Flat Location and Size as a Determinant of Homeownership Duration

• Autorzy: Iwona Foryś
• Języki publikacji: EN

Abstrakty

EN

Motivation: Both the research on the residential market focuses primarily on analyses of the size and quality of the housing stock, or seeking dependencies with socio-economic factors. The second research area is the analysis of prices and construction of residential price indices. As an equally important issue is assessing the intensity of trade in particular types of flat and location. A standard view is that those small flats are more frequently traded on the market than large ones. Aim: The study concerns analysis of ownership duration of a flat by the same owner (from the day of purchase to the sale day). It depends on the characteristics of the dwelling, including the location and size. The research will verify the hypothesis of a shorter duration for small units and its location. The study relies on the example of one local housing market. The study use regression analysis to examine the property value on the city's districts and duration analysis to explore ownership duration time, and nonparametric models of a proportional model Cox gambling with explanatory variables dependent on time. Results: This research is significant in socio-spatial connection to the housing market. It shows that the current practice of buying a small flat as an investment in the housing market is appropriate. Due to the rapid price increase of small flats and high turnover, the chances for a good investment are increasing. With the help of the Cox model, the study shows that on the local market poor location in the old city housing estate and a larger floor area decreased the odds of a property to be sold quickly. The study results are valuable due to the unique role of housing on investing in the local market.(original abstract)

Słowa kluczowe

EN

Real estate's value; Real estate; Real estate prices; Real estate housing

PL

Wartość nieruchomości; Nieruchomości; Ceny nieruchomości; Nieruchomości mieszkaniowe

• Czasopismo: Ekonomia i Prawo
• Rocznik: 2022
• Tom: 21
• Numer: nr 2
• Strony: 369--387

Twórcy

autor

Iwona Foryś

• University of Szczecin

Bibliografia

• Alkali, M., Sipan, I., & Razali, M.N. (2019). The effect of negative information on the volatility of real estate residential prices in Abuja, Nigeria. International Journal of Housing Markets and Analysis, 13(2), 267-280. https://doi.org/10.1108/IJHMA-03-2019-0036.
• Alkay, E. (2011). The residential mobility pattern in the Istanbul metropolitan area. Housing Studies, 26(4), 521-539. https://doi.org/10.1080/02673037.2011.559752.
• Ambrose, P. (1992). The performance of national housing systems: a three nations comparison. Housing Studies, 7(3), 163-176. https://doi.org/10.1080/02673039208720733.
• Blossfeld, H.-P., Hamerle, A., & Mayer, K.U. (1989). Event history analysis: statistical theory and application in the social sciences. Psychology Press. https://doi.org/10.4324/9781315808161.
• Bowers, N.L., Gerber, H.U., Hivkman, J.C., Jones, D.A., & Nesbitt, C.J. (1987). Actuarial mathematics. Transactions of the Faculty of Actuaries, 41, 91-94.
• Cai, X., & Wu, W.-N. (2019). Affordable housing policy development: public official perspectives. International Journal of Housing Markets and Analysis, 12(5), 934-951. https://doi.org/10.1108/ijhma-08-2018-0063.
• Case, K.E., & Shiller, R.J. (1989). Association the efficiency of the market for single-family homes. The American Economic Review, 79(1), 125-137.
• Cox, D.R., & Oakes, D. (1984). Analysis of survival data. Chapman & Hall.
• Day, B. (2001). The theory of hedonic markets: obtaining welfare measures for changes in environmental quality using hedonic market data. Retrieved 02.09.2021 from https://discovery.ucl.ac.uk/id/eprint/17583/1/17583.pdf.
• Ewen, H.H., & Carswell, A. (2019). Differences in conventional and seniors-oriented flat management. Facilities, 37(3/4), 157-167. https://doi.org/10.1108/f-12-2017-0121.
• Golland, A. (1998). Systems of housing supply and housing production in Europe: a comparison of the United Kingdom, the Netherlands and Germany. Routledge. https://doi.org/10.4324/9780429437854.
• Herath, S., & Maier, G. (2015). Informational efficiency of the real estate market: a meta-analysis. Journal of Economic Research, 20(2), 117-168. http://dx.doi.org/10.17256/jer.2015.20.2.001.
• Hosmer, D.W., & Lemeshow, S. (1999). Applied survival analysis: regression modeling of time to event data. Wiley.
• Isakson, H.R. (1998). The review of real estate appraisals using multiple regression analysis. Journal of Real Estate Research, 15(2), 177-190. https://doi.org/10.1080/10835547.1998.12090922.
• Jayantha, W.M., & Oladinrin, O.T. (2020). Bibliometric analysis of hedonic price model using Citespace. International Journal of Housing Markets and Analysis, 13(2), 357-371. https://doi.org/10.1108/ijhma-04-2019-0044.
• Kleinbaum, D.G. (1996). Survival analysis: a self- learning text. Springer.
• Lee, J.S. (2016). Measuring the value of flat density: the effect of residential density on housing prices in Seoul. International Journal of Housing Markets and Analysis, 9(4), 483-501. https://doi.org/10.1108/ijhma-08-2015-0047.
• Manase, D., & Siamuzwe, V. (2020). The effectiveness of the housing needs and demand. International Journal of Housing Markets and Analysis, 13(2), 125-141. https://doi.org/10.1108/ijhma-12-2018-0103.
• Mayers, R.H. (1990). Classical and modern regression with application. Duxbury.
• Miles, W. (2020). Home prices and fundamentals: solving the mystery for the g-7 by accounting for nonlinearities. International Journal of Housing Markets and Analysis, 13(2), 299-315. https://doi.org/10.1108/ijhma-03-2019-0029.
• Rencher, A.C. (2002). Methods of multivariate analysis. Wiley.
• Tajima, K. (2020). Shared amenities' impacts on condominium resale values. International Journal of Housing Markets and Analysis, 13(2), 281-297. https://doi.org/10.1108/ijhma-03-2019-0038.
• Wu, H., Jiao, H., Yu, Y., Li, Z., Peng, Z., Liu, L., & Zeng, Z. (2018). Influence factors and regression model of urban housing prices based on internet open access data. Sustainability, 10(5), 1-17. https://doi.org/10.3390/su10051676.

Identyfikatory

DOI

https://doi.org/10.12775/EiP.2022.020