IDEAS home Printed from https://ideas.repec.org/a/ire/issued/v28n032025p359-377.html

Financial and Macroeconomic Impacts on Real Estate Prices of Turkiye: 2013 to 2023

Author

Listed:
  • Olcay Ölçen

    (Aviation Management Department, İstanbul Gelisim University)

Abstract

The period between 2013 and 2023 was extraordinary for the economy of Türkiye. The citizens felt that all of the negativities resulted from the 2023 Kahramanmaras earthquake, the attempt of a military coup in 2016 and COVID-19 pandemic. During these events, sustaining economic policies with healthy dynamics is not easy in terms of micro, macro and international dimensions. It is indispensable for multi-layered real estate markets to exist normally in such unpredictable times. This research mainly focuses on these situations and investigates the relationship between the macroeconomic variables and housing price index changes, which has been accepted as an important variable of price in the real estate market as a price indicator. Using the Markov switching regression model, it is found that inflation and unemployment impact the housing price index changes. On the other hand, another important finding of this research work is the statistical, negative and positive-sided (asymmetric) relationship between gross domestic product growth and housing price index changes. It can be concluded from these findings that the government, investors and consumers of the real estate markets have been subjected to challenging and difficult macro-periods; these extraordinary events have also been so destructive that the expectations, wishes and desires of the market participants are not easily met.

Suggested Citation

  • Olcay Ölçen, 2025. "Financial and Macroeconomic Impacts on Real Estate Prices of Turkiye: 2013 to 2023," International Real Estate Review, Global Social Science Institute, vol. 28(3), pages 359-377.
    • Handle: RePEc:ire:issued:v:28:n:03:2025:p:359-377
    DOI: 10.53383/100407
    as

    Download full text from publisher

    File URL: https://doi.org/10.53383/100407
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.53383/100407?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jack H. Rubens & Michael T. Bond & James R. Webb, 1989. "The Inflation-Hedging Effectiveness of Real Estate," Journal of Real Estate Research, American Real Estate Society, vol. 4(2), pages 45-56.
    2. Daniel Fehrle, 2023. "Hedging against inflation: housing versus equity," Empirical Economics, Springer, vol. 65(6), pages 2583-2626, December.
    3. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    4. Yasmine Essafi Zouari & Aya Nasreddine & Arnaud Simon, 2022. "The Role of Housing in a Mixed-Asset Portfolio: The Particular Case of Direct Housing Within the Greater Paris Area," Post-Print halshs-04010367, HAL.
    5. Aizenman, Joshua & Jinjarak, Yothin, 2009. "Current account patterns and national real estate markets," Journal of Urban Economics, Elsevier, vol. 66(2), pages 75-89, September.
    6. François Geerolf & Thomas Grjebine, 2014. "Assessing House Price Effects on Unemployment Dynamics," Working Papers 2014-25, CEPII research center.
    7. Yasmine Essafi Zouari & Aya Nasreddine & Arnaud Simon, 2022. "The Role of Housing in a Mixed-Asset Portfolio: The Particular Case of Direct Housing Within the Greater Paris Area," Journal of Housing Research, Taylor & Francis Journals, vol. 31(2), pages 196-219, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chelghoum, Amirouche & Boumimez, Fayçal & Alsamara, Mouyad, 2025. "Factors influencing asymmetries in Saudi Arabia's housing market," The Journal of Economic Asymmetries, Elsevier, vol. 31(C).
    2. João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020. "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
    3. Winkelried, Diego, 2012. "Predicting quarterly aggregates with monthly indicators," Working Papers 2012-023, Banco Central de Reserva del Perú.
    4. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    5. Hans-Joachim Dübel, 2014. "Transatlantic mortgage credit boom and bust - the impact of market structure and regulation," Chapters, in: Susan Wachter & Man Cho & Moon Joong Tcha (ed.), The Global Financial Crisis and Housing, chapter 6, pages 112-146, Edward Elgar Publishing.
    6. Diakonova, Marina & Molina, Luis & Mueller, Hannes & Pérez, Javier J. & Rauh, Christopher, 2024. "The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(4).
    7. Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2024. "Panel data nowcasting: The case of price–earnings ratios," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 292-307, March.
    8. Charles Ka Yui Leung & Joe Cho Yiu Ng, 2018. "Macro Aspects of Housing," GRU Working Paper Series GRU_2018_016, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    9. Marie Bessec, 2019. "Revisiting the transitional dynamics of business cycle phases with mixed-frequency data," Econometric Reviews, Taylor & Francis Journals, vol. 38(7), pages 711-732, August.
    10. Qifa Xu & Lu Chen & Cuixia Jiang & Yezheng Liu, 2022. "Forecasting expected shortfall and value at risk with a joint elicitable mixed data sampling model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 407-421, April.
    11. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Economics Working Papers ECO2013/02, European University Institute.
    12. Lane, Philip R. & Milesi-Ferretti, Gian Maria, 2012. "External adjustment and the global crisis," Journal of International Economics, Elsevier, vol. 88(2), pages 252-265.
    13. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
    14. Lu Wang & Feng Ma & Guoshan Liu, 2020. "Forecasting stock volatility in the presence of extreme shocks: Short‐term and long‐term effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 797-810, August.
    15. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    16. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
    17. David E. Allen & Michael McAleer & Marcel Scharth, 2009. "Realized Volatility Risk," CIRJE F-Series CIRJE-F-693, CIRJE, Faculty of Economics, University of Tokyo.
    18. Zadrozny, Peter A., 2016. "Extended Yule–Walker identification of VARMA models with single- or mixed-frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 438-446.
    19. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," JRFM, MDPI, vol. 7(2), pages 1-30, June.
    20. Andrew Powell & Pilar Tavella, 2012. "Capital Inflow Surges in Emerging Economies: How Worried Should LAC Be?," Research Department Publications 4782, Inter-American Development Bank, Research Department.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ire:issued:v:28:n:03:2025:p:359-377. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: IRER Graduate Assistant/Webmaster (email available below). General contact details of provider: https://www.gssinst.org/gssinst/index.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.