IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/20921.html
   My bibliography  Save this paper

Statistical Analysis of the Relationship between Public Transport Accessibility and Flat Prices in Riga

Author

Listed:
  • Pavlyuk, Dmitry

Abstract

A relationship between public transport accessibility and residential land value is a point of interest of many recent researches. A hedonic price regression model, widely used in this research area, has one very important shortcoming – it calculates an "average" influence of factors on land value in the analysing area. Usually spatial effects present in data, and the influence of public transport accessibility can be distributed over the area non-uniformly. In this study we apply a comparatively new modification of the regression model – geographically weighted regression – to examine the relationship between public transport accessibility and residential land value (in a form of rent and sell prices) in Riga. The proposed method allows taking into account spatial effects present in the relationship. We use information about geographical locations of urban public transport stops and routes to calculate a level of transport accessibility. Together with the transport accessibility level and a common set of property-specific parameters (floor area, number of rooms, etc.) we consider additional hedonic properties of a flat location such as distances to supermarkets, higher schools and natural attractors like large parks, the river, and the seaside.

Suggested Citation

  • Pavlyuk, Dmitry, 2009. "Statistical Analysis of the Relationship between Public Transport Accessibility and Flat Prices in Riga," MPRA Paper 20921, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:20921
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/20921/1/MPRA_paper_20921.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Timothy J. Fik & David C. Ling & Gordon F. Mulligan, 2003. "Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(4), pages 623-646, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:grz:wpaper:2014-05 is not listed on IDEAS
    2. Chris Leishman & Greg Costello & Steven Rowley & Craig Watkins, 2013. "The Predictive Performance of Multilevel Models of Housing Sub-markets: A Comparative Analysis," Urban Studies, Urban Studies Journal Limited, vol. 50(6), pages 1201-1220, May.
    3. Natale Arcuri & Manuela De Ruggiero & Francesca Salvo & Raffaele Zinno, 2020. "Automated Valuation Methods through the Cost Approach in a BIM and GIS Integration Framework for Smart City Appraisals," Sustainability, MDPI, vol. 12(18), pages 1-16, September.
    4. Jos魍ar𨁍ontero-Lorenzo & Beatriz Larraz-Iribas, 2012. "Space-time approach to commercial property prices valuation," Applied Economics, Taylor & Francis Journals, vol. 44(28), pages 3705-3715, October.
    5. David Ling & Milena Petrova, 2008. "Avoiding Taxes at Any Cost: The Economics of Tax-Deferred Real Estate Exchanges," The Journal of Real Estate Finance and Economics, Springer, vol. 36(4), pages 367-404, May.
    6. Neil T Coffee & Tony Lockwood & Peter Rossini & Theo Niyonsenga & Stanley McGreal, 2020. "Composition and context drivers of residential property location value as a socioeconomic status measure," Environment and Planning B, , vol. 47(5), pages 790-807, June.
    7. Ramya Aroul & J. Hansz, 2014. "The Valuation Impact on Distressed Residential Transactions: Anatomy of a Housing Price Bubble," The Journal of Real Estate Finance and Economics, Springer, vol. 49(2), pages 277-302, August.
    8. Fuess, Roland & Koller, Jan A. & Weigand, Alois, 2017. "Best Land Use with Negative Externalities: Determining Land Values from Residential Rents," Working Papers on Finance 1705, University of St. Gallen, School of Finance, revised May 2019.
    9. John I. Carruthers & David E. Clark, 2010. "Valuing Environmental Quality: A Space‐Based Strategy," Journal of Regional Science, Wiley Blackwell, vol. 50(4), pages 801-832, October.
    10. Karolien De Bruyne & Jan Van Hove, 2013. "Explaining the spatial variation in housing prices: an economic geography approach," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1673-1689, May.
    11. Gaaff, Aris & Reinhard, Stijn, 2012. "Incorporating the value of ecological networks into cost–benefit analysis to improve spatially explicit land-use planning," Ecological Economics, Elsevier, vol. 73(C), pages 66-74.
    12. Shibashis Mukherjee & Arthur Caplan, 2011. "GIS-based estimation of housing amenities: the case of high grounds and stagnant streams," Letters in Spatial and Resource Sciences, Springer, vol. 4(1), pages 49-61, March.
    13. Roland Füss & Jan A. Koller & Alois Weigand, 2021. "Determining Land Values from Residential Rents," Land, MDPI, vol. 10(4), pages 1-29, March.
    14. Mariusz Doszyń, 2024. "Might expert knowledge improve econometric real estate mass appraisal?," The Journal of Real Estate Finance and Economics, Springer, vol. 69(4), pages 719-740, November.
    15. Richard J. Vyn & Max Zongyuan Shang, 2021. "Prices paid for farmland in Ontario: Does buyer type matter?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(1), pages 59-72, March.
    16. Gao, Qishuo & Shi, Vivien & Pettit, Christopher & Han, Hoon, 2022. "Property valuation using machine learning algorithms on statistical areas in Greater Sydney, Australia," Land Use Policy, Elsevier, vol. 123(C).
    17. Libertun de Duren, Nora Ruth, 2017. "La carga de la vivienda de interés social: Comparación entre hogares de la periferia y del centro en ciudades de Brasil, Colombia y México," IDB Publications (Working Papers) 8417, Inter-American Development Bank.
    18. José-María Montero-Lorenzo & Beatriz Larraz-Iribas & Antonio Páez, 2009. "Estimating commercial property prices: an application of cokriging with housing prices as ancillary information," Journal of Geographical Systems, Springer, vol. 11(4), pages 407-425, December.
    19. Steven C. Bourassa & Eva Cantoni & Martin Hoesli, 2005. "Spatial Dependence, Housing Submarkets, and House Prices," FAME Research Paper Series rp151, International Center for Financial Asset Management and Engineering.
    20. Bhattacharjee, Arnab & Jensen-Butler, Chris, 2013. "Estimation of the spatial weights matrix under structural constraints," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 617-634.
    21. Danlin Yu & Yehua Dennis Wei & Changshan Wu, 2007. "Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI," Environment and Planning B, , vol. 34(6), pages 1085-1102, December.

    More about this item

    Keywords

    geographically weighted regression; hedonic price model; public transport accessibility;
    All these keywords.

    JEL classification:

    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:20921. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.