Abstract

Background: The ability of the Baltic Dry Index to predict economic activity has been evaluated in a number of developed and developing countries. Aim: Firstly, the article determines the primary factors driving the dynamics of the Baltic Dry Index (BDI) and, secondly, whether the BDI can predict future share price reactions on the Johannesburg Stock Exchange All Share Index (JSE ALSI), South Africa. Setting: This article investigates the dynamics and predictive properties of the BDI in South Africa between 1985 and 2016. Methods: The article uses a review of a wide range of published data and two time-series data sets to adopt a mixed methods approach. An inductive contents analysis is used to answer the first research question and a combination of a unit root test, correlation analysis and a Granger causality model is employed to test the second research question. Results: The results show that the BDI price is primarily driven by four underlying constructs that include the supply and demand for dry bulk shipping, as well as risk, cost and logistics management factors. Secondly, the results indicate a break in the BDI data set in July 2008 that influences a fundamental change in its relationship with the JSE ALSI index. In the pre-break period (1985 to 2008), the BDI is positively correlated with the ALSI (0.837, α = 0.05) before sharply diverging in the second period from August 2008 to 2016. In the first period, the BDI showed an optimal lag period of 6 months as a predictor of the ALSI index, but this predictive ability ceases after July 2008. The article makes a two-part contribution. Firstly, it demonstrates that the BDI is a useful predictor of future economic activity in an African developing country. Secondly, the BDI can be incorporated in government and industry sector planning models as a variable to assess future gross domestic product trends. Conclusion: The study confirms that the BDI is only a reliable indicator of future economic activity when the supply of shipping capacity is well matched with the demand.

Highlights

  • Six billion tonnes of sea freight were transported in 2010 by 93 000 vessels operating in 25 key shipping routes (Bowden et al 2010)

  • The demand versus supply of dry bulk shipping capacity is tracked by the Baltic Dry Index (BDI)2 (Geman & Smith 2012), which is developed from data obtained from an international panel of ship brokers

  • This article examined two key questions that included evaluating the dynamics of the BDI and whether the BDI was a predictor of economic activity

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Summary

Introduction

Six billion tonnes of sea freight were transported in 2010 by 93 000 vessels operating in 25 key shipping routes (Bowden et al 2010). 40% of sea freight consists of dry bulk cargo.. The demand versus supply of dry bulk shipping capacity is tracked by the Baltic Dry Index (BDI) (Geman & Smith 2012), which is developed from data obtained from an international panel of ship brokers. The Johannesburg Stock Exchange All Share Index (JSE ALSI) index increased until 2009/2010; it did not track the BDI trend after 2009. The BDI index, based on the demand for dry bulk cargo, has widely been proposed as a proxy for future economic activity (Bakshi, Panayotov & Skoulakis 2011; Koskinen & Hilmola 2005). The ability of the Baltic Dry Index to predict economic activity has been evaluated in a number of developed and developing countries

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