CPI Turns Messy as Shutdown Distorts the Inflation Signal the Fed Usually Trusts

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What better way to end this crazy year than with an economic data point that we don’t know how to really interpret? Happy New Year!

Recall that, thanks to the government shutdown, the BLS released September (by recalling workers to calculate the number based on data already collected) but didn’t do any of the normal price-collection procedures for the prices that are normally collected by hand. That’s far less than 100% of the index, but it’s a lot and so the October CPI was not released at all. Which brings us to today, and the November CPI – where the data was mostly collected somewhat normally. However, the calculation procedures had to be adjusted in ways we don’t really know about. You’d think that the way you do this is that you figure out the value that equates to the price level you just measured, and just say ‘hey, that’s a two-month change’ but it isn’t quite that easy. And some very smart people think this could bias the CPI lower for a few months. Whatever they end up doing, the lack of an October number is still going to mess up all the feeds (e.g. from Bloomberg) and all of the scripts and spreadsheets based on those feeds.

The BLS said in a FAQ yesterday that “November 2025 indexes were calculated by comparing November 2025 prices with October 2025 prices…BLS could not collect October 2025 reference period survey data, so survey data were carried forward to October 2025 from September 2025 in accordance with normal procedures.” In other words, November will basically be a 2-month change. (Or so we thought: see below).

Looking back to the last real data we got, in September: recall CPI was weaker than expected, but a big part of that was because of what looked like a one-off in OER. But the breadth of the basket that was accelerating was increasing, which was not a good sign. Normally the OER question would have been answered last month but…oh well.

Coming into the month…we at least have market data!

Inflation Market Overview – Monthly Change

There was a big drop in short inflation swaps and breakevens this month. A lot of that is due to the steady drop in gasoline prices (see chart below), but some of it may be because sharp-penciled people anticipated that the BLS adjustment for October’s missed data is going to bias the number lower.

US National Average Gasoline Prices (3AGSREG – Daily Chart)

And boy, did it. This number is absolute garbage.

There are going to be two eras going forward: pre-shutdown inflation data and post-shutdown inflation data. Much like when there are large one-offs in the data, as in Japan years ago when there was an increase in the national sales tax rate, the year-over-year data for the next year are going to look artificially low. The BLS never adjusts the NSA data ex-post. If it’s wrong, it stays wrong. We can really hope that this doesn’t affect seasonal adjustments when the BLS calculates the new factors for next year, because that would mean next October’s CPI is going to be massively biased upwards.

Because what it looks like is that for many series the BLS didn’t calculate a two-month change based on the current price level – it looks like, especially for housing, they assumed October’s change was zero so that the two-month change reported for this month was actually a one-month change spread over two months. For example, even with the low Owners’ Equivalent Rent print in September, the y/y figure was 3.76%, so about 0.31% per month. The BLS tells us that the two-month change in OER was +0.27%. That looks more than a little suspicious to me.

Owners’ Equivalent Rent and Primary Rents (OER vs Primary Rents – YoY Inflation Chart)

Largely from that effect, dropped from 3.5% y/y to 3.0% y/y in just two months. Riiiiight.

Core Services vs Core Goods Inflation (YoY Comparison Chart)

If in fact these two-month changes are all (or mostly) one-month changes, then the data makes a lot more sense. Either way, it’s hard to believe that the y/y change in Health Insurance dropped from 4.2% y/y to 0.57% y/y, thanks to a -2.86% decline in November from September. Yes, the Health Insurance category does not directly measure the cost of health insurance policies, and October is often when the new estimation from the BLS goes into effect, but a monthly -1.43% pre month decline for the next 12 months in Health Insurance is implausible.

Ergo, I’m not going to show most of my usual charts. This is garbage all the way down. Now, in my database instead of having a blank for October as the BLS does (for many but not all series. Seriously this is going to completely mess up any spreadsheet based on pulling data from Bloomberg), I am going to assume the price level adjusted smoothly over those two months – that is, I interpolated between September and November. That’s naïve, but it’s necessary to assume something and that’s better than assuming no change for October!

I have no idea what this will do to Median. If the Cleveland Fed follows the BLS lead, they’ll report a blank for October and a Median of something like 0.24% for the two-month period (that’s what I calculate), but it’s also garbage because garbage-in, garbage-out.

Really, this is a low point for inflation people and a low point honestly for Inflation Guy. I expected more from the BLS. I spend a lot of time defending these guys (heck, I just wrote a column on “Why Hedonic Adjustment in the CPI Shouldn’t Tick You Off”) because the staff involved in calculating the CPI are solid non-partisan professionals (aka pointy-head types) who really are trying to get as close to the ‘right’ answer as actual data allows. I can’t say that’s true in this case. Now, maybe when we get more data we will discover that the economy has abruptly shifted into something like price stability on the way to outright deflation, and it just happened to have a major inflection in October when no one was looking. But to me, it just looks like bad data.

Policymakers still gotta make policy, even if garbage data is all they have. But the correct response to not knowing what’s happening is not to assume you know what’s really happening and act accordingly – the right approach to extremely wide error bars is to do nothing. The correct approach for the is to do nothing until they have another 3-6 months of data and can start getting some confidence about current trends again. That’s not the world we live in. In this world, the Fed will recognize that the inflation data is squirrelly so their behavioral response will be to ignore it and in the policy context that means that they’ll make policy for a while here based solely on the labor market. Get ready for much more market volatility around the again! To me, that looks like it’s likely to be an ease in two of the next three meetings, before the FOMC needs to recognize that the new inflation data is still showing 3-4% inflation. It’s possible that the Committee could take a pause while they wait for the incoming Fed Chair in May. But the inflation data will not be an impediment to an ease, and will no longer be a strong argument for holding the line if growth data looks weak.

I may be being overgenerous here. It’s also possible this will reinforce the members’ priors since many of them were utterly convinced that inflation was going to drop significantly due to housing. This, in the presence of bad data, would be a pure error. But the result is the same: an easier Fed than is healthy for the monetary system right now.

There are lots of reasons to think that yields further out the curve will stay stable or rise. But yields at the short end should probably reflect easier money going forward.

Sorry I couldn’t be more help. Here’s looking forward to 2026!

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