Main Article Content

Abstract

Purpose – This study aims to analyze the dynamics of economic growth convergence and the factors influencing income per capita in BRICS 11 countries over the period 2002–2023. The main focus is to identify the existence of both absolute and conditional convergence in economic growth across countries.
Methods – This study employs a quantitative approach using dynamic panel data. The model is estimated using System GMM and Difference GMM methods to address endogeneity problems and ensure instrument validity. The variables used include GDP per capita as the dependent variable, while Human Development Index (HDI), Foreign Direct Investment (FDI), unemployment rate, and labor force participation rate are used as independent variables.
Findings – The results indicate evidence of economic convergence among BRICS 11 countries, both in absolute and conditional forms. FDI is found to have a positive and significant effect on GDP per capita, while the unemployment rate and labor force participation tend to have negative effects. Meanwhile, HDI does not show a significant impact on income per capita.
Implication – These findings suggest that policies promoting foreign investment and strengthening labor market quality are important factors in driving economic growth and accelerating income convergence in BRICS countries.
Originality – This study contributes empirically by integrating absolute and conditional convergence approaches using dynamic panel data with System and Difference GMM estimators on the updated BRICS 11 country group over the most recent observation period.



Abstrak
Tujuan – Penelitian ini bertujuan untuk menganalisis dinamika konvergensi pertumbuhan ekonomi serta faktor-faktor yang memengaruhi pendapatan per kapita pada negara-negara anggota BRICS 11 selama periode 2002–2023. Fokus utama penelitian adalah mengidentifikasi adanya konvergensi absolut maupun kondisional dalam pertumbuhan ekonomi antarnegara.
Metode – Penelitian ini menggunakan pendekatan kuantitatif dengan data panel dinamis. Estimasi model dilakukan menggunakan metode System GMM dan Difference GMM. Variabel yang digunakan meliputi GDP per kapita sebagai variabel dependen, serta Human Development Index (HDI), Foreign Direct Investment (FDI), tingkat pengangguran, dan tingkat partisipasi angkatan kerja sebagai variabel independen.
Temuan – Hasil penelitian menunjukkan adanya indikasi konvergensi ekonomi di negara-negara BRICS 11, baik secara absolut maupun kondisional. Variabel FDI terbukti berpengaruh positif dan signifikan terhadap GDP per kapita, sedangkan tingkat pengangguran dan partisipasi angkatan kerja cenderung memberikan pengaruh negatif. Sementara itu, HDI belum menunjukkan pengaruh signifikan terhadap peningkatan pendapatan per kapita.
Implikasi – Temuan ini mengindikasikan bahwa kebijakan peningkatan investasi asing serta penguatan kualitas pasar tenaga kerja menjadi faktor penting dalam mendorong pertumbuhan ekonomi dan mempercepat proses konvergensi pendapatan di negara-negara BRICS.
Orisinalitas – Penelitian ini memberikan kontribusi empiris dengan menggabungkan pendekatan konvergensi absolut dan kondisional menggunakan panel dinamis System GMM dan Difference GMM pada kelompok negara BRICS 11 terbaru dengan periode pengamatan terkini.

Keywords

Konvergensi ekonomi GDP per kapita data panel dinamis System GMM Difference GMM

Article Details

How to Cite
Bagaskoro, D., & Anwar, A. (2026). Analisis konvergensi pertumbuhan ekonomi Negara-Negara BRICS Periode 2002 – 2023. Jurnal Kebijakan Ekonomi Dan Keuangan, 5(1), 30–45. https://doi.org/10.20885/JKEK.vol5.iss1.art3

References

  1. Barro, R. J. (2016). Economic Growth and Convergence, Applied Especially to China. NBER Working Paper.
  2. Barro, R. J., & Sala-i-Martin, Xavier. (1991). Convergence across States and Regions. The Journal of Political Economy, 100(2).
  3. Caselli, F., Esquivel, G., & Lefort, F. (1996). Reopening the Convergence Debate : A New Look at Cross-Country Growth Empirics. Journal of Economic Growth, 1(3), 363–389.
  4. Chand, K., Tiwari, R., & Phuyal, M. (2017). Economic Growth and Unemployment Rate: An Empirical Study of Indian Economy. PRAGATI : Journal of Indian Economy, 4(02). https://doi.org/10.17492/pragati.v4i02.11468
  5. Das, R. C. (2019). Is There Cross-Country Income Convergence Among the BRICS Nations? An Examination. Journal of Infrastructure Development, 11(1–2), 121–135. https://doi.org/10.1177/0974930619880440
  6. Das, R. C., Das, U., & Das, A. (2021a). BRICS Nations and Income Convergence: An Insight from the Quarterly Data for 2006Q1–2017Q2. Global Business Review, 22(4), 1054–1069. https://doi.org/10.1177/0972150918822057
  7. Das, R. C., Das, U., & Das, A. (2021b). BRICS Nations and Income Convergence: An Insight from the Quarterly Data for 2006Q1–2017Q2. Global Business Review, 22(4), 1054–1069. https://doi.org/10.1177/0972150918822057
  8. Dědeček, R., & Dudzich, V. (2022). Exploring the limitations of GDP per capita as an indicator of economic development: a cross-country perspective. Review of Economic Perspectives, 22(3), 193–217. https://doi.org/10.2478/revecp-2022-0009
  9. Dykas, P., Tokarski, T., & Wisła, R. (2022). The Solow Model of Economic Growth. Routledge. https://doi.org/10.4324/9781003323792
  10. Feng, G., Gao, J., & Peng, B. (2022). An integrated panel data approach to modelling economic growth. Journal of Econometrics, 228(2), 379–397. https://doi.org/10.1016/j.jeconom.2020.09.009
  11. Holifah, H., Laut, L. T., & Sugiharti, R. R. (2024). Analisis Potensi Konvergensi Ekonomi Negara Anggota ASEAN-10 Tahun 2015-2021 dan Faktor-Faktor yang Mempengaruhinya. Jurnal Inovasi Daerah, II(1), 41–56. http://jurnal.magelangkota.go.id
  12. Ibrahim, Dr. A. A. (2024). Analyzing The Impact of the Labor Force on Economic Growth in Somalia (1991-2022). Mogadishu University Journal, Volume 10. https://doi.org/10.70457/MUJ00103
  13. International Labour Organizations. (2022). Unemployment rate. https://ilostat.ilo.org/methods/concepts-and-definitions/description-labour-force-statistics/#elementor-toc__heading-anchor-34
  14. Islam, N. (1995). Growth Empirics : A Panel Data Approach. The Quarterly Journal of Economics, 110(4), 1127–1170. https://doi.org/10.2307/2946651
  15. Kremer, M., Willis, J., & You, Y. (2022). Converging to Convergence. In NBER Macroeconomics Annual (Vol. 36, Number 1, pp. 337–412). University of Chicago Press. https://doi.org/10.1086/718672
  16. Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A Contribution to the Empirics of Economic Growth. In Source: The Quarterly Journal of Economics (Vol. 107, Number 2). https://www.jstor.org/stable/2118477
  17. Miron, D., Holobiuc, A. M., Cojocariu, R. C., & Budacia, A. E. (2022). Real Convergence in the Euro Area: Mirage or Reality? Journal of Competitiveness, 14(1), 100–117. https://doi.org/10.7441/joc.2022.01.06
  18. Popov, Vladimir., & Dutkiewicz, Piotr. (2017). Mapping a new world order : the rest beyond the West. Edward Elgar Publishing.
  19. Siahaan, S. Y. M., Udjianto, D. W., & Sodik, J. (2023). Analisis Konverengensi Pertumbuhan Ekonomi Negara-Negara ASEAN Tahun 2011-2020. https://ejournal.upi.edu/index.php/JPEI
  20. Suryanto, S.-, Trinugroho, I., & Susilowati, F. (2022). Simultaneous Analysis: The Effect of Electricity Consumption on Human Development Index in ASEAN 5. JEJAK, 15(2), 234–243. https://doi.org/10.15294/jejak.v15i2.37743
  21. Thoifur, A. (2025). Does Cross-Country Income Convergence Occur? Ekuilibrium : Jurnal Ilmiah Bidang Ilmu Ekonomi, 20(1), 62–75. https://doi.org/10.24269/ekuilibrium.v20i1.2025.pp62-75
  22. Thuy Dao, T. B., Khuc, V. Q., Dong, M. C., & Cao, T. L. (2024). How does FDI Matter for Economic Growth? Evidence from a Comparative Study in Country Groups by Level of Development. Contemporary Economics, 18(4), 376–390. https://doi.org/10.5709/ce.1897-9254.544
  23. Todaro, M. P. ., & Smith, S. C. . (2006). Economic development. Pearson Addison Wesley.
  24. United Nations Conference on Trade and Development. (n.d.). Foreign direct investment: Inward and outward flows and stock, annual. Retrieved February 23, 2026, from https://unctadstat.unctad.org/datacentre/reportInfo/US.FdiFlowsStock
  25. United Nations Development Programme. (2023). Human Development Index (HDI). https://hdr.undp.org/data-center/human-development-index#/indicies/HDI
  26. Wooldridge, J. M. (2013). Introductory Econometrics (5th ed.). Cengage Learning.
  27. World Bank. (2024). GDP per capita (current US$). World Bank. https://data.worldbank.org/indicator/NY.GDP.PCAP.CD
  28. World Bank. (2026). A World Bank Group Flagship Report Global Economic Prospects.
  29. Wuri, J., Widodo, T., & Hardi, A. S. (2023). Speed of convergence in global value chains: Forward or backward linkage. Heliyon, 9(7), e18070. https://doi.org/10.1016/j.heliyon.2023.e18070
  30. Yakubu, M. M., & Akanegbu, B. N. (2020). Labour Force Participation and Economic Growth in Nigeria. In Advances in Management & Applied Economics (Vol. 10, Number 1). online) Scientific Press International Limited.
  31. Yeboah, E. (2025). Economic growth in 26 European Union Economies: evidence from conditional convergence. Future Business Journal, 11(1). https://doi.org/10.1186/s43093-025-00671-y
  32. Zekarias, S. M. (2016). The Impact of Foreign Direct Investment (FDI) on Economic Growth in Eastern Africa: Evidence from Panel Data Analysis. Applied Economics and Finance, 3(1). https://doi.org/10.11114/aef.v3i1.1317
  33. Zhang, X., & Yao, S. (2024). Spatial convergence and differentiation characteristics of ecological efficiency of forestry carbon sink: Evidence from China. Geosystems and Geoenvironment, 3(1), 100241. https://doi.org/10.1016/j.geogeo.2023.100241