DHL Global Trade Barometer increases

The DHL Global Trade Barometer is based on import and export data for a number of intermediate and early-cycle commodities that serve as the basis for further industrial production, e.g. brand labels for clothes, bumpers for cars or touch screens for mobile devices. Sources for the index are aggregated market data from air and containerized ocean freight in seven countries, which account for more than 75 percent of world trade. Using artificial intelligence and various statistical methods this data is compressed to a single index value, which is published on a global level and individually for the seven countries evaluated.

The DHL Global Trade Barometer index represents the weighted average of the current growth and the upcoming two months of global trade. An index value above 50 indicates a positive development; values below 50 point to a decline in world trade. Tests with historical data have revealed a high correlation between the DHL Global Trade Barometer and real containerized trade, providing a three-month forward-looking estimate.

In addition to the findings on world trade in general, the DHL Global Trade Barometer provides deep insights into specific issues, e.g. the main macroeconomic factors that are affecting trade trends or the countries and regions that are driving global trade. By breaking down the global supply chain, volume trends within industry sectors could be identified, pointing to outperforming and declining sectors.

The insights from the DHL Global Trade Barometer will help DHL customers to optimize their business processes, for example providing guidance for investment and supply chain decisions. Moreover, DHL itself will leverage the indicator to fine-tune its own resource planning for its international logistics operations. Due to the high quality of the data, the company believes that the DHL Global Trade Barometer has a high significance also beyond logistics. Since it is an indicator for future trade and economic growth worldwide, the index could be integrated into forecast models by banks, associations or economic research institutes.