Demand for the transport sector is a derived demand; however, the transport sector is not only affected by the demand for the goods transported, but can also influence demand for itself by providing more transport facilities, which can affect trade by generating more options for foreign trade stakeholders. Accordingly, we have examined the effect of the Liner Shipping Connectivity Index (LSCI) variable, which is an indicator of countries' liner transportation connectivity, on Turkey's export and import container traffic, by using regression analysis. We have enriched our model by adding the real exchange rate variable, which is the most important factor affecting foreign trade. Our results show that a 1% increase in the country's LSCI increases export and import container traffic by approximately 1%. This result shows that not only exchange rate and production policies, but also transportation policies, are critical in improving foreign trade of the country. The development of transportation facilities can both reduce transport costs and shorten the delivery time, thereby supporting Turkey's policies to become a production centre.
The purpose of this study is to determine the causal relationship between container traffic in Turkish ports and industrial production of Turkey considering the possible nonlinear structures and lagged impacts in order to generate results which are likely to be useful for the future planning of the ports. In accordance with this purpose, the non-linear test proposed by Diks and Panchenko (2006) has been used. The dataset consists of 172 monthly observations and covers the period between January 2005 and April 2019. According to the results obtained by considering the nonlinear structures, there is a significant unidirectional causality relationship from industrial production index to port throughputs and the impact continues during 3 periods (months). This situation can be thought to be caused by the intensive use of imported intermediate goods by Turkish producers. According to the demand level, it may take several periods for the changes in the future production planning to be reflected in the ports. These results are hoped to provide significant contributions both to ports, port users and policy makers in terms of strategy development and planning.
Fleet productivity increases in two directions. First one is achieved by increasing the speed of the vessels in the market conditions where high freight rates are observed, this increases the amount of cargo per unit capacity they carry at the unit time. The other one is related to the short run inelastic supply curve in shipping because of the time to build effect. When the demand increases occur, the amount of cargo carried per unit capacity increases since the increase in supply is limited in the short run. In this context, it is determined the relationship between freight rates and the amount of cargo carried per unit capacity in this study. The Baltic Dry Index (BDI) was selected as a measure of the freight rates, and the tonnage carried per DWT from the portion of the total cargo tonnage carried by the sea to the dry cargo fleet capacity during that year was selected as an indicator of the fleet productivity. The dataset used in the study consists of annual observations covering the period from 1985 to 2020. Correlation and regression methods were used to determine the econometric relationship between the variables. As a result of the study, a significant strong relationship was found between freight rates and productivity in the positive direction. According to the developed model, a 10% increase in the freight rate causes an increase of about 1.3% in fleet productivity.
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