D — Constitutionalizing an incorruptible index

Appendice D

CONSTITUTIONALIZING AN INCORRUPTIBLE INDEX

Reference: Chapter VIII (The Flat Tax)

D.1 — The Problem: Price Indices Are Manipulable

The standard deduction—initially set at €500 per month—must be indexed to the real cost of living. This amount will be adjusted by economic simulations, but the indexing mechanism must be defined and locked in now.

But who calculates this cost of living evolution? And how do we guarantee this calculation won’t be manipulated by political power?

Governments have incentives to underestimate inflation to:

Reduce indexed expenditures (pensions, social minimums)
Display more flattering real growth
Maintain artificially low interest rates

Current methods are vulnerable:

The CPI basket is defined by civil servants
Weightings are arbitrarily chosen
“Hedonic adjustments” can be biased
Product substitutions mask real inflation

The MIT Billion Prices Project demonstrated that official indices regularly underestimate real inflation, sometimes by several points [96].

D.2 — The Solution: The Dynamic Pseudo-Basket (DPB)

The DPB is not a theoretical invention. It is the synthesis of three proven techniques, combined to create an automatic, transparent, and incorruptible index.

Pillar 1: Chained Indices

Traditional indices (Laspeyres) use a fixed basket that becomes obsolete. Chained indices solve this problem:

Fisher Index: combines old basket and current basket
Tornqvist Index: weights by average budget shares
Chained indices: the basket changes automatically each year

The U.S. Bureau of Economic Analysis (BEA) already uses chained indices for real GDP [H2]. Nobody manually chooses the weightings—they derive from the data.

Pillar 2: Real Transactional Data

Instead of declarative surveys, the DPB uses anonymized and aggregated transaction data:

Cash register receipts (scanner data)
Aggregated bank transactions
Payment operator data

Statistics Netherlands pioneered the use of scanner data to calculate inflation [H3]. The U.S. BLS is also experimenting with this approach [H4].

Pillar 3: Unsupervised Classification

This is the key to incorruptibility. Instead of civil servants deciding which categories of goods to include in the basket, a clustering algorithm automatically defines categories from the data.

Techniques used:

K-means, DBSCAN for clustering
Embeddings to represent products
No human intervention in category definition

Banks and fintechs (Visa, Mastercard, Revolut) already use these techniques to classify their clients’ spending [H5].

D.3 — Existing Implementations

Project	Organization	Method	Limits
Billion Prices Project	MIT	Online price scraping	Not institutional
Chain-weighted GDP	BEA (USA)	Chained indices	Applied to GDP, not CPI
Scanner Data CPI	Statistics Netherlands	Cash register receipts	Not automated
Real-time Inflation	Various central banks	Transactions	Internal use only

No country has yet institutionalized a complete DPB. The reasons are political, not technical:

It would remove governments’ manipulation capacity
Statistical institutes protect their historical prerogative
Constitutionalizing an algorithm is revolutionary

D.4 — Proposed Constitutional Formulation

Article X. — Standard Deduction Indexation
The standard deduction provided in Article Y is adjusted annually according to a cost of living index calculated by the following method:
Source data: anonymized and aggregated transactions from at least three independent payment operators, covering at minimum 30% of territory transactions.
Classification: spending categories are defined by unsupervised classification algorithm, without human intervention in category choice.
Calculation: the index is chained (Fisher or Tornqvist), recalculated monthly with automatic publication.
Source code: the complete algorithm is public, auditable, and executable by any citizen with access to aggregated data.
Lock-in: any modification of this method requires a four-fifths majority in each chamber.
Challenge: any citizen can petition the Constitutional Council if they believe the published index does not correspond to application of the official algorithm.

D.5 — Objections and Responses

Objection	Response
Privacy	Data is aggregated and anonymized. No individual transaction is traceable. Only category totals are used.
Exclusion of cash payments	The sample doesn’t need to be exhaustive, but representative. 70% of transactions suffice if properly distributed.
Technical complexity	Source code is public. Universities, NGOs, and citizens can independently verify calculations.
Algorithm manipulation	The 4/5 lock-in and code publication prevent discreet modifications.
Goodhart’s Law (“what is measured is manipulated”)	Unsupervised classification automatically adapts to behavior changes.
Bugs or hacking	Multiple independent implementations must converge. Divergence = automatic alert.

D.6 — Why This Is Revolutionary

The DPB would be the first truly scientific economic measure inscribed in a constitution:

Reproducible: anyone can recalculate the index
Falsifiable: one can demonstrate whether the calculation is correct or not
Evolving: the basket adapts without political intervention
Incorruptible: no civil servant chooses what counts

It’s the application of the Libertarian Libertarianism principle: trust data, not institutions.

D.7 — References

References [96] to [102] in the general bibliography document the theoretical and empirical foundations of the DPB.

Return to chapter VIII