gatogetaway

gatogetaway OP t1_j0ewdep wrote

It is delayed by the (N-1)/2 timeframe. But you're right that it's certainly influenced by the most recent month too.

One way to think of it is it's influenced by all 12 months, and the average age of the data for those 12 months is about 6 months old.

The derivation can be found in Understanding Digital Signal Processing by Richard Lyons. In signal processing, filters similar to moving averages are commonly used, and the delay of that signal can be absolutely critical to the functional design of the system.

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gatogetaway OP t1_j0cii18 wrote

You are right if seasonally adjusted numbers are used.

However, the values are not seasonally adjusted because seasonal adjustments don't really apply (or shouldn't) to YOY numbers, the focus of the chart.

The main idea is the YOY numbers are well out of date by the time they're published and may not reliable indicators of the current state of prices.

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gatogetaway OP t1_j0chvzz wrote

>A general audience would probably find this confusing without additional explanation.

Agreed. Fortunately, the audience here tends to be more chart savvy.

The YOY CPI change for November (centered on 11/15) is reported around 12/15, so that introduces 1 month of delay right off the bat.

A YOY change is also an average of the 12 most recent monthly inflation numbers (actually averaging log(1+MonthlyInflation) and annualizing it is more accurate). Regardless, an N-sample average introduces a signal delay of (N-1)/2.

In the case of YOY, the delay is 11/2, or 5.5. Add on the 1 month of delay in the reporting and you have 6.5 months. So, the number reported on 12/15 actually represents the inflation on 6/1.

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