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The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye

Yıl 2023, , 424 - 439, 10.08.2023
https://doi.org/10.17494/ogusbd.1294814

Öz

The demographic transition would affect almost every aspect of life and our surroundings and could lead to significant changes and consequences in the social and economic sub-systems. In addition, it is a vital factor in economics. Therefore, a deep understanding of demographic transitions, characteristics, and dimensions would be helpful due to better managing the consequences and preparing for the future. The aim of this paper is to explore the impact of Türkiye's demographic transition on total factor productivity (TFP) from 1970 to 2021 using a Probit model. The results indicate that factors such as dependency ratio, elderly population ratio, youth population ratio, deaths per 1000 people, life expectancy, population density, gross capital formation per capita, and manufacturing production can increase the likelihood of TFP growth. However, factors such as capital stock, urban population, and births per 1000 people are shown to potentially reduce this likelihood.

Kaynakça

  • Aksoy, Y., Basso, H. S., Smith, R. & Grasl, T. (2015). Demographic Structure and Macroeconomic Trends. Madrid, Spain: Banko de Espana.
  • Becker, G., Glaeser, E. & Murphy, K. (1999). Population and economic growth. American Economic Review, 89(2), 145-49.
  • Birdsall, N. and Sinding, S. W. (2001). How and Why Population Matters: New Findings, New Issues. Book: Population Matters: Demographic Change, Economic Growth, and Poverty in the Developing World Population, Oxford University Press: 3-23.
  • Bloom, D. E. and Canning, D. (2004). Contraception and the Celtic Tiger. Economic and Social Review 34.
  • Bloom, D. E., Canning, D. & Sevilla, J. (2003). The Demographic Dividend: A New Perspective on the Economic Consequences of Population Change. Population Matters Monograph MR-1274, RAND, Santa Monica.
  • Bloom, D. E., Canning, D. & Fink, G. (2010). Implications of ppulation ageing for economic growth. Oxford Review of Economic Policy, 26 (4), 583_612.
  • Choe, C., Jung, S. and Oaxaca, R. L. (2017). Identification and Decompositions in Probit and Logit Models. IZA DP No. 10530.
  • Dzeha, G. C., Turkson, F., Agbloyor, E. K. & Abor, J. Y. (2018). Total Factor Productivity Growth and Human Development: The Role of Remittances in Africa. African Journal of Economic and Sustainable Development 7 (1): 47 – 72.
  • Gomez, R. and Hernandez, P. (2003). Demographic Maturity and Economic Performance: the Effect of Demographic Transitions on Per Capita GDP Growth. Working Papers 0318, Banco de España.
  • Feyrer, J. (2007). Demographics and Productivity. The Review of Economics and Statistics, vol. 89, issue 1, 100-109.
  • Fischer, S. (2016). Why Are Interest Rates So Low? Causes and Implications. Remarks at the Economic Club of New York.
  • Goodhart, C. and Pradhan, M. (2017). Demographics will reverse three multi-decade global trends. BIS Working Paper No 656.
  • Griliches, Z. (1998). R&D and productivity: The econometric evidence. University of Chicago Press.
  • Hoetker, G. (2007). The use of logit and probit models in strategic management research: Critical issues, Strategic Management Journal, Wiley Blackwell, vol. 28(4), pages 331-343.
  • Inokuma, H. and Sanchez, J. M. (2023). From Population Growth to TFP Growth. Working Papers 006, Federal Reserve Bank of St. Louis.
  • Jones, C. I. (2022). The End of Economic Growth? Unintended Consequences of a Declining Population, American Economic Review, American Economic Association, vol. 112(11), pages 3489-3527.
  • Kelley, A. C., and Schmidt, R. M. (2007). Evolution of recent economic-demographic modeling: A synthesis. In A. Mason & M. Yamaguchi (Eds.), Population change, labor markets and sustainable growth: Towards a new economic paradigm (pp. 5–38). Amsterdam: Elsevier.
  • Li, X., and Zhao, X. (2019). Interaction between population aging and technological innovation: A Chinese case study. Journal of Advanced Computational Intelligence and Intelligent Informatics, 23(6), 971–979.
  • Li, X. and Zhao, X. (2022). Does low birth rate affect China’s total factor productivity? Economic Research-Ekonomska Istrazıvanja, VOL. 35, NO. 1, 2712–2731.
  • Liu, Y. and Westelius, N. (2016). The Impact of Demographics on Productivity and Inflation in Japan. IMF Working Paper.
  • Mason, A. (1988). Saving, Economic Growth, and Demographic Change. Population and Development Review 14(1): 113-144.
  • Macrotrends Data Set (2023), http://www.macrotrends.net/ (Accessed on 15 April 2023).
  • Nguyen, A. (2020). Patterns of Growth, Demographic Pattern and The Role of Total Factor Productivity in Growth in Taiwan, SSRN.
  • OECD (2023), Population (indicator). DOI: 10.1787/d434f82b-en (Accessed on 15 April 2023).
  • Peng, X. (2005). The Demographic Window, Human Capital Accumulation and Economic Growth in China: An Applied General Equilibrium Analysis, Asian Population Studies, 1 (2): 169-188.
  • Skans, O. N. (2008). How does the age structure affect regional productivity? Applied Economics Letters, 15(10), 787–790.
  • Solow, R. M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39(3), 312–320.
  • Todaro, M. (2012). Economic Development. 11th Ed., New York, London.
  • Ursavaş, U. (2020). Total factor productivity growth and demographics: The case of Turkey. Ekonomi Politika ve Finans Araştırmaları Dergisi, 5(1), 81-90.
  • Wei, Z.A. and Hao, R. (2011). The role of human capital in China's total factor productivity growth: A cross-Province analysis. The Developing Economies 49(1):1 – 35.
  • Wu, J. X. (2010). Knowledge diffusion, human capital composition and total factor productivity: A research based on Chinese provincial data. Journal of Huizhou University (Social Science Edition), 30(2), 60–65.

Türkiye’de Demografik Geçişin Toplam Faktör Verimliliğine Etkisi

Yıl 2023, , 424 - 439, 10.08.2023
https://doi.org/10.17494/ogusbd.1294814

Öz

Ölüm ve doğurganlık oranlarının yüksekten düşüğe doğru bir değişimi olan demografik geçiş, hayatın hemen hemen her alanını etkilemekte ve sosyal ve ekonomik alt sistemlerde önemli değişikliklere ve sonuçlara yol açmaktadır. Ayrıca, demografik geçiş ekonomide hayati bir faktöre sahiptir. Bu nedenle, sonuçları daha iyi yönetmek ve geleceğe dair daha iyi hazırlanmak için demografik geçişlerin, özelliklerinin ve boyutlarının derinlemesine anlaşılması önemlidir. Bu çalışmanın amacı, Türkiye'deki 1970-2021 yılları arasındaki demografik geçişin toplam faktör verimliliği (TFP) üzerindeki etkisini bir Probit modeli kullanarak analiz etmektir. Sonuçlar, bağımlılık oranı, yaşlı nüfus oranı, genç nüfus oranı, 1000 kişi başına düşen ölüm sayısı, yaşam beklentisi, nüfus yoğunluğu, kişi başına brüt sermaye oluşumu ve imalat üretimi gibi faktörlerin TFP büyüme olasılığını artırabileceğini ortaya koymaktadır. Bununla birlikte, sermaye stoku, kentsel nüfus ve 1000 kişi başına düşen doğum sayısı gibi faktörlerin ise bu olasılığı azaltabileceğini göstermektedir.

Kaynakça

  • Aksoy, Y., Basso, H. S., Smith, R. & Grasl, T. (2015). Demographic Structure and Macroeconomic Trends. Madrid, Spain: Banko de Espana.
  • Becker, G., Glaeser, E. & Murphy, K. (1999). Population and economic growth. American Economic Review, 89(2), 145-49.
  • Birdsall, N. and Sinding, S. W. (2001). How and Why Population Matters: New Findings, New Issues. Book: Population Matters: Demographic Change, Economic Growth, and Poverty in the Developing World Population, Oxford University Press: 3-23.
  • Bloom, D. E. and Canning, D. (2004). Contraception and the Celtic Tiger. Economic and Social Review 34.
  • Bloom, D. E., Canning, D. & Sevilla, J. (2003). The Demographic Dividend: A New Perspective on the Economic Consequences of Population Change. Population Matters Monograph MR-1274, RAND, Santa Monica.
  • Bloom, D. E., Canning, D. & Fink, G. (2010). Implications of ppulation ageing for economic growth. Oxford Review of Economic Policy, 26 (4), 583_612.
  • Choe, C., Jung, S. and Oaxaca, R. L. (2017). Identification and Decompositions in Probit and Logit Models. IZA DP No. 10530.
  • Dzeha, G. C., Turkson, F., Agbloyor, E. K. & Abor, J. Y. (2018). Total Factor Productivity Growth and Human Development: The Role of Remittances in Africa. African Journal of Economic and Sustainable Development 7 (1): 47 – 72.
  • Gomez, R. and Hernandez, P. (2003). Demographic Maturity and Economic Performance: the Effect of Demographic Transitions on Per Capita GDP Growth. Working Papers 0318, Banco de España.
  • Feyrer, J. (2007). Demographics and Productivity. The Review of Economics and Statistics, vol. 89, issue 1, 100-109.
  • Fischer, S. (2016). Why Are Interest Rates So Low? Causes and Implications. Remarks at the Economic Club of New York.
  • Goodhart, C. and Pradhan, M. (2017). Demographics will reverse three multi-decade global trends. BIS Working Paper No 656.
  • Griliches, Z. (1998). R&D and productivity: The econometric evidence. University of Chicago Press.
  • Hoetker, G. (2007). The use of logit and probit models in strategic management research: Critical issues, Strategic Management Journal, Wiley Blackwell, vol. 28(4), pages 331-343.
  • Inokuma, H. and Sanchez, J. M. (2023). From Population Growth to TFP Growth. Working Papers 006, Federal Reserve Bank of St. Louis.
  • Jones, C. I. (2022). The End of Economic Growth? Unintended Consequences of a Declining Population, American Economic Review, American Economic Association, vol. 112(11), pages 3489-3527.
  • Kelley, A. C., and Schmidt, R. M. (2007). Evolution of recent economic-demographic modeling: A synthesis. In A. Mason & M. Yamaguchi (Eds.), Population change, labor markets and sustainable growth: Towards a new economic paradigm (pp. 5–38). Amsterdam: Elsevier.
  • Li, X., and Zhao, X. (2019). Interaction between population aging and technological innovation: A Chinese case study. Journal of Advanced Computational Intelligence and Intelligent Informatics, 23(6), 971–979.
  • Li, X. and Zhao, X. (2022). Does low birth rate affect China’s total factor productivity? Economic Research-Ekonomska Istrazıvanja, VOL. 35, NO. 1, 2712–2731.
  • Liu, Y. and Westelius, N. (2016). The Impact of Demographics on Productivity and Inflation in Japan. IMF Working Paper.
  • Mason, A. (1988). Saving, Economic Growth, and Demographic Change. Population and Development Review 14(1): 113-144.
  • Macrotrends Data Set (2023), http://www.macrotrends.net/ (Accessed on 15 April 2023).
  • Nguyen, A. (2020). Patterns of Growth, Demographic Pattern and The Role of Total Factor Productivity in Growth in Taiwan, SSRN.
  • OECD (2023), Population (indicator). DOI: 10.1787/d434f82b-en (Accessed on 15 April 2023).
  • Peng, X. (2005). The Demographic Window, Human Capital Accumulation and Economic Growth in China: An Applied General Equilibrium Analysis, Asian Population Studies, 1 (2): 169-188.
  • Skans, O. N. (2008). How does the age structure affect regional productivity? Applied Economics Letters, 15(10), 787–790.
  • Solow, R. M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39(3), 312–320.
  • Todaro, M. (2012). Economic Development. 11th Ed., New York, London.
  • Ursavaş, U. (2020). Total factor productivity growth and demographics: The case of Turkey. Ekonomi Politika ve Finans Araştırmaları Dergisi, 5(1), 81-90.
  • Wei, Z.A. and Hao, R. (2011). The role of human capital in China's total factor productivity growth: A cross-Province analysis. The Developing Economies 49(1):1 – 35.
  • Wu, J. X. (2010). Knowledge diffusion, human capital composition and total factor productivity: A research based on Chinese provincial data. Journal of Huizhou University (Social Science Edition), 30(2), 60–65.
Toplam 31 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Kalkınma Ekonomisi - Makro
Bölüm Makaleler
Yazarlar

Sevgi Coskun 0000-0002-9561-7200

Yayımlanma Tarihi 10 Ağustos 2023
Gönderilme Tarihi 9 Mayıs 2023
Yayımlandığı Sayı Yıl 2023

Kaynak Göster

APA Coskun, S. (2023). The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, 24(2), 424-439. https://doi.org/10.17494/ogusbd.1294814
AMA Coskun S. The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi. Ağustos 2023;24(2):424-439. doi:10.17494/ogusbd.1294814
Chicago Coskun, Sevgi. “The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye”. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi 24, sy. 2 (Ağustos 2023): 424-39. https://doi.org/10.17494/ogusbd.1294814.
EndNote Coskun S (01 Ağustos 2023) The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi 24 2 424–439.
IEEE S. Coskun, “The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye”, Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, c. 24, sy. 2, ss. 424–439, 2023, doi: 10.17494/ogusbd.1294814.
ISNAD Coskun, Sevgi. “The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye”. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi 24/2 (Ağustos 2023), 424-439. https://doi.org/10.17494/ogusbd.1294814.
JAMA Coskun S. The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi. 2023;24:424–439.
MLA Coskun, Sevgi. “The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye”. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, c. 24, sy. 2, 2023, ss. 424-39, doi:10.17494/ogusbd.1294814.
Vancouver Coskun S. The Impact of the Demographic Transition on the Total Factor Productivity in Türkiye. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi. 2023;24(2):424-39.