At a conference at the Tobin Center for Economic Policy at Yale, academia and business experts gathered to discuss new ways in which research could help predict, avoid and manage supply chain disruptions.
Yale economist Aleh Tsyvinski and Princeton economist Ernest Liu are developing a new platform that “offers highly detailed information on supply chain disruptions on in near-real-time across a range of product, industries, and localities, “according to an article in the Yale News.
Part of their goal is to move economic theory closer to policies. “Typically, in economics, theory takes years, even decades to trickle down to policy,” explains Tsyvinski. “This is one of the very few examples where the distance between cutting-edge-theory, cutting-edge data analysis, and practical applications are very short."
In describing the platform, Tsyvinki said gave an example of how they analyzed 200 million datapoints of containers coming into the US. In an excerpt from the article, he explained how the data can be used.
Analyzing this super-detailed data with state-of-the-art computer modeling allowed us to create a sweeping monthly index of supply-chain disruption — interruptions in the production, sale, or distribution of products. In close to real time and with an unprecedented level of granularity, we can measure disruptions across industries, products, and localities. We can identify whether magnets are more disrupted than toys. We can provide details on which kinds of toys are being disrupted. At the firm level, we can show whether an individual company, say American Airlines, faces more disruptions than another firm. We can also show whether it is American Airlines being disrupted or one of its subsidiaries. We can do this for every major company in the United States. We can also track the temporary breakdowns in the long-term supplier, manufacturer, and customer relationships. And, crucially, we can identify and measure disruptions to critical supplies.
