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Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?

Year 2024, Issue: 81, 60 - 71, 26.07.2024
https://doi.org/10.51290/dpusbe.1429793

Abstract

Bu çalışmada Türkiye’de 2001-2020 yılları arasında dijitalleşmenin gelir eşitsizliğini ampirik olarak nasıl etkilediği araştırılmıştır. Dijitalleşme göstergesi olarak genişbant aboneliği, internet kullanımı ve mobil abonelik, gelir eşitsizlik göstergesi olarak ise harcanabilir gelir üzerinden hesaplanan GİNİ katsayısı kullanılmıştır. ARDL yöntemi, KPSS durağanlık ve ADF birim kök testleriyle elde edilen bulgular şöyledir: i) Değişkenlerin bazıları seviyede durağan iken bazıları birinci dereceden durağanlaşmaktadır. ii) Açıklayıcı değişkenler bağımlı değişkeni uzun dönemde istikrarlı bir şekilde açıklayabilmektedir. iii) Her üç dijitalleşme göstergesindeki ve ticari açıklıktaki artış uzun dönemde gelir eşitsizliğini iyileştirmektedir. iv) Kişi başına reel gelirdeki artış uzun dönemde gelir eşitsizliğini arttırmaktadır. Bundan dolayı karar alıcılar dijitalleşme ve ticari açıklığı arttıracak ve iktisadi büyümenin gelir eşitsizliği üzerindeki bozucu etkisini ortadan kaldıracak politikalar tasarlamalı ve yürürlüğe koymalıdırlar.

References

  • Acaravcı, A., Akalin, G., & Erdoğan, S. (2019). Araştırmageliştirme harcamalarının Türkiye ihracatına etkileri. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 37(1), 1-16.
  • Acemoglu, D. (1998). Why do new technologies complement skills? Directed technical change and wage inequality. The Quarterly Journal of Economics, 113(4), 1055-1089.
  • Acemoglu, D. (2002). Technical change, inequality, and the labor market. Journal of Economic Literature, 40(1), 7-72.
  • Adams, S., & Akobeng, E. (2021). ICT, governance and inequality in Africa. Telecommunications Policy, 45(10), 102198.
  • Ali, B., Ullah, A., & Khan, D. (2021). Does the prevailing Indian agricultural ecosystem cause carbon dioxide emission? A consent towards risk reduction. Environmental Science and Pollution Research, 28, 4691-4703.
  • Alvaredo, F., Chancel, L., Piketty, T., Saez, E., & Zucman, G. (Eds.). (2018). World inequality report 2018. Belknap Press.
  • Al-Mulali, U., Solarin, S. A., & Ozturk, I. (2016). Investigating the presence of the environmental Kuznets curve (EKC) hypothesis in Kenya: an autoregressive distributed lag (ARDL) approach. Natural Hazards, 80, 1729-1747.
  • Al Qudah, A., Zouaoui, A., & Aboelsoud, M. E. (2020). Does corruption adversely affect economic growth in Tunisia? ARDL approach. Journal of Money Laundering Control, 23(1), 38-54.
  • Ariansyah, K., Barsei, A. N., Syahr, Z. H. A., Sipahutar, N. Y. P., Damanik, M. P., Perdananugraha, G. M., ... & Suryanegara, M. (2023). Unleashing the potential of mobile broadband: Evidence from Indonesia's underdeveloped regions on its role in reducing income inequality. Telematics and Informatics, 82, 102012.
  • Asongu, S. A., & Odhiambo, N. M. (2019). How enhancing information and communication technology has affected inequality in Africa for sustainable development: An empirical investigation. Sustainable Development, 27(4), 647-656.
  • Autor, D. H., Katz, L. F., & Krueger, A. B. (1998). Computing inequality: have computers changed the labor market?. The Quarterly Journal of Economics, 113(4), 1169-1213.
  • Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An empirical exploration. The Quarterly Journal of Economics, 118(4), 1279-1333.
  • Das, S., & Chatterjee, A. (2023). Impacts of ICT and digital finance on poverty and income inequality: a sub-national study from India. Information Technology for Development, 29(2-3), 378-405.
  • Efobi, U. R., Tanankem, B. V., & Asongu, S. A. (2018). Female economic participation with information and communication technology advancement: Evidence from Sub‐Saharan Africa. South African Journal of Economics, 86(2), 231-246.
  • Florida, R., & Mellander, C. (2016). The geography of inequality: Difference and determinants of wage and income inequality across US metros. Regional Studies, 50(1), 79-92.
  • Francalanci, C., & Morabito, V. (2008). IS integration and business performance: The mediation effect of organizational absorptive capacity in SMEs. Journal of Information Technology, 23, 297-312.
  • Gao, Y., Zang, L., & Sun, J. (2018). Does computer penetration increase farmers’ income? An empirical study from China. Telecommunications Policy, 42(5), 345–360.
  • Hasan, I., Horvath, R., & Mares, J. (2020). Finance and wealth inequality. Journal of International Money and Finance, 108, 102161.
  • Houngbonon, G. V., & Liang, J. (2017). Broadband internet and income inequality. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2963860.
  • Kuhn, M., Schularick, M., & Steins, U. I. (2020). Income and wealth inequality in America, 1949–2016. Journal of Political Economy, 128(9), 3469-3519.
  • Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54(1-3), 159-178.
  • Li, L., Zeng, Y., Ye, Z., & Guo, H. (2021). E‐commerce development and urban‐rural income gap: Evidence from Zhejiang Province, China. Papers in Regional Science, 100(2), 475-494.
  • Michaels, G., Natraj, A., & Van Reenen, J. (2014). Has ICT polarized skill demand? Evidence from eleven countries over twenty-five years. Review of Economics and Statistics, 96(1), 60-77.
  • Mah, J. S. (2000). An empirical examination of the disaggregated import demand of Korea — The case of information technology products. Journal of Asian Economics, 11(2), 237-244.
  • Njangang, H., Beleck, A., Tadadjeu, S., & Kamguia, B. (2022). Do ICTs drive wealth inequality? Evidence from a dynamic panel analysis. Telecommunications Policy, 46(2), 102246.
  • Noh, Y. H., & Yoo, K. (2008). Internet, inequality and growth. Journal of Policy Modeling, 30(6), 1005-1016.
  • Qiu, L., Zhong, S., & Sun, B. (2021). Blessing or curse? The effect of broadband Internet on China’s inter-city income inequality. Economic Analysis and Policy, 72, 626-650.
  • Pattichis, C.A. (1999), “Price and income elasticities of disaggregated import demand: results from UECMs and an application”, Applied Economics, 31(9), 1061-1071.
  • Pesaran, M. H., & Shin, Y. (1995). An autoregressive distributed lag modelling approach to cointegration analysis (Vol. 9514). Cambridge, UK: Department of Applied Economics, University of Cambridge.
  • Pesaran, H., & Shin, Y. (1999). An autoregressive distributed lag modelling approach to cointegration “chapter 11. In Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch Centennial Symposium. Cambridge University Press Cambridge.
  • Pesaran M.H., Shin, Y., R.J. Smith ( 2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16, 289–326.
  • Ponce, P., Yunga, F., Larrea-Silva, J., & Aguirre, N. (2023). Spatial determinants of income inequality at the global level: The role of natural resources. Resources Policy, 84, 103783.
  • Rajan, R. G., & Zingales, L. (2004). Saving capitalism from the capitalists: Unleashing the power of financial markets to create wealth and spread opportunity. Princeton University Press.
  • Richmond, K., & Triplett, R. E. (2018). ICT and income inequality: a cross-national perspective. International Review of Applied Economics, 32(2), 195-214.
  • Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review. Telematics and informatics, 32(1), 129-142.
  • Siaw, A., Jiang, Y., Twumasi, M. A., & Agbenyo, W. (2020). The impact of internet use on income: The case of rural Ghana. Sustainability, 12(8), 3255.
  • Smith, M. L., Spence, R., & Rashid, A. T. (2011). Mobile phones and expanding human capabilities. Information Technologies & International Development, 7(3), pp-77.
  • Stolper, W. F., & Samuelson, P. A. (1941). Protection and real wages. The Review of Economic Studies, 9(1), 58-73.
  • Tang, T., Cuesta, L., Tillaguango, B., Alvarado, R., Rehman, A., Bravo-Benavides, D., & Zárate, N. (2022). Causal link between technological innovation and inequality moderated by public spending, manufacturing, agricultural employment, and export diversification. Sustainability, 14(14), 8474.
  • Tchamyou, V. S., Erreygers, G., & Cassimon, D. (2019). Inequality, ICT and financial access in Africa. Technological Forecasting and Social Change, 139, 169-184.
  • TUİK, (2017). Gelir ve Yaşam Koşulları Araştırması, 2016, https://data.tuik.gov.tr/Bulten/Index?p=Gelir-ve-Yasam-Kosullari-Arastirmasi-2016-24579, Erişim Tarihi:27.09.2023
  • Ureta, S. (2008). Mobilising poverty?: Mobile phone use and everyday spatial mobility among low-income families in Santiago, Chile. The Information Society, 24(2), 83-92.
  • Wahiba, N. F., & Mahmoudi, D. (2023). Technological Change, Growth and Income Inequality. International Journal of Economics and Financial Issues, 13(1), 121.
  • Wang, J., & Xu, Y. (2023). Digitalization, income inequality, and public health: Evidence from developing countries. Technology in Society, 73, 102210.
  • World bank. (2016). Digital dividends, USA (World Development Report 2016).
  • Yin, Z. H., & Choi, C. H. (2023). Does digitalization contribute to lesser income inequality? Evidence from G20 countries. Information Technology for Development, 29(1), 61-82.
  • Zhang, X., Wan, G., Wang, C., & Luo, Z. (2017). Technical change and income inequality in China. The World Economy, 40(11), 2378-2402.
  • Zhang, F., & Li, D. (2018). Regional ICT access and entrepreneurship: Evidence from China. Information & Management, 55(2), 188–198.
  • Zhang, Y., Long, H., Ma, L., Tu, S., Li, Y., & Ge, D. (2022). Analysis of rural economic restructuring driven by e-commerce based on the space of flows: The case of xiaying village in central China. Journal of Rural Studies, 93, 196–209.

How does Digitalization Affect Income Inequality in Turkey?

Year 2024, Issue: 81, 60 - 71, 26.07.2024
https://doi.org/10.51290/dpusbe.1429793

Abstract

TThis study investigated how digitalization empirically affected income inequality in Turkey between 2001 and 2020. Broadband subscription, internet usage, and mobile subscription were used as digitalization indicators, and the GINI coefficient calculated on disposable income was used as an income inequality indicator. The findings obtained by the ARDL method, KPSS stationarity and ADF unit root tests are as follows: i) While some variables are stationary at level, some are stationary at first degree. ii) Explanatory variables can explain the dependent variable stably in the long run. iii) The increase in all three digitalization indicators and trade openness improves income inequality in the long run. iv) The real income per capita enhancement increases income inequality in the long run. Therefore, policymakers should design and implement policies that will increase digitalization and trade openness and eliminate the distorting effect of economic growth on income inequality.

References

  • Acaravcı, A., Akalin, G., & Erdoğan, S. (2019). Araştırmageliştirme harcamalarının Türkiye ihracatına etkileri. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 37(1), 1-16.
  • Acemoglu, D. (1998). Why do new technologies complement skills? Directed technical change and wage inequality. The Quarterly Journal of Economics, 113(4), 1055-1089.
  • Acemoglu, D. (2002). Technical change, inequality, and the labor market. Journal of Economic Literature, 40(1), 7-72.
  • Adams, S., & Akobeng, E. (2021). ICT, governance and inequality in Africa. Telecommunications Policy, 45(10), 102198.
  • Ali, B., Ullah, A., & Khan, D. (2021). Does the prevailing Indian agricultural ecosystem cause carbon dioxide emission? A consent towards risk reduction. Environmental Science and Pollution Research, 28, 4691-4703.
  • Alvaredo, F., Chancel, L., Piketty, T., Saez, E., & Zucman, G. (Eds.). (2018). World inequality report 2018. Belknap Press.
  • Al-Mulali, U., Solarin, S. A., & Ozturk, I. (2016). Investigating the presence of the environmental Kuznets curve (EKC) hypothesis in Kenya: an autoregressive distributed lag (ARDL) approach. Natural Hazards, 80, 1729-1747.
  • Al Qudah, A., Zouaoui, A., & Aboelsoud, M. E. (2020). Does corruption adversely affect economic growth in Tunisia? ARDL approach. Journal of Money Laundering Control, 23(1), 38-54.
  • Ariansyah, K., Barsei, A. N., Syahr, Z. H. A., Sipahutar, N. Y. P., Damanik, M. P., Perdananugraha, G. M., ... & Suryanegara, M. (2023). Unleashing the potential of mobile broadband: Evidence from Indonesia's underdeveloped regions on its role in reducing income inequality. Telematics and Informatics, 82, 102012.
  • Asongu, S. A., & Odhiambo, N. M. (2019). How enhancing information and communication technology has affected inequality in Africa for sustainable development: An empirical investigation. Sustainable Development, 27(4), 647-656.
  • Autor, D. H., Katz, L. F., & Krueger, A. B. (1998). Computing inequality: have computers changed the labor market?. The Quarterly Journal of Economics, 113(4), 1169-1213.
  • Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An empirical exploration. The Quarterly Journal of Economics, 118(4), 1279-1333.
  • Das, S., & Chatterjee, A. (2023). Impacts of ICT and digital finance on poverty and income inequality: a sub-national study from India. Information Technology for Development, 29(2-3), 378-405.
  • Efobi, U. R., Tanankem, B. V., & Asongu, S. A. (2018). Female economic participation with information and communication technology advancement: Evidence from Sub‐Saharan Africa. South African Journal of Economics, 86(2), 231-246.
  • Florida, R., & Mellander, C. (2016). The geography of inequality: Difference and determinants of wage and income inequality across US metros. Regional Studies, 50(1), 79-92.
  • Francalanci, C., & Morabito, V. (2008). IS integration and business performance: The mediation effect of organizational absorptive capacity in SMEs. Journal of Information Technology, 23, 297-312.
  • Gao, Y., Zang, L., & Sun, J. (2018). Does computer penetration increase farmers’ income? An empirical study from China. Telecommunications Policy, 42(5), 345–360.
  • Hasan, I., Horvath, R., & Mares, J. (2020). Finance and wealth inequality. Journal of International Money and Finance, 108, 102161.
  • Houngbonon, G. V., & Liang, J. (2017). Broadband internet and income inequality. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2963860.
  • Kuhn, M., Schularick, M., & Steins, U. I. (2020). Income and wealth inequality in America, 1949–2016. Journal of Political Economy, 128(9), 3469-3519.
  • Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54(1-3), 159-178.
  • Li, L., Zeng, Y., Ye, Z., & Guo, H. (2021). E‐commerce development and urban‐rural income gap: Evidence from Zhejiang Province, China. Papers in Regional Science, 100(2), 475-494.
  • Michaels, G., Natraj, A., & Van Reenen, J. (2014). Has ICT polarized skill demand? Evidence from eleven countries over twenty-five years. Review of Economics and Statistics, 96(1), 60-77.
  • Mah, J. S. (2000). An empirical examination of the disaggregated import demand of Korea — The case of information technology products. Journal of Asian Economics, 11(2), 237-244.
  • Njangang, H., Beleck, A., Tadadjeu, S., & Kamguia, B. (2022). Do ICTs drive wealth inequality? Evidence from a dynamic panel analysis. Telecommunications Policy, 46(2), 102246.
  • Noh, Y. H., & Yoo, K. (2008). Internet, inequality and growth. Journal of Policy Modeling, 30(6), 1005-1016.
  • Qiu, L., Zhong, S., & Sun, B. (2021). Blessing or curse? The effect of broadband Internet on China’s inter-city income inequality. Economic Analysis and Policy, 72, 626-650.
  • Pattichis, C.A. (1999), “Price and income elasticities of disaggregated import demand: results from UECMs and an application”, Applied Economics, 31(9), 1061-1071.
  • Pesaran, M. H., & Shin, Y. (1995). An autoregressive distributed lag modelling approach to cointegration analysis (Vol. 9514). Cambridge, UK: Department of Applied Economics, University of Cambridge.
  • Pesaran, H., & Shin, Y. (1999). An autoregressive distributed lag modelling approach to cointegration “chapter 11. In Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch Centennial Symposium. Cambridge University Press Cambridge.
  • Pesaran M.H., Shin, Y., R.J. Smith ( 2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16, 289–326.
  • Ponce, P., Yunga, F., Larrea-Silva, J., & Aguirre, N. (2023). Spatial determinants of income inequality at the global level: The role of natural resources. Resources Policy, 84, 103783.
  • Rajan, R. G., & Zingales, L. (2004). Saving capitalism from the capitalists: Unleashing the power of financial markets to create wealth and spread opportunity. Princeton University Press.
  • Richmond, K., & Triplett, R. E. (2018). ICT and income inequality: a cross-national perspective. International Review of Applied Economics, 32(2), 195-214.
  • Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review. Telematics and informatics, 32(1), 129-142.
  • Siaw, A., Jiang, Y., Twumasi, M. A., & Agbenyo, W. (2020). The impact of internet use on income: The case of rural Ghana. Sustainability, 12(8), 3255.
  • Smith, M. L., Spence, R., & Rashid, A. T. (2011). Mobile phones and expanding human capabilities. Information Technologies & International Development, 7(3), pp-77.
  • Stolper, W. F., & Samuelson, P. A. (1941). Protection and real wages. The Review of Economic Studies, 9(1), 58-73.
  • Tang, T., Cuesta, L., Tillaguango, B., Alvarado, R., Rehman, A., Bravo-Benavides, D., & Zárate, N. (2022). Causal link between technological innovation and inequality moderated by public spending, manufacturing, agricultural employment, and export diversification. Sustainability, 14(14), 8474.
  • Tchamyou, V. S., Erreygers, G., & Cassimon, D. (2019). Inequality, ICT and financial access in Africa. Technological Forecasting and Social Change, 139, 169-184.
  • TUİK, (2017). Gelir ve Yaşam Koşulları Araştırması, 2016, https://data.tuik.gov.tr/Bulten/Index?p=Gelir-ve-Yasam-Kosullari-Arastirmasi-2016-24579, Erişim Tarihi:27.09.2023
  • Ureta, S. (2008). Mobilising poverty?: Mobile phone use and everyday spatial mobility among low-income families in Santiago, Chile. The Information Society, 24(2), 83-92.
  • Wahiba, N. F., & Mahmoudi, D. (2023). Technological Change, Growth and Income Inequality. International Journal of Economics and Financial Issues, 13(1), 121.
  • Wang, J., & Xu, Y. (2023). Digitalization, income inequality, and public health: Evidence from developing countries. Technology in Society, 73, 102210.
  • World bank. (2016). Digital dividends, USA (World Development Report 2016).
  • Yin, Z. H., & Choi, C. H. (2023). Does digitalization contribute to lesser income inequality? Evidence from G20 countries. Information Technology for Development, 29(1), 61-82.
  • Zhang, X., Wan, G., Wang, C., & Luo, Z. (2017). Technical change and income inequality in China. The World Economy, 40(11), 2378-2402.
  • Zhang, F., & Li, D. (2018). Regional ICT access and entrepreneurship: Evidence from China. Information & Management, 55(2), 188–198.
  • Zhang, Y., Long, H., Ma, L., Tu, S., Li, Y., & Ge, D. (2022). Analysis of rural economic restructuring driven by e-commerce based on the space of flows: The case of xiaying village in central China. Journal of Rural Studies, 93, 196–209.
There are 49 citations in total.

Details

Primary Language Turkish
Subjects Economic Models and Forecasting, Macroeconomic Theory
Journal Section RESEARCH ARTICLES
Authors

Güray Akalin 0000-0002-6647-5418

Publication Date July 26, 2024
Submission Date February 1, 2024
Acceptance Date July 12, 2024
Published in Issue Year 2024 Issue: 81

Cite

APA Akalin, G. (2024). Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi(81), 60-71. https://doi.org/10.51290/dpusbe.1429793
AMA Akalin G. Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. July 2024;(81):60-71. doi:10.51290/dpusbe.1429793
Chicago Akalin, Güray. “Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 81 (July 2024): 60-71. https://doi.org/10.51290/dpusbe.1429793.
EndNote Akalin G (July 1, 2024) Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi 81 60–71.
IEEE G. Akalin, “Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 81, pp. 60–71, July 2024, doi: 10.51290/dpusbe.1429793.
ISNAD Akalin, Güray. “Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi 81 (July 2024), 60-71. https://doi.org/10.51290/dpusbe.1429793.
JAMA Akalin G. Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2024;:60–71.
MLA Akalin, Güray. “Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 81, 2024, pp. 60-71, doi:10.51290/dpusbe.1429793.
Vancouver Akalin G. Dijitalleşme Türkiye’de Gelir Eşitsiziliğini Nasıl Etkilmektedir?. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2024(81):60-71.

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