Küresel Konteyner Navlun Endekslerinden Türkiye’deki Limanların Çıktısına Oynaklık Yayılımı

Öz

Bu çalışmanın amacı konteyner navlun endeksleriyle Türk limanlarında elleçlenen konteyner hacmi arasındaki ilişkiyi tespit etmektir. Küresel konteyner navlun endekslerinden olan Şangay Konteynırlaşmış Navlun Endeksi (SCFI) ve Çin Konteynırlaşmış Navlun Endeksi (CCFI) değişkenlerinden Türk limanlarında elleçlenen konteyner hacmine olan oynaklık yayılımını tespit etmeyi sağlayan varyansta nedensellik analizi kullanılmıştır. Çalışmada kullanılan veri seti Kasım 2010 ve Temmuz 2018 tarihleri arasını kapsayan aylık bazda 93 gözlemden oluşmaktadır. Elde edilen sonuçlara göre sadece CCFI endeksinden konteyner hacmine anlamlı bir oynaklık yayılımı tespit edilmiştir. Ayrıca, Türk limanlarındaki konteyner hacminin Çin navlun endeksindeki pozitif şoklara negatif tepki verdiği belirlenmiştir. Bu sonuçların liman işletmecilerine bir öncü gösterge sağlayarak politika geliştirme süreçlerinde yardımcı olacağı umulmaktadır.

Anahtar Kelimeler

• Türk limanları,Konteyner navlun endeksleri,Taşıma maliyetleri,Varyansta nedensellik

Volatility Spillover from Global Container Freight Indices to Port Throughputs in Turkey

Abstract

The purpose of this study is to determine the relationship between the container freight rates and the volume of container handled at Turkish ports. To do this, causality in variance analysis is used which enables to determine the volatility spillover from global container freight indices, which are Shanghai Containerized Freight Index (SCFI) and China Containerized Freight Index (CCFI), to container volume handled in Turkish ports. The data set used in the study consists of 93 observations on a monthly basis covering the dates between November 2010 and July 2018. According to the results obtained, a significant volatility spillover has been only detected from the CCFI variable to the container volume. In addition, it has been found that the container volume in Turkish ports has reacted negatively to a positive shock in China container freight index. It is hoped that these results will help the port operators in the policy development stages by providing a leading indicator.

Keywords

• Turkish ports,Container freight indices,Transport costs,Causality in variance

References

1. Akar, O. and Esmer, S. (2015). Cargo Demand Analysis of Container Terminals in Turkey. Journal of ETA Maritime Science, 3(2), 117-122.
2. Akgül, E. F., Fişkin, C. S., Düzalan, B., Erdoğan, T. and Çetin, Ç. K. (2015). Liman Rekabetçiliği ve Etkinlik: Türkiye’deki Konteyner Limanlari Üzerine Bir Analiz. 2. Ulusal Liman Kongresi, İzmir.
3. Akyürek, E. (2017). Türkiye Karadeniz Limanlari Verimlilik Analizi. Verimlilik Dergisi, 4, 29-45.
4. Ateş, A. and Esmer, S. (2014). Farklı Yöntemler ile Türk Konteyner Limanlarının Verimliliği. Verimlilik Dergisi, 1, 61–76.
5. Ateş, A., Esmer, S., Çakir, E. and Balci, K. (2013). Karadeniz Konteyner Terminallerinin Göreceli Etkinlik Analizi. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 5 (1), 1-22.
6. Behar, A. and Venables, A. J. (2011). Transport Costs and International Trade. Handbook of Transport Economics, 97-115.
7. Bloomberg (2018). Container Freight Indices, https://www.bloomberg.com/professional/, (Accessed: 20.08.2018)
8. Branch, A. E. (2012). Economics of Shipping Practice and Management. Springer Science & Business Media.

9. Chang, C. L. and McAleer, M. (2017). A Simple Test for Causality in Volatility. Econometrics, 5(1), 15.
10. Cheung, Y. W. and Ng, L. K. (1996). A Causality-in-Variance Test and Its Application to Financial Market Prices. Journal of Econometrics, 72(1-2), 33-48.
11. Chi, J. and Cheng, S. K., (2016). Do Exchange Rate Volatility and Income Affect Australia’s Maritime Export Flows to Asia?. Transport Policy, 47, 13-21.
12. Crucial Perspective (2018). https://crucialperspective.com, (Accessed: 26.09.2018)
13. Demirci, Y and Tarhan, D . (2016). Türkiye’de Faaliyet Gösteren Liman İşletmeleri Ve Bu İşletmelerin Etkinliklerinin Veri Zarflama Analizi Yöntemiyle Ölçümü. Uluslararası İktisadi ve İdari Bilimler Dergisi, 2(2), 144-160.
14. Dickey, D. A. and Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with A Unit Root. Journal of the American Statistical Association, 74, 427–431.
15. Flex Port (2018). www.flexport.com, (Accessed: 26.09.2018)
16. Güner, S. (2015a). Investigating Infrastructure, Superstructure, Operating and Financial Efficiency in The Management of Turkish Seaports Using Data Envelopment Analysis. Transport Policy, 40, 36-48.
17. Güner, S. (2015b). Proposal of a Two-Stage Model for Measuring the Port Efficiency and an Implication on Turkish ports. Alphanumeric Journal, 3(2), 99-106.
18. Hu, J. W. S., Chen, M. Y., Fok, R. C. and Huang, B. N. (1997). Causality in Volatility and Volatility Spillover Effects between US, Japan and Four Equity Markets in the South China Growth Triangular. Journal of International Financial Markets, Institutions and Money, 7(4), 351-367.
19. Karamperidis, S., Jackson, E. and Mangan, J. (2013). The Use of Indices in the Maritime Transport Sector. Maritime Policy & Management, 40(4), 339-350.
20. Kim, C. B., (2016). Impact of Exchange Rate Movements, Global Economic Activity, and the BDI Volatility On Loaded Port Cargo Throughput in South Korea. The Asian Journal of Shipping and Logistics, 32(4), 243-248.
21. Kim, C. B., (2017) Does Exchange Rate Volatility Affect Korea's Seaborne Import Volume?. The Asian Journal of Shipping and Logistics, 33(1), 43-50.
22. Korinek, J. and Sourdin, P. (2009). Maritime Transport Costs and Their Impact on Trade. Organization for Economic Co-operation and Development TAD/TC/WP. 7, 1-24.
23. Korkmaz, O. (2012). Türkiye'de Gemi Tasimaciliginin Bazi Ekonomik Göstergelere Etkisi. Business and Economics Research Journal, 3(2), 97-109.
24. Koseoglu, S. D. and Cevik, E. I. (2013). Testing for Causality in Mean and Variance Between the Stock Market and The Foreign Exchange Market: An Application to the Major Central and Eastern European Countries. Finance a Uver, 63(1), 65.
25. Kwiatkowski, D., Phillips, P.C.B., Schmidt, P. and Shin, Y. (1992). Testing the Null Hypothesis of Stationarity Against the Alternative of A Unit Root. Journal of Econometrics, 54, 159-178.
26. Nazlioglu, S., Erdem, C. and Soytas, U. (2013). Volatility Spillover Between Oil and Agricultural Commodity Markets. Energy Economics, 36, 658-665.
27. Nouira R, Amor T. H., and Rault C, (2018). Oil Price Fluctuations and Exchange Rate Dynamics in the MENA Region: Evidence from Non-Causality-in-Variance and Asymmetric Non-Causality Tests. Quarterly Review of Economics and Finance, 1-23.
28. Papież, M. and Śmiech, S. (2013). Causality-in-Mean and Causality-in-Variance Within the International Steam Coal Market. Energy Economics, 36, 594-604.
29. Phillips, P.C.B. and Perron, P. (1988). Testing for Unit Root in Time Series Regression. Biometrica, 75, 335-346.
30. Sağlam, B. B., Açık, A., and Ertürk, E. (2018). Evaluation of Investment Impact on Port Efficiency: Berthing Time Difference as a Performance Indicator. Journal of ETA Maritime Science, 6(1), 37-46.
31. Shanghai Shipping Exchange (2018a). http://en.sse.net.cn/brief/function0303.jsp, (Accessed: 26.09.2018).
32. Shanghai Shipping Exchange (2018b) http://en.sse.net.cn/indices/introduction_ccfi_new.jsp, (Accessed: 26.09.2018).
33. Shanghai Shipping Exchange (2018c) https://en.sse.net.cn, (Accessed: 26.09.2018).
34. Stopford, M. (2009). Maritime Economics, London: Routledge.
35. UDHB (2018). Container Statistics, https://atlantis.udhb.gov.tr/istatistik/istatistik_arsiv.aspx, (Accessed: 20.10.2018).