Housing Price Forecasting in Selected Polish Cities During the COVID-19 Pandemic

• Autorzy: Bełej Mirosław

Identyfikatory

DOI

10.7494/geom.2021.15.4.59

• Języki publikacji: EN

Abstrakty

EN

The COVID-19 pandemic represents a combined supply and demand shock to the financial and housing market but also an unusual negative shock in terms of the health of society (households) and national economy. The fall in housing demand was initially assumed together with price decreases as a consequence of the uncertainty of the health of society, significant falls in stock markets and corporate solvency. However, the results of research in selected Polish cities do not indicate such a significant market recession. This article examines the housing price dynamics and forecasting in Polish cities during the COVID-19 pandemic. The TRAMO/SEATS and ARIMA models were used for the decomposition and forecasting of dwelling time series. The Polish housing market, represented by selected local housing markets, still shows a growing trend despite the COVID-19 pandemic throughout 2020. The housing market may slow down in 2021, but the strong forecasted growth trends in Warszawa and Poznań suggest that there will be no significant price decline in Poland in the near future.

Słowa kluczowe

EN

housing market; housing price dynamics; COVID-19 pandemic

PL

rynek mieszkaniowy; dynamika cen mieszkań; pandemia COVID-19

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Geomatics and Environmental Engineering
• Rocznik: 2021
• Tom: Vol. 15, no. 4
• Strony: 59--80
• Opis fizyczny: Bibliogr. 62 poz., tab., wykr.

Twórcy

autor

Bełej Mirosław

• University of Warmia and Mazury in Olsztyn, Department of Spatial Analysis and Real Estate Market, Olsztyn, Poland

• https://orcid.org/0000-0001-8650-6990

Bibliografia

• [1] Baek S., Mohanty S.K., Glambosky M.: COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, vol. 37, 2020, 101748. https://doi.org/10.1016/j.frl.2020.101748.
• [2] Biswas T.K., Das M.C.: Selection of the barriers of supply chain management in Indian manufacturing sectors due to COVID-19 impacts. Operational Research in Engineering Sciences: Theory and Applications, vol. 3(3), 2020, pp. 1–12. https://doi.org/10.31181/oresta2030301b.
• [3] Altieri M.A., Nicholls C.I.: Agroecology and the emergence of a post COVID-19 agriculture. Agriculture and Human Values, vol. 37(3), 2020, pp. 525–526. https://doi.org/10.1007/s10460-020-10043-7.
• [4] Gössling S., Scott D., Hall C.M.: Pandemics, tourism and global change: a rapid assessment of COVID-19. Journal of Sustainable Tourism, vol. 29(1), 2021, pp. 1–20. https://doi.org/10.1080/09669582.2020.1758708.
• [5] Lau H., Khosrawipour V., Kocbach P., Mikolajczyk A., Ichii H., Zachar- ski M. et al.: The association between international and domestic air traffic and the coronavirus (COVID-19) outbreak. Journal of Microbiology. Immunology and Infection, vol. 53(3), 2020, pp. 467–472. https://doi.org/10.1016/j.jmii.2020.03.026.
• [6] Parnell D., Widdop P., Bond A., Wilson R.: COVID-19, networks and sport. Managing Sport and Leisure, 2020, pp. 1–7. https://doi.org/10.1080/23750472.2020.1750100.
• [7] Sharma A., Borah S.B.: Covid-19 and Domestic Violence: an Indirect Path to Social and Economic Crisis. Journal of Family Violence, 2020. https://doi.org/10.1007/s10896-020-00188-8.
• [8] Baqaee D., Farhi E.: Supply and Demand in Disaggregated Keynesian Economies with an Application to the Covid-19 Crisis. Working Paper 27152, National Bureau of Economic Research, Cambridge, May 2020. https://doi.org/10.3386/w27152, https://www.nber.org/papers/w27152 [access: 22.03.2021].
• [9] del Rio-Chanona R.M., Mealy P., Pichler A., Lafond F., Farmer J.D.: Supply and demand shocks in the COVID-19 pandemic: an industry and occupation perspective. Oxford Review of Economic Policy, vol. 36 (Supplement_1), 2020, pp. S94–S137. https://doi.org/10.1093/oxrep/graa033.
• [10] Castro M.F., Duarte J.B., Brinca P.: Measuring Labor Supply and Demand Shocks during COVID-19. Working Paper 2020-011F, Economic Research Federal Reserve Bank of St. Louis, St. Louis 2020. https://doi.org/10.20955/wp.2020.011, https://research.stlouisfed.org/wp/more/2020-011 [access: 22.03.2021].
• [11] De Toro P., Nocca F., Buglione F.: Real Estate Market Responses to the COVID-19 Crisis: Which Prospects for the Metropolitan Area of Naples (Italy)? Urban Science, vol. 5(1), 2021, 23. https://doi.org/10.3390/urbansci5010023.
• [12] Wang B.: How Does COVID-19 Affect House Prices? A Cross-City Analysis. Journal of Risk and Financial Management, vol. 14(2), 2021, 47. https://doi.org/10.3390/jrfm14020047.
• [13] Guterres A.: COVID-19 in an Urban World. United Nations, 2020. https://www.un.org/en/coronavirus/covid-19-urban-world [access: 22.03.2021].
• [14] Bieda A.: Urban renewal and the value of real properties. Studia Regionalne i Lokalne, nr 3 (69), 2017, pp. 5–28. https://doi.org/10.7366/1509499536901.
• [15] Rabiei-Dastjerdi H., Matthews S.A., Ardalan A.: Measuring Spatial Accessibility to Urban Facilities and Services in Tehran. Spatial Demography, vol. 6(1), 2018, pp. 17–34. https://doi.org/10.1007/s40980-016-0028-2.
• [16] Senetra A., Szarek-Iwaniuk P.: Socio-economic development of small towns in the Polish Cittaslow Network – A case study. Cities, vol. 103, 2020, 102758. https://doi.org/10.1016/j.cities.2020.102758.
• [17] Jaszczak A., Kristianova K., Pochodyła E., Kazak J.K., Młynarczyk K.: Revitalization of Public Spaces in Cittaslow Towns: Recent Urban Redevelopment in Central Eu- rope. Sustainability, vol. 13(5), 2021, 2564. https://doi.org/10.3390/su13052564.
• [18] Kisiała W., Rącka I.: Spatial and Statistical Analysis of Urban Poverty for Sustainable City Development. Sustainability, vol. 13(2), 2021, 858. https://doi.org/10.3390/su13020858.
• [19] Bełej M.: Synergistic Network Connectivity among Urban Areas Based on Non-Linear Model of Housing Prices Dynamics. Real Estate Management and Valuation, vol. 26(4), 2018, pp. 22–34. https://doi.org/10.2478/remav-2018-0033.
• [20] Bełej M., Kulesza S., Cellmer R.: Logical Homologies between Housting Prices Dynamics and Damped Harmonic Oscillations. Acta Physica Polonica A, vol. 138(1), 2020, pp. 89–95. https://doi.org/10.12693/APhysPolA.138.89.
• [21] Galster G.: William Grigsby and the analysis of housing sub-markets and filtering. Urban Studies, vol. 33(10), 1996, pp. 1797–805. https://doi.org/10.1080/0042098966376.
• [22] Jiang X., Xu L., Cui Y.: Seasonal Model and Its Application in Short-term Forecasting. [in:] Iyer V., Bhardwaj M., Weller K. (eds.), Proceedings of the 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018), Advances in Intelligent Systems Research, vol. 143, Atlantis Press, 2018, pp. 194–196. https://doi.org/10.2991/ammsa-18.2018.39.
• [23] Maciąg A., Pietroń R., Kukla S.: Prognozowanie i symulacja w przedsiębiorstwie. Polskie Wydawnictwo Ekonomiczne, Warszawa 2013.
• [24] Cleveland W.P., Tiao G.C.: Decomposition of Seasonal Time Series: A Model for the Census X-11 Program. Journal of the American Statistical Association, vol. 71(355), 1976, pp. 581–587. https://doi.org/10.1080/01621459.1976.10481532.
• [25] Gómez V., Maravall Herrero A.: Programs TRAMO and SEATS: instructions for the user (beta version: September 1996). Banco de España – Servicio de Estudios, 1995.
• [26] Maravall Herrero A.: An Application of TRAMO-SEATS: Automatic Procedure and Sectoral Aggregation. Working Paper 0207, Banco de España, 2002.
• [27] Bee Dagum E., Bianconcini S.: Seasonal Adjustment Based on ARIMA Model Decomposition: TRAMO-SEATS. [in:] Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation, Statistics for Social and Behavioral Sciences, Springer International Publishing, Cham 2016, pp. 115–145. https://doi.org/10.1007/978-3-319-31822-6_5.
• [28] Mossad A., Alazba A.: Drought Forecasting Using Stochastic Models in a Hyper-Arid Climate. Atmosphere, vol. 6(4), 2015, pp. 410–30. https://doi.org/10.3390/atmos6040410.
• [29] Kokot S.: The analysis of differences in residential property price indices. Real Estate Management and Valuation, vol. 22(3), 2014, pp. 14–27. https://doi.org/10.2478/remav-2014-0023.
• [30] Klimach A., Dawidowicz A., Źróbek R.: The Polish land administration system supporting good governance. Land Use Policy, vol. 79, 2018, pp. 547–55. https://doi.org/10.1016/j.landusepol.2018.09.003.
• [31] Dawidowicz A., Źróbek R.: A methodological evaluation of the Polish cadastral system based on the global cadastral model. Land Use Policy, vol. 73, 2018, pp. 59–72. https://doi.org/10.1016/j.landusepol.2018.01.037.
• [32] GUS: Ludność. Stan i struktura oraz ruch naturalny w przekroju terytorialnym (stan w dniu 31.12.2020) w 2016 r. Główny Urząd Statystyczny, 30.04.2021. https://stat.gov.pl/obszary-tematyczne/ludnosc/ludnosc/ludnosc-stan-i-struktura-ludnosci-oraz-ruch-naturalny-w-przekroju-terytorialnym-stan-w-dniu-31-12-2020,6,29.html [access: 31.12.2020].
• [33] Bełej M., Kulesza S.: Real Estate Market under Catastrophic Change. Acta Physica Polonica A, vol. 123(3), 2013, pp. 497–501.
• [34] Brzezicka J., Wisniewski R.: Translocality on the real estate market. Land Use Policy, vol. 55, 2016, pp. 166–181. https://doi.org/10.1016/j.landusepol.2016.03.031.
• [35] Siemińska E., Krajewska M.: Conditions and Directions of Investing on the World Real Estate Market. Real Estate Management and Valuation, vol. 25(4), 2017, pp. 99–112. https://doi.org/10.1515/remav-2017-0033.
• [36] Forrester J.W.: Lessons from system dynamics modeling. System Dynamics Review, vol. 3(2), 1987, pp. 136–49.
• [37] van Geert P.: Dynamic systems approaches and modeling of developmental processes. [in:] Valsiner J., Connolly K.J. (eds.), Handbook of Developmental Psychology, SAGE, 2002, pp. 640–672.
• [38] Łapkowska-Baster B.: Miary współzależności i dynamiki zjawisk w statystyce opisowej: przykłady i zadania. Wydawnictwo Uniwersytetu Jagiellońskiego, Kraków 2009.
• [39] Grudkowska S., Nehrebecka N.: Identyfikacja i usuwanie sezonowości z polskich agregatów monetarnych. Materiały i Studia, nr 237, Narodowy Bank Polski, Warszawa 2009.
• [40] Zimny A.: Statystyka opisowa: materiały pomocnicze do ćwiczeń. Materiały dydaktyczne, nr 17, Państwowa Wyższa Szkoła Zawodowa w Koninie, 2010.
• [41] Cox D.R., Gudmundsson G., Lindgren G., Bondesson L., Harsaae E., Laake P. et al.: Statistical analysis of time series: Some recent developments [with discussion and reply]. Scandinavian Journal of Statistics, vol. 8, 1981, pp. 93–115.
• [42] Wooldridge J.M.: Econometric Analysis of Cross Section and Panel Data. MIT Press, Cambridge 2002.
• [43] Hannonen M.: An analysis of land prices: A structural time-series approach. International Journal of Strategic Property Management, vol. 9(3), 2005, pp. 145–172. http://dx.doi.org/10.3846/1648715X.2005.9637534.
• [44] McDowall D., McCleary R., Bartos B.J.: Interrupted Time Series Analysis. Oxford University Press, Oxford 2019.
• [45] Fernandez-Perez A., Gilbert A., Indriawan I., Nguyen N.H.: COVID-19 pandemic and stock market response: A culture effect. Journal of Behavioral and Experimental Finance, vol. 29, 2021, 100454. https://doi.org/10.1016/j.jbef.2020.100454.
• [46] Ali M., Alam N., Rizvi S.A.R.: Coronavirus (COVID-19) – An epidemic or pandemic for financial markets. Journal of Behavioral and Experimental Finance, vol. 27, 2020, 100341. https://doi.org/10.1016/j.jbef.2020.100341.
• [47] Izzeldin M., Muradoğlu Y.G., Pappas V., Sivaprasad S.: The impact of Covid-19 on G7 stock markets volatility: Evidence from a ST-HAR model. International Review of Financial Analysis, vol. 74, 2021, 101671. https://doi.org/10.1016/j.irfa.2021.101671.
• [48] Contessi S., De Pace P.: The international spread of COVID-19 stock market collapses. Finance Research Letters, 2021, 101894. https://doi.org/10.1016/j.frl.2020.101894.
• [49] Milcheva S.: Volatility and the Cross-Section of Real Estate Equity Returns during Covid-19. The Journal of Real Estate Finance and Economics, 2021. https://doi.org/10.1007/s11146-021-09840-6.
• [50] Case K.E., Quigley J.M., Shiller R.J.: Comparing wealth effects: the stock market versus the housing market. Advances in Macroeconomics, vol. 5(1), 2005, pp. 1235–1235. https://doi.org/10.2202/1534-6013.1235.
• [51] Lis P.: Wahania cykliczne rynków mieszkaniowych: aspekty teoretyczne i praktyczne. Wydawnictwo Adam Marszałek, Toruń 2012.
• [52] Ball M.: Housing policy and economic power: the political economy of owner occupation. University Paperbacks, vol. 828, Routledge, 2017.
• [53] Urbanavičiene V., Kaklauskas A., Zavadskas E.K.: The conceptual model of construction and real estate negotiation. International Journal of Strategic Property Management, vol. 13(1), 2009, pp. 53–70. https://doi.org/10.3846/1648-715X.2009.13.53-70.
• [54] Abraham J.M., Hendershott P.H.: Patterns and Determinants of Metropolitan
• [55] House Prices, 1977–91. NBER Working Paper 4196, National Bureau of Economic Research, Cambridge 1992. [55] Beltratti A., Morana C.: International house prices and macroeconomic fluctuations. Journal of Banking & Finance, vol. 34(3), 2010, pp. 533–545. https://doi.org/10.1016/j.jbankfin.2009.08.020.
• [56] Cheung K.S., Yiu C.Y., Xiong C.: Housing Market in the Time of Pandemic: A Price Gradient Analysis from the COVID-19 Epicentre in China. Journal of Risk and Financial Management, vol. 14(3), 2021, 108. https://doi.org/10.3390/jrfm14030108.
• [57] Tanrıvermiş H.: Possible impacts of COVID-19 outbreak on real estate sector and possible changes to adopt: A situation analysis and general assessment on Turkish perspective. Journal of Urban Management, vol. 9(3), 2020, pp. 263–269. https://doi.org/10.1016/j.jum.2020.08.005.
• [58] Yoruk B.: Early Effects of the COVID-19 Pandemic on Housing Market in the United States. Social Science Research Network, May 2020. https://doi.org/10.2139/ssrn.3607265.
• [59] Qian X., Qiu S., Zhang G.: The impact of COVID-19 on housing price: Evidence from China. Finance Research Letters, 2021, 101944. https://doi.org/10.1016/j.frl.2021.101944.
• [60] Del Giudice V., De Paola P., Del Giudice F.P.: COVID-19 Infects Real Estate Markets: Short and Mid-Run Effects on Housing Prices in Campania Region (Italy). Social Sciences, vol. 9(7), 2020, 114. https://doi.org/10.3390/socsci9070114.
• [61] Pichler M., Skutnik F., Vlad A., Shahri H., Ridwan M.: Housing Price Index, Wealth, and Protective Shield against Covid-19. SIASAT. 2021, vol. 6(1), pp. 1–8. https://doi.org/10.33258/siasat.v6i1.84.
• [62] Zhao Y.: US Housing Market During COVID-19: Aggregate and Distributional Evidence. COVID Economics, vol. 50, 2020, pp. 113–154. https://dx.doi.org/10.2139/ssrn.3677651.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)