Batı Balkan Ülkelerinde Makroekonomik Göstergeler ve Yolsuzluk Algı Endeksi Arasındaki İlişki: Sabit Etkiler Panel Veri Analizi

Öz

Bu çalışma, Arnavutluk, Bosna-Hersek, Kosova, Karadağ, Kuzey Makedonya ve Sırbistan’dan oluşan altı Batı Balkan ülkesinde Yolsuzluk Algı Endeksi (CPI) skorları ile seçili makroekonomik göstergeler arasındaki ilişkiyi incelemektedir. Bu çalışmanın amacı, söz konusu ilişkileri ampirik olarak değerlendirmektir. Tahmin örneklemi 2002-2024 dönemine yayılan 115 ülke-yıl gözleminden oluşmaktadır. Analizde ekonomik gelişmişlik gayrisafi yurt içi hasıla, makroekonomik istikrarsızlık enflasyon, dış sermaye kanalı ise doğrudan yabancı sermaye yatırımları aracılığıyla temsil edilmektedir. CPI skorunun yükselmesi algılanan yolsuzluğun azalması anlamına geldiğinden, tahmin edilen pozitif katsayılar daha düşük yolsuzluk algısıyla, negatif katsayılar ise daha yüksek yolsuzluk algısıyla ilişkilendirilmektedir. Analizde ülke ve yıl sabit etkilerini içeren iki yönlü sabit etkiler modeli kullanılmış, yatay kesit bağımlılığı ve otokorelasyon nedeniyle katsayılar Driscoll-Kraay dirençli standart hatalarıyla raporlanmıştır. İki yönlü sabit etkiler modelinde enflasyon katsayısı negatif ve istatistiksel olarak anlamlı iken, GSYH katsayısı istatistiksel olarak anlamlı değildir. Doğrudan yabancı sermaye yatırımlarına ilişkin bulgular ise spesifikasyona duyarlıdır. Bulgular nedensel etkilerden ziyade koşullu panel ilişkileri olarak değerlendirilmelidir.

Anahtar Kelimeler

• Yolsuzluk Algı Endeksi
• Batı Balkanlar
• Makroekonomik İstikrar
• Doğrudan Yabancı Sermaye Yatırımları

The Relationship Between Macroeconomic Indicators and the Corruption Perceptions Index in Western Balkan Countries: A Fixed-Effects Panel Data Analysis

Öz

This study examines the relationship between Corruption Perceptions Index (CPI) scores and selected macroeconomic indicators in six Western Balkan countries: Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, and Serbia. The aim of this study is to empirically examine these relationships. The estimation sample consists of 115 country-year observations covering 2002-2024. In the analysis, economic development is represented by gross domestic product, macroeconomic instability by inflation, and the external capital channel by foreign direct investment. Since a higher CPI score indicates a lower perceived level of corruption, positive estimated coefficients are associated with lower perceived corruption, whereas negative coefficients are associated with higher perceived corruption. The analysis uses a two-way fixed-effects model with country and year effects, and because of cross-sectional dependence and autocorrelation the coefficients are reported with Driscoll-Kraay robust standard errors. In the two-way fixed-effects model, while the inflation coefficient is negative and statistically significant, the GDP coefficient is not statistically significant. The findings regarding the foreign direct investment is specification-sensitive. The findings should be interpreted as conditional panel associations rather than causal effects.

Anahtar Kelimeler

• Corruption Perceptions Index
• Western Balkans
• Macroeconomic Stability
• Foreign Direct Investments

Kaynakça

1. Acemoglu, D., Johnson, S. and Robinson, J.A. (2001). The colonial origins of comparative development: An empirical investigation. American Economic Review, 91(5), 1369-1401. https://doi.org/10.1257/aer.91.5.1369
2. Ades, A. and Di Tella, R. (1999). Rents, competition, and corruption. American Economic Review, 89(4), 982-993. https://doi.org/10.1257/aer.89.4.982
3. Aidt, T.S. (2003). Economic analysis of corruption: A survey. The Economic Journal, 113(491), 632-652. https://doi.org/10.1046/j.0013-0133.2003.00171.x
4. Al-Marhubi, F.A. (2000). Corruption and inflation. Economics Letters, 66(2), 199-202. https://doi.org/10.1016/S0165-1765(99)00230-X
5. Bartlett, W. (2008). Europe’s troubled region: Economic development, institutional reform, and social welfare in the Western Balkans. London: Routledge.
6. Braun, M. and Di Tella, R. (2004). Inflation, inflation variability, and corruption. Economics & Politics, 16(1), 77-100. https://doi.org/10.1111/j.1468-0343.2004.00132.x
7. Breusch, T.S. and 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
8. Chaudhry, M.A. and Shabbir, G. (2007). Determinants of corruption in developing countries (HWWI Research Paper No. 2-11). Retrieved from https://www.econstor.eu/bitstream/10419/48268/1/664013651.pdf

9. Danish, B.M.A. and Wang, B. (2019). Analyzing the role of governance in CO2 emissions mitigation: The BRICS experience. Structural Change and Economic Dynamics, 51, 119-125. https://doi.org/10.1016/j.strueco.2019.08.007
10. De Hoyos, R.E. and Sarafidis, V. (2006). Testing for cross-sectional dependence in panel-data models. The Stata Journal, 6(4), 482-496. https://doi.org/10.1177/1536867X0600600403
11. Driscoll, J.C. and Kraay, A.C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. Review of Economics and Statistics, 80(4), 549-560. https://doi.org/10.1162/003465398557825
12. Dritsaki, M. and Dritsaki, C. (2024). The relationship between health expenditure, CO2 emissions, and economic growth in G7: Evidence from heterogeneous panel data. Journal of the Knowledge Economy, 15(1), 4886-4911. https://doi.org/10.1007/s13132-023-01349-y
13. Efendic, A., Pugh, G. and Adnett, N. (2011). Institutions and economic performance: A meta-regression analysis. European Journal of Political Economy, 27(3), 586-599. https://doi.org/10.1016/j.ejpoleco.2010.12.003
14. Egger, P. and Winner, H. (2005). Evidence on corruption as an incentive for foreign direct investment. European Journal of Political Economy, 21(4), 932-952. https://doi.org/10.1016/j.ejpoleco.2005.01.002
15. Estrin, S. and Uvalic, M. (2014). FDI into transition economies: Are the Balkans different? Economics of Transition, 22(2), 281-312. https://doi.org/10.1111/ecot.12040
16. Gani, A. (2017). Corruption and economic growth in developing countries. Economies, 5(1), 4. https://doi.org/10.3390/economies5010004
17. Granger, C.W.J. and Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111–120. https://doi.org/10.1016/0304-4076(74)90034-7
18. Hausman, J.A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251-1271. https://doi.org/10.2307/1913827
19. Hoechle, D. (2007). Robust standard errors for panel regressions with cross-sectional dependence. The Stata Journal, 7(3), 281–312. https://doi.org/10.1177/1536867X0700700301
20. Kadooğlu Aydın, G. ve Büyükoğlu, B. (2025). Corruption perception, financial secrecy, and globalization: An empirical analysis of 19 European countries. Ekonomi, Politika & Finans Araştırmaları Dergisi, 10(4), 1382-1398. https://doi.org/10.30784/epfad.1692382
21. Kesar, A., Kamaiah, B., Jena, P.K. and Yadav, M.P. (2022). The asymmetric relationship between corruption, political stability and economic growth: New evidence from BRICS countries. The Indian Economic Journal, 70(2), 1-22. https://doi.org/10.1177/00194662221082204
22. La Porta, R., Lopez-de-Silanes, F., Shleifer, A. and Vishny, R. (1999). The quality of government. Journal of Law, Economics, & Organization, 15(1), 222-279. https://doi.org/10.1093/jleo/15.1.222
23. Mauro, P. (1995). Corruption and growth. The Quarterly Journal of Economics, 110(3), 681-712. https://doi.org/10.2307/2118445
24. Mauro, P. (1998). Corruption and the composition of government expenditure. Journal of Public Economics, 69(2), 263-279. https://doi.org/10.1016/S0047-2727(98)00025-5
25. Méon, P.G. and Sekkat, K. (2005). Does corruption grease or sand the wheels of growth? Public Choice, 122(1-2), 69-97. https://doi.org/10.1007/s11127-005-3988-0
26. Mungiu-Pippidi, A. (2006). Corruption: Diagnosis and treatment. Journal of Democracy, 17(3), 86-99. https://doi.org/10.1353/jod.2006.0050
27. Murgasova, Z., Ilahi, N., Miniane, J., Scott, A. and Vladkova-Hollar, I. (2015). The Western Balkans: 15 years of economic transition (Regional Economic Issues, Special Report). Retrieved from https://www.imf.org/external/pubs/ft/reo/2015/eur/eng/erei0315.htm
28. Paldam, M. (2002). The cross-country pattern of corruption: Economics, culture and the seesaw dynamics. European Journal of Political Economy, 18(2), 215-240. https://doi.org/10.1016/S0176-2680(02)00078-2
29. 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
30. Ridwan, M., Urbee, A.J., Voumik, L.C., Das, M.K., Rashid, M. and Esquivias, M.A. (2024). Investigating the environmental Kuznets curve hypothesis with urbanization, industrialization, and service sector for six South Asian countries: Fresh evidence from Driscoll Kraay standard error. Research in Globalization, 8, 100223. https://doi.org/10.1016/j.resglo.2024.100223
31. Rodrik, D. (2011). The globalization paradox: Democracy and the future of the world economy. New York: W.W. Norton & Company.
32. Rodrik, D., Subramanian, A. and Trebbi, F. (2004). Institutions rule: The primacy of institutions over geography and integration in economic development. Journal of Economic Growth, 9(2), 131-165. https://doi.org/10.1023/B:JOEG.0000031425.72248.85
33. Roland, G. (2002). The political economy of transition. Journal of Economic Perspectives, 16(1), 29-50. https://doi.org/10.1257/0895330027102
34. Sanfey, P., Milatovic, J. and Kresic, A. (2016). How the Western Balkans can catch up (EBRD Working Paper No. 185). Retrieved from https://ssrn.com/abstract=3119685
35. Serra, D. (2006). Empirical determinants of corruption: A sensitivity analysis. Public Choice, 126(1-2), 225-256. https://doi.org/10.1007/s11127-006-0286-4
36. Shleifer, A. and Vishny, R.W. (1993). Corruption. The Quarterly Journal of Economics, 108(3), 599-617. https://doi.org/10.2307/2118402
37. Simo-Kengne, B.D. and Bitterhout, S. (2023). Corruption’s effect on BRICS countries’ economic growth: a panel data analysis. Journal of Economics, Finance and Administrative Science, 28(56), 257-272. https://doi.org/10.1108/JEFAS-04-2021-0041
38. Svensson, J. (2005). Eight questions about corruption. Journal of Economic Perspectives, 19(3), 19-42. https://doi.org/10.1257/089533005774357860
39. Tanzi, V. (1998). Corruption around the world: Causes, consequences, scope, and cures. IMF Staff Papers, 45(4), 559-594. https://doi.org/10.2307/3867585
40. Tanzi, V. and Davoodi, H. (1997). Corruption, public investment, and growth (IMF Working Paper No. 1997/139). Retrieved from https://www.imf.org/en/publications/wp/issues/2016/12/30/corruption-public-investment-and-growth-2353
41. Topaloğlu, E.E. (2018). Bankalarda finansal kırılganlığı etkileyen faktörlerin panel veri analizi ile belirlenmesi. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 13(1), 15–38. https://doi.org/10.17153/oguiibf.344856
42. Transparency International. (2025). Corruption Perceptions Index 2024. Retrieved from https://www.transparency.org/en/cpi/2024
43. Treisman, D. (2000). The causes of corruption: A cross-national study. Journal of Public Economics, 76(3), 399-457. https://doi.org/10.1016/S0047-2727(99)00092-4
44. Treisman, D. (2007). What have we learned about the causes of corruption from ten years of cross-national empirical research? Annual Review of Political Science, 10, 211-244. https://doi.org/10.1146/annurev.polisci.10.081205.095418
45. Wei, S.J. (2000). How taxing is corruption on international investors? Review of Economics and Statistics, 82(1), 1-11. https://doi.org/10.1162/003465300558533
46. Westerlund, J. (2008). Panel cointegration tests of the Fisher effect. Journal of Applied Econometrics, 23(2), 193-233. https://doi.org/10.1002/jae.967
47. World Bank. (2024). World development indicators. Retrieved from https://databank.worldbank.org
48. Yerdelen Tatoğlu, F. (2012). Panel veri ekonometrisi. İstanbul: Beta Yayıncılık.