Supply chain failures and the O-Ring

Difficulties in the global supply chain are a recurrent news item since the beginning of fall. The result has been that many pundits or politicians have argued for new policies that spout platitudes such as the need to “rethink trade“. For my part, all I could think of was the O-Ring theory of development developed by Michael Kremer.

The name for that theory is taken from the 1986 Challenger disaster, in which the failure of one small, inexpensive part caused the shuttle to explode upon take-off. Generally, the theory is applied to questions of development and speaks to high complementarities between inputs. Suppose the economy is divided into multiple sectors that exchange intermediaries goods between them (i.e. all firms are dependent on each other). Each of these goods can be labelled as n and producing these goods require skills q. However, each sector buys multiple different n as intermediary goods. For example, this would mean that sector “Vincent” buys goods from sectors “Joy”, “Jeremy” and “James” to produce the “Vincent” goods.

Imagine now that q is the percentage chance that n is produced with sufficient quality so that it bears its full market value (in which case, 1-q is the probability that n is produced so poorly that it gets a zero-price). This means that, to produce its goods, sector “Vincent” needs sectors “Joy”, “Jeremy” and “James” to produce high-quality goods. If one of the intermediary goods “Vincent” buys from the other is inefficient, all of Vincent’s production is worthless. Hence, the analogy to the O-Ring of the Challenger disaster.

So what’s the link with the supply chain failures you ask? Well, its pretty straightforward: the O-Ring theory implies that the impact of a bottleneck has a multiplicative effect on other productions. Now, everyone may be excused for thinking that I simply explained in a complex way something that is simple (i.e. dont half-ass things). However, this way of formulating is very helpful because of q.

If q is the probability of a badly-performed task, what determines q? Some could say its the pandemic, but that would be incorrect. An article in Nature shows that COVID-19 has yielded widely disparate effects on supply chains in different countries. If it was global, it should be roughly similar everywhere. Ergo, some local factors must be in play. Local factors of relevance would be laws on shipping such as the Jones Act in the United States or the public ownership of ports in many western countries. By preventing cabotage and limiting foreign ships, such as in the Jones Act, there is little excess capacity in the American shipping industry available when demand shocks occur. By being more bureaucratically rigid, ports may be unable to adapt to unforeseen events (which is why there are papers in transportation economics that show that privatizing ports tends to increase productivity and reduce shipping costs notably by speeding turnarounds).

Each of these local factors have to do with local policies that reduce q and tend to increase the likelihood of failures (i.e. bottlenecks) which then reverberate on total output (beyond the narrow supply chain sector). From this, I get to a simple: complications that we attribute to the COVID crisis are more likely the results of local factors.

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