I had written earlier to propose an econometric modeling application that may lend itself to a quantum computing approach, and was asking how best to proceed.

The model would be centered around the interdependencies of industries within an economy. This approach, known as input-output economic modeling, is used to quantify the output of an industrial sector given inputs from a another sector. As the inputs/outputs change over time, the result is change in demand, which in turn provides a measure of industrial sector's well-being.

The recent Black Swan event that caused an unimaginable labor crisis for the chief provider of the economy's supply chain, has shed new light on the risk of outsourcing dependency, and the effect on global economics. This is new territory. So, the question becomes: How can we monitor the global industrial interdepencies in a timely fashion to create a valuable commercial early warning system? Given the stochastic nature of the problem, I imagined input-output econometric modeling might provide a leaping off point for an application suited to this new computing approach.

Does this make sense?

Thank you

Rich Z

  • 1
    $\begingroup$ Please rewrite this question with more specifics. $\endgroup$
    – AHusain
    Mar 4, 2020 at 21:55