmentioning

confidence: 99%

Measuring the Willingness to Pay for Improved Air Quality: A Contingent Valuation Survey

Ligus¹

2018

Pol. J. Environ. Stud.

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“…Regression model indicates, how much property changes by changing in each characteristic of variables through the coefficient values of each characteristic. Therefore, this technique has many complications such as all independent variables may not have a linear relationship or may not be directionally proportional to each other due to heterogeneity effect (Ligus and Peternek 2016). It can decrease the significance of result.…”

Section: Regression Model and Property Valuesmentioning

confidence: 99%

“…The pervious literature found that combination of GIS with regression, fully explored the neighborhood amenities, distance base land values provide the evidence in numerical formwork (Noor et al 2015), Where GIS is technique applied for implementation of locational dataset of environmental attributes (Ligus and Peternek 2016). GIS is widely used for handling of spatial data in urban developmental projects, decision making and policies (Pedro et al 2019).…”

Section: Regression Model and Property Valuesmentioning

confidence: 99%

The impact of neighborhood services on land values: an estimation through the hedonic pricing model

2020

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A strong need exists to increase the knowledge and recognize the values of neighborhood services. This paper makes an attempt to examine the impact of neighborhood services on land values, through analysis based on results obtained from multi linear regression analysis. This case study was done in area of dense urban settlement to check the consequence of neighborhood services through the hedonic pricing model base variables which include the structural, locational, community and neighborhood services. The regression coefficient was checked at (p \ 0.05) level of significance for each variable. The primary data was collect through the questionnaire filling by random sampling and Punjab Urban Gazette was used for the verification of land values in study area. The results found a valuable potential on land and property values of neighborhood services through the regression analysis results express through R (0.926), R 2 (0.856) and coefficient tables to represent the effect of each individual variable on property and land values. Every individual variable play role in defining the values of land and property based upon its utilization such as larger the structure of a property, more the covered area, larger size of a property more the land area higher price. Similarly, for locational factor study in geography, a piece of land adjacent to the road have high land values 50-70% compare to those located at distance. Very less attention has been paid on such issues in the world due to lack of effective urban planning and research on such crucial issues. If empirical studies on such issue has been done, effective way can be obtained for urban planning.

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“…1. Hence we consider the sale price of the apartment, alongside several structural attributes similar to previous papers such as number of rooms (Keskin, 2008;Czembrowski and Kronenberg, 2016;Ligus andPeternek, 2016 Selim, 2009;Baranzini and Schaerer, 2011), house surface (Wilhelmsson, 2002;Jim and Chen, 2009;Selim, 2009;Chen and Jim, 2010;Hui et al, 2012;Ibeas et al, 2012;Efthymiou and Antoniou, 2013;Ooi et al, 2014;Zhang and Leonard, 2014;Kim et al, 2015;Czembrowski and Kronenberg, 2016;Ligus and Peternek, 2016;Tian et al, 2017;Wu et al, 2017;Brecard et al, 2018;McCord et al, 2018;Yuan et al, 2018;Dahal et al, 2019;Laszkiewicz et al, 2019;Yang et al, 2019), comfort, floor level (Keskin, 2008;Jim and Chen, 2009;Chen and Jim, 2010;Baranzini and Schaerer, 2011;Hui et al, 2012;Ibeas et al, 2012;Efthymiou and Antoniou, 2013;Ooi et al, 2014;Ligus and Peternek, 2016;Wu et al, 2017;Li et al, 2019), number of bathrooms (Conroy and Milosch, 2011;Ibeas et al, 2012;Larsen and Blair, 2014;Zhang and Leonard, 2014;…”

Section: Sample and Variablesmentioning

confidence: 99%

“…Ooi et al (2014) noticed for Singapore that a one standard deviation betterment in the construction Quality Assessment System score lift the selling price of an average home by 2.92%. For transactions undertaken in Wroclaw, Ligus and Peternek (2016) documented that larger floor area and the presence of a garage positively influence the transaction price, the rise in the distance from the city center and older building diminish the price and, floor level does not show any significant impact on price. Wilhelmsson (2002) concluded that if living area increases by 1%, price will rise by 0.51%.…”

Section: Introductionmentioning

confidence: 99%

Towards a Hedonic Pricing Method for the Bucharest Private Housing Market

Zilişteanu¹,

Muntean²,

Gherghina

et al. 2019

SAEB

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This paper aims at exploring the drivers of dwellings’sale prices in Bucharest, Romania, over the period 2014-2018. Several housing structural attributes are covered, such as the number of rooms, useful and constructed surface, type of comfort, floor, the number of bathrooms, balconies and parking, the seniority from construction, as well as from renovation, structure type, height regime, and the duration until completion of the real estate transaction. By estimating a standard hedonic price model via OLS regression for a sample of 765 transactions, we notice that all the selected variables, except the floor level and seniority from construction, positively influence the property prices. However, in case of useful and constructed surface, nonlinear relationships with property prices were acknowledged. Robustness checks in form of quantile regressions reinforce the empirical findings.

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Measuring Structural, Location and Environmental Effects: A Hedonic Analysis of Housing Market in Wroclaw, Poland

Cited by 18 publications

References 15 publications

Measuring the Willingness to Pay for Improved Air Quality: A Contingent Valuation Survey

Measuring the Willingness to Pay for Improved Air Quality: A Contingent Valuation Survey

The impact of neighborhood services on land values: an estimation through the hedonic pricing model

Towards a Hedonic Pricing Method for the Bucharest Private Housing Market

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