Supply Chain Disruptions, Time to Build, and the Business Cycle

Bt Matthias Meier

http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2020_160

We provide new evidence that (i) time to build is volatile and countercyclical, and that (ii) supply chain disruptions lengthen time to build. Motivated by these findings, we develop a general equilibrium model in which heterogeneous firms face non-convex adjustment costs and multi-period time to build. In the model, supply chain disruptions lengthen time to build. Calibrating the model to US micro data, we show that disruptions, which lengthen time to build by 1 month, depress GDP by 1% and aggregate TFP by 0.2%. Structural vector autoregressions corroborate the quantitative importance of supply chain disruptions.

A timely study of supply chain disruptions, within business cycles, though. I doubt that if the current disruption due to Covid-19 last a couple of months, the impact on output will be just a couple of percents. Business cycle models approximated around their steady-state show their limitations in that case. But I wonder what lessons for today we could still draw form this model.

One Response to Supply Chain Disruptions, Time to Build, and the Business Cycle

  1. Thanks a lot for covering my paper on your blog.

    One lesson of the paper for today is that we better not ignore the misallocation effect of supply chain disruptions caused by Covid-19. A longer waiting times for capital good delivery means that firms with increases in productivity/demand cannot quickly increase their capital stock. E.g., Amazon currently receives a lot of extra demand, but they may struggle to import logistics machinery from China to open new warehouses. Misallocation and lower agggregate productivity is the result. Importantly, this misallocation effect of supply chain disruptions can be very persistent.

    Let me also follow up on your comments:

    1) On the magnitude of the effects. I focus on disruptions in the supply of capital goods. If you add disruptions that delay the delivery of consumer goods, that would raise the GDP costs of disruptions. Clearly, Covid-19 implies both types of disruptions.

    2) On the solution method. In an earlier version of the paper, I have solved the model using a Krusell-Smith algorithm. The results were very similar in magnitude. Hence, solving the model through an approximation around the steady state (the Campbell-Reiter method in may case) appears not to be important for the results.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: