Turizm Talebinin Finansal Piyasa Şoklarına Duyarlılığı: TVP-VAR Yaklaşımıyla Bir Volatilite Yayılımı Analizi

Abstract

Bu çalışma, Türkiye’nin turizm talebinin finansal piyasa şoklarına duyarlılığını incelemek amacıyla döviz kuru, BIST100, BIST Turizm, CDS ve VIX gibi temel finansal değişkenler ile turist sayısı arasındaki volatilite ilişkilerini GARCH türü modeller aracılığıyla analiz etmektedir. Turizm sektörünün ekonomik ve finansal dalgalanmalara yüksek duyarlılık sergilediği literatürde geniş ölçüde kabul görmektedir; bu bağlamda çalışma, Türkiye piyasalarının özgün dinamiklerini dikkate alarak finansal volatilite ve turizm talebi arasındaki yönlü bağlantılılığı ortaya koymaktadır. Ampirik bulgular, finansal piyasalarda artan oynaklığın turizm talebinde belirgin dalgalanmalara yol açtığını ve özellikle döviz kuru ile CDS primindeki şokların turizm talebi üzerinde güçlü etkiler yarattığını göstermektedir. Bu sonuçlar, hem arz hem de talep yönlü ekonomik aktörler açısından finansal risklerin etkin izlenmesinin gerekliliğini ortaya koymakta ve turizm sektörünün finansal kırılganlıklara karşı yapısal savunmasızlığını bir kez daha doğrulamaktadır. Çalışmanın bulguları literatürdeki mevcut çalışmalar ile genel olarak uyumlu olmakla birlikte, dinamik yönlü bağlantılılık analizleri aracılığıyla turizm talebine yönelik finansal şokların eşzamanlı ve gecikmeli etkilerini birlikte değerlendirmesi bakımından literatüre özgün bir metodolojik katkı sunmaktadır. Elde edilen sonuçlara dayanarak, politika yapıcılara turizm sektörünün finansal kırılganlığını azaltmaya yönelik makro ihtiyati tedbirlerin güçlendirilmesi ve turizm gelirlerinin çeşitlendirilmesi yönünde stratejik öneriler sunulmaktadır.

Keywords

• Turizm talebi
• finansal volatilite
• döviz kuru şokları
• GARCH modelleri
• Türkiye ekonomisi.

The Sensitivity of Tourism Demand to Financial Market Shocks: A Volatility Spillover Analysis Using the TVP-VAR Approach

Abstract

This study analyses the volatility relationships between key financial variables such as exchange rate, BIST100, BIST Tourism, CDS and VIX, and tourist numbers, using GARCH-type models, with the aim of examining the sensitivity of Turkey's tourism demand to financial market shocks. It is widely accepted in the literature that the tourism sector exhibits high sensitivity to economic and financial fluctuations; in this context, the study reveals the directional link between financial volatility and tourism demand, taking into account the unique dynamics of Turkish markets. Empirical findings show that increased volatility in financial markets leads to significant fluctuations in tourism demand and that shocks in the exchange rate and CDS premiums, in particular, have a strong impact on tourism demand. These results highlight the necessity of effectively monitoring financial risks for both supply and demand-side economic actors and reaffirm the tourism sector's structural vulnerability to financial fragilities. The findings of this study are generally consistent with existing studies in the literature. However, it offers a unique methodological contribution to the literature by simultaneously assessing the simultaneous and lagged effects of financial shocks on tourism demand through dynamic interconnectivity analyses. Based on the results obtained, strategic recommendations are presented to policymakers regarding the strengthening of macroprudential measures aimed at reducing the financial fragility of the tourism sector and diversifying tourism revenues.

Keywords

• Tourism demand
• financial volatility
• exchange rate shocks
• GARCH models
• Turkish economy.

References

1. Agiomirgianakis, G., Serenis, D., & Nicholas Tsounis, N. (2014). Effects of exchange rate volatility on tourist flows into ıceland. Procedia Economics and Finance, 24, 25-34. https://doi.org/10.1016/S2212-5671(15)00608-5.
2. Akdağ, S., Kiliç, İ., & Yildirim, H. (2019). Does VIX scare stocks of tourism companies? Letters in Spatial and Resource Sciences, 12(3), 215–232. https://doi.org/10.1007/s12076-019-00238-w
3. Antonakakis, N., & Gabauer, D. (2017). Refined measures of dynamic connectedness based on TVP-VAR. Journal of Risk and Financial Management, 10(2), 1–21. https://doi.org/10.3390/jrfm10020010
4. Aizenman, J., Hutchison, M., & Jinjarak, Y. (2013). What is the risk of European sovereign debt defaults? Journal of International Money and Finance, 34, 37–59.
5. Arslan, E., & Çetiner, T. (2020). Turizm geliri döviz kuru ilişkisi: Türkiye örneği (2008–2019). Ankara Hacı Bayram Veli Üniversitesi Turizm Fakültesi Dergisi, 23(1), 1–17. https://doi.org/10.34189/tfd.23.01.001
6. Balli, F., Balli, H. O., & Lou, W. (2019). Modelling the volatility of international tourist arrivals. Tourism Economics, 25(1), 5–27. https://doi.org/10.1177/1354816618778466
7. Banerjee, A., & Duflo, E. (2019). Good economics for hard times. PublicAffairs.
8. Bekaert, G., Hoerova, M., & 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

9. Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3), 623–685. https://doi.org/10.3982/ECTA6248
10. Büyük, Ö., & Can, E. (2020). COVID-19 salgınının Türk turizmine etkisi: Seyahat ve konaklama endüstrileri üzerine değerlendirme. Ankara Hacı Bayram Veli Üniversitesi Turizm Fakültesi Dergisi, 23(2), 312–331. https://doi.org/ 10.34189/tfd.23.02.005
11. Caporale, G. M., & Gil-Alana, L. A. (2020). Persistence in the tourist sector: Evidence from long-memory modeling. Applied Economics Letters, 27(4), 332–337. https://doi.org/10.1080/13504851.2019.1616057
12. Caporale, Guglielmo Maria and Gil-Alana, Luis A., Persistence and Long Memory in Monetary Policy Spreads (2020). CESifo Working Paper, 8664, 1-27. http://dx.doi.org/10.2139/ssrn.3727738
13. Chan, F., Lim, C., & McAleer, M. (2005). Modelling multivariate international tourism demand and volatility. Tourism Management, 26(3), 459–471. https://doi.org/10.1016/j.tourman.2004.02.013
14. Chang, C.-L., Hsu, H.-K., & McAleer, M. (2014). The impact of China on stock returns and volatility in the Taiwan tourism industry. North American Journal of Economics and Finance, 29, 381–401. https://doi.org/10.1016/j.najef.2014.06.007
15. Chang, C.-L., McAleer, M., & Ramos, V. (2020). A Charter for Sustainable Tourism after COVID-19. Sustainability, 12(9), 3671. https://doi.org/10.3390/su12093671
16. Chatziantoniou, I., Duffy, D., & Filis, G. (2019). Stock market response to monetary and fiscal policy shocks: Multi-country evidence. Economic Modelling, 81, 1–14. https://doi.org/10.1016/j.econmod.2018.12.020
17. Chen, H., Yang, S., & Yang, L. (2021). Exchange rate volatility and inbound tourism demand: Evidence from China. Journal of Travel Research, 60(4), 846–864. https://doi.org/10.1177/0047287519899987
18. Chen, M.-H. (2007). Interactions between business conditions and financial performance of tourism firms: Evidence from Taiwan. Tourism Management, 28(1), 188–203. https://doi.org/10.1016/j.tourman.2005.11.012
19. Crouch, G. I. (1994). The study of international tourism demand: A review of findings. Journal of Travel Research, 33(1), 12–23.
20. Crouch, G. I. (1995). A meta-analysis of tourism demand. Annals of Tourism Research, 22(1), 103–118.
21. Çeti, B., & Ünlüönen, K. (2019). Salgın hastalıklar sebebiyle oluşan krizlerin turizm sektörü üzerindeki etkisinin değerlendirilmesi. Ankara Hacı Bayram Veli Üniversitesi Turizm Fakültesi Dergisi, 22(2), 109–128. https://doi.org/10.34189/tfd.22.2.001
22. Demir, E., & Gozgor, G. (2018). Does economic policy uncertainty affect tourism flows? Annals of Tourism Research, 69, 15–17. https://doi.org/10.1016/j.annals.2017.12.005
23. Diebold, F. X., & 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
24. Dogru, T., & Bulut, U. (2018). Is tourism an engine for economic recovery? Journal of Travel Research, 57(10), 1201–1217. https://doi.org/10.1016/j.tourman.2017.06.014
25. Dragouni, M., Filis, G., Gavriilidis, K., & Santamaria, D. (2016). Sentiment, mood and outbound tourism demand. Annals of Tourism Research, 60, 80–96. https://doi.org/10.1016/j.annals.2016.06.004
26. Gupta R, Subramaniam S, Bouri E, Ji Q.(2021). Infectious disease-related uncertainty and the safe-haven characteristic of US treasury securities. International Review of Economics & Finance, 71, 289–98. https://doi: 10.1016/j.iref.2020.09.019.
27. Gürsoy, D., & Diker, O. (2020). Finansal göstergeler ile turizm sektörü performansı arasındaki ilişki. Ankara Hacı Bayram Veli Üniversitesi Turizm Fakültesi Dergisi, 23(2), 345–362.
28. Imamboccus, R., Seetanah, B., Jaffur, Z.K. & Nunkoo, R. (2024). The exchange rate; its volatility and tourism demand. An International Journal of Tourism and Hospitality Research, 1-14. https://doi.org/10.1080/13032917.2024.2303639
29. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.
30. Kızılırmak, İ., & Acar, Y. (2021). Döviz kuru oynaklığı ve turizm talebi ilişkisi: Türkiye örneği. Ankara Hacı Bayram Veli Üniversitesi Turizm Fakültesi Dergisi, 24(1), 85–104.
31. Lee, J. W., & Brahmasrene, T. (2013 Investigating the influence of tourism on economic growth and carbon emissions: Evidence from panel analysis of the European Union. Tourism Management, 38, 36-76. https://doi.org/10.1016/j.tourman.2013.02.016
32. Lim, C. (1997). Review of international tourism demand models. Annals of Tourism Research, 24(4), 835–849. https://doi.org/10.1016/S0160-7383(97)00049-2
33. Lim, C. and McAleer, M. (2001) Forecasting tourist arrivals. Annals of Tourism Research, 28, 965-977. http://dx.doi.org/10.1016/S0160-7383(01)00006-8
34. Narayan, P. K., Devpura, N. & Wang, H. (2020). Japanese currency and stock market—What happened during the COVID-19 pandemic? Economic Analysis and Policy, 68, 191-198. https://doi.org/10.1016/j.eap.2020.09.014
35. Parray WA, Soudager MA, Dada ZA, Yasmin E, Darzi TA (2024), "Impact of geopolitical risk on tourism demand: evidence from asymmetric NARDL approach". Journal of Hospitality and Tourism Insights, 7(5), 2546–2559. https://doi.org/10.1108/JHTI-06-2022-0248
36. Peng, B., Song, H., & Crouch, G. I. (2015). A meta-analysis of international tourism demand elasticities. Journal of Travel Research, 54(5), 611–633. https://doi.org/10.1177/0047287514528283
37. Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72(3), 821–852. https://doi.org/10.1111/j.1467-937X.2005.00353.x
38. Rookayyah, I., Kasseeah, H., & Gopaul, A. (2024). The impact of exchange rate and exchange rate volatility on tourism demand. International Journal of Tourism Research. https://doi.org/10.1002/jtr.2640
39. Santana-Gallego, M. Ledesma-Rodríguez, F.& J, Pérez-Rodríguez J. V. (2016) International trade and tourism flows an extension of the gravity model. Economic Modelling, 52,1026–1033 https://doi.org/10.1016/j.econmod.2015.10.043
40. Saayman, A., & Saayman, M. (2013). Exchange rate volatility and tourism – revisiting the nature of the relationship. European Journal of Tourism Research, 6(2), 104–121.
41. Sharma, C., & Pal, D. (2020). Exchange rate volatility and tourism demand in India: Unraveling the asymmetric relationship. Journal of Travel Research, 59(7), 1282–1297. https://doi.org/10.1177/0047287519878516
42. Song, H., & Li, G. (2008). Tourism demand modelling and forecasting—A review of recent research. Tourism Management, 29(2), 203–220. https://doi.org/10.1016/j.tourman.2007.07.016
43. Song, H., Qiu, R. T. R., & Park, J. (2019). A review of research on tourism demand forecasting: Launching the Annals of Tourism Research curated collection on tourism demand forecasting. Annals of Tourism Research, 75, 338–362. https://doi.org/10.1016/j.annals.2018.12.001
44. Şahin, S., & Yılmaz, Ö. (2019). Finansal belirsizlik ve turizm gelirleri arasındaki ilişki. Ankara Hacı Bayram Veli Üniversitesi Turizm Fakültesi Dergisi, 22(1), 45–62.
45. UNWTO. (2023). World Tourism Barometer. United Nations World Tourism Organization.
46. Webber, A. G. (2001). Exchange rate volatility and cointegration in tourism demand. Journal of Travel Research, 39(4), 398–405. https://doi.org/10.1177/004728750103900406
47. Zhang, H., Jiang, Z., Gao, W., & Yang, C. (2022). Time-varying impact of economic policy uncertainty and geopolitical risk on tourist arrivals: Evidence from a developing country. Tourism Management Perspectives, 41, 100928. https://doi.org/10.1016/j.tmp.2021.100928