Upward CPI Revisions Further Undercut Disinflation Narrative
CPI came in hotter than expected in January and threw cold water on the “disinflation” narrative that was gaining steam in the mainstream. Less-reported were the revisions of past CPI data. These undercut that narrative even further.
The CPI data for October, November and December were all revised higher.
Here are the revisions for December.
- Overall CPI originally reported -0.1%; revised to +0.1%.
- Core CPI originally report +0.3%; revised to +0.4%
- Services CPI, originally report +0.6%; revised to +0.7%.
WolfStreet noted that services CPI accounts for nearly two-thirds of consumer spending. “And it is red hot.”
For November, month-on-month CPI was revised up to 0.2% from 0.1%. For October, the CPI rose 0.5%, revised up from the previously reported 0.4% increase.
Core CPI in November was revised upward from +0.2 to +0.3.
WolfStreet summed up the implications of these revisions.
Disinflation means inflation, but easing rather than worsening inflation. These revisions for the past three months show that there was less disinflation in October and November than cited in all the hoopla about it, and that there has been worsening inflation in December.”
The Commerce Department revised some CPI data going all the back to 2018.
Reason to Be Skeptical
Why does the Commerce Department revise the data? According to Reuters, “The revisions were the result of recalculated seasonal adjustment factors, the model used by the government to strip out seasonal fluctuations from the data.”
These revisions provide a reason to be skeptical of any numbers featuring large seasonal adjustments. In effect, these are just made-up numbers.
As I noted recently, there were huge seasonal adjustments in the BLS non-farm payroll data for January that look questionable.
Retail sales data are also subject to seasonal adjustments.
Economist Murray Rothbard explained why we should always be wary of government “adjustments” to the data.
The further one gets from the raw data the further one goes from reality, and therefore the more erroneous any concentration upon that figure. Seasonal adjustments in data are not as harmless as they seem, for seasonal patterns, even for such products as fruit and vegetables, are not set in concrete. Seasonal patterns change, and they change in unpredictable ways, and hence seasonal adjustments are likely to add extra distortions to the data.”
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