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Prices on the Second-hand Market for Swedish Family Houses – Correlation, Causation and Determinants

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The structural differences and the dynamics in prices on the second-hand market for family houses in large(Stockholm, Gothenburg and Malmo), medium-sized, small and industrial cities and sparsely populated areas are analysed in this paper. The basic house price data set used in the analysis consists of constant quality monthly price indexes. The sample starts in January 1981 and ends in July 1997. The real price change in house prices for all seven regions display a high degree of autocorrelation, and the correlograms reveal a mean reverting pattern. The Granger causality test indicates that the real price changes for the Stockholm area “Granger cause” the price changes in the other areas. Thus, the real price change in the Stockholm area has a ripple effect on the six other areas. Both bivariate and multivariate Granger test indicate information content in a number of macroeconomic variables versus the real price changes for the Stockholm area. A simple VAR model was estimated with the price changes for family houses in the Stockholm area, a proxy for consumption growth and the change in the rate in the unemployment rate as endogenous variables and a number of exogenous macro variables. Experiments with impulse response functions show that a shock in the change in the rate of unemployment has a strong effect on real house prices and consumption.

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  • Berg, Lennart, 2000. "Prices on the Second-hand Market for Swedish Family Houses – Correlation, Causation and Determinants," Working Paper Series 2000:7, Uppsala University, Department of Economics.
    • Handle: RePEc:hhs:uunewp:2000_007
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    1. Oikarinen, Elias, 2005. "The Diffusion of Housing Price Movements from Centre to Surrounding Areas," Discussion Papers 979, The Research Institute of the Finnish Economy.
    2. 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.
    3. Chen, Pei-Fen & Chien, Mei-Se & Lee, Chien-Chiang, 2011. "Dynamic modeling of regional house price diffusion in Taiwan," Journal of Housing Economics, Elsevier, vol. 20(4), pages 315-332.
    4. Huayi Yu, 2015. "The spillovers and heterogeneous responses of housing prices: a GVAR analysis of China's 35 major cities," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 20(4), pages 535-558, October.
    5. Gong, Yunlong & Hu, Jinxing & Boelhouwer, Peter J., 2016. "Spatial interrelations of Chinese housing markets: Spatial causality, convergence and diffusion," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 103-117.
    6. Lee, Hahn Shik & Lee, Woo Suk, 2019. "Cross-regional connectedness in the Korean housing market," Journal of Housing Economics, Elsevier, vol. 46(C).
    7. Hsiao-Jung Teng & Chin-Oh Chang & Ming-Chi Chen, 2017. "Housing bubble contagion from city centre to suburbs," Urban Studies, Urban Studies Journal Limited, vol. 54(6), pages 1463-1481, May.
    8. Hallberg, Daniel & Johansson, Per, 2002. "Turnover and Price in the Housing Market: Causation, Association or Independence?," Working Paper Series 2002:12, Uppsala University, Department of Economics.
    9. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2010. "Unit Roots and Structural Change: An Application to US House-Price Indices," Working papers 2010-04, University of Connecticut, Department of Economics, revised Dec 2010.
    10. Hernán Enríquez Sierra & Jacobo Campo Robledo & Antonio Avendaño Arosemena, 2015. "Relaciones regionales en los precios de vivienda nueva en Colombia," Revista Ecos de Economía, Universidad EAFIT, vol. 19(40), pages 25-47, June.
    11. Engerstam, Sviatlana, 2020. "Macroeconomic determinants of apartment prices in Swedish and German cities," Working Paper Series 20/2, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    12. Mehmet Balcilar & Abebe Beyene & Rangan Gupta & Monaheng Seleteng, 2013. "‘Ripple’ Effects in South African House Prices," Urban Studies, Urban Studies Journal Limited, vol. 50(5), pages 876-894, April.
    13. Feng Lan & Chengcai Jiao & Guoying Deng & Huili Da, 2021. "Urban agglomeration, housing price, and space–time spillover effect—Empirical evidences based on data from hundreds of cities in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 898-919, June.
    14. Geoffrey Meen, 2016. "Spatial housing economics: A survey," Urban Studies, Urban Studies Journal Limited, vol. 53(10), pages 1987-2003, August.
    15. Mary Riddel, 2011. "Are Housing Bubbles Contagious? A Case Study of Las Vegas and Los Angeles Home Prices," Land Economics, University of Wisconsin Press, vol. 87(1), pages 126-144.
    16. Giorgio Canarella & Stephen Miller & Stephen Pollard, 2012. "Unit Roots and Structural Change," Urban Studies, Urban Studies Journal Limited, vol. 49(4), pages 757-776, March.
    17. Mei-Se Chien, 2013. "The Non-linear Ripple Effect of Housing Prices in Taiwan: A Smooth Transition Regressive Model," ERES eres2013_51, European Real Estate Society (ERES).
    18. Gauvin, Laetitia & Vignes, Annick & Nadal, Jean-Pierre, 2013. "Modeling urban housing market dynamics: Can the socio-spatial segregation preserve some social diversity?," Journal of Economic Dynamics and Control, Elsevier, vol. 37(7), pages 1300-1321.

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    More about this item

    Keywords

    Regional house price; Granger causality; ripple effect; VAR modelling;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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