# **1 Introduction**

The business literature has extensively analyzed how delays and unpredictable delivery times influence firms’ supply chain management decisions (Arvis, Carruthers, Smith, and Willoughby, 2011; Kunaka and Carruthers, 2014). With the development of lean retailing and just-in-time manufacturing practices, together with the increased fragmentation of production across the world,<sup>1</sup> timeliness and reliability have become the watchwords of firms involved in supply-chain trade. Import and export activities have grown increasingly intertwined, with foreign inputs typically imported and incorporated in the production of final goods or transformed and exported to other countries where they may further enter as intermediate inputs in the value-added exported to third countries (Koopman, Powers, Wang, and Wei, 2010; Koopman, Wang, and Wei, 2014). Against this background, unexpected factors such as late shipment arrivals, including truck breakdown-related transport delays, or uncertainty over the time required to clear the consignment after it has reached destination, owing for instance to excessive formalities and physical inspections by border authorities, can lead to postponed delivery of key inputs, thereby disrupting the supply chain. Such uncertainty carries reputational costs for the importing firm, undermining its ability to meet buyer quality requirements and delivery deadlines, and exposing it to the risk of losing sales contracts, market shares and valued customer relationships. Unexpected delays in delivery and their potential snowball effect across the supply chain (Harrigan and Venables, 2006) prompt importers to adopt costly hedging strategies, such as switching to more reliable but expensive transportation modes (Hummels, 2001) or maintaining safety stocks. Evidence suggests that inventory holding to guard against uncertainty generates costs that can vary from 15 percent of the cost of goods per year to as much as 50 percent; reaching on average 27 percent of the goods value in the case of the US (Clark, Kozlova, and Schaur, 2016).

Several studies have formally quantified the effect of timeliness on trade volumes. Based on disaggregated import data for the US, Hummels (2001) finds that each day in transit reduces the probability that the US imports manufactured goods from a given country by 1.5 percent and is equivalent to an ad valorem tariff rate of 0.8 percent, a figure updated to range between 0.6 and 2.3 percent in Hummels and Schaur (2013). Using similar data, Clark, Kozlova, and Schaur (2016) show that unexpected delays in the arrival date of shipments at ports in the US, captured by the difference between the actual and expected dates of arrival, reduce imports by 1 to 2 percent. Time costs also impede exports both at the extensive and intensive margins. Using a sample of 98 countries, Djankov, Freund, and Pham (2010) argue that each additional day required to move products from the factory gate and onto the ship reduces the volume of exports by more than 1 percent, while Li and Wilson (2009) find that it decreases the probability to export and the share of exports in total sales in developing countries. Freund and Rocha (2011) convey a similar message in the case of African countries and find inland transit delays to matter more than those related to documentation processing and Customs clearance. Likewise, Volpe Martincus, Carballo, and Graziano (2015) show that a 10 percent increase in Customs-driven delays in the time to export leads to a 3.8 percent decline in firms’ exports in Uruguay, with additional negative consequences for export

> 1World Bank Group; IDE-JETRO; OECD; UIBE; World Trade Organization (2017), _Global Value Chain Development Report 2017: Measuring and Analyzing the Impact of GVCs on Economic Development._ Washington, DC: World Bank.

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