TOWARDS A GENERAL THEORY OF

INFRASTRUCTURE AND THE ECONOMY

Åke E. Andersson, JIBS, Jonkoping, Sweden (ake.andersson@ju.se)

David Emanuel Andersson, ShanghaiTech University, Shanghai,

China

The games of the markets and economic development have always taken place on an arena of the combined material and non-material infrastructure.

There are two fundamental attributes of

infrastructure:

1.It is a public good that many firms and

households can use at the same time.

2.It is much more durable than other capital.

Synergetics

The theory of synergetics as applied to chemical and physical processes

uses a subdivision of phenomena according to their typical time scales and

the scope of their effects. This subdivision is also advantageous when

applied to the infrastructure and its impact on market phenomena.

Haken (1978; 1983) offers a clear presentation of the theory of synergetics.

Sugakov (1998) presents the synergetic modeling strategy with a

subdivision of equations according to their relevant time scales and

collectivity of impacts.

Synergetics (1978-) Advanced synergetics (1983-)

Physics:

Laser

Super-conduction

Ferromagnetism

Physics:

Laser

Bénard effect

Hydrodynamics

Plasma physics

Solid state physics

Chemistry:

Bénard effect

Chemistry:

Belousov-Zhabotinsky processes

Brusselator

Oregenator

Biology:

Hyper-cycle (Eigen)

Biology:

Biological clocks

Coordinated muscle operation

Morphogenesis/evolution

Immune system

Computer science:

Pattern recognition

Self-organization/parallel computing

Reliable systems

Scope of effects

Time scale (speed of change)

Fast Slow

Individual (private) Ordinary goods:

Short-term equilibrium

Spatial general equilibrium

Market entrepreneurship

Short term prices

Private capital goods

(machinery, buildings, human

capital):

Growth of capital

Market entrepreneurship

Interest rates

Long-term prices

Collective (public) Information/communication:

Networking

Product diffusion

Material and non-material

infrastructure:

Networks

Knowledge

Institutions

Political entrepreneurship

EQULIBRIUM TRADE

VALUE

C Connectivity of network

Kaufmann´s conjecture:

If the number of links exceeds

0.5 times the number of nodes

then there will be a bifurcation

into an almost total

connectivity of all nodes.

There are three fundamental periods of bifurcations or phase transitions

in the economic history of Europe:

1. The First Logistical Revolution from the 12th century;

2. The Second Logistical (or Commercial) Revolution in the 16th century;

3. The Third Logistical (or Industrial) Revolution) in the late 18th and 19th

centuries.

ESTABLISHMENT OF NEW TOWNS AND CITIES IN EUROPE 1100 - 1950

F IRST LOGISTICAL REVOLUTION SECOND THIRD

Urban

population

Four largest

towns

Amsterdam

SECOND LOGISTICAL REVOLUTION WITH FOCUS ON THE

NETHERLANDS

REDUCED TRANSACTION COST

Like Smith, Heckscher claimed that industrial revolution was institutional:

1. The Enlightenment with a belief in science and democracy

2. The steady decline of the power of the central state and the

commercial cities,

3. The use of common law in Britain and the USA,

4. The freedom of internal and external trade and

5. The protection of private property rights

were the essential institutional infrastructure needed to provide the

necessary conditions for economic development and the efficient working of

the competitive economy.

Institutions, networks and knowledge were primary causes

New resources and new technology were secondary innovations

London 959 000 2 804 000 2.9

Manchester 90 000 338 000 3.8

Liverpool 80 000 444 000 5.6

Birmingham 74 000 296 000 4.0

Bristol 64 000 154 000 2.4

Sheffield 31 000 185 000 6.0

Leeds 53 000 207 000 3.9

Table Growth of population in English towns from 1800 to 18601800 1860 Relative growth

THIRD LOGISTICAL REVOLUTION WITH INITIAL

FOCUS ON BRITAIN AND LATER THE WHOLE

NORTH ATLANTIC COAST

The OECD-countries, and especially their advanced regions, are

in a process of transformation - away from the industrial system

into a globally extended post-industrial system of C-regions.

In these C-regions the production system is increasingly being

based upon the exploitation of the

1. New Communication Networks,

2. Cognitive skills of the populations,

3. Creativity in scientific research and R&D, increasing the

4. Complexity of the goods produced and marketed globally.

5. A new informal institutional Culture based on post-materialistic

values.

Thefourth logistical revolution

A creative society with new scientific knowledge infrastructure

1. At the end of the 19th century many scientists believed that the end of science had come. Nothing could have

been more wrong. The whole body of Post-Newtonian physics was slowly abandoned in favor of relativity theory

and quantum theory with later to lead to great technological and even greater political consequences.

2. From the 1930s new mathematical theories of importance for information and communication technology were

created by Alan Turing and John von Neumann.

3. The foundation of the emerging Nano-technology and the new material science technology as proposed by

Richard Feynman on December 29th 1959 at the annual meeting of the American Physical Society.

4. Crick and Watson revolutionized genetics leading to gene technology and other parts of biotechnology, which

have become a rapidly growing part of applied biology and medicine.

The fundamental rule is that these findings in pure and applied

mathematics quickly nowadays become publically accessible and yet have

delays of many decades before making a technological and economic

impact in terms of innovations and major private capital growth and

eventually determining equilibria in the markets.

The world of science is now dominated by major metropolitan

regions in Europe, USA and East Asia.

Rank 1996-1998 2002-2004 2008-2010

City region SCI papers City region SCI papers City region SCI papers

1 London 69,303 Tokyo-Yokohama 81,798 Beijing 100,835

2 Tokyo-Yokohama 67,628 London 73,403 London 96,856

3 San Francisco Bay

Area

50,212 San Francisco Bay

Area

56,916 Tokyo-

Yokohama

94,043

4 Paris 49,438 Osaka-Kobe 54,300 Paris 77,007

5 Osaka-Kobe 48,272 Paris 53,005 San Francisco

Bay Area

75,669

6 Moscow 45,579 New York 51,047 New York 70,323

7 Boston 42,454 Boston 49,265 Boston 69,250

8 New York 41,566 Los Angeles 44,401 Seoul 67,292

9 Randstad

(Amsterdam)

37,654 Randstad

(Amsterdam)

44,094 Randstad

(Amsterdam)

65,527

10 Los Angeles 37,437 Beijing 42,007 Osaka-Kobe 60,615

11 Philadelphia 29,376 Moscow 41,001 Los Angeles 58,176

12 Berlin 24,514 Seoul 33,083 Shanghai 50,597

COUNTRY CITYREGION REGIONAL

PRODUCT 2020

GROWTH RATE

2005-2020

CHINA BEIJING 259 6.6%

UK LONDON 708 3.0%

JAPAN TOKYO 1602 2.0%

FRANCE PARIS 611 1.9%

USA SAN

FRANCISCO346 2.4%

USA NEW YORK 1561 2.2%

USA BOSTON 413 2.4%

KOREA SEOUL 349 3.2%

NETHERLAND

S

AMSTERDAM

ROTTERDAM

120 2.5%

JAPAN OSAKA 430 1.6%

USA LOS ANGELES 886 2.2%

CHINA SHANGHAI 360 6.5%

INDIVIDUAL

(PRIVATE)

ORDINARY MARKET GOODS

1. General Equilibrium models from

Walras, Cassel, Wald, Arrow-Debreu

to Sonnenschein/Mantel, and Smale

2. General Spatial Equilibrium model of

location and trade in two-dimensional

space or on network ( Beckmann/Puu;

Nagurney)

PRIVATE CAPITAL GOODS:

MACHINERY,

BUILDINGS,

HUMAN CAPITAL

1. Von Neumann theory of capital growth and

interest.

2. Programming models of location of capital

From Weber/Launhardt models to

integer programming of facility location

COLLECTIVE

(PUBLIC)

INFORMATION/COMMUNICATION

Models of exchange mechanisms and of

diffusion and interaction of ideas

(Hurwicz, Saari, Mansfield,

Granovetter)

INFRASTRUCTURE:

NETWORKS, KNOWLEDGE,

INSTITUTIONS

(Theories formulated e.g. by Pirenne, Braudel,

Heckscher, Schumpeter, North, Montesquieu,

Assume a dynamic system of N ordinary differential equations that can be divided into

two groups of equations.

The first group consists of m fast equations; the second group consists of (m + 1 ,…,

N) slow equations.

Tikhonov’s theorem states that the system

d𝑥𝑖/dt= 𝑓𝑖 (x,g); i = 1,…,m (fast equations); General equlibrium equations

ε d𝑔𝑗/dt=𝑓𝑗(x,g) ≈ 0; j = m + 1,…,N (slow equations); Infrastructure equations

has a solution if the following conditions are satisfied:

1. The values of x are isolated roots.

2. The solutions of x constitute a stable stationary point of 𝑓𝑗=0 for any x, and the

initial conditions are in the attraction domain of this point.

For each position of the slow subsystem, the fast subsystem has plenty of time to

stabilize. Such an approximation is called “adiabatic” (Sugakov, 1998; Haken, 1983).

SOLVABILITY OF A DIFFERENTIAL EQUATION SYSTEM WITH FAST (GET) AND

SLOW (INFRASTRUCTURE) EQUATIONS