When you have a dozen ways to measure the same thing, you're no longer measuring — you're choosing which story to tell. Central banks have transformed inflation statistics into the art of political rhetoric, where each metric is not a tool of knowledge but a weapon of narrative. CPI too high? Let's look at Core. Core still spooking investors? We've got Supercore. And PCE. And Trimmed Mean. And Median CPI. This statistical zoo exists not to give you an accurate picture of what's happening — it exists so there's always the right number to point to at the right moment.
The problem isn't the metrics themselves — each has its methodological justification. The problem is that measurement redundancy creates an illusion of scientific rigor while simultaneously killing any possibility of holding anyone accountable. When a regulator can switch between indicators like TV channels, the concept of "inflation targeting" becomes a farce. You promised to keep inflation at two percent? Great, by which metric exactly — the one that's convenient today or the one that was convenient yesterday?
The Zoo of Metrics — A Tour of Statistical Cages
Let's navigate this bestiary. CPI (Consumer Price Index) — the grandfather of all indices, measuring price changes in a basket of goods and services supposedly purchased by the average consumer. Manipulation begins here: the basket composition is regularly "updated," with items that have risen in price mysteriously disappearing. PCE (Personal Consumption Expenditures) — the Fed's darling, which "accounts for substitution." Translation: if steak gets expensive, you're assumed to switch to chicken, and that's not counted as inflation. Brilliant, isn't it?
Core Inflation excludes food and energy — precisely the things you cannot live without. The logic? "Too volatile." Translation: "too obviously showing we screwed up." Supercore is a relatively new invention, excluding housing from services as well. Trimmed Mean cuts off extreme values from both ends of the distribution. Median CPI takes the middle value. Each tool can show a 2-3 percentage point difference when measuring the same economic reality.
The Art of Statistical Acrobatics
Here's where the real show begins. In 2021-2022, when U.S. inflation soared to forty-year highs, Fed rhetoric performed acrobatic somersaults. First, we were told to look at "headline" inflation — while it was low. Then they switched to Core — when headline became inconvenient. Then Supercore appeared — when Core stopped pleasing the eye. Each switch was accompanied by scholarly explanations of why this particular metric "better reflects underlying trends."
But wait, it gets even better. When even Supercore showed stubbornly high numbers, seasonal adjustments, methodology revisions, and "one-time factors" came into play. Car prices up? That's the "chip shortage" — a temporary phenomenon. Rental costs rising? That's a "lagged effect" — it'll reverse soon. Food getting expensive? That's a "supply shock" — not our responsibility. As a result, every month we got an explanation of why current figures don't reflect the "true" picture, and the "true" picture, of course, is much better.
This semantic gymnastics has very concrete consequences. When a central bank can choose metrics post factum, the concept of an "inflation target" loses all meaning. Two percent of what exactly? And measured how? With which adjustments?
Historical Lessons in Selective Blindness
History knows many examples of creative approaches to statistics. In 1983, the U.S. Bureau of Labor Statistics changed the methodology for accounting housing costs in CPI, switching from actual real estate prices to "owner's equivalent rent." The result? Formal inflation magically decreased, even though actual household expenses continued to rise. By some estimates, if 1970s methodology were applied today, official inflation would be 3-4 percentage points higher.
In the 1990s, hedonic adjustment was introduced. The idea is simple to the point of cynicism: if your computer became more powerful while the price stayed the same — the price actually dropped! The fact that you still need to pay the same amount of money is not taken into account. Similar logic applies to televisions, smartphones, and automobiles. As a result, technological progress artificially deflates official inflation, even when your wallet tells you something completely different.
Argentina went even further — from 2007 to 2015, the government simply falsified data, understating inflation by a factor of three. The IMF issued an official censure. But let's be honest: the difference between outright falsification and "creative methodology selection" is a matter of style rather than substance.
The Philosophy of Diluted Responsibility
Here we arrive at the philosophical core of the problem. Accountability requires clear criteria for success and failure. If a footballer promises to score ten goals per season, we know exactly whether he delivered or not. But if a central bank promises to "maintain price stability," measured by a dozen different methods yielding different results — who can say whether it succeeded or failed?
Multiple metrics create a cognitive fog in which any criticism dissolves. An economist points to rising CPI? He'll be told why PCE is a more appropriate measure. He switches to PCE? He'll learn about the advantages of Core. And so on ad infinitum. This isn't dialogue — it's bureaucratic aikido, where the energy of criticism is redirected into the void of methodological discussions.
Moreover, multiple metrics create a convenient opportunity for retrospective reassessment. A policy that looked wrong by one indicator can be declared successful by another. "We always focused on the long-term Trimmed Mean trend" — and try to prove otherwise by digging through hundreds of hours of press conferences and thousands of pages of minutes.
The Digital Age — New Tools for an Old Deception
Twenty-first century technologies have opened new horizons for statistical creativity. Machine learning allows the creation of increasingly complex adjustment models that virtually no one can understand or verify except their creators. The algorithm's "black box" produces a number — and that number acquires the status of scientific truth, even though no one can explain exactly how it was derived.
Big Data enables real-time inflation measurement using prices of millions of goods — seemingly progress. But who chooses which goods to include? What weights to assign? Which "outliers" to filter out? At every stage, there's room for discretionary decisions that can shift results in the desired direction. Technology doesn't eliminate subjectivity — it masks it as objectivity.
The irony is that the abundance of data was supposed to bring transparency. Instead, it brought complexity, which became a new form of opacity. When understanding the methodology requires a PhD in econometrics, democratic control over monetary policy becomes a fiction.
When Transparency Becomes a Luxury
Central banks love to talk about transparency and "communication with markets." But true transparency implies simplicity and unambiguity. When you publish ten different indicators and reserve the right to cite any of them, that's not transparency — it's information noise creating an illusion of openness while completely lacking real accountability.
The solution seems obvious: choose one metric and stick with it. But that would mean voluntarily giving up the wiggle room that bureaucrats so treasure. Which means the statistical buffet will continue to overflow with dishes for every taste — as long as it's the chef who picks the taste, not the hungry guests.
DeflationCoin — Algorithmic Honesty vs. Bureaucratic Flexibility
Against this backdrop of statistical acrobatics, the idea of algorithmic monetary policy embedded in immutable code looks particularly attractive. The DeflationCoin project represents a radically different approach: instead of a dozen manipulable metrics — one transparent mechanism of deflationary halving that burns tokens not placed in staking, creating real supply reduction. No "transitory factors," no "seasonal adjustments," no room for interpretation.
When the rules of the game are written in a smart contract audited by SolidProof, the question "which metric are you using" loses its meaning. The smooth unlock mechanism eliminates the possibility of manipulative mass sell-offs, while Smart Staking pays rewards from actual ecosystem revenue — without minting new coins, without creating inflation. In a world where central banks have turned inflation measurement into political art, a deflationary crypto asset with mathematically defined monetary policy isn't just an investment — it's a vote for transparency against the culture of institutional irresponsibility.