IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i18p7774-d416448.html
   My bibliography  Save this article

Possibilities of House Valuation Automation in the Czech Republic

Author

Listed:
  • Stanislav Endel

    (Department of Urban Engineering, Faculty of Civil Engineering, VSB-Technical University of Ostrava, 708 00 Ostrava-Poruba, Czech Republic)

  • Marek Teichmann

    (Department of Urban Engineering, Faculty of Civil Engineering, VSB-Technical University of Ostrava, 708 00 Ostrava-Poruba, Czech Republic)

  • Dagmar Kutá

    (Department of Urban Engineering, Faculty of Civil Engineering, VSB-Technical University of Ostrava, 708 00 Ostrava-Poruba, Czech Republic)

Abstract

Valuation of single-family detached houses is necessary when determining the amounts of some taxes. The current systems of the Czech Republic are outdated in this respect, and they are based on procedures used in the 1980s. The values found do not correspond to current market conditions very often. This article attempts to verify the applicability of a methodology where the value of a detached house is decomposed into the value of the land and the value of the object as such when considering wear. For verification, 122 sales of detached houses in Ostrava and its surroundings were analyzed, and the results show that the values determined by the verified methodology do not differ by more than 10% from the actual sales prices in most cases. The methodology is very simple and practically applicable for users without deep knowledge of construction or valuation principles. It can be applied, for example, when calculating the bases of certain taxes or as an indicative guide for the pricing of real estate for sellers, buyers, real estate agents, etc.

Suggested Citation

  • Stanislav Endel & Marek Teichmann & Dagmar Kutá, 2020. "Possibilities of House Valuation Automation in the Czech Republic," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7774-:d:416448
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/18/7774/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/18/7774/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charles Himmelberg & Christopher Mayer & Todd Sinai, 2005. "Assessing High House Prices: Bubbles, Fundamentals and Misperceptions," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 67-92, Fall.
    2. Füss, Roland & Koller, Jan A., 2016. "The role of spatial and temporal structure for residential rent predictions," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1352-1368.
    3. Michael Doumpos & Dimitrios Papastamos & Dimitrios Andritsos & Constantin Zopounidis, 2020. "Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches," Post-Print hal-02880099, HAL.
    4. Bradford Case & John Clapp & Robin Dubin & Mauricio Rodriguez, 2004. "Modeling Spatial and Temporal House Price Patterns: A Comparison of Four Models," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 167-191, September.
    5. Mi Diao & Yi Zhu & Jiren Zhu, 2017. "Intra-city access to inter-city transport nodes: The implications of high-speed-rail station locations for the urban development of Chinese cities," Urban Studies, Urban Studies Journal Limited, vol. 54(10), pages 2249-2267, August.
    6. Reichert, Alan K, 1990. "The Impact of Interest Rates, Income, and Employment upon Regional Housing Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 3(4), pages 373-391, December.
    7. Are Oust & Simen N. Hansen & Tobias R. Pettrem, 2020. "Combining Property Price Predictions from Repeat Sales and Spatially Enhanced Hedonic Regressions," The Journal of Real Estate Finance and Economics, Springer, vol. 61(2), pages 183-207, August.
    8. Jin Han Park & Dong Kun Lee & Chan Park & Ho Gul Kim & Tae Yong Jung & Songyi Kim, 2017. "Park Accessibility Impacts Housing Prices in Seoul," Sustainability, MDPI, vol. 9(2), pages 1-14, January.
    9. Steven C. Bourassa & Eva Cantoni & Martin Hoesli, 2010. "Predicting House Prices with Spatial Dependence: A Comparison of Alternative Methods," Journal of Real Estate Research, American Real Estate Society, vol. 32(2), pages 139-160.
    10. Du, Mengbing & Zhang, Xiaoling, 2020. "Urban greening: A new paradox of economic or social sustainability?," Land Use Policy, Elsevier, vol. 92(C).
    11. Feng Lan & Qi Wu & Tao Zhou & Huili Da, 2018. "Spatial Effects of Public Service Facilities Accessibility on Housing Prices: A Case Study of Xi’an, China," Sustainability, MDPI, vol. 10(12), pages 1-20, November.
    12. Chao Xue & Yongfeng Ju & Shuguang Li & Qilong Zhou, 2020. "Research on the Sustainable Development of Urban Housing Price Based on Transport Accessibility: A Case Study of Xi’an, China," Sustainability, MDPI, vol. 12(4), pages 1-15, February.
    13. Robert A. Simons & Jesse D. Saginor, 2006. "A Meta-Analysis of the Effect of Environmental Contamination and Positive Amenities on Residential Real Estate Values," Journal of Real Estate Research, American Real Estate Society, vol. 28(1), pages 71-104.
    14. R. Kelley Pace & Otis W. Gilley, 1998. "Generalizing the OLS and Grid Estimators," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 26(2), pages 331-347, June.
    15. Bourassa, Steven C. & Hoesli, Martin & Peng, Vincent S., 2003. "Do housing submarkets really matter?," Journal of Housing Economics, Elsevier, vol. 12(1), pages 12-28, March.
    16. Kettani, Ossama & Oral, Muhittin, 2015. "Designing and implementing a real estate appraisal system: The case of Québec Province, Canada," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 1-9.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Natalie Szeligova & Marek Teichmann & Frantisek Kuda, 2021. "Research of the Disparities in the Process of Revitalization of Brownfields in Small Towns and Cities," Sustainability, MDPI, vol. 13(3), pages 1-18, January.
    2. Tomáš Krulický & Thomas Schmallowsky, 2022. "Tax systems and their differences in use in selected countries, digitalization of a tax system," International Journal of Economic Sciences, European Research Center, vol. 11(1), pages 47-67, April.
    3. Francesco Tajani & Felicia Di Liddo & Rossana Ranieri, 2022. "The Effective Use of National Recovery and Resilience Plan Funding: A Methodological Approach for the Optimal Assessment of the Initiative Costs," Land, MDPI, vol. 11(10), pages 1-21, October.

    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. Juergen Deppner & Marcelo Cajias, 2024. "Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 68(2), pages 235-273, February.
    2. Dieudonné Tchuente & Serge Nyawa, 2022. "Real estate price estimation in French cities using geocoding and machine learning," Annals of Operations Research, Springer, vol. 308(1), pages 571-608, January.
    3. Marko Kryvobokov, 2011. "Defining apartment neighbourhoods with Thiessen polygons and fuzzy equality clustering," ERES eres2011_142, European Real Estate Society (ERES).
    4. 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.
    5. Steven Bourassa & Eva Cantoni & Martin Hoesli, 2007. "Spatial Dependence, Housing Submarkets, and House Price Prediction," The Journal of Real Estate Finance and Economics, Springer, vol. 35(2), pages 143-160, August.
    6. Seungwoo Choi & Mun Yong Yi, 2021. "Computational Valuation Model of Housing Price Using Pseudo Self Comparison Method," Sustainability, MDPI, vol. 13(20), pages 1-22, October.
    7. Michalis Doumpos & Dimitrios Papastamos & Dimitrios Andritsos & Constantin Zopounidis, 2021. "Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches," Annals of Operations Research, Springer, vol. 306(1), pages 415-433, November.
    8. Katja Hanewald & Michael Sherris, 2011. "House Price Risk Models for Banking and Insurance Applications," Working Papers 201118, ARC Centre of Excellence in Population Ageing Research (CEPAR), Australian School of Business, University of New South Wales.
    9. Yunjong Kim & Seungwoo Choi & Mun Yong Yi, 2020. "Applying Comparable Sales Method to the Automated Estimation of Real Estate Prices," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    10. Dorsey, Robert E. & Hu, Haixin & Mayer, Walter J. & Wang, Hui-chen, 2010. "Hedonic versus repeat-sales housing price indexes for measuring the recent boom-bust cycle," Journal of Housing Economics, Elsevier, vol. 19(2), pages 75-93, June.
    11. Chica-Olmo, Jorge & Cano-Guervos, Rafael, 2020. "Does my house have a premium or discount in relation to my neighbors? A regression-kriging approach," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    12. Benítez-Silva, Hugo & Eren, Selçuk & Heiland, Frank & Jiménez-Martín, Sergi, 2015. "How well do individuals predict the selling prices of their homes?," Journal of Housing Economics, Elsevier, vol. 29(C), pages 12-25.
    13. Füss, Roland & Koller, Jan A., 2016. "The role of spatial and temporal structure for residential rent predictions," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1352-1368.
    14. Konstantin Kholodilin, 2015. "Speculative Bubbles in Urban Housing Markets in Germany," ERSA conference papers ersa15p67, European Regional Science Association.
    15. Alice Barreca & Rocco Curto & Diana Rolando, 2018. "Housing Vulnerability and Property Prices: Spatial Analyses in the Turin Real Estate Market," Sustainability, MDPI, vol. 10(9), pages 1-20, August.
    16. Antonio Páez & Fei Long & Steven Farber, 2008. "Moving Window Approaches for Hedonic Price Estimation: An Empirical Comparison of Modelling Techniques," Urban Studies, Urban Studies Journal Limited, vol. 45(8), pages 1565-1581, July.
    17. Xiaolong Liu, 2013. "Spatial and Temporal Dependence in House Price Prediction," The Journal of Real Estate Finance and Economics, Springer, vol. 47(2), pages 341-369, August.
    18. Ana-María Martínez-Llorens & Paloma Taltavull de La Paz & Raul-Tomas Mora-Garcia, 2020. "Effect of The Physical Characteristics of a Dwelling on Energy Consumption and Emissions: The Case of Castellón And Valencia (Spain)," Sustainability, MDPI, vol. 12(22), pages 1-20, November.
    19. Antonio Páez, 2009. "Recent research in spatial real estate hedonic analysis," Journal of Geographical Systems, Springer, vol. 11(4), pages 311-316, December.
    20. Nikodem Szumilo & Edyta Laszkiewicz & Franz Fuerst, 2017. "The spatial impact of employment centres on housing markets," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(4), pages 472-491, October.

    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:gam:jsusta:v:12:y:2020:i:18:p:7774-:d:416448. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.