Hierarchical Flow Among Four Shipping Markets: An Integrated Approach for Capesize Shipping Markets

Year 2021, Volume: 10 Issue: 1, 85 - 98, 31.03.2021

Abdullah Açık

https://doi.org/10.33714/masteb.779124

Abstract

Although there are theoretical researches on the interactions between four shipping sub-markets, empirical studies examining four to cover are rare. Also, market interactions may differ in positive or negative environments. Accordingly, the purpose of this study is to examine the hierarchical structure among the 4 sub-maritime markets by providing a methodological proposition. This study integrates the Interpretive Structural Modelling (ISM) method with the asymmetric causality analysis and examines the hierarchical structure between the four markets in terms of positive and negative shocks through the Capesize markets. The dataset used in the study covers the period between 07.01.2013 - 18.07.2019 and consists of 342 weekly observations. The results show that the hierarchical flow of positive and negative shocks differs in the Capesize market. In terms of positive shocks, the demolition market stands out as the starting point of the shocks, while in terms of negative shocks, freight and new building markets come to the fore. Our study reveals hierarchical structures for maritime markets by testing their relationships empirically and contributes to the maritime literature where the freight market is theoretically considered a pioneer. A new methodical perspective is thought to be presented to the maritime economics literature.

Keywords

Demolition market, Freight market, Hierarchical structure, Newbuilding market, Secondhand market

References

• Açık, A. & Baran, E. (2019). The reflection of ship demolition prices to construction costs in Turkey. Marine Science and Technology Bulletin, 8(1): 23-29. https://doi.org/10.33714/masteb.547103
• Açık, A. & Başer, S. Ö. (2018). The relationship between freight rates and demolition prices. Uluslararası Ticaret ve Ekonomi Araştırmaları Dergisi, 2(1): 16-32. https://doi.org/10.30784/epfad.363721
• Açık, A. & Başer, S. Ö. (2017). The relationship between freight revenues and vessel disposal decisions. Journal of Research in Economics, Politics & Finance, 2(2): 96-112. https://doi.org/10.30784/epfad.363721
• Açık, A. & İnce, M. R. (2019). Income and asset value relationship: A nonlinear approach to Capesize shipping market (pp. 35-43). In Koc, S., Yilmaz Genc, S., Benli, V.H. (Eds.), Economic Issues: Global and Local Perspectives. London: Cambridge International Academics. 196p.
• Adland, R. & Jia, H. (2015). Shipping market integration: The case of sticky new building prices. Maritime Economics & Logistics, 17(4): 389-398. https://doi.org/10.1057/ mel.2014.35
• Alizadeh, A. H. & Nomikos, N. K. (2003). The price-volume relationship in the sale and purchase market for dry bulk vessels. Maritime Policy & Management, 30(4): 321-337. https://doi.org/10.1080/0308883032000145627
• Alizadeh, A. & Nomikos, N. (2009). Shipping Derivatives and Risk Management. London: Palgrave. 527p.
• Athenian, S. A. (2019). Weekly demolition report. Retrieved on August 5, 2019 from https://www.atheniansa.gr.
• Başer, S. Ö. & Açık, A. (2019). The effects of global economic growth on dry bulk freight rates. Uluslararası Ticaret ve Ekonomi Araştırmaları Dergisi, 3(1): 1-17. https://doi.org/10.30711/utead.507566
• Başer, S. Ö. & Açık, A. (2018). The response of shipbuilding activities to freight market. International Journal of Economics and Administrative Sciences, 4(1): 120-136. https://doi.org/10.29131/uiibd.415303
• Beenstock, M. & Vergottis, A. (1993). Econometric Modelling of World Shipping. Netherlands: Springer. 254p.
• Beenstock, M. & Vergottis, A. (1989). An econometric model of the world market for dry cargo freight and shipping. Applied Economics, 21(3): 339-356. https://doi.org/ 10.1080/758522551
• Bildirici, M. E. & Turkmen, C. (2015). Nonlinear causality between oil and precious metals. Resources Policy, 46(2): 202-211. https://doi.org/10.1016/j.resourpol.2015.09. 002
• Bloomberg (2019). Freight, Second hand, Newbuilding Values Retrieved on August 7 from https://www.bloomberg.com/professional
• Branch, A. E. (2007). Elements of Shipping (8th ed.) New York: Routledge. 528p.
• Brock, W., Dechect, W. & Scheinkman, J. (1987). A test for independence based on the correlation dimension. Working Paper, Department of Economics, University of Wisconsin, Madison.
• Buxton, I. L. (1991). The market for ship demolition. Maritime Policy & Management, 18(2): 105–112. https://doi.org/ 10.1080/03088839100000034
• Chuang, H-M., Lin, C-K., Chen, D-R. & Chen, Y. S. (2013). Evolving MCDM applications using hybrid expert-based ISM and DEMATEL models: An example of sustainable ecotourism. The Scientific World Journal, 2013: 1-18. https://doi.org/10.1155/2013/751728
• Dai, L., Hu, H., Chen, F. & Zheng, J. (2015). The dynamics between new building ship price volatility and freight volatility in dry bulk shipping market. International Journal of Shipping and Transport Logistics, 7(4): 393-406. https://doi.org/10.1504/IJSTL.2015.069666
• 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. https://doi.org/10.31217/ p.33.1.5
• Engle, R. (1982). ARCH with estimates of variance of United Kingdom inflation. Econometrica, 50(4): 987-1007. https://doi.org/10.2307/1912773
• Geman, H. (2009). Risk Management in Commodity Markets: From Shipping to Agriculturals and Energy (Vol. 445), England: John Wiley & Sons. 320p.
• Hatemi-J, A. (2012). Asymmetric causality tests with an application. Empirical Economics, 43(1): 447-456. https://doi.org/10.1007/s00181-011-0484-x
• 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. https://doi.org/10.1016/j.ecosys.2011.10.005
• Jugović, A., Komadina, N. & Hadžić, A. (2015). Factors influencing the formation of freight rates on maritime shipping markets. Scientific Journal of Maritime Research, 29: 23–29.
• Kagkarakis, N. D., Merikas, A. G. & Merika, A. (2016). Modelling and forecasting the demolition market in shipping. Maritime Policy & Management, 43(8): 1021-1035. https://doi.org/10.1080/03088839.2016.1185181
• Karakitsos, E. & Varnavides, L. (2014). Maritime Economics: A Macroeconomic Approach. London: Springer. 386p.
• Kavussanos, M. G. (1997). The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector. Applied Economics, 29(4): 433-443. https://doi.org/10.1080/000368497326930
• Kavussanos, M. G. & Alizadeh, A. H. (2002). Efficient pricing of ships in the dry bulk sector of the shipping industry. Maritime Policy & Management, 29(3): 303-330. https://doi.org/10.1080/03088830210132588
• Knapp, S., Kumar, S. N. & Remijn, A. B. (2008). Econometric analysis of the ship demolition market. Maritime Policy & Management, 32(6): 1023-1036. https://doi.org/ 10.1080/03088839.2016.1185181
• Koopmans, T. C. (1939). Tanker Freight Rates and Tankship Building: An Analysis of Cyclical Fluctuations. Holland: Haarlem.
• Langdana, F. K. (2009). Macroeconomic Policy: Demystifying Monetary and Fiscal Policy (2nd Ed.). US: Springer. 279p.
• Lawson, M. (2008). If Not Now, When? Three Actions the G20 Must Take Now to Protect the Word’s Poor from The Economic Crisis and Build a New Political and Economic Governance System. London: Oxfam.
• Lee, J. & Strazicich, M. C. (2003). Minimum Lagrange Multiplier unit root test with two structural breaks. Review of Economics and Statistics, 85(4): 1082-1089. https://doi.org/10.1162/003465303772815961
• Lee, J. & Strazicich, M. C. (2013). Minimum LM unit root test with one structural break. Economics Bulletin, 33(4): 2483-2492.
• Lun, Y. V., Lai, K. H. & Cheng, T. E. (2010). Shipping and Logistics Management. London: Springer. 231p.
• Luthra, S., Garg, D. & Haleem, A. (2015). An analysis of interactions among critical success factors to implement green supply chain management towards sustainability: An Indian perspective. Resources Policy, 46(1): 37-50. https://doi.org/10.1016/j.resourpol.2014.12.006
• McConville J. (1999). Economics of Maritime Transport, Theory and Practice. London: Whiterby. 394p.
• Metaxas, V. (1988). Principles of Maritime Economics. Athens: Papazisis.
• Mikelis, N. E. (2007). A statistical overview of ship recycling. Proceedings of the International Symposium on Maritime Safety, Security & Environmental Protection, Athens, Greece.
• Narayan, P. K. & Popp, S. (2010). A new unit root test with two structural breaks in level and slope at unknown time. Journal of Applied Statistics, 37: 1425-1438. https://doi.org/10.1080/02664760903039883
• Pruyn, J. F. J., Van de Voorde, E., & Meersman, H. (2011). Second hand vessel value estimation in maritime economics: A review of the past 20 years and the proposal of an elementary method. Maritime Economics & Logistics, 13(2): 213-236. https://doi.org/10.1057/ mel.2011.6
• Sage, A. P. (1977). Interpretive Structural Modeling: Methodology for Large-scale Systems. New York: McGraw-Hill. 445p.
• Şahin, B., Gürgen, S., Ünver, B. & Altin, I., (2018). Forecasting Baltic Dry Index by using an artificial neural network approach. Turkish Journal of Electrical Engineering & Computer Sciences, 26(3): 1673-1684. https://doi.org/ 10.3906/elk-1706-155
• 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. https://doi.org/10.1016/j.eneco.2017.01. 023
• Stopford, M. (2009). Maritime Economics (3rd ed.). New York: Routledge. 815p.
• Strandenes, S. P. (2012). Maritime freight markets (pp. 107-120). In Walley, T.K. (Ed.), The Blackwell Companion to Maritime Economics. UK: Wiley-Blackwell. 735p.
• Tarı, R. and İnce, M. R. (2019). Analysis of global trade volume within the scope of maritime transport market: Markov regime switching model. Kocaeli Üniversitesi Sosyal Bilimler Dergisi, 37: 1-20. https://doi.org/10.35343/ kosbed.581404
• Toda, H. Y. & Yamamoto, T. (1995). Statistical inference in Vector Autoregressions with Possibly Integrated Processes. Journal of Econometrics, 66: 225–250. https://doi.org/10.1016/0304-4076(94)01616-8
• Tsolakis, S. (2005). Econometric analysis of bulk shipping markets: Implications for investment strategies and financial decision-making. Ph.D. Thesis. Erasmus University, Rotterdam.
• Tugcu, C. T. & Topcu, M. (2018). Total, renewable and non-renewable energy consumption and economic growth: revisiting the issue with an asymmetric point of view. Energy, 152: 64–74. https://doi.org/10.1016/j.energy. 2018.03.128
• Tugcu, C. T., Ozturk, I. & Aslan, A. (2012). Renewable and non-renewable energy consumption and economic growth relationship revisited: evidence from G7 countries. Energy Economics, 34(6): 1942–1950. https://doi.org/ 10.1016/j.eneco.2012.08.021
• Tunç, M. & Açık, A. (2019). The impact of steel price on ship demolition prices: Evidence from heterogeneous panel of developing countries. Sosyoekonomi, 27(42): 227-240. https://doi.org/10.17233/sosyoekonomi.2019.04.12
• Tvedt, J. (2003). A new perspective on price dynamics of the dry bulk market. Maritime Policy & Management, 30(3): 221-230. https://doi.org/10.1080/0308883032000133413
• 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.
• UN. (2009). United Nations. World Economic Situation and Prospects 2009 (World Economic and Social Survey. Supplement). New York. 33p.
• Yudatama, U., Hidayanto, A. N. & Nazief, B. A. A. (2018). Approach using interpretive structural model (ISM) to determine key sub-factors at factors: Benefits, risk reductions, opportunities and obstacles in awareness IT Governance. Journal of Theoretical and Applied Information Technology, 96(16): 5537-5549.
• Zivot, E. & Andrews, D. W. K. (1992). Further evidence on the Great Crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 20(1): 25-44. https://doi.org/10.1080/07350015.1992. 10509904