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'd be careful believing any data the EIA is pushing out now, since they changed their "methodology" for gas and diesel price collection in June. I'll save you the rest of my government data rant, which can pretty much be summed up as "Old Man Yells at Sky".
As a rule, one should never "believe" economic metrics, as the measurements are in all cases of dubious accuracy. Even inflation metrics are open to challenge as to their magnitude.
However, when "official" government data contradicts the assertions of a government official, that is still a relevant criticism, especially when two nominally independent data sets challenge a claim based on timing and overall trend.
The reason for using the government's data is simple: the government's data is what the government will use to determine its next steps. One hardly needs to read a Substack article to know the practical impacts of food price inflation or energy price inflation in their own lives--people have the best data in the world for that already: their own spending patterns. However, to have a sense of what is likely to happen next it is important to have some thought on what the government is going to do next. That the Fed's actions are likely to be counterproductive does not change the reality that they are also likely to be highly impactful.
Superb job.
This 'core inflation' spin can't ignore the reality of food and transportation costs going up effects everything!
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.
I'd be careful believing any data the EIA is pushing out now, since they changed their "methodology" for gas and diesel price collection in June. I'll save you the rest of my government data rant, which can pretty much be summed up as "Old Man Yells at Sky".
As a rule, one should never "believe" economic metrics, as the measurements are in all cases of dubious accuracy. Even inflation metrics are open to challenge as to their magnitude.
However, when "official" government data contradicts the assertions of a government official, that is still a relevant criticism, especially when two nominally independent data sets challenge a claim based on timing and overall trend.
The reason for using the government's data is simple: the government's data is what the government will use to determine its next steps. One hardly needs to read a Substack article to know the practical impacts of food price inflation or energy price inflation in their own lives--people have the best data in the world for that already: their own spending patterns. However, to have a sense of what is likely to happen next it is important to have some thought on what the government is going to do next. That the Fed's actions are likely to be counterproductive does not change the reality that they are also likely to be highly impactful.