An essay on industrial classifications

(Article by Bernard Guibert, Jean Laganier and Michel Volle in Économie et statistique No 20, February 1971)

French version: Essai sur les nomenclatures industrielles.

There can be no economic analysis without a classification. Only a classification can give precise enough meaning to the terms that crop up so often in economic reports - "textile industry", "furniture", "steel industry" and the rest. Classifications play an absolutely crucial role, but they tend to be dismissed as tedious. They consist of tiresome lists with only the occasional intriguing oddity to break the boredom. A classification specialist is seen as a real technology geek, and has to be exactly that to answer the seemingly hair-splitting questions (s)he is faced with every day: should the manufacture of plastic footwear come under footwear manufacture or under manufacture of plastic products? What is the distinction between shipbuilding and the building of pleasure boats? Should joinery be classed as manufacture of wood and wood products or as building construction?

The limit of statistics

In French : La limite de la statistique.

We know that statistics is not appropriate to describe a small population. We can certainly count the individuals who compose it, but it will be virtually impossible to go from description to explanation.

In fact, explanation requires that we find in the statistical observation clues that guide us to causal hypothèses, between which we will choose based on the accumulation of past interpretations provided by the theory.

We find these clues in comparing the distribution of a character between different populations (eg, comparing the structure of age between two countries or between two times in the same country) and in looking at the correlation between characters within the same population.

One can always extract a representative sample in a large population, that is to say that distributions and correlations observed in this sample are not substantially different from those that could be observed on the entire population because the clues they provide lead to the same hypotheses.

Here is the test that will tell if the size of a population is sufficient to interpret its statistical description: that population must be able to be considered a representative sample drawn from a virtual population of infinite size whose structure is explained by the same causes that the population considered.

*     *

Some populations are therefore not "statistisable" (please forgive this neologism). For sure we can count their individuals and calculate totals, averages, dispersions and correlations, then publish it all in tables and graphs: but this morass will be impossible to interpret, we cannot move from this description to an explanation.

This is the case, for example, for much of business statistics: it often happens that the production of a branch or sector is concentrated in a few large companies whose number is too low for this population being “statistisable".

There is a remedy: if it is impossible to interpret a statistical description, we will use the monograph. The search for causal relationships at work in the population will no longer consider distributions and correlations, but consider each individual case in its particular history.

Of course history never provides more than assumptions, because the past is essentially enigmatic, but after all statistics also provides in the best case only assumptions... but they are not of the same nature, and the monograph requires a depth of investigation which statistics does not require.

The world of nature is ultra fractal

In French : Le monde de la nature est ultra fractal

Whatever the scale at which they are considered, fractals have the same degree of complexity. This is for example the case of the coast of Brittany: whatever the scale of the map, it is shredded. Magnify the detail of a fractal reveals a pattern similar to that of the entire drawing.

Examination of a natural object - whether the whole universe or a speck of dust - let appears, when the scale is changed, a series of views of the same complexity - but unlike Fractals they are not similar.

Consider the universe. Its geometry is non-Euclidean (space is curved). At the level of everyday experience the geometry is Euclidean. We find clusters of molecules in the grain dust examined by electron microscopy. Later we will encounter atoms, then the probability waves of quantum mechanics. Farther particles appear. We could go on, we could also select other scales ...

In the thinnest detail of nature lies, as in a fractal, a complexity which is equivalent to that of the whole. However each of the scales follows a peculiar geometry. This adds another kind of complexity to the complexity of the fractal. Nature, being essentially complex, is "ultra-fractal."

*     *

The examination of any physical object - your hand, a pencil, a speck of dust - can never achieve a detailed and complete description. This despairs those whose only absolute knowledge can satisfy the thirst for knowledge, but "absolute knowledge" is a mirage consisting of words that should not be juxtaposed.

The destiny of every human being is the both comic and tragic theater of the dialectic between the ultra-fractal world of physical, human and social nature and the world of values that animate his intentions. . This dialectic is the action.

To act he doesn't need an absolute knowledge: he needs only a relevant knowledge, that is to say a knowledge that is adequate to the action he intends to achieve. This knowledge, being expressed in a finite number of concepts, will always be simple compared to the complexity of nature.

The concepts that are necessary to driving - identifying obstacles and signals, anticipating the behavior of other drivers - select for example, in the complexity of the visual spectacle, a finite number of events. It is the same for all our actions: explicit thought is always simple and it is best to reserve to nature the qualifier "complex" ("complex thought", expression dear to Edgar Morin, is an oxymoron) even if a thought can be complicated in the sense that its acquisition requires a long apprenticeship. By cons the process of elaboration of thought is complex because the brain belongs to the world of nature.

*     *

The contrast between the simplicity of thought and the complexity of nature invites to postulate that this complexity is unlimited (that is to say not only infinite as a right line, but without limit). This hypothesis is an axiom because we can neither prove it nor demonstrate the opposite.

This axiom has the consequence that any mathematical theory, that is to say any logical structure based on a non-contradictory battery of axioms, is the model of a phenomenon belonging to the world of nature: thus the non-Euclidean geometries, created as an exercise in pure logic, provided subsequently a model for the geometry of the cosmos). If this was not the case, this theory would be a limit to the complexity of nature.

A mathematical theory can wait a long time or even never encounter the phenomenon it models because, being not revealed by experiment has revealed, this phenomenon remains is buried in the complexity of nature: but we are sure it exists. This confers to the math a radical realism, with an obvious caveat: if any mathematical theory models a phenomenon, it does not model all phenomena. It follows that the ambition of a "Theory of Everything" in physics is a mirage.

Two utility functions

In French: Deux fonctions d'utilité

The classical economic theory (Debreu, Theory of Value, 1959) is based on three elements: the utility function, the production function, the initial endowment that divides ownership of the goods among actors. Starting from these elements one can deduce the vector of relative prices that, directing the exchange, guides the economy to a Pareto optimum.

The elegant simplicity of this model provides it a great power. The general equilibrium is detailed in partial equilibrium, each market being the scene of a supply and a demand. This can be completed by introducing the time: the production function is then modified by the investment.

In "A Suggestion for Simplifying the Theory of Money" (Oxford University Press, February 1935) John Hicks proposed however to fill a gap in this theory. He noted that each agent has actually two utility functions: one describes the satisfaction that comes from consumption, and the other one describes the satisfaction that gives him the possession of a patrimony.

Assets can be classified according to their liquidity. Money, which is the pure liquidity, is readily usable and implies no risk but provides no income. Illiquid assets provide an interest or a rent, but their price is changing: their possession presents a risk of depreciation.

Creative intelligence

(Tranlated from: L'intelligence créative)

Creativity is a mystery. As we tend to spontaneously reproduce our conditions of existence we are fundamentally conservative, even those who call themselves "leftists." How is it then that we may yet evolve?

In any business, in any institution, conservative forces are struggling to ensure the sustainability of the organization and, as we well know, the leaders never understand anything new. The economic reasoning is not enough to explain why so many innovations happen: for an enterprise embarks on a new project it is not enough that innovation seems profitable, the potential profitability must also have been understood or at least glimpsed. How leaders "who never understand anything new" can nevertheless understand finally the value of an innovation?

These two mysteries are similar to the one the evolution of species confront us. If parents pass their genes to their children, how is it that one species can evolve, that forms life takes can diversify? The answer, as we know, lies in the mutations: genes are not transmitted all the same.

Mutations are random, most of them are harmful and their carriers disappear. Some, however, are so positive that they will benefit their holders in the competition for reproduction: hence evolution.

Does not happen in our minds, in our institutions, a phenomenon similar to this one that would explain the creative thinking in the individual and the innovation in the enterprise?

e-conomy

(Translated from e-conomie).

This book was published in 2000 by Economica, 49, rue Héricart, 75015 Paris, ISBN 2-7178-4073-7

The "e-conomy" is based on the synergy between microelectronics, software and network. It is also called "new economy" because it changes the competition on the market, the internal organization of firms and their cooperation.

This is certainly an "immaterial economy" but this characteristic stems from another, more fundamental: the cost of production being virtually independent of the volume produced, it is paid from the initial investment: e-conomy is a "sunk cost economy."

This has profound consequences on the economic equilibrium. The plants are automated, employment lies in design and distribution. The distribution of income is not connected to employment. Enterprises are organized around their information system and differentiate their products to build niche monopoly. Trade occurs through electronic intermediation. The investment being risky, competition is global and extremely violent.

Modeling the "e-conomy" enlightens the game of competition in microelectronics, software, network and in the sectors that use these technologies: broadcasting, airlines, trade. This allows to interpret the evolution of information systems and to diagnose some obstacles.

The "e-conomy" is highly effective but its power can lead to disaster if it is treated in the manner of "laissez-faire". It is therefore necessary to go beyond the economic dimension to consider the requirements of ethics and social cohesion.

Table of Contents: full text access.

List of my books

Table of contents of e-conomy

This book was published by Economica in October 2000. Some details would of course need to be updated, but the structure of the model and of the reasoning remains relevant.

Most of the texts are in French. I shall translate them progressively into English.

Foreword
Acknowledgments
Preface

Part I: The model
1 - Overview (in English)
2 - Increasing Returns
3 - Contemporary technical system
4 - Monopolistic competition
5 – Layer Model

Part II: Areas
6 - Computing
7 - Audiovisual
8 - Dimensioning
9 - Telecommunications
10 - Airlines

Part III: Uses
11 - Information System
12 - Obstacles
13 - E-commerce
14 - Relationship between nations
15 - Putting in perspective