Acta Nat. Sci.   |  e-ISSN: 2718-0638

Original article | Acta Natura et Scientia 2022, Vol. 3(1) 15-23

Asymmetric Reflection of Shocks in Baltic Dry Index to Istanbul Freight Index

Ayhan Salar

pp. 15 - 23   |  DOI:   |  Manu. Number: MANU-2111-22-0006.R1

Published online: January 17, 2022  |   Number of Views: 92  |  Number of Download: 557


Since the maritime freight markets have inelastic supply structures in the short run, freight is considered an indicator of trade volume. Freight rates can rise rapidly when fleet utilization is high, as supply, which does not increase in the short run due to time of ship building, cannot respond to increases in demand. In this sense, the relationships between the relevant freight indices can be examined in order to determine the regional reflections of global commercial developments. The aim of this study is to examine the effects of the shocks in Baltic Dry Index (BDI), which is an indicator of dry bulk trade in the global sense and considered as a leading indicator of the world economy by many researchers, on Istanbul Freight Index (ISTFIX), which is an indicator of trade in the Mediterranean and Aegean in the regional sense. The dataset covers the period between 31.12.2007 and 19.02.2018, and consists of 524 weekly observations. Asymmetric causality test is used in order to reveal relationship between variables. According to the findings, a significant causality relationship was determined only from negative shocks in BDI to negative shocks in ISTFIX. This situation shows that the contraction in global trade is immediately reflected in the ISTFIX region, while the expansion in trade is not immediately reflected.

Keywords: Asymmetric Causality, Shocks, Baltic Dry Index, Istanbul Freight Index

How to Cite this Article?

APA 6th edition
Salar, A. (2022). Asymmetric Reflection of Shocks in Baltic Dry Index to Istanbul Freight Index . Acta Natura et Scientia, 3(1), 15-23. doi: 10.29329/actanatsci.2022.351.02

Salar, A. (2022). Asymmetric Reflection of Shocks in Baltic Dry Index to Istanbul Freight Index . Acta Natura et Scientia, 3(1), pp. 15-23.

Chicago 16th edition
Salar, Ayhan (2022). "Asymmetric Reflection of Shocks in Baltic Dry Index to Istanbul Freight Index ". Acta Natura et Scientia 3 (1):15-23. doi:10.29329/actanatsci.2022.351.02.

  1. Açık, A. Başer, S. Ö., & Ertürk, E. (2018). What triggers the ISTFIX bubbles? International Journal of Economics and Innovation, 4(2), 119-135. [Google Scholar] [Crossref] 
  2. Açık, A., & Başer, S. Ö. (2020). Asymmetric causality from commodity prices to shipping markets: An empirical research on ISTFIX region. World Review of Intermodal Transportation Research, 9(1), 47-62. [Google Scholar] [Crossref] 
  3. Başer, Ö. S., & Açık, A. (2018). Stock market as an indicator of maritime transport demand: An evidence from Turkey and ISTFIX region. Journal of Kastamonu University Faculty of Economics and Administrative Sciences, 20(4), 7-22. [Google Scholar]
  4. Bildirici, M. E., & Turkmen, C. (2015). Nonlinear causality between oil and precious metals. Resources Policy, 46(2), 202-211. [Google Scholar] [Crossref] 
  5. Bloomberg. (2018). Baltic Dry Index. Retrieved on August 8, 2018, from [Google Scholar]
  6. Branch, A. E., & Robarts, M. (2014). Branch's elements of shipping. Routledge. [Google Scholar]
  7. Buxton, I. L. (1991). The market for ship demolition. Maritime Policy & Management, 18(2), 105-112. [Google Scholar] [Crossref] 
  8. Chevallier, J., & Ielpo, F. (2013). The economics of commodity markets. John Wiley & Sons. [Google Scholar]
  9. Dickey, D. A., & Fuller, W. A. (1979) Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431. [Google Scholar] [Crossref] 
  10. Efes, K. Ö., Başer, S. Ö., & Açık, A. (2019). Supply-demand interaction in the formation of freight rates: China’s trade volume as demand side in the dry bulk market. Pomorstvo, 33(1), 46-55. [Google Scholar] [Crossref] 
  11. Geman, H. (Ed.). (2009). Risk management in commodity markets: from shipping to agriculturals and energy (Vol. 445). John Wiley & Sons. [Google Scholar]
  12. Hatemi-J, A. (2012). Asymmetric causality tests with an application. Empirical Economics, 43(1), 447-456. [Google Scholar] [Crossref] 
  13. Hatemi-J, A., & Uddin, G. S. (2012). Is the causal nexus of energy utilization and economic growth asymmetric in the US? Economic Systems, 36(3), 461-469. [Google Scholar] [Crossref] 
  14. ISTFIX. (2018). Istanbul Freight Index. Retrieved on March 10, 2018, from [Google Scholar]
  15. Kavussanos, M., Visvikis, I., & Dimitrakopoulos, D. (2010). Information linkages between panamax freight derivatives and commodity derivatives markets. Maritime Economics and Logistics, 12(1), 91-110. [Google Scholar] [Crossref] 
  16. Korinek, J., & Sourdin, P. (2010). Clarifying trade costs: Maritime transport and its effect on agricultural trade. Applied Economic Perspectives and Policy, 32(10), 417-435. [Google Scholar] [Crossref] 
  17. Köseoğlu, S. D., & Mercangöz, B. A. (2012). 2008 küresel finansal krizinin küçük tonaj gelirleri üzerindeki etkisinin yapısal kırılma testi ile araştırılması [Analysing 2008 global financial crisis effect on coaster tonnage revenues by structural break test]. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 4(1), 25-38. [Google Scholar]
  18. Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54, 159–178. [Google Scholar] [Crossref] 
  19. Langdana, F. K. (2009). Macroeconomic policy: Demystifying monetary and fiscal policy (2nd Ed.), Springer. [Google Scholar]
  20. Lawson, M. (2008). If not now, when? Three actions the G20 must take now to protect the world’s poor from the economic crisis and build a new political and economic governance system. Oxfam. [Google Scholar]
  21. Metaxas, V. (1988). Principles of maritime economics. Papazisis. [Google Scholar]
  22. Radetzki, M. (2008). A handbook of primary commodities in the global economy. Cambridge University Press. [Google Scholar]
  23. Randers, J., & Göluke, U. (2007). Forecasting turning points in shipping freight rates: lessons from 30 years of practical effort. System Dynamics Review, 23(2-3), 253-284. [Google Scholar] [Crossref] 
  24. Shahbaz, M., van Hoang, T. H., Mahalik, M. K., & Roubaud, D. (2017). Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis. Energy Economics, 63, 199-212. 023 [Google Scholar] [Crossref] 
  25. Stopford, M. (2009). Maritime Economics, 3rd ed. Routledge. [Google Scholar]
  26. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in Vector Autoregressions with Possibly Integrated Processes. Journal of Econometrics, 66, 225-250. [Google Scholar] [Crossref] 
  27. Umar, M., & Dahalan, J. (2016). An application of asymmetric Toda-Yamamoto causality on exchange rate-inflation differentials in emerging economies. International Journal of Economics and Financial Issues, 6(2), 420-426. [Google Scholar]
  28. Ünal, G., & Derindere Köseoğlu, S. (2014). Revealing the freight market risk in ISTFIX shipping area. International Journal of Shipping and Transport Logistics, 6(6), 593–610. [Google Scholar] [Crossref] 
  29. Zeren, F., & Kahramaner, H. (2019). Baltık kuru yük endeksi ile istanbul navlun endeksi arasındaki etkileşimin incelenmesi: ekonometrik bir uygulama [The investigation of interaction between Baltic dry index and Istanbul freight index: An econometric application]. Journal of International Management Educational and Economics Perspectives, 7(1), 68-79. [Google Scholar]