Determinants of Freight Rates: A Study on the Baltic Dry Index

Abstract

The aim of this study is to find out the determinants of the Baltic Dry Index (BDI) which is published by the Baltic Exchange in the period of 2003-2016 by a multiple OLS regression analysis.  For this purpose, the most important factors that are considered to have an impact on BDI, are analysed by the help of E-views 9.0 program thereby establishing optimum model. Empirical findings indicate that phosphate rock and barley have the highest impact on BDI. Additionally, the results of the analysis also showed that, while crude oil prices which is the core cost factor has positive effect on the BDI, cement and maize prices have  significant but negative effects. 

Keywords

• Baltic Dry Index,Freight Rates,Freight Rates,Main Bulks,Multiple Regression (OLS) Analysis,Seaborne Trade

Navlun Fiyatlarına Etki Eden Faktörler: Baltık Kuru Yük Endeksi Üzerine Bir Çalışma

Abstract

Bu çalışmanın amacı Baltık Borsası tarafından yayınlanan Baltık Kuru Yük Endeksi’ne etki eden faktörlerin tespit edilmesidir.2003-2016 dönemine ilişkin verilerin kullanıldığı çalışmada endekse etkisi araştırılan en önemli faktörler çoklu regresyon analizi yöntemi ile E-views 9.0 programı kullanılarak ile test edilmiştir. Elde edilen bulgulara göre fosfat kaya ile arpa fiyatlarında yaşanan değişimler Baltık Kuru Yük Endeksi’ne etki eden en önemli faktörlerdir. Bununla birlikte, sektörün temel maliyet unsuru olan ham petrol fiyatlarının Baltık Kuru Yük Endeksi üzerinde pozitif yönlü bir etkisinin çimento ve mısır fiyatlarındaki değişimin ise negatif yönlü bir etkilerinin olduğu tespit edilmiştir.  

Keywords

• Baltık Kuru Yük Endeksi,Navlun Fiyatları,Temel Yükler,Çoklu Regresyon Analizi,Denizyolu Ticareti

References

1. ALIZADEH A. H. and TALLEY W. K., “Microeconomic Determinants of Dry Bulk Shipping Freight Rates and Contract Times”, Transportation, Vol. 38 No 3, 2011, pp. 561-579.
2. BAKSHI, G., PANAYOTOV, G., and SKOULAKIS G., “The Baltic Dry Index as a Predictor of Global Stock Returns, Commodity Returns, and Global Economic Activity”, Chicago Meetings Paper, 2012, 52 p.
3. BATRINCA, G. I. and COJANU, G. S., “The Dynamics of the Dry Bulk Sub-Markets”, Journal of Knowledge Management, Economics and Information Technology, Special Issue December 2013, pp. 13-23.
4. BATRINCA, G. I. and COJANU, G. S., “The Determining Factors of the Dry Bulk Market Freight Rates”, 2014 International Conference on Economics, Management and Development (pp. 109-112). Organized by INASE. February 22-24.
5. BILDIRICI, M. E., KAYIKÇI, F., and ŞAHIN ONAT, I., “Baltic Dry Index as a Major Economic Policy Indicator: The relationship with Economic Growth”, Procedia - Social and Behavioral Sciences, Vol. 210, 2015, pp. 416-424.
6. DURU, O., “A Fuzzy Integrated Logical Forecasting Model for Dry Bulk Shipping Index Forecasting: An Improved Fuzzy Time Series Approach”, Expert Systems with Applications, Vol. 37, 2010, pp. 5372-5380.
7. DURU, O., BULUT, E., and YOSHIDA, S., “Bivariate Long Term Fuzzy Time Series Forecasting of Dry Cargo Freight Rates”, The Asian Journal of Shipping and Logistics, Vol. 26, No 2, 2010, pp. 205-223.
8. DURU, O. and YOSHIDA, S., “Long Term Freight Market Index and Inferences”, The Asian Journal of Shipping & Logistics, Vol. 27, No 3, 2011, pp. 405-422.

9. KIM, H., “Study about How the Chinese Economic Status Affects to the Baltic Dry Index”, International Journal of Business and Management, Vol. 6, No 3, 2011, pp. 116-123.
10. KO, B., “Dynamics of Dry Bulk Freight Market: Through the Lens of a Common Stochastic Trend Model”, The Asian Journal of Shipping and Logistics, Vol. 27, No 3, 2011, pp. 387-404.
11. LIN, F. and SIM, N., “Trade, Income and the Baltic Dry Index”, European Economic Review, Vol. 59, 2013, pp. 1-18.
12. LIN, F. and SIM, N., “Baltic Dry Index and the Democratic Window of Opportunity”, Journal of Comparative Economics, Vol. 42, 2014, pp. 143-159.
13. LIN, F. and SIM, N., “Exports, HIV Incidents and the Baltic Dry Index: Further Evidence from Sub-Saharan Africa”, Economics Letters, Vol. 126, 2015, pp. 35-39.
14. LIN, Y. and WANG, C., “The Dynamic Analysis of Baltic Exchange Dry Index”, International Mathematical Forum, Vol. 9 No 17, 2014, pp. 803-823.
15. READY, R., ROUSSANOV, N., and WARD, C., “After the Tide: Commodity Currencies and Global Trade”, Journal of Monetary Economics, Vol. 85, 2017, pp. 69-86.
16. RUAN, Q., WANG, Y., LU, X., and QIN, J., “Cross-Correlations between Baltic Dry Index and Crude Oil Prices”, Physica A, Vol. 453, 2016, pp. 278-289.
17. UNCTAD, Review of Maritime Transport, UNCTAD Publishing, Geneva 2016.
18. UYAR, K., İLHAN, Ü., and İLHAN A., “Long Term Dry Cargo Freight Rates Forecasting by Using Recurrent Fuzzy Neural Networks”, Procedia Computer Science, Vol. 102, 2016, pp. 642-647.
19. ZENG, Q. and QU, C., “An Approach for Baltic Dry Index Analysis Based on Empirical Mode Decomposition”, Maritime Policy and Management, Vol. 41 No 3, 2014, pp. 224-240.