dEjournals Home Page
Competitio
Online ready Current Most Read Archives Search
Register Login

Competitio

Vol. 23 No. 1-2 (2024)
Papers

A non-stationary panel data approach for examining convergence in South Africa

Published:
2024-12-31
DOI Linkhttps://doi.org/10.21845/comp/2024/1-2/3
Author
Stacey-Lee Marais
View
PDF
Keywords
convergence economic development emerging economies endogenous growth theory
License

Copyright (c) 2025 Stacey Lee Marais

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How To Cite
Selected Style: APA
Marais, S.-L. (2024). A non-stationary panel data approach for examining convergence in South Africa. Competitio, 23(1-2), 42-74. https://doi.org/10.21845/comp/2024/1-2/3
Received 2024-09-02
Accepted 2024-11-21
Published 2024-12-31
Abstract

Economic convergence has received much attention since the 1980s when researchers tried to ascertain whether low-income countries would stay that way in the long run, or they would gain ‘developmental traction’ and become the affluent nations of the future. This article gives fresh insight on this topic from an African perspective by comparing 39 countries—South Africa, 32 Organisation for Economic Cooperation and Development (OECD) members and 6 Latin American countries. The author investigated their average steady-state equilibria and tested convergence trends from 1980 to 2019. The Solow–Swan model was tested. Furthermore, this study applies panel econometric modelling to determine the relationship between the variables analysed in the convergence analysis. This commenced with the Levin–Lin–Chu and Im–Pesaran–Shin panel unit root tests. Then, the Kao test and the vector error correction model were used to evaluate the cointegration and relationships between variables. The findings revealed that South Africa’s economic performance is significantly lower than the OECD average gross domestic product per capita with an annual growth rate of 0.54%, which falls below the ‘iron law of convergence’ hypothesis.

JEL classifications: C01, C32, C33, E13, F62, F63

References
  1. Ascani, A., Crescenzi, R. & Iammarino, S. (2012). Regional Economic Development: Review. London: SEARCH Working Paper. https://doi.org/10.4324/9781315143736-9
  2. Barro, R. J. & Sala-i-Martin, X. (1991). Convergence Across States and Regions. Washington D.C.: Brookings Papers on Economic Activity, 1991(1), 107-182. https://doi.org/10.2307/2534639
  3. Blonigen BA. (2005). A review of the empirical literature on FDI determinants. Atlantic Economic Journal, 33(4), 383-403. https://doi.org/10.1007/s11293-005-2868-9
  4. Dumitrescu, E.I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29 (4), 1450-1460. https://doi.org/10.1016/j.econmod.2012.02.014
  5. Eberts, R. W. (1990). Public Infrastructure and Regional Economic Development. Cleveland: Federal Reserve Bank of Cleveland. https://doi.org/10.26509/frbc-wp-199004
  6. Egri, Z. & Tánczos, T. (2018). The spatial peculiarities of economic and social convergence on Central and Eastern Europe. Regional Statistics, 8(1), 49-77. https://doi.org/10.15196/rs080108
  7. Feenstra, R.C., Inklaar, R. & Timmer, M.P. (2015). The Next Generation of the Penn World Table. American Economic Review, 105(10), 3150-3182. https://doi.org/10.1257/aer.20130954
  8. Fedderke, J. & Garlick, R. (2008). Infrastructure Development and Economic Growth in South Africa: A review of the accumulated evidence. Cape Town: University of Cape Town.
  9. Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross-spectral models. Econometrica, 37, 424-438. https://doi.org/10.2307/1912791
  10. Gibb, R. (2007). Regional integration in post-apartheid southern Africa. Tijdschrift voor Economiesche en Sociale Geografie, 98(4), 421-435. https://doi.org/10.1111/j.1467-9663.2007.00412.x
  11. Grigoras, S. (2015). Public Sector's Influence on Economic Growth and Convergence as Proof of Development. Economics and Applied Informatics, 221(3), 36-44.
  12. Im, K.S., Pesaran, M.H. & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115, 53-74. https://doi.org/10.1016/s0304-4076(03)00092-7
  13. Islam, N. (1995). Growth empirics: A panel data approach. The Quarterly Journal of Economics, 110 (4), 1127–1170. https://doi.org/10.2307/2946651
  14. Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90, 1-44. https://doi.org/10.1016/s0304-4076(98)00023-2
  15. Kanó, I. S. & Lengyel, I. (2021). Convergence Clubs of NUTS3 Regions of the V4 Group. E&M Economics and Management, 24(4), 22-38. https://doi.org/10.15240/tul/001/2021-4-002
  16. Kurniawati, M. A. (2020). The role of infrastructure, innovation, and globalization on economic growth in OECD countries, 1996-2017. Journal of Science and Technology Policy Management, 11(2), 193-215. https://doi.org/10.1108/jstpm-06-2019-0065
  17. Lengyel, I. & Kotosz, B. (2018). The Catching up Processes of the Regions of the Visegrad Group Countries. Comparative Economic Research, 21(4), 5-24. https://doi.org/10.2478/cer-2018-0024
  18. LSEG Data & Analytics, 2023. Workspace Refinitiv https://workspace.refinitiv.com/ (accessed: 13/10/2023).
  19. Levin, A., Lin, C-F., & Chu, C-S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108, 1-24. https://doi.org/10.1016/s0304-4076(01)00098-7
  20. Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A contribution to the empirics of economic growth. The Quarterly Journal of Economics, 107(2), 407–437. https://doi.org/10.2307/2118477
  21. McCoskey, S.K. (2002). Convergence in Sub-Saharan Africa: a nonstationary panel data approach. Applied Economics, 34(7), 819-829. https://doi.org/10.1080/00036840110061668
  22. Monfort, P. & Nicolini, R. (2000). Regional convergence and international integration. Journal of Urban Economics, 48(1), 286-306. https://doi.org/10.1006/juec.1999.2167
  23. Nagy, B., Lengyel, I. & Udvari, B. (2020). Reindustrialisation patterns in the post-socialist EU members: a comparative study between 2000 and 2017. The European Journal of Comparative Economics, 17(2), 253-275.
  24. Ouattara, B. & Zhang, Y.F. (2019). Infrastructure and long-run economic growth: evidence from Chinese provinces. Empirical Economics, 57, pp.263-284. https://doi.org/10.1007/s00181-018-1429-4
  25. Phillips, C.B. & Sul, D. (2009). Economic transition and growth. Journal of Applied Econometrics, 24, pp.1153-1185. https://doi.org/10.1002/jae.1080
  26. Phillips, P. & Hansen, B. (1990). Statistical inferences in instrumental variables regression with I(1) processes. Review of Economic Studies, 57, 99‐125. https://doi.org/10.2307/2297545
  27. Pradhan, R.P. & Bagchi, T.P. (2013). Effect of transportation infrastructure on economic growth in India: The VECM approach. Research in Transportation Economics, 38(1), 139-148. https://doi.org/10.1016/j.retrec.2012.05.008
  28. Rogerson, C.M. (1997). Local economic development and post-apartheid reconstruction in South Africa. Singapore Journal of Tropical Geography, 18(2), 175-195. https://doi.org/10.1111/1467-9493.00015
  29. Rogerson, C.M. & Rogerson, J. M. (2010). Local economic development in Africa: Global context and research directions. Development Southern Africa, 27(4), 465-480. https://doi.org/10.1080/0376835x.2010.508577
  30. Saba, C. S. & Ngepah, N. (2020). Convergence in military expenditure and economic growth in Africa and its regional economic communities: evidence from a club clustering algorithm. Cogent Economics & Finance, 8(1), 1-35. https://doi.org/10.1080/23322039.2020.1832344
  31. Sahoo, P., Dash, R. K. & Nataraj, G. (2010). Infrastructure development and growth in China. Chiba: Institute of Developing Economies.
  32. Sala-i-Martin, X. (1996). The classical approach to convergence analysis. The Economic Journal, 106(437), 1019-1036. https://doi.org/10.2307/2235375
  33. Sala-i-Martin, X. (2006). The world distribution of income: Falling poverty and convergence, period. The Quarterly Journal of Economics, 121(2), 351-397. https://doi.org/10.1162/qjec.2006.121.2.351
  34. Sims, C.A. (1980). Comparison of interwar and postwar business Cycles: Monetarism reconsidered. https://doi.org/10.3386/w0430
  35. 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
  36. Wehner, J. (2000). Development strategies in post-apartheid South Africa. Afrika Spectrum, 35(2), 183-192.
  37. Yahyaoui, I. & Bouchoucha, N. (2021). The long‐run relationship between ODA, growth and governance: An application of FMOLS and DOLS approaches. African Development Review, 33(1), 38-54. https://doi.org/10.1111/1467-8268.12489
  38. Young, J., Watt, A. & van den Hove, S. (2013). Effective interfaces between science, policy, and society: the SPIRAL project handbook., Swindon Wiltshire: SPIRAL.
  39. Zeng, D.Z. (2015). Global experiences with special economic zones: Focus on China and Africa., Washington D.C.: The World Bank Group. https://doi.org/10.1596/1813-9450-7240