Freight Rate as A Determinant Factor of Ship Recycling Volume
Abstract views: 208
/ 
PDF downloads: 93
Keywords:
Baltic Dry Index, Causality, Ship Demolition, Dry Bulk ShippingAbstract
The ship recycling sector is important for both the maritime market and the steel market. Therefore, understanding its dynamics contributes to many sector stakeholders. In our study, we preferred Baltic Dry Index (BDI), and Recycled Bulker Tonnage (RBT) variables to examine the relationship between freight rate and recycled tonnage in the dry bulk market. Our data consists of 153 observations covering the period from the first quarter of 1985 to the first quarter of 2023. Applied Granger causality analysis showed that changes in freight affect the tonnage sent for recycling, an unexpected positive shock in freights generate a negative effect on tonnage and this effect loses its effect after three periods.
References
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.
Alizadeh, A. H., Strandenes, S. P. & Thanopoulou, H. (2016). Capacity retirement in the dry bulk market: A vessel-based logit model. Transportation Research Part E: Logistics and Transportation Review, 92, 28-42.
Athenian S.A. (2023). Demolition Quick Update. (07.05.2023), Retrieved from https://www.hellenicshippingnews.com/
Bhar, R. (2010). Stochastic Filtering with Applications in Finance. World Scientific.
Bo, C. & Xing, X. (2011). Military Spending and Economic Growth in China, 1953-2007: A Note on Econometric Analysis Using EViews. In: Chatterji, M., Bo, C. and Misra, R. (Eds.), Frontiers of Peace Economics and Peace Science (pp. 115-132). UK: Emerald Group Publishing.
Braemar (2023). Dry Demolition Tonnage. (13.04.2023), Retrieved from https://braemar.com/
Brooks, C. (2014). Introductory Econometrics for Finance (3rd ed.). United Kingdom: Cambridge University Press.
Capital Link (2023). Baltic Dry Index. (13.04.2023). Retrieved from https://www.capitallink.com/.
Choi, J. K., Kelley, D., Murphy, S. & Thangamani, D. (2016). Economic and environmental perspectives of end-of-life ship management. Resources, Conservation and Recycling, 107, 82-91.
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, 366a, 427-431.
Engels, U. D. (2013). European Ship Recycling Regulation: Entry-Into-Force Implications of the Hong Kong Convention (Vol. 24). Springer Science & Business Media.
Galley, M. (2014). Shipbreaking: Hazards and Liabilities. Springer International Publishing.
Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 37(3), 424-438.
Hossain, M. S., Fakhruddin, A. N. M., Chowdhury, M. A. Z. & Gan, S. H. (2016). Impact of ship-breaking activities on the coastal environment of Bangladesh and a management system for its sustainability. Environmental Science & Policy, 60, 84-94.
Kagkarakis, N. D., Merikas, A. G., & Merika, A. (2016). Modelling and forecasting the demolition market in shipping. Maritime Policy & Management, 43(8), 1021-1035.
Karlis, T., Polemis, D. & Georgakis, A. (2016). Ship demolition activity. An evaluation of the effect of currency exchange rates on ship scrap values. SPOUDAI-Journal of Economics and Business, 66(3), 53-70.
Kirchgässner, G. & Wolters, J. (2007). Introduction to Modern Time Series Analysis. Berlin: Springer.
Knapp, S., Kumar, S. N. & Remijn, A. B. (2008). Econometric analysis of the ship demolition market. Maritime Policy & Management, 32(6), 1023–1036.
Kočenda, E. & Černý, A. (2015). Elements of Time Series Econometrics: An Applied Approach. Prague: Karolinum Press.
Kwiatkowski, D., P.C.B. Phillips, P. Schmidt, & Y. Shin (1992). Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root. Journal of Econometrics, 54(1-3), 159-178,
Nazlioglu, S. (2019). Oil and Agricultural Commodity Prices. In: Soytaş, U. and Sarı, R. (Eds.), Routledge Handbook of Energy Economics. Routledge (pp. 385-395). New York: Routledge.
NGO (2023). 2022 Shipbreaking Records. (07.05.2023), Retrieved from https://www.offthebeach.org/
Phillips, P. C. & Perron, P., 1988, Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.
Totakura, B. R., Sharma, V., Kashav, V., & Das, S. R. (2021). Volatility of Ship Demolition Index Prices. Transactions on Maritime Science, 10(02), 488-495.
Tunç, M. & Açik, A. (2019). The impact of steel price on ship demolition prices: Evidence from heterogeneous panel of developing countries. Sosyoekonomi, 27(42), 227-240.
UNCTAD (2023). Ship recycling, by country, annual. (07.05.2023), Retrieved from https://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=89492
World Bank (2023). Population Statistics. (07.05.2023), Retrieved from https://data.worldbank.org/indicator/SP.POP.TOTL
Xiarchos, I. M. & Fletcher, J. J. (2009). Price and volatility transmission between primary and scrap metal markets. Resources, Conservation and Recycling, 53(12), 664-673.
Yin, J. & Fan, L. (2018). Survival analysis of the world ship demolition market. Transport Policy, 63, 141-156.
Yu, L., Li, J., Tang, L., & Wang, S. (2015). Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach. Energy Economics, 51, 300-311.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Journal of Recycling Economy & Sustainability Policy
This work is licensed under a Creative Commons Attribution 4.0 International License.
