Lucian Cernat / Dec 2014
Photo: Wikimedia Commons
International trade is present in everyone's life. Be it the fruits we have at breakfast or the electrical devices we use, our daily routine depends on complex trade flows and production processes scattered across multiple countries that hardly get noticed by the final consumer. Trade flows have evolved over time and are becoming increasingly intricate, with countless parts and components crossing multiple borders at different stages of production along global supply chains, before reaching the final consumer.
International trade was revolutionized by the introduction of the standardized container, which led to a considerable reduction in shipping costs. The revolutionary technological changes did not stop with the invention of the container. Today, a limited but growing number of these containers are equipped with sophisticated global tracking technologies (GPS, radio frequency identification, satellite communications, etc.) that can locate products and shipments in real time, optimizing supply chains and inventories for the ultimate benefit of consumers.
"Big data" on actual shipments, by exporting and importing firms, with specific product details and their port of origin and entry are publicly available. The wealth of detailed trade data does not stop at the docks: producers can track in real-time their stocks on each supermarket's shelf and plan the next shipment to make sure consumers do not face shortages, while avoiding waste and costly warehousing. Firms engaged in global supply chains and those specialised in logistics have developed detailed classifications that allow the identification of producers, the location of their production facilities and the most detailed product characteristics about brands, quantity (weight, number of units, pack sizes), quality (concentration levels of various key ingredients) as well as pricing, delivery and invoicing information.
But is this multifaceted reality fully accounted for in trade theories and well reflected in the statistical and analytical support available to trade policy makers? The short answer is: not really!
However, recent technological and analytical developments clearly offer a good basis for an upgraded "Trade Policy Analysis 2.0" platform, thus bringing trade policy closer to where the action is. The traditional analytical tools we have at our disposal have great strengths, notably at estimating the macro-economic effects of trade policy, but they remain imperfect. Firm-level trade statistics may be the new frontier of an enhanced data-driven trade policy making, similar to recent analytical developments underpinning other public policies and many corporate decisions. Big data is making major inroads in economics, as a recent article in the Science magazine argued convincingly. Big data produced already a shift in the way certain public policy decisions are made, with major improvements in the efficiency of such policies, from law enforcement to road maintenance.
Trade policy makers can also tap into these publicly available firm-level databases. There are also good news coming from global value chains (GVCs). Firms managing such supply chains rely on various standard, universal product codes and global databases developed by the logistics industry to allow GVC participating firms (e.g. suppliers of components and final assembly firms) to know exactly the brand, variety, quality, dimensions, essential product characteristics, and price range of billions of traded products. In "Trade Policy Analysis 2.0" the unit of analysis will shift from countries and sectors to exporting and importing firms, and from customs codes classifying trade products in broad categories to so-called Global Trade Item numbers (GTINs) that are used routinely by companies trading along the supply chain.
The leap towards "Trade Policy Analysis 2.0" does not mean that current analytical tools should be discarded, quite the contrary. New theoretical discussions and the wealth of empirical firm-level data make the goal of building policy-relevant analytical tools "at firm level" look attainable.
Containers revolutionized shipping and reduced international trade costs. Firm heterogeneity revolutionized trade theory and the new firm-level data "by container" revolutionized empirical trade analyses. Finally, the big data approach stands to revolutionize economics, as well as public policies. Will all these disrupting technologies revolutionize the analytical support to trade policy making towards a more systematic use of firm-level trade data? Based on the arguments presented above, most probably the question is not "whether" but "when".
A longer version of this paper was published as part of the DG Trade Chief Economist Note, available online at goo.gl/Nig0p1.
The opinions expressed herein are those of the author and do not necessarily reflect the views of the European Commission