Revisiting the Impact of Fragility on Economic Growth: New Insights From Sub-Saharan Africa

Öz

This research examines fragility impact on Sub-Saharan Africa's economic growth from 2006 to 2019. The variables of interest for this study include economic decline, economic inequality, human flight, brain drain, external intervention, and economic growth. The research objectives are to empirically investigate the connection between fragility indices and economic growth and determine the impact of fragility indices on economic growth. The existence of cointegration was ascertained in our variable using the Westerlund cointegration test. A fully modified ordinary least squares estimation technique was adopted for the first objective, and the findings showed that only external intervention indices positively impacted economic growth. In achieving our second objective, we adopted mean group, augmented mean group, and common correlated effect mean group estimation technique and found that the coefficients of economic decline, economic inequality, and human flight and brain drain had negative impacts on economic growth. In contrast, the external intervention had a positive impact. The research study recommends that fragile countries' governments develop corrective measures to remove these indicators to ensure progressive growth. Also, state administrations must ensure that suitable policies are implemented to encourage research and development. This will limit the problem of human flight and brain drain, which are significant problems in fragile countries.

Anahtar Kelimeler

• Fragility Indices
• Economic Growth
• Foreign Direct Investment
• Sub-Saharan Africa
• Panel Data

Kırılganlığın Ekonomik Büyüme Üzerindeki Etkisinin İncelenmesi: Sahra Altı Afrika'dan Yeni Görüşler

Öz

Bu araştırma, kırılganlık endekslerinin 2006'dan 2019'a kadar Sahra Altı Afrika'nın ekonomik büyümesi üzerindeki etkisini incelemektedir. Çalışmanın değişkenleri arasında ekonomik gerileme, ekonomik eşitsizlik, insan kaçışı, beyin göçü, dış müdahale ve ekonomik büyüme yer almaktadır. Araştırmanın amacı, kırılganlık endeksleri ile ekonomik büyüme arasındaki bağlantıyı ampirik olarak araştırmak ve kırılganlık endekslerinin ekonomik büyüme üzerindeki etkisini belirlemektir. Westerlund eşbütünleşme testi kullanılarak değişkenler arasında eşbütünleşmenin varlığı tespit edilmiştir. Birinci amaç için FMOLS tahmin tekniği benimsenmiş ve bulgular sadece dış müdahale endekslerinin ekonomik büyümeyi pozitif yönde etkilediğini göstermiştir. İkinci olarak ise, ortalama grubu, artırılmış ortalama grubu ve ortak ilişkili etki ortalama grubu tahmin tekniğini benimsenmiş ve ekonomik gerileme katsayısı, ekonomik eşitsizlik ve insan kaçışı ve beyin göçünün ekonomik büyüme üzerinde olumsuz bir etkisi olduğu ve buna karşılık dış müdahalenin ekonomik büyüme üzerinde olumlu bir etkisi olduğu bulunmuştur.

Anahtar Kelimeler

• Kırılganlık Endeksleri
• Ekonomik Büyüme
• Doğrudan Yabancı Yatırım
• Sahra Altı Afrika
• Panel Veri

Kaynakça

1. African Devolopment Bank Group, ADBG. (2013). https://www.afdb.org/fileadmin/uploads/afdb/Documents/Publications/Annual_Report_2013.pdf
2. Akokpari, J. (2017). The EU and Africa: The political economy of an asymmetrical partnership. The ACP Group and the EU development partnership: Beyond the North-South debate, 55-77. https://link.springer.com/chapter/10.1007/978-3-319-45492-4_3
3. Amaizo, E. Yves. 2012. An Alternative African Developmentalism: A Critique of Zero-Sum Games and Palliative Economics. African Development, 37 (4), 117–40.
4. Berdal, M. (2005). Beyond greed and grievance--and not too soon. Review of International Studies, 31(4), 687. https://doi.org/10.1017/S0260210505006698
5. Bertocchi, G., & Guerzoni, A. (2010). The Fragile Definition of State Fragility.Mimeo. University of Modena. https://doi.org/10.1427/34976
6. 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
7. Bryman, A., & Cramer, D. (1997). Quantitative data analysis with SPSS for Windows: A guide for social scientists. Routledge, London.
8. Carment, D., Prest, S., & Samy, Y. (2007). State fragility and implication for aid allocation: An empirical analysis. Conflict Management and Peace Science. ISSN: 0738-8942 print/ 1549-9219 online. https://doi.org/10.1080/07388940802397509

9. Chami, R et al. (2021). Macroeconomy Policy in fragile states. Oxford University Press.
10. Cordina, G. (2004). Economic vulnerability and economic growth: some results from a neoclassical growth modelling approach. Journal of Economic Development, 29(2), 21-39. https://core.ac.uk/download/pdf/6294615.pdf
11. Dalia, H. (2016). Inequality and Economic Outcomes in Sub-Saharan Africa. Regional economic outlook. International Monetary Fund working paper. WP/16/111.
12. 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
13. Gounder, R., ve Saha, S. (2007). Economic volatility, economic vulnerability and foreign aid: empirical results for the South Pacific Island Nations, (Discussion Paper No. 07.02). http://econfin.massey.ac.nz/school/publications/discuss/dp07-02.pdf
14. Hakura, D. S., & Grigoli, F. (2014). Recoveries in the Middle East, North Africa, and Pakistan: have macroeconomic policies been effective? Middle East Development Journal, 6(1), 45-65. https://doi.org/10.1080/17938120.2014.885485
15. Ibrahim, M. D., & Alola, A. A. (2020). Integrated analysis of energy-economic development-environmental sustainability nexus: Case study of MENA countries. Science of the Total Environment, 737, 139768. https://doi.org/10.1016/j.scitotenv.2020.139768
16. Khan, J., Khan, J. A., & Mirwani, R. (2022). The Relation between Corruption and Economy in OECD Countries: A Moderating Role of Tax Revenue. Annals of Human and Social Sciences, 3(3), 90-105. https://doi.org/10.35484/ahss.2022(3-III)10
17. Kılınç, E. C. (2021). Yükselen Piyasa Ekonomilerinde Ekonomik Kırılganlık-Ekonomik Kalkınma İlişkisi. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (69), 20-38. https://doi.org/10.51290/dpusbe.837520
18. McGillivray M., & Feeny, S. (2008). Aid and Growth in Fragile States. UNU-WIDER Research PaperNo. 2008/3. https://www.econstor.eu/handle/10419/63412
19. Nyamongo, E. M., Misati, R. N., Kipyegon, L., & Ndirangu, L. (2012). Remittances, financial development and economic growth in Africa. Journal of economics and business, 64(3), 240-260. https://doi.org/10.1016/j.jeconbus.2012.01.001
20. OECD. (2018). https://ec.europa.eu/commission/presscorner/detail/it/ip_19_3432
21. Okafor, O. (2017). Empirical Investigation into the determinants of terrorism: Evidence from Fragile States. Defence and Peace Economics, 1-15. https://doi.org/10.1080/10242694.2017.1289746
22. Olorogun, L. A. (2021) ‘The nexus between FDI inflows and economic development in Ghana: Empirical analysis from ARDL model. Journal of Global Business Advancement, 14 (1), 93–114. https://doi.org/10.1504/JGBA.2021.114319
23. Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967-1012. https://doi.org/10.1111/j.1468-0262.2006.00692.x
24. 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
25. Pesaran, M. H., & Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics, 68(1), 79-113. https://www.econ.cam.ac.uk/people-files/emeritus/mhp1/jasaold.pdf
26. Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93. https://doi.org/10.1016/j.jeconom.2007.05.010
27. Phillips, P. C., & Hansen, B. E. (1990). Statistical inference in instrumental variables regression with I(1) processes. The Review of Economic Studies, 57(1), 99-125. https://doi.org/10.2307/2297545
28. Saba, C.S., & Ngepah, N. (2019). A cross-regional analysis of military expenditure, state fragility and economic growth in Africa. Quality and Quantity, 53, 2885–2915. https://doi.org/10.1007/s11135-019-00905-6
29. Saba, T. (2021). Military expenditure, security outcome and industrialization in Africa. Evidence from a panel analysis. African Security Review, 30. https://doi.org/10.1080/10246029.2021.1917432 Signe, G. (2020). Illicit financial flows in Africa: Drivers, destinations, and policy options. Africa Growth Initiative at Brookings. https://africaportal.org/publication/illicit-financial-flows-africa-drivers-destinations-and-policy-options/
30. Swamy, P. A. (1970). Efficient inference in a random coefficient regression model. Econometrica: Journal of the Econometric Society, 311-323. https://doi.org/10.2307/1913012
31. Tabassam, A. H., Hashmi, S. H., & Rehman, F. U. (2016). Nexus between political instability and economic growth in Pakistan. Procedia-Social and Behavioral Sciences, 230, 325-334. https://doi.org/10.1016/j.sbspro.2016.09.041
32. Thorbecke, E. (2019). Andy McKay University of Sussex, UK and Erik Thorbecke Cornell University, USA. Fragility of Growth in African Economies, 1., https://aercafrica.org/old-website/wp-content/uploads/2022/03/SPS-XXI-Papers.pdf#page=9
33. Toh, K. (2016). Assessing macroeconomic volatility on economic growth: the case of Sub-Saharan African Economies, Journal of Economics and Development Studies September, 4 (3), 1- 11. https://doi.org/10.15640/jeds.v4n3a1
34. Tugcu, C. T. (2018). Panel data analysis in the energy-growth nexus (EGN). In The economics and econometrics of the energy-growth nexus (pp. 255-271). Academic Press. https://doi.org/10.1016/B978-0-12-812746-9.00008-0
35. Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and statistics, 69(6), 709-748. https://doi.org/10.1111/j.1468-0084.2007.00477.x
36. Zaouali, A., & Ouechtati, I. (2013). Economic vulnerability and economic growth: what is the role of institutions in MENA countries? International journal of advanced research, 1(8), 667- 675.