This is a great example of how you can make up anything by aggregating unrelated statistical measures and then mislead people with a new definition on top of another woozy commonly used definition.
We can certainly argue the technical merits of how they created their 'generation-weighted price index', but differential impacts of inflation seems plausible on the face of it.
If you are looking for work in a big city, and big city real estate prices are growing much faster than nationwide, that is a real effect.
Well... sort of, but why call it 'inflation'? That certain age groups tended to act in certain ways and were impacted by differences in price trends in different ways -- that's accurate. What's misleading or confusing is to then redefining the already-muddled term of 'inflation' from an absolute index to multiple indices and then trying to say that because Index B went up more than Index A that some group of people were much more impacted by Index B than another people were by Index A.
The Fed has a price index that most entities in the US use to measure what it calls inflation. There are plenty of arguments out there that go into detail about how that index can be misleading and how certain institutional prerogatives encourage the people who maintain that index to keep it misleading (e.g. many entities are obligated to increase salaries and pension payouts tied to the CPI).
Sibling comment also asks this question, so I'll just respond here: inflation measures the purchasing power of some nominal currency, but that measurement is always relative to a basket of goods.
CPI is a basket of 'typical' consumer goods that an average person might buy. But if you're not the average consumer, then in what sense is CPI relevant to you, rather than to a macroeconomist?
I agree that there's a risk of confusion, but I think the confusion is inherent in what we're trying to measure (I have some dollars, how much stuff [that I care about] can I buy with them?), and not mainly a function of terminological confusion.
You could imagine a service like Mint that has all your spending data and calculating your own 'personal CPI', privacy considerations notwithstanding.
The various market baskets that make up the various inflation measures contain goods that will matter to some people more than others. And some of the big ticket items will disproportionately affect certain groups.
Want to live in a high-cost urban area and don't already own a home? Of course, rising housing prices will affect you more than someone who already owns in one of those areas or lives somewhere else.
Are pre-college? Education costs more relatively than it used to?
But, yeah, I don't think inflation measures ever claimed to be equably applicable to everyone, especially those measures that excluded some of the major costs precisely because they affect different groups.
>big city real estate prices are growing much faster than nationwide
Important point to make is that is not inflation. Inflation is a decrease in the purchasing power of a currency, and it can be inferred by the cost of many products going up across the entire market that currency is used. But one product going up in one segment of the whole economy is not inflation. What you're referring to is more accurately described as a local cost of living.
We just bought a house about two years ago. Say a younger couple living in our same area of town was renting. Our housing cost may have gone up 5% because of insurance and taxes, but the couple renting would have seen rent go up by 30% during the same period.
It's also a great example of using statistics to create a conclusion that fits a narrative, based upon statistically insignificant behavior.
This article is entitled, "Over the Past 5 Years, Inflation for Millennials was 14% Higher than for Baby Boomers". Yet, we find out in the last paragraph, indeed in the final sentence, that there is virtually no difference between groups over a longer, more significant period of 18 years.
There are three kinds of lies: lies, damned lies, and statistics.
Their use of the word significantly in this context does not refer to statistical significance. The percentages you are referring too are just basic metrics based on the last years data, not something that was t-tested. The longer time period changes the starting index, it doesn't really make this type of analysis more or or less statistically significant. As the author alluded, this could mean that economic mechanisms close this gap over time when it appears, or it could be a recent effect. Your criticism isn't really valid.
You are making a statement about statistics that isn't correct. Statistics is collecting and analyzing numerical data, which is what this article does. That is a truth, regardless of it being a different sort of analysis than what you believe to be the only model of statistics.
That is also orthogonal to what I wrote, which you seemed to intentionally misunderstand in order for you to argue.
I think the way that percentages were expressed in the headline was intentionally deceptive- 14% seems like a lot of inflation in 5 years! That makes for good clickbait. But the percent that is being talked about is the comparative difference between groups, per the line:
Over the past five years, millennials have seen their goods become 8.7% more expensive, Generation X 8%, and baby boomers 7.6%. This means that the price increase for millennials was 14% higher than for baby boomers.
I think the way that percentages were expressed in the headline was intentionally deceptive- 14% seems like a lot of inflation in 5 years! That makes for good clickbait.
Yep. That's my point. The article's premises do not support the conclusion. And, in actuality the end of the article contradicts its own conclusion.
But the percent that is being talked about is the comparative difference between groups, per the line: Over the past five years, millennials have seen their goods become 8.7% more expensive, Generation X 8%, and baby boomers 7.6%. This means that the price increase for millennials was 14% higher than for baby boomers.
There is a subtle error in this analysis. If companies A and B both grow with A growing 300% and B growing 1% per year, it seems that A might be a better company. That is often why companies that don't make money are valued similarly to companies that do make money. Putting the perception aside, A may have only increased by $4 but B could have increased by $4,000,000,000. Therefore it is not correct to say that the increase of A was 29,999% higher than for B.
Comparing percentages always has the potential to invoke that sort of confusion, but FWIW I'm pretty sure the headline is written correctly. If it were subtracting percentage values from one another rather than dividing, it would be "percentage points" rather than "%".
That said, the article itself is just silly, a true puff piece. I think one could make a more substantive (and more interesting) argument around the idea of the "basket of goods" measurement as a basis for measuring inflation in the first place, as goods make up a smaller and smaller percentage of our total expenses.
