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How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?

Year 2023, Volume: 10 Issue: 2, 505 - 523, 02.08.2023

Ahmet Usta

Abstract

This study empirically investigates the impact financial inclusion through digital banking channels has on income inequality in Türkiye using quarterly data for the 2011:Q1-2021:Q4 period. The study uses the Gini index to measure the dependent variable of income inequality and employs two variables as proxies for digital banking. The first variable is the share of the investment volume in the total financial transaction volume made by retail customers through Internet banking. The second variable is a factor constructed based on the transaction volume per unitof main items under financial transactions. The study relies on time series approaches to test whether digital banking-driven financial inclusion has a significant impact on income inequality in Türkiye. As for the empirical evidence, the study employs the dynamic ordinary least squares method to obtain long-run coefficients, a vector autoregressive model to obtain short-run dynamics through impulse response functions with biascorrected bootstrap confidence intervals that account for the bias and skewness of the small sample, and a causality analysis. The findings show that digital financial inclusion has a widening impact on income inequality. Regarding the dynamic interactions, the Gini coefficient has been discovered to increase in response to digital banking innovations. The findings also reveal digital banking to have a forecasting ability on income inequality in Türkiye regarding the sample period.

Keywords

Digitalization Banking Financial inclusion Income inequality Economic development

References

  • Asongu, S. A. & Nwachukwu, J. C. (2018). Comparative human development thresholds for absolute and relative pro-poor mobile banking in developing countries. Information Technology & People, 31 (1), 63-93. https://doi. org/10.1108/ITP-12-2015-0295 google scholar
  • Asongu, S. A. & Odhiambo, N. M. (2019a). Mobile banking usage, quality of growth, inequality, and poverty in developing countries. Information Development, 35(2), 303-318. https://doi.org/10.1177/0266666917744006 google scholar
  • Asongu, S. A. & Odhiambo, N. M. (2019b). How enhancing information and communication technology has affected inequality in Africa for sustainable development: An empirical investigation. Sustainable Development, 27(4), 647-656. https://doi.org/10.1002/sd.1929 google scholar
  • BKM. (n.d.). Reports. https://bkm.com.tr/en/reports-and-publications/reports-2/ google scholar
  • Canh, N. P., Schinckus, C., Thanh, S. D., & Ling, F. C. H. (2020). Effects of the internet, mobile, and land phones on income inequality and the Kuznets curve: Cross country analysis. Telecommunications Policy, 44(10), 1-15. https://doi.org/10.1016/j.telpol.2020.102041 google scholar
  • Daud, S. N. M., Ahmad, A. H. & Ngah, W. A. S. W. (2021). Financialization, digital technology, and income inequality. Applied Economics Letters, 28(16), 1339-1343, https://doi.org/10.1080/13504851.2020.1808165 google scholar
  • Demir, A., Pesque-Cela, V., Altunbas, Y. & Murinde, V (2022). Fintech, fnancial inclusion, and income inequality: a quantile regression approach. The European Journal ofFinance, 28(1), 86-107. https://doi.org/10.1080/1351 847X.2020.1772335 google scholar
  • Dickey, D. A. & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root.Journal ofAmerican Statistical Association, 74(306), 427-431 google scholar
  • EVDS-CBRT. (n.d.). https://evds2.tcmb.gov.tr/index.php?/evds/serieMarket google scholar
  • GPFI. (2016). G20 high-level principles for digital financial inclusion. https://www.gpfi.org/sites/gpfi/files/ G20%20High%20Level%20Principles%20for%20Digital%20Financial%20Inclusion.pdf google scholar
  • ICT. (n.d.). Statistics. Retrieved September 3 from https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx google scholar
  • Kilian, L. (1998). Small-sample confidence intervals for impulse response functions. The Review ofEconomics and Statistics, 80(2), 218-230. https://doi.org/10.1162/003465398557465 google scholar
  • MacKinnon, J. G. (1996). Numerical distribution functions for unit root and cointegration tests. Journal ofApplied Econometrics, 11(6), 601-618. google scholar
  • Phillips, P. C. B. & Perron, P. (1988). Testing for a unit root in time series regression, Biometrika, 75(2): 335-346 google scholar
  • Richmond, K. & Triplett, R. E. (2018). ICT and income inequality: a cross-national perspective. International Review ofApplied Economics, 32(2), 195-214. https://doi.org/10.1080/02692171.2017.1338677 google scholar
  • Saikkonen, P. (1991). Asymptotically efficient estimation of cointegration regressions. Econometric Theory, 7(1), 1-21. http://www.jstor.org/stable/3532106 google scholar
  • Stock, J. H. & Watson, M. W. (1993). A simple estimator of cointegrating vectors in higher-order integrated systems. Econometrica, 61(4), 783-820. https://doi.org/10.2307/2951763 google scholar
  • TBB. (2022a, February). Digital, Internet and Mobile Banking Statistics, December 2021. Retrieved September 6, 2022, from https://www.tbb.org.tr/Content/Upload/istatistikiraporlar/ekler/3328/Digital-Internet-Mobile_ Banking_Statistics-December_2021.pdf google scholar
  • TBB. (2022b, February). Digital, Internet and Mobile Banking Statistics, March 2006-December 2021. Retrieved google scholar
  • September 6, 2022, from https://www.tbb.org.tr/tr/bankacilik/banka-ve-sektor-bilgileri/istatistiki-raporlar/59 google scholar
  • Tchamyou, V. S., Erreygers, G. & Cassimon, D. (2019). Inequality, ICT, and financial access in Africa. Technological Forecasting and Social Change, 139, 169-184. https://doi.org/10.1016/j.techfore.2018.11.004 google scholar
  • Toda, H. Y. & Yamamoto, T. (1995). Statistical Inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. https://doi.org/10.1016/0304-4076(94)01616-8 google scholar
  • TURKSTAT. (2022, May 6). Income and Living Conditions Survey, 2021. Retrieved October 3, 2022, from https:// data.tuik.gov.tr/Bulten/Index?p=Income-and-Living-Conditions-Survey-2021-45581&dil=2 google scholar
  • World Bank. (n.d.). Metadata Glossary. Retrieved October 10, 2022, from https://databank.worldbank.org/ metadataglossary/world-development-indicators/series/SI.POV.GINI google scholar
  • Yin, Z. H. & Choi, C. H. (2022). Does digitalization contribute to lesser income inequality? Evidence from G20 countries. Information Technology for Development. https://doi.org/10.1080/02681102.2022.2123443 google scholar

Türkiye’de Dijital Bankacılık Kanalıyla Finansal Içerilme Gelir Eşitsizliğini Nasıl Etkiler?

Year 2023, Volume: 10 Issue: 2, 505 - 523, 02.08.2023

Ahmet Usta

Abstract

Bu çalışma Türkiye’de dijital bankacılık kanalıyla yaygınlaşan finansal içerilmenin gelir eşitsizliği üzerine etkisini 2011:Ç1 ve 2021:Ç4 dönemine ait çeyreklik veri seti ile ampirik olarak incelemiştir. Gelir eşitsizliğini ölçmek için kullandığımız Gini katsayısı bağımlı değişken olarak belirlenmiştir. Dijital bankacılığı ölçmek için iki tane vekil değişken kullanılmıştır. Birinci vekil değişken Internet bankacılığı kanalıyla bireysel müşteriler tarafından yapılan yatırım işlemlerine ait işlem hacminin toplam finansal işlemler hacmi içindeki payı olarak belirlenmiştir. İkinci vekil değişken ise yine bireysel yatırımcılar tarafından Internet bankacılığı kanalıyla yapılan ve finansal işlemler altındaki kalemlerin birim başına düşen işlem hacimlerinden elde edilen faktör olarak belirlenmiştir. Türkiye’de dijital bankacılık yoluyla artan finansal içerilmenin gelir eşitsizliği üzerinde anlamlı bir etkisinin olup olmadığını test etmek için zaman serileri yaklaşımları kullanılmıştır. Ampirik bulgular için dinamik olağan en küçük kareler yöntemi, küçük örneklemler için yanlılığı ve çarpıklığı dikkate alan güven aralıklarına sahip etki-tepki fonksiyonlarını ede etmek için vektör otoregresif modeli ve nedensellik testi kullanılmıştır. Analiz sonuçlarına göre dijital finansal içerilme zengin ve yoksul hane halkları arasındaki gelir eşitsizliğini arttırıcı etki göstermiştir. Dinamik etkileşimler dikkate alındığında ise dijital bankacılık kullanımının yaygınlaşmasına tepki olarak Gini katsayısının arttığı ortaya çıkmıştır. Ayrıca, Türkiye için söz konusu analiz döneminde dijital bankacılıktan gelireşitsizliğine doğru tek yönlü bir nedensellik ortaya koyulmuştur.

Keywords

Dijitalleşme Bankacılık Finansal içerilme Gelir eşitsizliği İktisadi gelişme

References

  • Asongu, S. A. & Nwachukwu, J. C. (2018). Comparative human development thresholds for absolute and relative pro-poor mobile banking in developing countries. Information Technology & People, 31 (1), 63-93. https://doi. org/10.1108/ITP-12-2015-0295 google scholar
  • Asongu, S. A. & Odhiambo, N. M. (2019a). Mobile banking usage, quality of growth, inequality, and poverty in developing countries. Information Development, 35(2), 303-318. https://doi.org/10.1177/0266666917744006 google scholar
  • Asongu, S. A. & Odhiambo, N. M. (2019b). How enhancing information and communication technology has affected inequality in Africa for sustainable development: An empirical investigation. Sustainable Development, 27(4), 647-656. https://doi.org/10.1002/sd.1929 google scholar
  • BKM. (n.d.). Reports. https://bkm.com.tr/en/reports-and-publications/reports-2/ google scholar
  • Canh, N. P., Schinckus, C., Thanh, S. D., & Ling, F. C. H. (2020). Effects of the internet, mobile, and land phones on income inequality and the Kuznets curve: Cross country analysis. Telecommunications Policy, 44(10), 1-15. https://doi.org/10.1016/j.telpol.2020.102041 google scholar
  • Daud, S. N. M., Ahmad, A. H. & Ngah, W. A. S. W. (2021). Financialization, digital technology, and income inequality. Applied Economics Letters, 28(16), 1339-1343, https://doi.org/10.1080/13504851.2020.1808165 google scholar
  • Demir, A., Pesque-Cela, V., Altunbas, Y. & Murinde, V (2022). Fintech, fnancial inclusion, and income inequality: a quantile regression approach. The European Journal ofFinance, 28(1), 86-107. https://doi.org/10.1080/1351 847X.2020.1772335 google scholar
  • Dickey, D. A. & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root.Journal ofAmerican Statistical Association, 74(306), 427-431 google scholar
  • EVDS-CBRT. (n.d.). https://evds2.tcmb.gov.tr/index.php?/evds/serieMarket google scholar
  • GPFI. (2016). G20 high-level principles for digital financial inclusion. https://www.gpfi.org/sites/gpfi/files/ G20%20High%20Level%20Principles%20for%20Digital%20Financial%20Inclusion.pdf google scholar
  • ICT. (n.d.). Statistics. Retrieved September 3 from https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx google scholar
  • Kilian, L. (1998). Small-sample confidence intervals for impulse response functions. The Review ofEconomics and Statistics, 80(2), 218-230. https://doi.org/10.1162/003465398557465 google scholar
  • MacKinnon, J. G. (1996). Numerical distribution functions for unit root and cointegration tests. Journal ofApplied Econometrics, 11(6), 601-618. google scholar
  • Phillips, P. C. B. & Perron, P. (1988). Testing for a unit root in time series regression, Biometrika, 75(2): 335-346 google scholar
  • Richmond, K. & Triplett, R. E. (2018). ICT and income inequality: a cross-national perspective. International Review ofApplied Economics, 32(2), 195-214. https://doi.org/10.1080/02692171.2017.1338677 google scholar
  • Saikkonen, P. (1991). Asymptotically efficient estimation of cointegration regressions. Econometric Theory, 7(1), 1-21. http://www.jstor.org/stable/3532106 google scholar
  • Stock, J. H. & Watson, M. W. (1993). A simple estimator of cointegrating vectors in higher-order integrated systems. Econometrica, 61(4), 783-820. https://doi.org/10.2307/2951763 google scholar
  • TBB. (2022a, February). Digital, Internet and Mobile Banking Statistics, December 2021. Retrieved September 6, 2022, from https://www.tbb.org.tr/Content/Upload/istatistikiraporlar/ekler/3328/Digital-Internet-Mobile_ Banking_Statistics-December_2021.pdf google scholar
  • TBB. (2022b, February). Digital, Internet and Mobile Banking Statistics, March 2006-December 2021. Retrieved google scholar
  • September 6, 2022, from https://www.tbb.org.tr/tr/bankacilik/banka-ve-sektor-bilgileri/istatistiki-raporlar/59 google scholar
  • Tchamyou, V. S., Erreygers, G. & Cassimon, D. (2019). Inequality, ICT, and financial access in Africa. Technological Forecasting and Social Change, 139, 169-184. https://doi.org/10.1016/j.techfore.2018.11.004 google scholar
  • Toda, H. Y. & Yamamoto, T. (1995). Statistical Inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. https://doi.org/10.1016/0304-4076(94)01616-8 google scholar
  • TURKSTAT. (2022, May 6). Income and Living Conditions Survey, 2021. Retrieved October 3, 2022, from https:// data.tuik.gov.tr/Bulten/Index?p=Income-and-Living-Conditions-Survey-2021-45581&dil=2 google scholar
  • World Bank. (n.d.). Metadata Glossary. Retrieved October 10, 2022, from https://databank.worldbank.org/ metadataglossary/world-development-indicators/series/SI.POV.GINI google scholar
  • Yin, Z. H. & Choi, C. H. (2022). Does digitalization contribute to lesser income inequality? Evidence from G20 countries. Information Technology for Development. https://doi.org/10.1080/02681102.2022.2123443 google scholar
There are 25 citations in total.

Details

Primary Language English
Subjects Economics
Journal Section RESEARCH ARTICLE
Authors

Ahmet Usta 0000-0001-9899-8072

Publication Date August 2, 2023
Submission Date December 31, 2022
Published in Issue Year 2023 Volume: 10 Issue: 2

Cite

APA Usta, A. (2023). How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?. İktisat Politikası Araştırmaları Dergisi, 10(2), 505-523.
AMA Usta A. How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?. JEPR. August 2023;10(2):505-523.
Chicago Usta, Ahmet. “How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?”. İktisat Politikası Araştırmaları Dergisi 10, no. 2 (August 2023): 505-23.
EndNote Usta A (August 1, 2023) How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?. İktisat Politikası Araştırmaları Dergisi 10 2 505–523.
IEEE A. Usta, “How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?”, JEPR, vol. 10, no. 2, pp. 505–523, 2023.
ISNAD Usta, Ahmet. “How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?”. İktisat Politikası Araştırmaları Dergisi 10/2 (August 2023), 505-523.
JAMA Usta A. How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?. JEPR. 2023;10:505–523.
MLA Usta, Ahmet. “How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?”. İktisat Politikası Araştırmaları Dergisi, vol. 10, no. 2, 2023, pp. 505-23.
Vancouver Usta A. How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye?. JEPR. 2023;10(2):505-23.
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