Spillovers Across House Price Convergence Clubs : Evidence from the Polish Housing Market

• Autorzy: Mateusz Tomal
• Języki publikacji: EN

Abstrakty

EN

The aim of this study is to assess whether significant spillovers exist among house price convergence clubs in the Polish housing market. This paper is a continuation of my previous research on house price convergence in Poland. In order to achieve the defined goal, VAR modelling was used. Based on the results of the VAR model, impulse response functions (IRFs) and the Spillover Index were calculated. The obtained results indicate that spillovers in the Polish housing market are strong. The relationships are observed both inside the primary and secondary markets and between them. In particular, a very powerful influence is exerted from a club of cities from the primary market, consisting of Cracow, Warsaw, Gdańsk, Poznań, Rzeszów and Wrocław, on the remaining identified house price convergence clubs. (original abstract)

Słowa kluczowe

EN

Housing market; Price convergence; Vector Autoregression Model (VAR)

PL

Rynek mieszkaniowy; Konwergencja cenowa; Model wektorowej autoregresji

• Czasopismo: Real Estate Management and Valuation
• Rocznik: 2020
• Numer: vol. 28, iss. 2
• Strony: 13--20

Twórcy

autor

Mateusz Tomal

• Cracow University of Economics

Bibliografia

• Phillips, P. C., & Sul, D. (2007). Transition modelling and econometric convergence tests. Econometrica, 75(6), 1771-1855. https://doi.org/10.1111/j.1468-0262.2007.00811.x
• Chow W.W., Fung M.K., Cheng A.C.S, 2016, Convergence and spillover of house prices in Chinese cities. Applied Economics, no. 48 (51), 4922-4941. https://doi.org/10.1080/00036846.2016.1167829
• Montagnoli A., Nagayasu J., 2015, UK house price convergence clubs and spillovers. Journal of Housing Economics, no. 30 (C), 50-58. https://doi.org/10.1016/j.jhe.2015.10.003
• Narodowy Bank Polski. 15.01.2019 (the National Bank of Poland, 15.01.2019). Online: https://www.nbp.pl/home.aspx?f=/publikacje/rynek_nieruchomosci/index2.html
• Gong, Y., Hu, J., & Boelhouwer, P. J. (2016). Spatial interrelations of Chinese housing markets: Spatial causality, convergence and diffusion. Regional Science and Urban Economics, 59, 103-117. https://doi.org/10.1016/j.regsciurbeco.2016.06.003
• Greenaway-Mcgrevy R., Grimes A., & Holmes M. (2018). Two countries, sixteen cities, five thousand kilometres: How many housing markets? Papers in Regional Science, no. 98 (1), 353-370. https://doi.org/10.29310/wp
• Tomal, M., 2019, House price convergence on the primary and secondary markets: Evidence from Polish provincial capitals. Real Estate Management and Valuation, no. 27 (4), 62-73. https://doi.org/10.2478/remav-2019-0036
• Schwarz, G.E., 1978, Estimating the dimension of a model. Annals of Statistics, no. 6 (2), 461-464. https://doi.org/10.1214/aos/1176344136
• Lütkepohl, H., Asymptotic Distributions of Impulse Response Functions and Forecast Error Variance Decompositions of Vector Autoregressive Models. The Review of Economics and Statistics, no. 72 (1), 116-125. https://doi.org/10.2307/2109746
• Diebold, F.X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets, The Economic Journal, no. 119 (534), 158-171.
• Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. https://doi.org/10.1016/j.ijforecast.2011.02.006
• Toyoshima Y., & Hamori S. 2018. Measuring the time-frequency dynamics of return and volatility connectedness in global crude oil markets. Energies, no. 11(11), 1-18. https://doi.org/10.3390/en11112893
• Marona B., & Bieniek A. (2013). Wykorzystanie modelu VECM do analizy wpływu bezpośrednich inwestycji zagranicznych na gospodarkę Polski w latach 1996-2010 (The analysis of the influence of foreign direct investment on polish economy in 1996-2010 using VECM methodology), Acta Universitatis Nicolai Copernici. Ekonomia (Acta Universitatis Nicolai Copernici. Economics), 44 (2), 333- 350.
• Dickey D.A., & Fuller W.A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 366 (74), 427-31.
• Dickey D.A., & Fuller W.A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 057-72. https://doi.org/10.2307/1912517

Identyfikatory

DOI

doi.org/10.1515/remav-2020-0012.