Inflation Calculation is Fake… and why Economists Watch a Lot of Porn

I have two new books out: Money is Biological and 90 Days to Create & Launch: It is the Easiest, Cheapest, and Quickest Time in History to be an Entrepreneur and Innovator.

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Let me start with some goofing around.

You can pass this section.

Why isn’t PornHub or XVideos price data usage included in the CPI calculations? These sites, after Google, YouTube, and Facebook, are the most visited on the internet worldwide.

According to the online data aggregation site, Similarweb, the two sites are the favorite under 25 sites for South Africans to visit on the internet. In 2017, South Africa was the only PornHub top porn-watching country in Africa and among the top-20 in the world.

We should not be proud of such; dammit!

Did you know porn-watching connoisseurs tend to be professionals, such as accountants and lawyers, and add in there economists?

Economists at the Reserve Bank do watch a lot of porn surely – there’s no way they don’t (both men and women).

I wonder what their search includes…. “South Africa’s economists and the new Government of National Unity rise against the dollar and conquer American BB….”

I am sure the argument against such economic data ‘inclusion’ will be that “porn is immoral.” Yes, it is, but it is real money passing hands through purchased internet data. Immoral is also when anyone, even an economist, cheats on their spouse. However, they still deserve their jobs.

Of course, I am goofing around before I get into the article.

With this, let me say, the following are also not arguments:

  • That a certain authority figure said such and such a statement. The argument has to be elaborated, measurable, and of course, make sense.
  • Shaming a person without providing measurable counter-evidence, or making them feel guilty, hurling insults, innuendo, name-calling, decrying their lack of empathy, and the other argument fallacies, is not an argument.

These are the arguments I normally get when I make the statement that state inflation is a false calculation.

Inflation Calculation is Fake

N.B. The South African currency is called the Rand and “R” is our currency representation sign.

For context, in this article, I will speak about Reserve Banks’ (Central Banks) inflation.

Also, follow only the mathematics of my argument, or rather the impossibility of the purported measurement. In any calculation, the math has to make sense and be applicable in the given case specifically, e.g., we cannot use division when we ought to be subtracting – to make an example.

Let’s start. Prices move up and down daily for various reasons, related or unrelated, e.g., fuel price adjustments, clearance discount sales (even at losses), promotional discount sales, upselling funnel sales.

Outside of constitutional or decreed price movements such as petrol prices, market players (businesses) decide for themselves how to move their prices. I call this latter price movement natural inflation, i.e., either an increase or decrease in natural inflation.

I call central bank inflation decreed inflation or cosmetic inflation. We have no choice in the matter; it is the decree of the land, and it’s their prerogative.

Only the central banks can decide on whether their math or survey makes sense. This is counter to what math is about; it’s about proving or disproving. Which is fine, it’s how central banks and fiat economy work.

Others can argue what alternatives are there; it’s not the point – unavailability of alternatives is not proof that the status quo is correct. The whole point, which I will show, is that central banks’ math of calculating inflation does not make sense nor reflects reality.

The inflation rate is largely calculated and based on the Consumer Price Index (CPI). The CPI is a representative percentage derived from the price movements of a determined basket of goods.

The basket is based on an intensive survey of goods consumed by households. Of course, not all products can be included in the basket – it’s impossible as there are millions of products and their different barcoded variations.

Even if it was possible to include all products that change hands in the republic, the math would still not be correct. This will be illustrated as you read.

In South Africa’s context, which is not far off from methods in other countries, they sample goods in each province, for example, and produce a national list of goods: There are over 300 sampled goods.

The mix can never be a sample reflection of reality.

Let’s go.

Averages Only Work Well for Limited Scales

Human Height

Let me illustrate this with some examples.

The tallest person ever recorded in the world is Robert Wadlow, an American who lived between 1918 and 1940. He was 2.72 meters tall.

What I am definitely sure of is that there is no person or adult living today who is 4 meters tall. So there is a limit to the scale of people’s heights. The average height in South Africa is 1.68 meters.

There is rarely anyone over 2 meters in the world – those beyond are an exception.

If you take 9 random people whose height aggregation averages 1.6 meters, and add another one who is 4 meters tall, you get a new average of 1.75 meters.

The further number of random people you add to this average, the likely it will reduce as most people and most random people are below 1.75 meters.

There are more people closer to 1.5 meters on both sides, and exponentially fewer people as you move beyond 1.75 meters.

You can safely build a door that fits almost all people who will walk into it if it’s about 2 meters tall. If anyone is taller, they will lean in (F them, and there is less of them).

People’s heights have no consequences or immediate consequences besides that, women say they prefer tall men – but they always get Kevin Harts of the world.

However, there are consequences when it comes to scalable measures, like money.

Let’s take it to salaries.

By the way, the Gender Pay Gap is a lie. It falls into the same distorted averaging calculation of inflation which I will illustrate.

Let’s say there are two women, called W1 and W2. W1 earns R5000 and W2 earns R55000. To find their average, you add their salaries and divide by them (the variables), i.e., 2 (W1 and W2). The average is R27500.

You can easily tell that R27500 neither represents the two women and it would be a lie to say it represents them: W1’s salary is overestimated by R22500; and W2’s salary is underestimated by R22500.

Similarly, this is how the gender pay gap is calculated, i.e., they average men and women’s salaries separately and thus compare them. The Gender Pay Gap compares two averages distorted in their inception inherently, and their latter difference is further distorted – it’s a distortion of a distortion.

To go into variables: the two women might be in varying careers, experience levels, and years on the job. Salaries vary per experience, role, industry, etc. Averaging doesn’t take that into place and makes no sense to compare them.

The consequence for such is it creates false narratives and anger, and such falsehoods have gone into many formal reports and academic papers. The other danger is it ill-informs women in this case about career choices.

Hold my beer, I am getting to inflation – don’t insert anything in it.

In calculating the CPI, the price movements or changes are calculated and divided by the number of goods to get an average, which is then compared to the previous period. The result is rounded off to a hundred to get a percentage change. This percentage change is the CPI and thus an increase or decrease in inflation.

Since prices of goods, unlike height, but like salaries, are scalable exponentially, the average would be a misrepresentation.

So this is the reason I say the CPI does not reflect reality.

However, it gets more distorted when you take the variability and dynamics of the products’ sizes, varying brand prices, etc; like comparing salaries of just women in different career fields and let alone juxtaposing women and men’s salaries.

Let’s say for example the basket includes beer, but could be any brand. Which beer brand represents the whole country? Let’s say Castle Lager 330 ML is selected – it’s arbitrary and there is no rationality to this.

Say they select it at a retail price. However, the beer is sold at different prices at different liquor shops, and in varying sizes, and with different prices. The makers sell at their wholesale and the resellers price them at their random discretion; it could be for promotion purposes or whatever reason.

At pubs and clubs, beer can sell at two or more times the retail price.

If the beer increases either because of taxes or the brand owner, at pubs and clubs the increase amount can be several times exponential.

So, the beer in the basket represents a lot of people but still does not represent a lot of people. People can spend more money on beer at clubs than at retail but for exponentially lower quantities.

A person can spend R200 for 12 units of 340ML Castle beer at retail and then R250 for 6 of the same beers. This is just at one store place (S1) and one club (C1). The others can have their own increases.

If the makers of Castle increase prices by R5 for a six-pack at retail, the owner of S1 can increase his price by R10, and the owner of C1 increases by R30.

These are just price increases of two shops. The other shops can increase amounts varying from these.

On top of Castle being the selected beer arbitrarily, few people can spend a sum at clubs greater than the sum of spend at retail. So then it’s not representational to include Castle from retail.

All these give a statistical and sampling problem. It’s a mess to assume or declare that it’s rational to include any beer; on top of that variables when averaged give a distorted view, like the salary example above.

This gives a fat tail probability problem packaged with an averaging problem, i.e., the few people can total a sum larger than that of the most people.

Even if Castle is not the single chosen beer but a collection of beers is chosen and then averaged, it still gives an averaging of variables problem.

So, the average of things limited in scale like height can give a representational number, however, if they scale, like salaries, prices, or even wealth, it becomes a severe distortion.

The effect of price movements, at best, is calculated as a sum for an individual, e.g., how much my beer spend has gone up or down. The averaging of a sample like that of the CPI will give a distorted view.

My whole point here is this randomness of pricing at different shops and the variety of different products and their variations cannot be aggregated to represent anything in the real world.

It’s too random to be pinned down to a representational percentage that can calculate inflation.

Thinking it can be done is another case of fooled by randomness.

In Conclusion

Inflation calculation is a fake survey. However, it’s how the fiat monetary system works.