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Inflation Spillovers and Geopolitical Risks: Evidence from Euro Area Countries Using TVP-VAR and Quantile Models

Year 2025, , 140 - 159, 28.03.2025
https://doi.org/10.30784/epfad.1599945

Abstract

This study examines the inflation transmission mechanism across 14 European Union countries, from May 1963 to November 2023. Contrary to the existing literature, this study employs a two-stage approach to examine the spillover effect of inflation in the European Region. The study identifies the inflation spillover effects by applying a time-varying parameter vector autoregressive (TVP-VAR) model with the joint connectedness framework. Moreover, we analyze the relationship between the Total Connectedness Index (TCI) and geopolitical risks (GPR) using the Quantile-on-Quantile (QoQ) model and explore how geopolitical uncertainties influence inflation transmission dynamics. The analysis provides significant contributions to the literature in terms of both methodology and scope by allowing responses to risk shocks of different magnitudes to be measured at quantile levels. The findings show that as Denmark, Germany, and France are highly interconnected with other countries in the region, they have an essential of spreading inflation. Unlike, the global and the US’s risk indices, Russia’s and Europe’s GPR have a more significant impact on inflation. Finally, the interaction between TCI and GPR differ across quantiles, implying the existence of non-linear and asymmetric impacts of geopolitical events on inflation interconnectedness.

References

  • Ahmed, S., Hasan, M.M. and Kamal, M.R. (2022). Russia–Ukraine crisis: The effects on the European stock market. European Financial Management, 29(4), 1078–1118. https://doi.org/10.1111/eufm.12386
  • Antonakakis, N., Gabauer, D., Gupta, R. and Plakandaras, V. (2018). Dynamic connectedness of uncertainty across developed economies: A time-varying approach. Economics Letters, 166, 63–75. https://doi.org/10.1016/j.econlet.2018.02.011
  • Baruník, J. and Křehlík, T. (2018). Measuring the frequency dynamics of financial connectedness and systemic risk. Journal of Financial Econometrics, 16(2), 271–296. https://doi.org/10.1093/jjfinec/nby001
  • Bekaert, G., Hoerova, M. and Lo Duca, M. (2013). Risk, uncertainty and monetary policy. Journal of Monetary Economics, 60(7), 771–788. https://doi.org/10.1016/j.jmoneco.2013.06.003
  • Bettarelli, L., Furceri, D., Pizzuto, P. and Yarveisi, K. (2024). Regional fiscal spillovers: The role of trade linkages. Journal of International Money and Finance, 140, 102995. https://doi.org/10.1016/j.jimonfin.2023.102995
  • Bouri, E., Gabauer, D., Gupta, R. and Kinateder, H. (2023). Global geopolitical risk and inflation spillovers across European and North American economies. Research in International Business and Finance, 66, 102048. https://doi.org/10.1016/j.ribaf.2023.102048
  • Brown, S., Harris, M.N., Spencer, C. and Taylor, K. (2023). Financial expectations and household consumption: Does middle-inflation matter? Journal of Money, Credit and Banking, 56(4), 741–768. https://doi.org/10.1111/jmcb.13063
  • Caldara, D., Cavallo, M. and Iacoviello, M. (2019). Oil price elasticities and oil price fluctuations. Journal of Monetary Economics, 103, 1-20. https://doi.org/10.1016/j.jmoneco.2018.08.004
  • Caldara, D. and Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, 112(4), 1194–1225. https://doi.org/10.1257/aer.20191823
  • Caloia, F.G., Cipollini, A. and Muzzioli, S. (2019). How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study. Energy Economics, 84, 104536. https://doi.org/10.1016/j.eneco.2019.104536
  • Chatziantoniou, I. and Gabauer, D. (2020). EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness. The Quarterly Review of Economics and Finance, 79, 1–14. https://doi.org/10.1016/j.qref.2020.12.003
  • Ciccarelli, M. and Mojon, B. (2010). Global inflation. Review of Economics and Statistics, 92(3), 524–535. https://doi.org/10.1162/REST_a_00008
  • Dai, P.F., Xiong, X., Huynh, T.L.D. and Wang, J. (2022). The impact of economic policy uncertainties on the volatility of European carbon market. Journal of Commodity Markets, 26, 100208. https://doi.org/10.1016/j.jcomm.2021.100208
  • Devereux, M.B., Gente, K. and Yu, C. (2023). International production networks, fiscal spillovers, and optimal fiscal policy (NBER Working Paper No. 28149). Retrieved from https://www.nber.org/papers/w28149
  • Diebold, F.X. and Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. https://doi.org/10.1016/j.ijforecast.2011.02.006
  • Diebold, F.X. and Yılmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119-134. https://doi.org/10.1016/j.jeconom.2014.04.012
  • ECB. (2021). ECB's Governing Council approves its new monetary policy strategy. Retrieved from https://www.ecb.europa.eu/press/pr/date/2021/html/ecb.pr210708~dc78cc4b0d.en.html
  • Eldor, R. and Melnick, R. (2004). Financial markets and terrorism. European Journal of Political Economy, 20(2), 367–386. https://doi.org/10.1016/j.ejpoleco.2004.03.002 Federal Reserve. (2023). Statement on longer-run goals and monetary policy strategy. Retrieved from https://www.federalreserve.gov/monetarypolicy/files/fomc_longerrungoals.pdf
  • Foglia, M., Palomba, G. and Tedeschi, M. (2023). Disentangling the geopolitical risk and its effects on commodities: Evidence from a panel of G8 countries. Resources Policy, 85, 104056. https://doi.org/10.1016/j.resourpol.2023.104056
  • Forbes, K.J., Hjortsoe, I. and Nenova, T. (2020). International evidence on shock-dependent exchange rate pass-through. IMF Economic Review, 68(4), 721–763. https://doi.org/10.1057/s41308-020-00107-7
  • García, J.S., Gómez, E.G. and Rambaud, S.C. (2024). Drivers of inflationary shocks and spillovers between Europe and the United States. Socio-Economic Planning Sciences, 95, 101977. https://doi.org/10.1016/j.seps.2024.101977
  • Gong, Y. (2023). Economic consequences in Europe of the Russian-Ukraine 2022 war. Advances in Economics, Management and Political Sciences, 4(1), 260–270. https://doi.org/10.54254/2754-1169/4/20221073
  • Hall, S.G., Tavlas, G.S. and Wang, Y. (2023). Drivers and spillover effects of inflation: The United States, the euro area, and the United Kingdom. Journal of International Money and Finance, 131, 102776. https://doi.org/10.1016/j.jimonfin.2022.102776
  • Hansen, N. (2023). Euro Area inflation after the pandemic and energy shock: Import prices, profits and wages (IMF Working Paper No. 23/131). https://doi.org/10.5089/9798400245473.001
  • Hossain, A.T., Masum, A. and Saadi, S. (2024). The impact of geopolitical risks on foreign exchange markets: Evidence from the Russia–Ukraine war. Finance Research Letters, 59, 104750. https://doi.org/10.1016/j.frl.2023.104750
  • Hu, D. (2024). Fluctuations in Chevron’s share price in the context of the Russia-Ukraine war. Highlights in Business Economics and Management, 24, 427–435. https://doi.org/10.54097/j2vz6880
  • Hui, H.C. (2021). The long-run effects of geopolitical risk on foreign exchange markets: Evidence from some ASEAN countries. International Journal of Emerging Markets, 17(6), 1543–1564. https://doi.org/10.1108/ijoem-08-2020-1001
  • Jarque, C.M. and Bera, A.K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5
  • Kang, S.H., Hernandez, J.A. and Yoon, S.M. (2019). Who leads the inflation cycle in Europe? Inflation cycle and spillover influence among Eurozone and non-Eurozone economies. International Economics, 160, 56-71. https://doi.org/10.1016/j.inteco.2019.10.001
  • Koop, G., Pesaran, M.H. and Potter, S.M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4
  • Köse, N. and Ünal, E. (2025). Brexit’s effects on energy inflation in the UK. Energy Sources, Part B: Economics, Planning, and Policy, 20(1), 2462047. https://doi.org/10.1080/15567249.2025.2462047
  • Lastrapes, W.D. and Wiesen, T.F.P. (2021). The joint spillover index. Economic Modelling, 94, 681–691. https://doi.org/10.1016/j.econmod.2020.02.010
  • Lee, C., Olasehinde-Williams, G. and Özkan, O. (2023). Geopolitical oil price uncertainty transmission into core inflation: Evidence from two of the biggest global players. Energy Economics, 126, 106983. https://doi.org/10.1016/j.eneco.2023.106983
  • López, C. and Papell, D.H. (2012). Convergence of Euro area inflation rates. Journal of International Money and Finance, 31(6), 1440–1458. https://doi.org/10.1016/j.jimonfin.2012.03.005
  • Mankiw, N.G. (2014). Principles of economics: Instructor’s edition (7th ed.). Boston: Cengage Learning.
  • Marangoz, C. (2025). Geopolitical turmoil and energy dynamics: Analyzing the impact on inflation in selected European economies. Heliyon, 11(3), e42302. Retrieved from https://www.cell.com/heliyon/
  • Mishkin, F.S. (2007). Inflation targeting: Successes, problems, and challenges (NBER Working Paper No. 13553). https://doi.org/10.3386/w13553
  • Pesaran, M.H. and Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/S0165-1765(97)00214-0
  • Pham, B.T. and Sala, H. (2022). Cross-country connectedness in inflation and unemployment: Measurement and macroeconomic consequences. Empirical Economics, 62(3), 1123–1146. https://doi.org/10.1007/s00181-021-02052-0
  • Qin, M., Su, C., Umar, M., Lobonț, O. and Manta, A. G. (2023). Are climate and geopolitics the challenges to sustainable development? Novel evidence from the global supply chain. Economic Analysis and Policy, 77, 748–763. https://doi.org/10.1016/j.eap.2023.01.002
  • Salisu, A.A., Cuñado, J. and Gupta, R. (2022). Geopolitical risks and historical exchange rate volatility of the BRICS. International Review of Economics & Finance, 77, 179–190. https://doi.org/10.1016/j.iref.2021.09.017
  • Sim, N. and Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking & Finance, 55, 1–8. https://doi.org/10.1016/j.jbankfin.2015.01.013
  • Stern, N. (2014). The role of energy and resource security in inflation dynamics. The Energy Journal, 35(4), 91–118. https://doi.org/10.5547/01956574.35.4.5
  • Taylor, J.B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195–214. https://doi.org/10.1016/0167-2231(93)90009-L
  • Tyagi, K. (2024). The impact of Russia – Ukraine war on global economy. International Journal for Multidisciplinary Research, 6(5), 1-7. https://doi.org/10.36948/ijfmr.2024.v06i05.29797
  • Umar, M., Farid, S. and Naeem, M.A. (2022). Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis. Energy, 240, 122702. https://doi.org/10.1016/j.energy.2021.122702
  • Windberger, T. and Zeileis, A. (2014). Structural breaks in inflation dynamics within the European Monetary Union. Eastern European Economics, 52(3), 66–88. https://doi.org/10.2753/EEE0012-8775520304
  • Yang, T., Dong, Q., Du, M. and Du, Q. (2023). Geopolitical risks, oil price shocks and inflation: Evidence from a TVP–SV–VAR approach. Energy Economics, 127, 107099. https://doi.org/10.1016/j.eneco.2023.107099
  • Ye, M., Mohammed, K.S., Tiwari, S., Raza, S.A. and Chen, L. (2023). The effect of the global supply chain and oil prices on the inflation rates in advanced economies and emerging markets. Geological Journal, 58(7), 2805–2817. https://doi.org/10.1002/gj.4742
  • Zimková, E., Bruncková, M., Pintér, Ľ. and Sičová, K. (2023). Pandemic and invasion related inflation in the selected European Union countries. Acta Aerarii Publici, 20(2), 44–55. https://doi.org/10.24040/aap.2023.20.2.44-55

Enflasyon Yayılma Etkileri ve Jeopolitik Riskler: TVP-VAR ve Kantil Modelleri Kullanılarak Euro Bölgesi Ülkelerinden Kanıtlar

Year 2025, , 140 - 159, 28.03.2025
https://doi.org/10.30784/epfad.1599945

Abstract

Bu çalışma, Mayıs 1963 ile Kasım 2023 arasındaki dönemde 14 Avrupa Birliği ülkesinde enflasyon yayılma mekanizmasını incelemektedir. Literatürün aksine, bu çalışmada Avrupa Bölgesi'nde enflasyonun yayılma etkisini incelemek için iki aşamalı bir yaklaşım kullanılmaktadır. Çalışmada, zamanla değişen parametreli vektör otoregresif (TVP-VAR) modeli ve ortak bağlantılılık çerçevesi kullanılarak enflasyonun yayılma etkileri belirlenmiştir. Ayrıca, Toplam Bağlantılılık Endeksi (TCI) ile jeopolitik riskler (GPR) arasındaki ilişki, Kantil-üzerinde-Kantil (QoQ) modeli ile analiz edilmiş ve jeopolitik belirsizliklerin enflasyon yayılma dinamiklerini nasıl etkilediği incelenmiştir. Analiz, farklı büyüklükteki risk şoklarına verilen tepkilerin kantil seviyelerinde ölçülmesine olanak tanıyarak hem metodoloji hem de kapsam açısından literatüre önemli katkılar sağlamaktadır. Bulgular, Danimarka, Almanya ve Fransa’nın bölgedeki diğer ülkelerle yüksek derecede bağlantılı olduğunu ve bu ülkelerin enflasyonun yayılmasında önemli bir role sahip olduğunu göstermektedir. Global ve ABD risk endekslerinin aksine, Rusya ve Avrupa’nın GPR’si enflasyon üzerinde daha önemli bir etkiye sahiptir. Son olarak, TCI ile GPR arasındaki etkileşimlerin farklı kantillerde değişiklik gösterdiği ve jeopolitik olayların enflasyon bağlantılılığı üzerinde doğrusal olmayan ve asimetrik etkiler yarattığı tespit edilmiştir.

References

  • Ahmed, S., Hasan, M.M. and Kamal, M.R. (2022). Russia–Ukraine crisis: The effects on the European stock market. European Financial Management, 29(4), 1078–1118. https://doi.org/10.1111/eufm.12386
  • Antonakakis, N., Gabauer, D., Gupta, R. and Plakandaras, V. (2018). Dynamic connectedness of uncertainty across developed economies: A time-varying approach. Economics Letters, 166, 63–75. https://doi.org/10.1016/j.econlet.2018.02.011
  • Baruník, J. and Křehlík, T. (2018). Measuring the frequency dynamics of financial connectedness and systemic risk. Journal of Financial Econometrics, 16(2), 271–296. https://doi.org/10.1093/jjfinec/nby001
  • Bekaert, G., Hoerova, M. and Lo Duca, M. (2013). Risk, uncertainty and monetary policy. Journal of Monetary Economics, 60(7), 771–788. https://doi.org/10.1016/j.jmoneco.2013.06.003
  • Bettarelli, L., Furceri, D., Pizzuto, P. and Yarveisi, K. (2024). Regional fiscal spillovers: The role of trade linkages. Journal of International Money and Finance, 140, 102995. https://doi.org/10.1016/j.jimonfin.2023.102995
  • Bouri, E., Gabauer, D., Gupta, R. and Kinateder, H. (2023). Global geopolitical risk and inflation spillovers across European and North American economies. Research in International Business and Finance, 66, 102048. https://doi.org/10.1016/j.ribaf.2023.102048
  • Brown, S., Harris, M.N., Spencer, C. and Taylor, K. (2023). Financial expectations and household consumption: Does middle-inflation matter? Journal of Money, Credit and Banking, 56(4), 741–768. https://doi.org/10.1111/jmcb.13063
  • Caldara, D., Cavallo, M. and Iacoviello, M. (2019). Oil price elasticities and oil price fluctuations. Journal of Monetary Economics, 103, 1-20. https://doi.org/10.1016/j.jmoneco.2018.08.004
  • Caldara, D. and Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, 112(4), 1194–1225. https://doi.org/10.1257/aer.20191823
  • Caloia, F.G., Cipollini, A. and Muzzioli, S. (2019). How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study. Energy Economics, 84, 104536. https://doi.org/10.1016/j.eneco.2019.104536
  • Chatziantoniou, I. and Gabauer, D. (2020). EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness. The Quarterly Review of Economics and Finance, 79, 1–14. https://doi.org/10.1016/j.qref.2020.12.003
  • Ciccarelli, M. and Mojon, B. (2010). Global inflation. Review of Economics and Statistics, 92(3), 524–535. https://doi.org/10.1162/REST_a_00008
  • Dai, P.F., Xiong, X., Huynh, T.L.D. and Wang, J. (2022). The impact of economic policy uncertainties on the volatility of European carbon market. Journal of Commodity Markets, 26, 100208. https://doi.org/10.1016/j.jcomm.2021.100208
  • Devereux, M.B., Gente, K. and Yu, C. (2023). International production networks, fiscal spillovers, and optimal fiscal policy (NBER Working Paper No. 28149). Retrieved from https://www.nber.org/papers/w28149
  • Diebold, F.X. and Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. https://doi.org/10.1016/j.ijforecast.2011.02.006
  • Diebold, F.X. and Yılmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119-134. https://doi.org/10.1016/j.jeconom.2014.04.012
  • ECB. (2021). ECB's Governing Council approves its new monetary policy strategy. Retrieved from https://www.ecb.europa.eu/press/pr/date/2021/html/ecb.pr210708~dc78cc4b0d.en.html
  • Eldor, R. and Melnick, R. (2004). Financial markets and terrorism. European Journal of Political Economy, 20(2), 367–386. https://doi.org/10.1016/j.ejpoleco.2004.03.002 Federal Reserve. (2023). Statement on longer-run goals and monetary policy strategy. Retrieved from https://www.federalreserve.gov/monetarypolicy/files/fomc_longerrungoals.pdf
  • Foglia, M., Palomba, G. and Tedeschi, M. (2023). Disentangling the geopolitical risk and its effects on commodities: Evidence from a panel of G8 countries. Resources Policy, 85, 104056. https://doi.org/10.1016/j.resourpol.2023.104056
  • Forbes, K.J., Hjortsoe, I. and Nenova, T. (2020). International evidence on shock-dependent exchange rate pass-through. IMF Economic Review, 68(4), 721–763. https://doi.org/10.1057/s41308-020-00107-7
  • García, J.S., Gómez, E.G. and Rambaud, S.C. (2024). Drivers of inflationary shocks and spillovers between Europe and the United States. Socio-Economic Planning Sciences, 95, 101977. https://doi.org/10.1016/j.seps.2024.101977
  • Gong, Y. (2023). Economic consequences in Europe of the Russian-Ukraine 2022 war. Advances in Economics, Management and Political Sciences, 4(1), 260–270. https://doi.org/10.54254/2754-1169/4/20221073
  • Hall, S.G., Tavlas, G.S. and Wang, Y. (2023). Drivers and spillover effects of inflation: The United States, the euro area, and the United Kingdom. Journal of International Money and Finance, 131, 102776. https://doi.org/10.1016/j.jimonfin.2022.102776
  • Hansen, N. (2023). Euro Area inflation after the pandemic and energy shock: Import prices, profits and wages (IMF Working Paper No. 23/131). https://doi.org/10.5089/9798400245473.001
  • Hossain, A.T., Masum, A. and Saadi, S. (2024). The impact of geopolitical risks on foreign exchange markets: Evidence from the Russia–Ukraine war. Finance Research Letters, 59, 104750. https://doi.org/10.1016/j.frl.2023.104750
  • Hu, D. (2024). Fluctuations in Chevron’s share price in the context of the Russia-Ukraine war. Highlights in Business Economics and Management, 24, 427–435. https://doi.org/10.54097/j2vz6880
  • Hui, H.C. (2021). The long-run effects of geopolitical risk on foreign exchange markets: Evidence from some ASEAN countries. International Journal of Emerging Markets, 17(6), 1543–1564. https://doi.org/10.1108/ijoem-08-2020-1001
  • Jarque, C.M. and Bera, A.K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5
  • Kang, S.H., Hernandez, J.A. and Yoon, S.M. (2019). Who leads the inflation cycle in Europe? Inflation cycle and spillover influence among Eurozone and non-Eurozone economies. International Economics, 160, 56-71. https://doi.org/10.1016/j.inteco.2019.10.001
  • Koop, G., Pesaran, M.H. and Potter, S.M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4
  • Köse, N. and Ünal, E. (2025). Brexit’s effects on energy inflation in the UK. Energy Sources, Part B: Economics, Planning, and Policy, 20(1), 2462047. https://doi.org/10.1080/15567249.2025.2462047
  • Lastrapes, W.D. and Wiesen, T.F.P. (2021). The joint spillover index. Economic Modelling, 94, 681–691. https://doi.org/10.1016/j.econmod.2020.02.010
  • Lee, C., Olasehinde-Williams, G. and Özkan, O. (2023). Geopolitical oil price uncertainty transmission into core inflation: Evidence from two of the biggest global players. Energy Economics, 126, 106983. https://doi.org/10.1016/j.eneco.2023.106983
  • López, C. and Papell, D.H. (2012). Convergence of Euro area inflation rates. Journal of International Money and Finance, 31(6), 1440–1458. https://doi.org/10.1016/j.jimonfin.2012.03.005
  • Mankiw, N.G. (2014). Principles of economics: Instructor’s edition (7th ed.). Boston: Cengage Learning.
  • Marangoz, C. (2025). Geopolitical turmoil and energy dynamics: Analyzing the impact on inflation in selected European economies. Heliyon, 11(3), e42302. Retrieved from https://www.cell.com/heliyon/
  • Mishkin, F.S. (2007). Inflation targeting: Successes, problems, and challenges (NBER Working Paper No. 13553). https://doi.org/10.3386/w13553
  • Pesaran, M.H. and Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/S0165-1765(97)00214-0
  • Pham, B.T. and Sala, H. (2022). Cross-country connectedness in inflation and unemployment: Measurement and macroeconomic consequences. Empirical Economics, 62(3), 1123–1146. https://doi.org/10.1007/s00181-021-02052-0
  • Qin, M., Su, C., Umar, M., Lobonț, O. and Manta, A. G. (2023). Are climate and geopolitics the challenges to sustainable development? Novel evidence from the global supply chain. Economic Analysis and Policy, 77, 748–763. https://doi.org/10.1016/j.eap.2023.01.002
  • Salisu, A.A., Cuñado, J. and Gupta, R. (2022). Geopolitical risks and historical exchange rate volatility of the BRICS. International Review of Economics & Finance, 77, 179–190. https://doi.org/10.1016/j.iref.2021.09.017
  • Sim, N. and Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking & Finance, 55, 1–8. https://doi.org/10.1016/j.jbankfin.2015.01.013
  • Stern, N. (2014). The role of energy and resource security in inflation dynamics. The Energy Journal, 35(4), 91–118. https://doi.org/10.5547/01956574.35.4.5
  • Taylor, J.B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195–214. https://doi.org/10.1016/0167-2231(93)90009-L
  • Tyagi, K. (2024). The impact of Russia – Ukraine war on global economy. International Journal for Multidisciplinary Research, 6(5), 1-7. https://doi.org/10.36948/ijfmr.2024.v06i05.29797
  • Umar, M., Farid, S. and Naeem, M.A. (2022). Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis. Energy, 240, 122702. https://doi.org/10.1016/j.energy.2021.122702
  • Windberger, T. and Zeileis, A. (2014). Structural breaks in inflation dynamics within the European Monetary Union. Eastern European Economics, 52(3), 66–88. https://doi.org/10.2753/EEE0012-8775520304
  • Yang, T., Dong, Q., Du, M. and Du, Q. (2023). Geopolitical risks, oil price shocks and inflation: Evidence from a TVP–SV–VAR approach. Energy Economics, 127, 107099. https://doi.org/10.1016/j.eneco.2023.107099
  • Ye, M., Mohammed, K.S., Tiwari, S., Raza, S.A. and Chen, L. (2023). The effect of the global supply chain and oil prices on the inflation rates in advanced economies and emerging markets. Geological Journal, 58(7), 2805–2817. https://doi.org/10.1002/gj.4742
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There are 50 citations in total.

Details

Primary Language English
Subjects Applied Macroeconometrics, Time-Series Analysis, Inflation
Journal Section Makaleler
Authors

Cumali Marangoz 0000-0002-0216-3490

Publication Date March 28, 2025
Submission Date December 11, 2024
Acceptance Date February 17, 2025
Published in Issue Year 2025

Cite

APA Marangoz, C. (2025). Inflation Spillovers and Geopolitical Risks: Evidence from Euro Area Countries Using TVP-VAR and Quantile Models. Ekonomi Politika Ve Finans Araştırmaları Dergisi, 10(1), 140-159. https://doi.org/10.30784/epfad.1599945