Abstract
The repercussions of geopolitical risks encountered by a nation extend beyond its borders and can have a ripple effect on neighboring and even distant countries. These geopolitical risks, stemming from a mix of political, geographical, and geopolitical factors, can influence other nations through international tensions, security concerns, trade disputes, acts of terrorism, armed conflicts, natural disasters, and political instability. The paper aims to investigate the dynamic relationships between geopolitical risk indices of G20 countries using spillover analysis based on the Time-Varying Parameter Vector Autoregression (TVP-VAR) model. For this purpose, the geopolitical risk indices calculated by Caldara and Iacoviello (2022) have been utilized. The analysis results indicate that the transmission of geopolitical risks is primarily directed from advanced Western countries (such as the US, the UK, and Germany) to other countries in the sample. Particularly, it has been identified that China and Russia have been transmitting geopolitical risks to other countries, especially after 2010. Furthermore, the time-varying total spillover index captures hightened geopolitical risks episodes. Indonesia, Argentina, and Mexico stand out as the countries receiving the highest level of geopolitical risk spillover. Since geopolitical risks are closely related to economic growth, trade, and financial markets, the analysis results will provide valuable insights for policymakers and market participants.
References
- Alptürk, Y., Sezal, L., & Gürsoy, S. (2021). Türkiye’de jeopolitik risk ile CDS primleri arasındaki ilişki: Asimetrik nedensellik analizi. Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(1), 107-126.
- Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. MDPI AG. Retrieved from http://dx.doi.org/10.3390/jrfm13040084
- Baker, S. R., Bloom, N. ve Davis, S. J. (2016). Measuring Economic Policy Uncertainty. Balli, F., Balli, H. O., Hasan, M., & Gregory-Allen, R. (2022). Geopolitical risk spillovers and its determinants. The Annals of Regional Science, 68(2), 463-500.
- Caldara, D., & Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, 112(4), 1194-1225.
- Caldara, D., Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, April, 112(4), 1194-1225.
- Cevik, N. K., Cevik, E. I., & Dibooglu, S. (2020). Oil prices, stock market returns and volatility spillovers: Evidence from Turkey. Journal of Policy Modeling, 42(3), 597-614.
- Cheng, S., Han, L., Cao, Y., Jiang, Q., & Liang, R. (2022). Gold-oil dynamic relationship and the asymmetric role of geopolitical risks: Evidence from Bayesian pdBEKK-GARCH with regime switching. Resources Policy, 78, 102917.
- Davis, S. J. (2016). An index of global economic policy uncertainty (No. w22740). National Bureau of Economic Research.
- Diebold, F. X. & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. doi:10.1016/j.ijforecast.2011.02.006.
- Elsayed, A. H., & Helmi, M. H. (2021). Volatility transmission and spillover dynamics across financial markets: the role of geopolitical risk. Annals of Operations Research, 305(1-2), 1-22.
- Feng, Z., Liu, X., & Yao, Y. (2023). Impact of geopolitical risk on the volatility spillovers among G7 and BRICS stock markets. Procedia Computer Science, 221, 878-884.
- Gürsoy, S., & Kiliç, E. (2021). Küresel ekonomik politik belirsizliğin Türkiye CDS primi ve BIST bankacılık endeksi üzerindeki volatilite etkileşimi: DCC-GARCH modeli uygulaması. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 35(4), 1323-1334.
- Hasan, M., Balli, F., Balli, H. O., & Gregory-Allen, R. (2018). Bilateral and country-specific drivers of geopolitical risk transmission. In Proceedings of the 23rd Annual New Zealand Finance Colloquium, Lincoln, New Zealand, 13-15.
- Jin, Y., Zhao, H., Bu, L., & Zhang, D. (2023). Geopolitical risk, climate risk and energy markets: A dynamic spillover analysis. International Review of Financial Analysis, 87, 102597.
- Koop, G., Korobilis, D. (2014). A New Index of financial conditions. European Economic Review, 71, 101–116. Koop, G., Pesaran, M. H. & Potter, S. M. (1996). Impulse response analysis in non-linear multivariate models. Journal of Econometrics, 74(1), 119-147. doi:10.1016/0304-4076(95)01753-4.
- Oad Rajput, S. K., Memon, A. A., Siyal, T. A., & Bajaj, N. K. (2023). Volatility spillovers among Islamic countries and geopolitical risk. Journal of Islamic Accounting and Business Research.
- Pesaran, H.H. & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17-29. doi:10.1016/S0165-1765(97)00214-0.
- Sweidan, O. D. (2023). Geopolitical risk spillover among nations: Evidence from Russia. GeoJournal, 88(3), 3029-3037.
- Wang, Y., Bouri, E., Fareed, Z., & Dai, Y. (2022). Geopolitical risk and the systemic risk in the commodity markets under the war in Ukraine. Finance Research Letters, 49, 103066.
- Yang, K., Wei, Y., Li, S., & He, J. (2021). Geopolitical risk and renewable energy stock markets: An insight from multiscale dynamic risk spillover. Journal of Cleaner Production, 279, 123429.
- Yıldırım, E. S., & Özgür, M. I. (2023). The Relationship Between Geopolitical Risk and Credit Default Swap Premium: Evidence from Turkey. Ekonomika,
- Zheng, J., Wen, B., Jiang, Y., Wang, X., & Shen, Y. (2023). Risk spillovers across geopolitical risk and global financial markets. Energy Economics, 127, 107051.
Abstract
Bir ülkenin karşılaştığı jeopolitik risklerin sonuçları, sınırlarının dışına yayılabilir ve komşu ülkeleri hatta kendisine mesafe olarak uzakta yer alan ülkeleri etkileyebilir. Söz konusu jeopolitik riskler, siyasi, coğrafi ve jeopolitik faktörlerin bir karışımından kaynaklanır ve uluslararası gerilimler, güvenlik endişeleri, ticaret anlaşmazlıkları, terör eylemleri, silahlı çatışmalar, doğal afetler ve siyasi istikrarsızlık yoluyla diğer ülkeleri etkileyebilir. Bu çalışmanın amacı, G20 ülkelerinin jeopolitik risk endeksleri arasındaki dinamik ilişkileri Zamanla Değişen Parametre Vektör Otoregresyon (TVP-VAR) modeline dayalı yayılma analizi ile incelemektir. Bu amaçla, Caldara ve Iacoviello’nun (2022) oluşturduğu jeopolitik risk endeksleri kullanılmıştır. Analiz sonuçları, jeopolitik risklerin yayılımının gelişmiş Batı ülkelerinden (örneğin ABD, İngiltere ve Almanya) örneklemde yer alan diğer ülkelere yönelik olduğunu göstermektedir. Özellikle Çin ve Rusya’nın, 2010 yılından sonra, diğer ülkelere jeopolitik risk yaydığı belirlenmiştir. Ayrıca, zamanla değişen toplam yayılma endeksi, yüksek jeopolitik risk dönemlerini yakalamaktadır. Endonezya, Arjantin ve Meksika, en fazla jeopolitik risk yayılmasına maruz kalan ülkeler olarak öne çıkmaktadır. Jeopolitik riskler ekonomik büyüme, ticaret ve finansal piyasalarla yakından ilişkili olduğundan, analiz sonuçları, politika yapıcılarına ve piyasa katılımcılarına değerli bilgiler sunmaktadır.
References
- Alptürk, Y., Sezal, L., & Gürsoy, S. (2021). Türkiye’de jeopolitik risk ile CDS primleri arasındaki ilişki: Asimetrik nedensellik analizi. Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(1), 107-126.
- Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. MDPI AG. Retrieved from http://dx.doi.org/10.3390/jrfm13040084
- Baker, S. R., Bloom, N. ve Davis, S. J. (2016). Measuring Economic Policy Uncertainty. Balli, F., Balli, H. O., Hasan, M., & Gregory-Allen, R. (2022). Geopolitical risk spillovers and its determinants. The Annals of Regional Science, 68(2), 463-500.
- Caldara, D., & Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, 112(4), 1194-1225.
- Caldara, D., Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, April, 112(4), 1194-1225.
- Cevik, N. K., Cevik, E. I., & Dibooglu, S. (2020). Oil prices, stock market returns and volatility spillovers: Evidence from Turkey. Journal of Policy Modeling, 42(3), 597-614.
- Cheng, S., Han, L., Cao, Y., Jiang, Q., & Liang, R. (2022). Gold-oil dynamic relationship and the asymmetric role of geopolitical risks: Evidence from Bayesian pdBEKK-GARCH with regime switching. Resources Policy, 78, 102917.
- Davis, S. J. (2016). An index of global economic policy uncertainty (No. w22740). National Bureau of Economic Research.
- Diebold, F. X. & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. doi:10.1016/j.ijforecast.2011.02.006.
- Elsayed, A. H., & Helmi, M. H. (2021). Volatility transmission and spillover dynamics across financial markets: the role of geopolitical risk. Annals of Operations Research, 305(1-2), 1-22.
- Feng, Z., Liu, X., & Yao, Y. (2023). Impact of geopolitical risk on the volatility spillovers among G7 and BRICS stock markets. Procedia Computer Science, 221, 878-884.
- Gürsoy, S., & Kiliç, E. (2021). Küresel ekonomik politik belirsizliğin Türkiye CDS primi ve BIST bankacılık endeksi üzerindeki volatilite etkileşimi: DCC-GARCH modeli uygulaması. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 35(4), 1323-1334.
- Hasan, M., Balli, F., Balli, H. O., & Gregory-Allen, R. (2018). Bilateral and country-specific drivers of geopolitical risk transmission. In Proceedings of the 23rd Annual New Zealand Finance Colloquium, Lincoln, New Zealand, 13-15.
- Jin, Y., Zhao, H., Bu, L., & Zhang, D. (2023). Geopolitical risk, climate risk and energy markets: A dynamic spillover analysis. International Review of Financial Analysis, 87, 102597.
- Koop, G., Korobilis, D. (2014). A New Index of financial conditions. European Economic Review, 71, 101–116. Koop, G., Pesaran, M. H. & Potter, S. M. (1996). Impulse response analysis in non-linear multivariate models. Journal of Econometrics, 74(1), 119-147. doi:10.1016/0304-4076(95)01753-4.
- Oad Rajput, S. K., Memon, A. A., Siyal, T. A., & Bajaj, N. K. (2023). Volatility spillovers among Islamic countries and geopolitical risk. Journal of Islamic Accounting and Business Research.
- Pesaran, H.H. & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17-29. doi:10.1016/S0165-1765(97)00214-0.
- Sweidan, O. D. (2023). Geopolitical risk spillover among nations: Evidence from Russia. GeoJournal, 88(3), 3029-3037.
- Wang, Y., Bouri, E., Fareed, Z., & Dai, Y. (2022). Geopolitical risk and the systemic risk in the commodity markets under the war in Ukraine. Finance Research Letters, 49, 103066.
- Yang, K., Wei, Y., Li, S., & He, J. (2021). Geopolitical risk and renewable energy stock markets: An insight from multiscale dynamic risk spillover. Journal of Cleaner Production, 279, 123429.
- Yıldırım, E. S., & Özgür, M. I. (2023). The Relationship Between Geopolitical Risk and Credit Default Swap Premium: Evidence from Turkey. Ekonomika,
- Zheng, J., Wen, B., Jiang, Y., Wang, X., & Shen, Y. (2023). Risk spillovers across geopolitical risk and global financial markets. Energy Economics, 127, 107051.
Details
| Primary Language | English |
|---|---|
| Subjects | Macroeconomics (Other) |
| Journal Section | Research Articles |
| Authors | |
| Early Pub Date | December 29, 2023 |
| Publication Date | December 30, 2023 |
| Submission Date | December 12, 2023 |
| Acceptance Date | December 22, 2023 |
| Published in Issue | Year 2023 Volume: 3 Issue: 2 |
