Abstract
The present paper aims to analyse the European residential real estate market through a set of indicators elaborated by Eurostat. By means of the use of correlation analysis, the comparison of several housing market indicators related to European nations enables the creation of a synthetic and unambiguous representation of the residential property market trend, as well as the comprehension of the dynamics that are seen within each nation and of the relationships that exist between the indicators with nations. The use of deflated indicators and the analysis of inflation trends has allowed us to highlight the peculiarities of the Italian residential property market and its ability to act as a safe-haven asset.
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References
Istat - Prezzi al consumo. https://www.istat.it/it/archivio/293510. Accessed 05 March 2024
Istat - Indice dei prezzi al consumo per le rivalutazioni monetarie. https://www.istat.it/it/archivio/30440. Accessed 27 Feb 2024
Istat - prezzi alla produzione dell’industria e delle costruzioni. https://www.istat.it/it/archivio/293447. Accessed 27 Feb 2024
Goodhart, C., Hofmann, B.: Do asset prices help to predict consumer price inflation? Manch. Sch. 68, 122–140 (2000)
Tsatsaronis, K., Zhu, H.: What drives housing price dynamics: cross-country evidence. BIS Q. Rev. (2004)
Yu, H., Huang, Y.: Regional heterogeneity and the trans-regional interaction of housing prices and inflation: evidence from China’s 35 major cities. Urban Stud. 53(16), 3472–3492 (2016)
Anari, A., Kolari, J.: House prices and inflation. Real Estate Econ. 30(1), 67−84 (2002)
Kuang, W., Liu, P.: Inflation and house prices: theory and evidence from 35 major cities in china. Int. Real Estate Rev. 18(2) (2015)
Aqsha, N.S., Masih, M.: Is residential property the ultimate hedge against inflation? new evidence from Malaysia based on ARDL and nonlinear ARDL. MPRA Paper No. 91508, (2018)
Ting, H., Huangjin, L.: Dynamic relationship between real estate prices and inflation rate. In: IEEE International Conference on Granular Computing (GrC), pp. 153–156. IEEE, China (December 2013)
Wu, Y., Tidwell, A.: Inflation-hedging properties of regional Chinese real estate market: evidence from 35 cities in China. Appl. Econ. 47(60), 6580–6598 (2015)
Christou, C., Gupta, R., Nyakabawo, W., Wohar, M.E.: Do house prices hedge inflation in the US? a quantile cointegration approach. Int. Rev. Econ. Financ. 54, 15–26 (2018)
Azmi, A.S.M., et al.: Inflation hedging characteristics of Malaysian residential properties. In: International Real Estate Research Symposium (IRERS), Kuala Lumpur, Malaysia (2010)
Lee, K.N.H.: Inflation and residential property markets: a bounds testing approach. Int. J. Trade Econ. Financ. 3(3), 183 (2012)
Nneji, O., Brooks, C., Ward, C.W.: House price dynamics and their reaction to macroeconomic changes. Econ. Model. 32, 172–178 (2013)
Clapp, J.M., Giaccotto, C.: The influence of economic variables on local house price dynamics. J. Urban Econ. 36(2), 161–183 (1994)
Demary, M.: The link between output, inflation, monetary policy and housing price dynamics. MPRA Paper No. 15978, (2009)
Tang, J., Ye, K., Qian, Y.: Rethinking the relationship between housing prices and inflation: new evidence from 29 large cities in China. Int. J. Strateg. Prop. Manag. 23(3), 142–155 (2019)
Wolski, R.: Residential real estate as a potential hedge of capital against inflation. Real Estate Manag. Valuation 31(1), 36–42 (2023)
Eurostat database. https://ec.europa.eu/eurostat/data/database. Accessed 16 Feb 2024
Housing price statistics - owner-occupied housing price index. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Housing_price_statistics_-_owner-occupied_housing_price_index#Weights_for_the_calculation_of_OOHPI. Accessed 27 Feb 2024
Cournède, B.: House prices and inflation in the Euro area. In: OECD Economics Department Working Papers No. 450. OECD Publishing (2005)
Eurostat. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Tutorial:Country_codes_and_protocol_order#EU_and_euro_area_aggregates. Accessed 27 Feb 2024
Housing price statistics – house price index. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Housing_price_statistics_-_house_price_index#Dynamics_in_the_housing_market:_uses_of_the_house_price_index_and_policy_implications. Accessed 27 Feb 2024
Lisi, G., Iacobini, M.: Measuring the effect of location on house prices in italy. Reg. Econ. Dev. Res. 54–62 (2020)
Manzoli, E., Mocetti, S.: The house price gradient: evidence from Italian cities. Ital. Econ. J 5, 281–305 (2019)
d’Acci, L.: Quality of urban area, distance from city centre, and housing value. case study on real estate values in Turin. Cities 91, 71–92 (2019)
Casolaro, L., Fabrizi, C.: House prices in local markets in Italy: dynamics, levels and the role of urban agglomerations. Bank Italy Occas. Paper No. 456, (2018)
Del Giudice, V., De Paola, P., Torrieri, F., Nijkamp, P.J., Shapira, A.: Real estate investment choices and decision support systems. Sustainability 11(11), 3110 (2019)
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Locurcio, M., Morano, P., Tajani, F., Sica, F., Acquafredda, T. (2024). Relationship Between Real Estate Indices and Inflation Trends: An Application to the European Residential Property Market. In: Gervasi, O., Murgante, B., Garau, C., Taniar, D., C. Rocha, A.M.A., Faginas Lago, M.N. (eds) Computational Science and Its Applications – ICCSA 2024 Workshops. ICCSA 2024. Lecture Notes in Computer Science, vol 14818. Springer, Cham. https://doi.org/10.1007/978-3-031-65273-8_8
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