Türkiye İllerinde Şehirleşme Dinamiklerinin “Üretim” ve “Tüketim” Şehirleri Yaklaşımına Göre Analizi

Year 2022, Volume: 11 Issue: 3, 151 - 175, 23.12.2022

Emine Tahsin , Furkan Börü

Abstract

Son yıllarda Türkiye özelinde şehirleşme dinamiklerinin, iller düzeyinde analizi de önem kazanmıştır. Buradan hareketle çalışma, şehirleşme eğilimlerini NUTS 3 düzeyinde tartışılması amaçlanmaktadır. Bu kapsamda, özellikle GSYH sektörel katma değer payları ile hava kalitesi verisi (PM10) üzerinde durularak şehirleşme dinamikleri analiz edilmektedir. İlgili yazında bir şehrin “üretim” ya da “tüketim” temelli olarak tanımlanması, ticarete konu olan ve olmayan sektörlere sahip olması ile ilgili olarak açıklanmaktadır. Buna bağlı olarak, Türkiye illerinin şehirleşme dinamiklerinin, “üretim” ya da “tüketim” şehirleri olarak farklılık gösterip göstermediği, çevre koşullarının ne ölçüde farklılaştığı yanıtlanmaya çalışılmaktadır. Bu amaçla, 2010-2020 arası dönemde, ilgili verileri NUTS 3 düzeyinde sınamak amacı ile Panel VAR(Vektör Otoregresyon) analizi kullanılmıştır. Temel bulgular, Türkiye illerindeki şehirleşme dinamiklerinin sadece sanayileşme olgusuyla açıklanamayacağını göstermektedir. Şehirleşme, farklı sektörel kapsamlarla ortaya çıkmakta, ayrıca şehirleşme dinamikleri hizmet ve inşaat sektörlerini etkilemektedir.

Keywords

Şehirleşme, Türkiye’nin şehirleri, Üretici şehirler, Çevresel tahribat ve şehirleşme, tüketim şehirleri

Analysis of Urbanization Dynamics in Turkey’s Provinces Based on “Production” and “Consumption” Cities Approach

Abstract

In recent years, analysis of urbanization dynamics in Turkey at the provincial level has become more important. Given that, the paper aims to discuss urbanization trends at the NUTS 3 level. In this context, urbanization dynamics are analyzed by focusing on sectoral value-added shares in GDP and air quality data (PM10). The approaches related to the classification of the cities- either as a “production” or “consumption”- depending on cities’ owning tradeable and non-tradeable sectors is considered. Accordingly, the urbanization dynamics of Turkey’s provinces and to what extent environmental conditions differ would be investigated. The panel VAR (Vector Autoregressive Regression) analysis is used for the relevant data on the NUTS 3 level for the period of 2010-2020. The main findings indicate that the urbanization dynamics in Turkey’s provinces cannot be explained only by the industrialization phenomenon. Urbanization occurs with different sectoral compositions additionally urbanization dynamics impacts services and construction sectors.

Keywords

Urbanization, Turkey’s cities, producer cities, environmental degradation and urbanization, consumption cities, tüketim şehirleri

References

• Abrigo, M. R. & Love, I. (2016). Estimation of panel vector autoregression in Stata. The Stata Journal, 16(3), 778-804. https://doi.org/10.1177/1536867X1601600314
• Aksoy, T., Taştan, H. & Kama, Ö. (2019). Revisiting income convergence in Turkey: Are there convergence clubs? Growth and Change, 50(3), 1185-1217. https://doi.org/10.1111/grow.12310
• Börü, F. & Tahsin E. (2022). Türkiye’de Nuts-2 düzeyinde “hizmetleşme” ve kalkınma biçimlerinin analizi. https://econanadolu.com/papers/Boru_Tahsin_An_F.pdf, VI. Anadolu International Conference on Economics, May 13-15, 2022, Eskişehir, Turkey.
• Cetin, M., Ecevit, E. & Yucel, A. G. (2018). Structural breaks, urbanization and CO2 emissions: evidence from Turkey. Journal of Applied Economics and Business Research, 8(2), 122-139.
• Dogan, E., Chishti, M. Z., Alavijeh, N. K. & Tzeremes, P. (2022). The roles of technology and Kyoto Protocol in energy transition towards COP26 targets: Evidence from the novel GMM-PVAR approach for G-7 countries. Technological Forecasting and Social Change, 181, 121756. https://doi.org/10.1016/j.techfore.2022.121756
• Durusu-Ciftci, D. & Nazlioğlu, Ş. (2019). Does income converge in Turkey? An empirical assessment. Ege Academic Review, 19(1), 15-32. Doi: 10.21121/eab.2019148772
• Erdun, H., Öztürk, A., Çapraz, Ö.,Toros, H., Dursun, S. & Deniz, A. (2015). Spatial variation of PM10 in Turkey. In 7th Atmospheric Sciences Symposium, Istanbul, Turkey, (pp. 311-323).
• Glaeser, E. L. (2010). Introduction to Agglomeration Economics. In Glaeser, E. L. (ed.) Agglomeration economics. (pp. 1-14). University of Chicago Press.
• Glaeser, E. L. (2014). A world of cities: the causes and consequences of urbanization in poorer countries. Journal of the European Economic Association, 12(5), 1154-1199. https://doi.org/10.1111/jeea.12100
• Glaeser, E. L. & Kahn, M. E. (2004). Sprawl and urban growth. In Handbook of regional and urban economics (Vol. 4, pp. 2481-2527). Elsevier.
• Gollin, D., Jedwab, R. & Vollrath, D. (2016). Urbanization with and without industrialization. Journal of Economic Growth, 21(1), 35-70. https://doi.org/10.1007/s10887-015-9121-4
• Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438. https://doi.org/10.2307/1912791
• Grossman, G. M. & Krueger, A. B. (1991). Environmental impacts of a North American free trade agreement. National Bureau of Economic Research Working Paper Series 3914. https://doi.org/10.3386/w3914.
• Güçlü, M. (2016). The environmental Kuznets curve for Turkish Nuts-3 regions: a spatial econometric analysis. A spatial econometric analysis. In Proceedings of the 12th International Conference of ASECU: Inclusive and Sustainable Development and the Role of Social and Solidarity Economy, Eskisehir, Turkey, 29–30 September 2016
• Henderson, J. V. (2010). Cities and development. Journal of Regional Science, 50(1), 515-540. https://doi.org/10.1111/j.1467-9787.2009.00636.x
• Holtz-Eakin, D., Newey, W. & Rosen, H. S. (1988). Estimating vector autoregressions with panel data. Econometrica, 56(6), 6371-1395.
• Jedwab, R., Ianchovichina, E. & Haslop, F. (2022). Consumption Cities versus Production Cities. World Bank Group Policy Research Working Paper 10105
• Karaca, O. (2018). 50 years of regional convergence in Turkey: New data set and analysis for the period 1960-2010. Sosyoekonomi, 26(35), 207-228. https://doi.org/10.17233/sosyoekonomi.343016
• Karahasan, B. C. & Pinar, M. (2022). The environmental Kuznets curve for Turkish provinces: a spatial panel data approach. Environmental Science and Pollution Research, 29(17), 25519-25531. https://doi.org/10.1007/s11356-021-17706-w
• Kocabas, A. (2013). The transition to low carbon urbanization in Turkey: Emerging policies and initial action. Habitat International, 37, 80-87. https://doi.org/10.1016/j.habitatint.2011.12.016
• Levin, A., Lin, C. F. & Chu, C. S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1-24. https://doi.org/10.1016/S0304-4076(01)00098-7
• Lin, B. & Zhu, J. (2017). Energy and carbon intensity in China during the urbanization and industrialization process: A panel VAR approach. Journal of Cleaner Production, 168, 780-790. https://doi.org/10.1016/j.jclepro.2017.09.013
• Lise, W. (2006). Decomposition of CO2 emissions over 1980–2003 in Turkey. Energy Policy, 34(14), 1841-1852. https://doi.org/10.1016/j.enpol.2004.12.021
• Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer Science & Business Media. Love, I. & Zicchino, L. (2006). Financial development and dynamic investment behavior: evidence from panel VAR. The Quarterly Review of Economics and Finance, 46(2), 190-210. https://doi.org/10.1016/j.qref.2005.11.007
• OECD (2018). Rethinking Urban Sprawl: Moving towards Sustainable Cities, OECD Publishing, Paris.
• Our World in Data (2022). www. OurWorldInData.org.
• Pata, U. K. (2018). Renewable energy consumption, urbanization, financial development, income and CO2 emissions in Turkey: testing EKC hypothesis with structural breaks. Journal of Cleaner Production, 187, 770-779. https://doi.org/10.1016/j.jclepro.2018.03.236
• Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels (IZA Discussion Paper No. 1240). Institute for the Study of Labor (IZA).
• Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of Applied Econometrics, 22(2), 265-312.
• Sigmund, M. & Ferstl, R. (2021). Panel vector autoregression in R with the package panelvar. The Quarterly Review of Economics and Finance, 80, 693-720.
• TurkStat (2022). www.tuik.gov.tr
• WHO, (2005). WHO Air Quality Guidelines For Particulate Matter, Ozone, Nitrogen Dioxide and Sulfur Dioxide.
• World Health Organization. http://whqlibdoc.who.int/hq/2006/WHO_SDE_ PHE_OEH_06. 02_eng. pdf
• World Bank (2022). www.worldbank.org
• Yildirim, J., Alpaslan, B. & Eker, E. E. (2021). The role of social capital in environmental protection efforts: evidence from Turkey. Journal of Applied Statistics, 48(13-15), 2626-2642. https://doi.org/10.1080/02664763.2020.1843609