Yves here. The mainstream financial media has been openly skeptical of the latest US inflation report, as these headlines demonstrate. First from the Wall Street Journal:
Wolf Richter explains the data fudge that the BLS used, and how it started before this inflation report.
Keep in mind that this sort of statistical manipulation is not just bad in itself, by among other things leading to deliberately setting inflation adjustments too low and producing an overstatement of GDP. It’s the sort of thing that occurs in pre-financial crisis periods, when the officialdom puts its finger on the dial to keep the party going. In the runup to the financial crisis, analysts like Michael Shedlock and Barry Ritholtz called out the “birth/death adjustment” to jobs creation data, which the BLS adds to allow for the fact that its survey doesn’t capture the creation or failure of businesses which too often were unusually large and increased the level of reported gains. In 2007, we included bogus official statistics on a list of Banana Republic Indicators. Readers can add to this list:
Compounds with private security for the very rich
Limited economic/class mobility
Militarization, exaggeration of external threats
Very high concentration of income and asset ownership in the very top echelon
Government policies heavily skewed towards the very rich; looting of the treasury
Limited/no press freedom
Election fraud; in extreme versions, coups, one party rule
Attacks on judicial independence/kangaroo courts
So this data chicanery may seem penny-ante taken in isolation, but it’s yet another indicator of continuing US decline.
By Wolf Richter, editor at Wolf Street. Originally published at Wolf Street
The Bureau of Labor Statistics explained today in its CPI report for November that most data for October was missing and some data for November was missing, and that it filled in the gaps in the November data, including by “approximating missing data points” with whatever, including for Owners Equivalent of Rent (OER), the biggest component of CPI, weighing 26% of overall CPI, for 33% of core CPI, and for 44% of core services CPI.
OER had a suspicious outlier-plunge in September, and that suspicious outlier-plunge in September was carried forward to October and November. And the BLS even explained some of it in separate notes, and so it’s not a secret.
This is a screenshot of the CPI summary table. You can see that nearly all the entries for month-to-month changes in October and November are missing. The exceptions are the entries for which BLS relies on “nonsurvey data,” such as gasoline prices and new and used vehicle prices (it purchases the vehicle data from J.D. Power).
What BLS Said About the Missing Data and How It Dealt With It
In its summary report, BLS said: “BLS did not collect survey data for October 2025 due to a lapse in appropriations. BLS was unable to retroactively collect these data. For a few indexes, BLS uses nonsurvey data sources instead of survey data to make the index calculations. BLS was able to retroactively acquire most of the nonsurvey data for October. CPI data collection resumed on November 14, 2025.”
In a separate note, BLS briefly explained some of the other shortcomings of this CPI release.
“What was the impact on November data collection? Collection began on Friday, November 14. By authorizing additional collection hours, BLS attempted to collect data for the entire month of November.”
It said “attempted to collect.”
And this is a bad joke: “How were November indexes calculated? November 2025 indexes were calculated by comparing November 2025 prices with October 2025 prices.” But October prices don’t exist in the data… “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, BLS just made up the October data.
And the September data, which was used as base for the made-up October data, was marred by the total outlier plunge of OER, which accounts for 26% of overall CPI, for 33% of core CPI, and for 44% of core services CPI. And that outlier plunge in September was carried forward to October and November.
Specifically about OER: “BLS calculates rent and owners’ equivalent rent using six-month panel collection [surveys are sent to the same address every six months, instead of every month].
So there was this suspicious outlier drop in September, and rather than bouncing back, as it should have done, it was carried forward to October and November, making for one heck of a funny chart below.
Using the BLS index data for OER as provided today…
Aug: 430.69
Sep: 431.27
Oct:
Nov: 432.44
…this is what the now clearly doctored OER looks like, month-to-month percentage change, annualized. It has been at an annualized rate of 1.6% for the past three months, compared to an average 4.1% in the six months before the doctored September. That’s a sudden 2.4 percentage-point plunge out of nowhere for the third month in a row.
And this doctored component is 26% of overall CPI, for 33% of core CPI, and for 44% of core services CPI, turning the entire CPI data into a bad joke 
or worse 
But It’s Not a Bad Joke, It’s Much Worse
Lots of things depend on CPI, including the calculation of the “inflation protection” in Treasury Inflation Protected Securities (TIPS), I-series savings bonds the government sells to retail investors, Social Security COLAs, and other inflation adjustments paid to investors and beneficiaries, and they will all be underpaid for inflation.
This data here also impacts broader economic data that is adjusted to inflation, including “real” consumer spending and “real” GDP because the BEA, which produces those overall economic indices, uses some of this CPI data, including OER, for its calculation of the PCE price index and the GDP deflator, among others.
BLS is now causing serious issues with all of them, with investors and beneficiaries getting short-changed on their inflation protection, and with inflation-adjusted economic data getting inflated, which would, of course, suit the administration’s narrative.
