Investigation of Factors Affecting Housing Sales in Turkey in Terms of Covid-19 Period: Count Time Series Model

Abstract

One of the important components of economic growth in Turkey is the housing sector. Achieving the balance of housing supply and demand depends on accurate housing sales forecasts using new generation techniques. However, while estimating the amount of house sales, extraordinary events such as economic and financial crises, epidemics, natural disasters in the examined period should be considered. The aim of this study is to estimate the relationship between housing demand and macroeconomic variables in Turkey by count time series analysis, considering the impact of the covid epidemic. The findings show that the consumer price index and housing loan rates have a negative effect on the amount of housing sales; reveal that the dollar exchange rate and the housing price index have a positive effect on housing sales. In the post-covid period, while the increases in the consumer price index have a higher reducing effect on the amount of house sales, it has been observed that the increases in the dollar exchange rate, housing price index, and housing loan rates have a positive effect on the amount of housing sales.

Keywords

• Housing demand
• count time series model
• covid-19

Türkiye’de Konut Satışlarını Etkileyen Faktörlerin Kovid-19 Süreci Açısından İncelenmesi: Sayma Zaman Serisi Modeli

Abstract

Türkiye’de ekonomik büyümenin önemli bileşenlerinden biri konut sektörüdür. Konut arz ve talebinin dengesinin sağlanmasında ise konut satış tahminlerinin yeni nesil tekniklerle doğru bir şekilde yapılmasına bağlıdır. Bununla birlikte, konut satış miktarına ait tahminler yapılırken incelenen dönemdeki ekonomik ve finansal krizler, salgın hastalıklar, doğal afetler gibi olağanüstü olaylar dikkate alınmalıdır. Bu çalışmanın amacı, Türkiye’de konut talebi ile makroekonomik değişkenler arasındaki ilişkinin kovid salgınının etkisini de dikkate alarak sayma zaman serisi analizi ile tahmin edilmesidir. Elde edilen bulgular, tüketici fiyat indeksi ve konut kredi faizlerinin konut satış miktarları üzerinde negatif bir etkiye sahip olduğunu; dolar kuru ve konut fiyat indeksinin ise konut satış miktarlarını pozitif etkilediğini ortaya çıkarmıştır. Kovid sonrası dönemde ise tüketici fiyat indeksindeki artışların konut satış miktarı üzerinde daha yüksek bir azaltıcı etkisi söz konusu iken; dolar kuru, konut fiyat indeksi ve konut kredi faizlerindeki artışların konut satış miktarı üzerinde pozitif bir etki yarattığı görülmüştür.

Keywords

• konut talebi
• sayma zaman serisi modeli
• kovid-19

References

1. Atasoy, T., & Tanrıvermiş, H. (2021). Türkiye’de Konut Kredisi Hacmi ile Seçilmiş Makroekonomik Faktörler Arasındaki İlişkinin Değerlendirilmesi. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 59, 461–484.
2. Barot, B. (2001). An econometric demand–supply model for Swedish private housing. International Journal of Housing Policy, 1(3), 417–444. https://doi.org/10.1080/14616710110091570
3. Barot, B. (2002). House Prices and Housing Investment in Sweden and the United Kingdom . Econometric Analysis for the period 1970 – 1998 By Bharat Barot National Institute of Economic Research ( N . I . E . R .), Sweden and Institute for Housing and Urban Research. Review of Urban & Regional Development Studies (RURDS), 14(2).
4. Blackley, D. M., & Follain, J. R. (1991). An econometric model of the metropolitan housing market. Journal of Housing Economics, 1, 140–167. https://doi.org/10.1016/S1051-1377(05)80030-0
5. Börsch-Supan, A., Heiss, F., & Seko, M. (2001). Housing demand in Germany and Japan. Journal of Housing Economics, 10, 229–252. https://doi.org/10.1006/jhec.2001.0295
6. Börsch-Supan, A., & Pitkin, J. (1988). On discrete choice models of housing demand. Journal of Urban Economics, 24, 153–172. https://doi.org/10.1016/0094-1190(88)90036-8
7. Box, G. E. P., & Jenkins, G. M. (1970). Time series analysis: Forecasting and control. San Francisco, CA: Holden-Day.
8. Dusansky, R., & Koç, Ç. (2007). The capital gains effect in the demand for housing. Journal of Urban Economics, 61, 287–298. https://doi.org/10.1016/j.jue.2006.07.008

9. Follain, J. R. (1982). Does Inflation Affect Real Behavior: The Case of Housing. Southern Economic Journal, 48(3), 570–582. https://doi.org/10.2307/1058651
10. Follain, J. R., & Jimenez, E. (1985). Estimating the demand for housing characteristics: A survey and critique. Regional Science and Urban Economics, 15, 77–107. https://doi.org/10.1016/0166-0462(85)90033-X
11. García, J. A. B., & Hernández, J. E. R. (2007). Housing and urban location decisions in Spain: An econometric analysis with unobserved heterogeneity. Urban Studies, 44(9), 1657–1676. https://doi.org/10.1080/00420980701426624
12. García, J. A. B., & Hernández, J. E. R. (2008). Housing demand in Spain according to dwelling type: Microeconometric evidence. Regional Science and Urban Economics, 38, 363–377. https://doi.org/10.1016/j.regsciurbeco.2008.02.002
13. Goodman, A. C. (1988). An Econometric Model of Housing Price, Permanent Income, Tenure Choice, and Housing Demand. Journal of Urban Economics, 23, 327–353.
14. Halicioglu, F. (2005). The Demand for New Housıng in Turkey: An Applıcatıon of ARDL Model. 2005 Business and Economics Society International Conference, 1–10.
15. Haurin, D. R. (1991). Income variability, homeownership, and housing demand. Journal of Housing Economics, 1, 60–74. https://doi.org/10.1016/S1051-1377(05)80025-7
16. Investing.com. (n.d.). Retrieved April 20, 2022, from https://www.investing.com/
17. Isaac, M., Allen, M., & Mary, S. (1991). The Economic Theory of Housing Demand: A Critical Review. Journal of Real Estate Research, 6(3), 381–393. https://doi.org/10.1080/10835547.1991.12090650
18. King, M. A. (1980). An econometric model of tenure choice and demand for housing as a joint decision. Journal of Public Economics, 14(2), 137–159. https://doi.org/10.1016/0047-2727(80)90038-9
19. Megbolugbe, I. F., & Cho, M. (1996). Racial and ethnic differences in housing demand: An econometric investigation. Journal of Real Estate Finance and Economics, 12, 295–318. https://doi.org/10.1007/BF00127539
20. Mussa, A., Nwaogu, U. G., & Pozo, S. (2017). Immigration and housing: A spatial econometric analysis. Journal of Housing Economics, 35, 13–25. https://doi.org/10.1016/j.jhe.2017.01.002
21. Özçim, H. (2022). Türkiye’deki Konut Satışı ile TCMB Politika Faiz Oranı ve Konut Fiyat Endeksi Arasındaki İlişkinin Analizi. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 12(1), 523–533.
22. Peng, R., & Wheaton, W. C. (1994). Effects of Restrictive Land Supply on Housing in Hong Kong: An Econometric Analysis. Journal of Housing Research, 5(2), 263–291.
23. Rapaport, C. (1997). Housing Demand and Community Choice: An Empirical Analysis. Journal of Urban Economics, 42, 243–260. https://doi.org/10.1006/juec.1996.2023
24. Rosen, H. S. (1979). Housing decisions and the U.S. income tax: An econometric analysis. Journal of Public Economics, 11, 1–23. https://doi.org/10.1016/0047-2727(79)90042-2
25. Salami, M. A., Tanrivermiş, H., & Tanrivermiş, Y. (2022). Performance evaluation and volatility of Turkey REITs during COVID-19 pandemic. Journal of Property Investment and Finance. https://doi.org/10.1108/JPIF-02-2022-0017
26. Solak, A. O., & Kabadayı, B. (2016). An econometric analysis of housing demand in Turkey. Advances in Management & Applied Economics, 6(3), 47–57. https://doi.org/10.17660/ActaHortic.1999.492.2
27. Sönmezer, S., & Aytüre, G. (2019). Türkiye’de Konut Piyasası Dinamikleri. International Conference on Eurasian Economies, 376–385.
28. Türkiye Cumhuriyet Merkez Bankası. (n.d.). Retrieved April 20, 2022, from http://evds.tcmb.gov.tr/cgi-bin/famecgi?cgi=$ozetweb&DIL=TR&ARAVERIGRUP=bie_dkdovizgn.db
29. Türkiye İstatistik Kurumu (TUİK). (n.d.). Retrieved April 20, 2022, from http://www.tuik.gov.tr
30. Vieira, A. B. de A. A. (2019a). Modeling Time Series of Counts : an Application to Basketball Analytics. Instituto Superior Tecnico, Lisboa, Portugal.
31. Vieira, A. B. de A. A. (2019b). Modeling Time Series of Counts : an Application to Basketball Analytics. https://fenix.tecnico.ulisboa.pt/downloadFile/281870113704928/Resumo_Alargado Final.pdf
32. Yaman Selçi, B. (2021). Türkiye’nin Konut Satışı Değerlerinin Yapay Sinir Ağları İle Öngörülmesi. Ekoist: Journal of Econometrics and Statistics, 0(35), 19–32. https://doi.org/10.26650/ekoist.2021.35.180033