DETERMINING THE CAUSAL RELATIONSHIP BETWEEN BALTIC DRY INDEX (BDI) AND MACROECONOMIC VARIABLES BY TODA-YAMAMOTO ANALYSIS

Year 2023, , 59 - 80, 31.03.2023

Nesrin Özcan Akdağ , Turan Kocabıyık , Meltem Karaatlı

https://doi.org/10.11611/yead.1173114

Cited By: 1

Abstract

The Baltic Dry Index (BDI) is the most critical indicator taking the pulse of maritime trade. Hence, it is essential to determine the macroeconomic variables that affect the BDI, which is a solid indicator for global economic activities in maritime transport.
This research paper studies the association between macroeconomic indicators and the BDI. For this purpose, the Toda-Yamamoto approach was performed to examine the causal association between macroeconomic variables and the BDI. The Lee-Strazicich (LS) unit root test was applied based on Model C (break) to determine the stationary of the model series.
The research's findings shed significant light on the relationship between the BDI and macroeconomic variables. According to the Toda-Yamamoto causality test results: BDI has a two-way relationship with S&P 500 and MSCI World indexes; besides, there is a one-way relationship from €/$ parity to BDI and from BDI to BCOM index.

Keywords

Baltic Dry Index, Lee-Strazicich Unit Root test, Toda-Yamamoto approach, Causality analysis

References

• Açık, A., & Başer, S.Ö. (2021). “Interaction Between Commodity Prices and Freight Rates: Content Analysis of The Dry Bulk Market Reports”. İzmir Sosyal Bilimler Dergisi, 3(1): 39-48. doi: 10.47899/ijss.20213104
• Açık, A., & Başer, S.O. (2018) “Baltık Kuru Yük Endeksi Etkin Mi?”, Journal of Yasar University, 13(50): 140-149. doi: https://doi.org/10.19168/jyasar.368149
• Açık, A., Okutucu, Ö., Efes, K.Ö., Başer, S.Ö. (2021) “Analyzing The Impact of Interest Rate on Dry Bulk Freight Market with Time-Varying Causality Method”, Journal of Research in Economics, Politics & Finance, 6(2): 403-417. doi: 10.30784/epfad.798092
• Alimi, S.A., Ofonyelu, C.C. (2013) “Toda-Yamamoto Causality Test Between Money Market Interest Rate and Expected Inflation: The Fisher Hypothesis Revisited”, European Scientific Journal, 9(7): 125-142.
• Alizadeh, A.H., & Talley W.K. (2011) “Microeconomic determinants of dry Bulk Shipping Freight Rates and Contract Times”, Transportation, 38(3): 561-579. doi: https://doi.org/10.1007/s11116-010-9308-7
• Baker, S.R., Bloom, N., Davis, S.J., & Renault, T. (2021) “Twitter-Derived Measures of Economic Uncertainty”, 13 May, 1-14.
• Bakshi, G., Panayotov, G., & Skoulaki, G. (2011) “The Baltic Dry Index as a Predictor of Global Stock Returns, Commodity Returns, and Global Economic Activity”, AFA 2012 Chicago Meetings Paper, 1-51. doi:10.2139/ssrn.1747345
• Bandyopadhyay, A., & Rajib, P. (2021) “The Asymmetric Relationship Between Baltic Dry Index and Commodity Spot Prices: Evidence From Nonparametric Causality-in-Quantiles Test”, Miner Econ. doi: https://doi.org/10.1007/s13563-021-00287-y
• Barut, A., Görgün, M., & Erdoğdu, A. (2020) “Baltık Kuru Yük Endeksi ve Dow Jones Demir-Çelik Endeksi Arasındaki İlişki”, İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 9(3): 3019-3033. doi: 10.15869/itobiad.700223
• Başer, Ö.S., & Açık, A. (2019) “The Effects of Global Economic Growth on Dry Bulk Freight Rates”, Uluslararası Ticaret ve Ekonomi Araştırmaları Dergisi, 3(1): 1-17. doi:10.30711/utead.507566
• Bildirici, M.E., Kayıkçı, F., & Onat, Ş.I. (2015) “Baltic Dry Index as A Major Economic Policy Indicator: The Relationship With Economic Growth”, Procedia Social and Behavioral Sciences, 210: 416 – 424. doi: 10.1016/j.sbspro.2015.11.389.
• Bontempi, E.M., Frigeri, M., Golinelli, R., & Squadrani, M. (2021) “EURQ: A New Web Search-Based Uncertainty Index”, Economica, 88(9): 69–1015. doi: https://doi.org/10.1111/ecca.12372
• Cancı, M. & Güngören, M. (2013) “İktisadi Yaşamda Taşımacılık Sektörü”, Elektronik Sosyal Bilimler Dergisi, 12(45): 198-213.
• Cihangir, Ç.K. (2018) “Küresel Risk Algısının Küresel Ticaret Üzerindeki Etkisi”, İşletme ve İktisat Çalışmaları Dergisi, 6(1): 1-10.
• Doane, D.P., Seward, L.E. (2011) “Measuring Skewness: A forgotten Statistic?”, Journal of Statistics Education, 19(2): 1-18.
• Dritsaki, C. (2017) “Toda-Yamamoto Causality Test between Inflation and nominal Interest Rates: Evidence From Three Countries of Europe”, International Journal of Economics and Financial Issues, 7(6): 120-129.
• Eryuzlu, H. (2019) “Dünya Deniz Ticareti ve Türkiye Dış Ticareti Ilişkileri: Ekonometrik bir Analiz”, The Journal of Social Science, 3(5): 152-162. doi: 10.30520/tjsosci.524826
• Fattah, A., & Kocabıyık, T. (2020) “Makroekonomik değişkenlerin Borsa Endeksleri Üzerine Etkisi: Türkiye ve ABD Karşılaştırması”, Finansal Araştırmalar ve Çalışmalar Dergisi, 12(22): 116–151. doi: https://doi.org/10.14784/marufacd.691108
• Gao R., Zhao, Y., & Zhang, B. (2021), “Baltic Dry Index and Global Economic Policy Uncertainty: Evidence from The Linear and Nonlinear Granger Causality Tests”, Applied Economics Letters, 1-6. doi: https://doi.org/10.1080/13504851.2021.1985720
• Geman, H., & Smith, W.O. (2012) “Shipping Markets and Freight Rates: An Analysis of The Baltic Dry Index”, The Journal of Alternative Investments, 15: 98–109.
• Giannarakis, G., Lemonakis, C., Sormas, A. & Georganakis, C. (2017) “The Effect of Baltic Dry Index, Gold, Oil and USA Trade Balance on Dow Jones Sustainability Index World”, International Journal of Economics and Financial Issues, 7(5): 155-160.
• Granger, C.W. (1969) “Investigating Causal Relations by Econometric Models and cross-Spectral Method”, Econometrica: Journal of the Econometric Society, 37(3): 424-438. doi: https://doi.org/10.2307/1912791
• Jurun, E., Ratkovic, N., & Moro, F. (2015) “The Baltic Dry Index and performance Excellence In A Crisis Environment”, Croatian Operational Research Review CRORR, 6(2015): 335–346. doi: 10.17535/crorr.2015.0026
• Kiracı, K. & Akan, E. (2020) “İşletme ve Finans Yazıları-IV:Baltık Kuru Yük Endeksi (BDI) ile Seçilmiş Makroekonomik Değişkenler Arasındaki Nedensellik Ilişkisi”, İstanbul: Beta Press.
• Laulajainen, R. (2007) “Dry Bulk Shipping Market Inefficiency, The Wide Perspective”, Journal of Transport Geography, 15(3), 217–224. doi:10.1016/j.jtrangeo.2006.05.003
• Lee, J., & Strazicich, M.C. (2003) “Minimum Lagrange Multiplier Unit Root Test with Two Structural Breaks”, The Review of Economics and Statistics, 85(4): 1082-1089.
• Lee, J., & Strazicich, M.C. (2013) “Minimum LM Unit Root Test with One Structural Break”, Economics Bulletin, 33(4): 2483-2492.
• Lin, F., & Sim, N.C.S. (2013) “Trade, Income and the Baltic Dry Index. European Economic Review”, 59: 1–18. doi: https://doi.org/10.1016/j.euroecorev.2012.12.004
• Lin, Y.J., & Wang, C.C. (2014) “The dynamic analysis of Baltic Exchange Dry Index”, International Mathematical Forum, 9(17): 803-823. doi: http://dx.doi.org/10.12988/imf.2014.4473
• Lin, A.J., Chang, H.Y., & Hsiao J.L. (2019) “Does the Baltic Dry Index Drive Volatility Spillovers in The Commodities, Currency, or Stock Markets?”, Transportation Research Part, E (127): 265–283. doi: https://doi.org/10.1016/j.tre.2019.05.013
• Papailias, F., Thomakos, D.D., & Liu, J. (2017) “The Baltic Dry Index: Cycliacalities, Forecasting and Hedging Strategies”, Empir Econ, 52: 255–282. doi: 10.1007/s00181-016-1081-9
• Ruan Q., Wang Y., Lu X., & Qin J. (2016) “Cross-Correlations Between Baltic Dry Index and Crude Oil Prices” Physica A, 453: 278–289. doi: 10.1016/j.physa.2016.02.018
• Sahan, D., Memişoğlu, R., & Baser, S.Ö. (2018) “Predicting Baltic Dry Index With Leading Indicators”, Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 10(2): 233-248. doi: 10.18613/deudfd.495820
• Şahin, B., Gürgen, S., Ünver, B. & Altin, I. (2018) “Forecasting the Baltic Dry Index by Using An Artificial Neural Network Approach”, Turkish Journal of Electrical Engineering & Computer Sciences, 26(3): 1673-1684. doi: https://doi.org/10.3906/elk-1706-155
• Saraç, M., Zeren, F., & Başar, R. (2015) “Küresel Altın Fiyatlarıyla ABD Ek Beslenme Yardımı Harcamaları ve Baltık Kuru Yük Endeksi Arasındaki Etkileşim”, İstanbul Üniversitesi İşletme Fakültesi Dergisi, 44(1): 12-20.
• Saraç, M., & Başar, R. (2015) “Amerikan Ekonomisindeki Borçluluğun Altın Fiyatlarına Etkisi”, Düzce Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 5(2): 1-21.
• Sartorius, K., Sartorius, B. & Zuccollo, D. (2018) “Does the Baltic Dry Index Predict Economic Activity in South Africa? A Review From 1985 to 2016”, South African Journal of Economic and Management Sciences, 21(1): a1457. doi: https://doi.org/10.4102/sajems.v21i1.1457
• Shahzad, U., Jena, S. K., Tiwari, A. K., Doğan, B. & Magazzino, C. (2022) “Time-Frequency Analysis Between Bloomberg Commodity Index (BCOM) and Wti Crude Oil Prices”, Resources Policy, 78: 1-8. doi:https://doi.org/10.1016/j.resourpol.2022.102823
• Shamika, M., & Sirimanne, N. (2021) “Container Shipping in Times of COVID-19: Why Freight Rates Have Surged, and Implications for Policymakers”, United Nations Conference on Trade and Development, April, 2(84): 1-4.
• Toda Y.H., & Yamamoto T. (1995) “Statistical Inference in Vector Autoregressions With Possibly Integrated Processes”, J Econom, 66: 225–250.
• UNCTAD. (2021, March). Covid-19 and maritime transport impact and responses, Transport and Trade Facilitation Series, United Nations Conference on Trade and Development Report, 15, 1-76. Retrieved from https://unctad.org/system/files/official-document/dtltlb2021d1_en.pdf, (02.07.2022)
• UNCTAD. (2022, 28 June). The war in Ukraine and its effects on maritime trade logistics, Maritime trade disrupted, United Nations Conference on Trade and Development Report, 1-10. Retrieved from: https://unctad.org/system/files/officialdocument/osginf2022d2_en.pdf, (02.07.2022)
• Wu, Y., Yin J., & Sheng P. (2018) “The Dynamics of Dry Bulk Shipping Market Under The Shipping Cycle Perspective: Market Relationships and Volatility”. Transportation Research Record, 2672(11): 1 – 9. doi: https://doi.org/10.1177/0361198118756622
• Wu Y. C., Chen C. S., Chan Y. J. (2020) “The Outbreak of COVID-19: An overview”, J Chin Med Assoc., 83(3): 217-220. doi: 10.1097/JCMA.0000000000000270
• Yang, M.J., & Liu, M. Y. (2012) “The Forecasting Power of The Volatility Index in Emerging Markets: Evidence from The Taiwan Stock Market”, International Journal of Economics and Finance, 4(2): 217- 231. doi: 10.5539/ijef.v4n2p217
• Yıldız, B., & Bucak, U. (2017) “Determinants of freight rates: A study on the baltic dry index”, IGU J. Soc. Sci., Spec. Iss. of ICEFM, 4(2): 17-32. doi: http://dx.doi.org/10.17336/igusbd.317006
• Zeren, F., & Kahramaner, H. (2019) “Baltık Kuru Yük Endeksi ile İstanbul Navlun Endeksi Arasındaki Etkileşimin İncelenmesi: Ekonometrik Bir Uygulama”, Journal of International Management, 7(1): 68 – 79.