I have long since come to the conclusion that the media (and people in general) invest far too much significance in the top-level numbers on economic data, inflation especially.
This misses the fact that inflation is never equal among all categories of goods and services. Gasoline Price Inflation is a staggering 60% year-on-year, which ma…
I have long since come to the conclusion that the media (and people in general) invest far too much significance in the top-level numbers on economic data, inflation especially.
This misses the fact that inflation is never equal among all categories of goods and services. Gasoline Price Inflation is a staggering 60% year-on-year, which makes concern over even a 9.1% YoY headline inflation rate seem almost quaint.
What the headline number tells us is that inflation is more broadly or less broadly impactful. The real understanding of consumer price metrics lies in parsing out the shifts within and among the various sub-categories and components of the headline number.
Perversely, Brian Deese' ham-handed effort to spin away from the headline number to focus on just one subcomponent is perhaps the best evidentiary support I could want for that thesis!
If you're a data geek and wonk like me you always hear about the sub components: they do get discussed, just in a more technocratic vein that doesn't make for much mass market consumption of the information.
One of the many things I do what I can to change within this Substack.
I have long since come to the conclusion that the media (and people in general) invest far too much significance in the top-level numbers on economic data, inflation especially.
This misses the fact that inflation is never equal among all categories of goods and services. Gasoline Price Inflation is a staggering 60% year-on-year, which makes concern over even a 9.1% YoY headline inflation rate seem almost quaint.
What the headline number tells us is that inflation is more broadly or less broadly impactful. The real understanding of consumer price metrics lies in parsing out the shifts within and among the various sub-categories and components of the headline number.
Perversely, Brian Deese' ham-handed effort to spin away from the headline number to focus on just one subcomponent is perhaps the best evidentiary support I could want for that thesis!
I predict this won't be the last we hear of 'subcomponents.' LOL
Superb analysis!
If you're a data geek and wonk like me you always hear about the sub components: they do get discussed, just in a more technocratic vein that doesn't make for much mass market consumption of the information.
One of the many things I do what I can to change within this Substack.
Yes, breaking down this mass market information "barrier" is critical to the understanding of not just the whole, but parts as well.