SavedAdd your journal

Journals / Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty / 2026 / Volume: 13 Issue: 1

The Dynamic Relationship Between Economic Complexity and Financial Development: New Findings on G7 Countries

Ayşegül Yılmaz0009-0001-9137-0327
Gülden Kadooğlu Aydın(HARRAN ÜNİVERSİTESİ)0000-0003-4214-5673
Rüya Kaplan Yıldırım(ADANA ALPARSLAN TÜRKEŞ BİLİM VE TEKNOLOJİ ÜNİVERSİTESİ)0000-0003-0455-568X
Turgay Münyas(OKAN ÜNİVERSİTESİ)0000-0002-8558-2032
Pages
—
Publication Date
2026-03-30
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The study finds that financial institutions in G7 countries are structurally strong, the main indicators of development in these countries are productivity, level of development and market structure; the complex production structure increases productivity; the increase in economic complexity is directly related to the quality of financial infrastructure and the ability of society to access the infrastructure; and the development of and access to financial markets is important for reducing structural inequality and increasing financial efficiency.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this study is to determine the relationship between economic complexity and financial development and financial depth in G7 countries for the period 2000-2021, and thus to reveal whether financial markets fulfil their basic functions such as ‘resource allocation, capital formation, liquidity provision, diffusion of ownership and risk distribution.
📊
Key Findings & Data:In this framework, the panel Granger causality-based network analysis (GCDN) is employed to reveal the directional and structural interactions between variables in a multidimensional context.
💡
Conclusion & Impact:The study finds that financial institutions in G7 countries are structurally strong, the main indicators of development in these countries are productivity, level of development and market structure; the complex production structure increases productivity; the increase in economic complexity is directly related to the quality of financial infrastructure and the ability of society to access the infrastructure; and the development of and access to financial markets is important for reducing structural inequality and increasing financial efficiency.
🔬Design:Research Article
📍Scope:2000-2021 Verileri
⚙️Variables:Economic Complexity · Financial Development · Financial Markets

Abstract

The aim of this study is to determine the relationship between economic complexity and financial development and financial depth in G7 countries for the period 2000-2021, and thus to reveal whether financial markets fulfil their basic functions such as ‘resource allocation, capital formation, liquidity provision, diffusion of ownership and risk distribution. In this framework, the panel Granger causality-based network analysis (GCDN) is employed to reveal the directional and structural interactions between variables in a multidimensional context. The study finds that financial institutions in G7 countries are structurally strong, the main indicators of development in these countries are productivity, level of development and market structure; the complex production structure increases productivity; the increase in economic complexity is directly related to the quality of financial infrastructure and the ability of society to access the infrastructure; and the development of and access to financial markets is important for reducing structural inequality and increasing financial efficiency.

🔖

Cite This Article

Yılmaz, A., Aydın, G. K., Yıldırım, R. K., Münyas, T. (2026). The Dynamic Relationship Between Economic Complexity and Financial Development: New Findings on G7 Countries. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, Volume: 13 Issue: 1. https://doi.org/10.30798/makuiibf.1710719

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (63)

  1. Akar, T. (2023). Ekonomik karmaşıklık, AR-GE harcamaları ve ekonomik büyüme ilişkisi. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (55), 315-329.
  2. Arooj, M., & Sajid, S. (2022). The dynamic relationship between financial development and economic complexity in Pakistan. Journal of Contemporary Macroeconomic Issues, 3(2), 30-43. https://doi.org/10.5281/zenodo.7421100
  3. Atılgan, D. (2025). Doğal kaynak rantı, ekonomik karmaşıklık ve ekonomik büyümenin çevresel sürdürülebilirlik üzerindeki etkisi. Yönetim ve Ekonomi Dergisi, 32(2), 207-224. https://doi.org/10.18657/yonveek.1538023
  4. Baltagi, B. H. (2008). Econometric analysis of panel data (Fourth ed.). Springer.
  5. Banerjee, A., Marcellino, M., & Osbat, C. (2004). Some cautions on the use of panel methods for integrated series of macroeconomic data. The Econometrics Journal, 7(2), 322–340. https://doi.org/10.1111/j.1368- 423X.2004.00133.x
  6. Başoğlu, A., & Kömürcüoğlu, Ö. F. (2024). Finansal teknolojilerdeki gelişmelerin ekonomik kompleksiteye yansımaları. Uluslararası Yönetim İktisat ve İşletme Dergisi, 20(4), 1230-1249. https://doi.org/10.17130/ijmeb.1521890
  7. Bayar, İ. (2022). Ekonomik karmaşıklık indeksi ve ekonomik büyüme: CIVETS ülkelerinden ampirik kanitlar. Uluslararası İktisadi ve İdari İncelemeler Dergisi, (36), 237-251. https://doi.org/10.18092/ulikidince.1052678
  8. Botta, A., Caverzasi, E., & Russo, A. (2022). When complexity meets finance: A contribution to the study of the macroeconomic effects of complex financial systems. Research Policy, 51(8), 103990. https://doi.org/10.1016/j.respol.2020.103990
  9. Breusch, T. S., & Pagan, A. R. (1980). The lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253. https://doi.org/10.2307/2297111
  10. Can, M., & Doğan, B. (2018). Ekonomik kompleksite ve finansal gelişme ilişkisi: Türkiye örnekleminde ampirik bir analiz. Finans Politik and Ekonomik Yorumlar, 55(638), 5-16.
  11. Caraiani, P. (2013). Using complex networks to characterize international business cycles. PloS one, 8(3), e58109.https://doi.org/10.1371/journal.pone.0058109
  12. Choi, I. (1993). Asymptotic normality of the least-squares estimates for higher order autoregressive integrated processes with some applications. Econometric Theory, 9(2), 263-282. https://doi.org/10.1017/S0266466600007532
  13. Chu, L. K. (2020). The effects of financial development on economic sophistication: Evidence from panel data. Applied Economics Letters, 27(15), 1260–1263. https://doi.org/10.1080/13504851.2019.1676866
  14. Çoban, M. N. (2020). Ekonomik kompleksite ve insani gelişmişlik ilişkisi: E7 ülkeleri için bir analiz. Ahi Evran Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 6(2), 467-479. https://doi.org/10.31592/aeusbed.659563
  15. Çolakoğlu, M. (2021). OECD ülkelerinde beşerî sermayenin yüksek teknolojili ürün ihracatı ve ekonomik kompleksite endeksi üzerindeki etkisi. (Unpublished master’s thesis). Pamukkale University.
  16. Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: Journal of the Econometric Society, 1057-1072. https://doi.org/10.2307/1912517
  17. Doru, Ö. (2022). Türkiye’de ekonomik karmaşıklık endeksi (eci) ve doğrudan yabancı yatırım ilişkisi. Artuklu Kaime Uluslararası İktisadi ve İdari Araştırmalar Dergisi, 5(2), 235-251. https://doi.org/10.55119/artuklu.1200656
  18. Efeoğlu, R. (2022). N11 ülkelerinde ekonomik kompleksite ve finansal gelişme. Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 20(01), 185-196.
  19. Eryüzlü, H., & Gültekin, Ö. (2021). Ekonomik karmaşiklik endeksi-ticari krediler ilişkisi: türkiye örneği. Lapseki Meslek Yüksekokulu Uygulamalı Araştırmalar Dergisi, 2(3), 14-19.
  20. Felipe, J., Kumar, U., Abdon, A., & Bacate, M. (2012). Product complexity and economic development. Structural Change and Economic Dynamics, 23(1), 36-68. https://doi.org/10.1016/j.strueco.2011.08.003
  21. Feyisa, H. L., Mamo, W. B., & Yitayaw, M. K. (2022). The impact of governance on financial institution and financial market development: Empirical evidence from emerging markets. Studia Universitatis Vasile Goldiș Arad, Seria Științe Economice, 32(3), 48-64. https://doi.org/10.2478/sues-2022-0012
  22. Gomez-Gonzalez, J. E., Uribe, J. M., & Valencia, O. M. (2025). Sovereign debt cost and economic complexity. Journal of International Financial Markets, Institutions and Money, 99, 102121. https://doi.org/10.1016/j.intfin.2025.102121
  23. Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 37(3), 424-438. https://doi.org/10.2307/1912791
  24. Granger, C. W. (1988). Some recent development in a concept of causality. Journal of Econometrics, 39(1-2), 199-211. https://doi.org/10.1016/0304-4076(88)90045-0
  25. Granger, C. W., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111- 120.
  26. Hadri, K., & Kurozumi, E. (2012). A simple panel stationarity test in the presence of serial correlation and a common factor. Economics Letters, 115(1), 31-34. https://doi.org/10.1016/j.econlet.2011.11.036
  27. Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences 106(26), 10570–10575. https://doi.org/10.1073/pnas.0900943106
  28. Hsiao, C. (2022). Analysis of panel data. Cambridge University Press.
  29. Ibrahim, R. L., Al-Mulali, U., Ozturk, I., Bello, A. K., & Raimi, L. (2022). On the criticality of renewable energy to sustainable development: Do green financial development, technological innovation, and economic complexity matter for China?. Renewable Energy, 199, 262-277. https://doi.org/10.1016/j.renene.2022.08.101
  30. Ike, G. N., Usman, O., & Sarkodie, S. A. (2020). Testing the role of oil production in the environmental kuznets curve of oil producing countries: New insights from method of moments quantile regression. Science of the Total Environment, 711, 135208. https://doi.org/10.1016/j.scitotenv.2019.135208
  31. Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53-74. https://doi.org/10.1016/S0304-4076(03)00092-7
  32. İspiroğlu, F. (2021). Yükselen piyasa ekonomilerinde ekonomik karmaşıklık ve ticarî dışa açıklık ilişkisi. Business & Management Studies: An International Journal, 9(3), 1021-1031. https://doi.org/10.15295/bmij.v9i3.1869
  33. Kar, M., Nazlıoğlu, Ş., & Ağır, H. (2011). Financial development and economic growth nexus in the MENA countries: Bootstrap panel granger causality analysis. Economic Modelling, 28(1-2), 685-693. https://doi.org/10.1016/j.econmod.2010.05.015
  34. Karabıyık, C. (2021). Ekonomik kompleksite ve doğrudan yabancı sermaye yatırımları ilişkisi: BRICS-T ülkeleri üzerine bir panel veri analizi. Yaşar Üniversitesi E-Dergisi, 16(63), 1133-1149. https://doi.org/10.19168/jyasar.916017
  35. Keles, S. S. (2022). Globalization, econom ic complexity and income inequaltiy in BRICS-T Countries: Heterogeneous panel data analysis. Journal of Emerging Economies and Policy, 7(2), 379-388.
  36. Kónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978-992. https://doi.org/10.1016/j.econmod.2006.04.008
  37. Kurt, U., & Azazi, H. (2018). The relationship financial development and sophisticated produced: An empirical analysis for Turkey. Economics, Finance and Politics, 13(22), 241-352. http://dx.doi.org/10.7827/TurkishStudies.13993
  38. Lumsdaine, R. L., & Papell, D. H. (1997). Multiple trend breaks and the unit-root hypothesis. Review of Economics and Statistics, 79(2), 212-218. https://doi.org/10.1162/003465397556791
  39. Maličká, L. (2024). Convergence of EU countries according to economic complexity. EnPress, 8(3), 1-14. https://doi.org/10.24294/jipd.v8i3.3123
  40. Mayer, S. S., Ibrid, A. A., Kalf, H. A. I., Altememy, H. A., Al-Muttar, M. Y. O., Hammoode, J. A., & Jalil, S. H. (2023). Is financial development having an impact on economic complexity? Empirical study of Iraq. Cuadernos de Economía, 46(131), 135-144. https://doi.org/10.32826/cude.v46i131.1114
  41. Ndoya, H., Ongo Nkoa, B. E., Kemeze, F. H., & Nchofoung, T. N. (2024). Financial development and economic complexity: The role of country stability. Economics of Transition and Institutional Change, 32(2), 415-447. https://doi.org/10.1111/ecot.12392
  42. Nguyen, C. P., & Su, T. D. (2021). Financing the economy: The multidimensional influences of financial development on economic complexity. Journal of International Development, 33(4), 644–684. https://doi.org/10.1002/jid.3541
  43. O’Connell, P. G. (1998). The overvaluation of purchasing power parity. Journal of International Economics, 44(1), 1-19. https://doi.org/10.1016/S0022-1996(97)00017-2
  44. Ogbuabor, J. E., Emeka, E. T., Orji, A., & Onuigbo, F. N. (2023). The effects of international financial inflows on economic complexity in Africa: does institutional quality play a moderation role?. Journal of Economic Policy Reform, 26(4), 348-369. https://doi.org/10.1080/17487870.2023.2220862
  45. Olaniyi, C. O., & Odhiambo, N. M. (2023). Does institutional quality matter in the financial development- economic complexity nexus? Empirical insights from Africa. Research in Globalization, 7, 100173. https://doi.org/10.1016/j.resglo.2023.100173
  46. 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. https://doi.org/10.1002/jae.951
  47. Pesaran, M. H. (2015). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6- 10), 1089-1117. https://doi.org/10.1080/07474938.2014.956623
  48. Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence. The Econometrics Journal, 11(1), 105-127. https://doi.org/10.1111/j.1368-423X.2007.00227.x
  49. Phillips, P. C., & Sul, D. (2003). Dynamic panel estimation and homogeneity testing under cross-section dependence. The Econometrics Journal, 6(1), 217-259. https://doi.org/10.1111/1368-423X.00108
  50. Prasad, E., Rogoff, K., Wei, S. J., & Kose, M. A. (2003). Effects of financial globalization on developing countries: Some empirical evidence. In India’s and China’s recent experience with reform and growth, 201-228. London: Palgrave Macmillan UK.
  51. Strauss, J., & Yigit, T. (2003). Shortfalls of panel unit root testing. Economics Letters, 81(3), 309- 313.https://doi.org/10.1016/S0165-1765(03)00210-6
  52. Sul, D., Phillips, P. C. B., & Choi, C. Y. (2005). Prewhitening bias in HAC estimation. Oxford Bulletin of Economics and Statistics, 67, 517-546. https://doi.org/10.1111/j.1468-0084.2005.00130.x
  53. Tang, Y., Xiong, J. J., Luo, Y., & Zhang, Y. C. (2019). How do the global stock markets influence one another? Evidence from finance big data and granger causality directed network. International Journal of Electronic Commerce, 23(1), 85-109. https://doi.org/10.1080/10864415.2018.1512283
  54. Tekbaş, M., & Tutumlu, H. (2023). Ekonomik büyüme, ekonomik karmaşıklık, yenilenebilir enerji tüketimi ve CO2 emisyonu ilişkisi: Türkiye örneği. Siyaset, Ekonomi ve Yönetim Araştırmaları Dergisi, 11(2), 124-141. https://doi.org/10.54429/seyad.1311540
  55. Tekin, D., Şimşek, İ., & Dışkaya, S. (2024). Finansal gelişme ve ekonomik büyüme arasındaki ilişkinin araştırılması: Türkiye ve G7 ülkeleri üzerine bir değerlendirme. Muhasebe ve Finans İncelemeleri Dergisi, 7(1), 46-57. https://doi.org/10.32951/mufider.1432778
  56. The Atlas of Economic Complexity (2025).Rankings. Retrieved [2025], https://atlas.hks.harvard.edu/rankings
  57. The Observatory of Economic Complexity. (2024). Economic Complexity Index (ECI) rankings. Retrieved [2025], from https://oec.world/en/rankings/eci/hs6/hs96?tab=ranking
  58. TheGlobalEconomy.com. (2025). Global economy, world economy. Retrieved [2025], https://www.theglobaleconomy.com/databases
  59. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66, 225–250. https://doi.org/10.1016/0304-4076(94)01616-8
  60. Ünsal, Y. (2023). A panel ARDL approach to the immiserating growth hypothesis through the lens of economic complexity. Dumlupınar Üniversitesi İİBF Dergisi, 12, 142-152. https://doi.org/10.58627/dpuiibf.1389959
  61. Yang, W., Yu, X., Zhang, B., & Huang, Z. (2021). Mapping the landscape of international technology diffusion (1994–2017): Network analysis of transnational patents. The Journal of Technology Transfer, 46(1), 138-171.
  62. Zhu, S., & Li, R. (2016). Economic complexity, human capital and economic growth: Empirical research based on cross-country panel data. Applied Economics, 49(38), 3815–3828. https://doi.org/10.1080/00036846.2016.1270413
  63. Zivot, E., & Andrews, D. W. K. (2002). Further evidence on the great crash, the oil-price shock and the unit-root hypothesis. Journal of Business and Economic Statistics, 20(1), 25-44. https://doi.org/10.1198/073500102753410372