Transcript XIV. Internationale InkriT-Tagung Demokratische Planung

The Seventh WAPE Forum
State, Market, the Public and the Human
Development in the 21st Century
May 25 - 27, 2012
Universidad Autonoma Metropolitana, Mexico City
Social Sciences
for the Support of a World of Solidarity
Peter Fleissner, Vienna, Austria
TU-Vienna, transform!at, http://transform.or.at
Outline
• Introduction: Socialism 21: from utopia to science
=> towards a society of solidarity
• A sketch of the theory of reflection
(„Widerspiegelungstheorie“)
• Simulation in the context of the cycle of change
• Basic elements of mathematical models
• Examples and classification of computer
simulation
• What to do?
Introduction (1/5)
Frederick Engels in „Socialism: Utopian and Scientific“ (The
original title in German describes the relationship between
Utopia and Science in a more precise way, it says „from utopia
to science“)
• „(T)wo great discoveries, the materialistic conception of
history and the revelation of the secret of capitalistic
production through surplus-value, we owe to Marx. With
these discoveries, Socialism became a science. The next thing
was to work out all its details and relations”.
• On the other hand, Engels legacy „The Dialectics of Nature“
offered essential features to posterity how to interpret
natural sciences in the context of a materialistic perspective.
• On the other hand, Marx and Engels showed in their writings
how to analyze both, society and nature, in an integrated
and dialectic way.
Introduction (2/5)
• The materialistic concept of history, the mechanism of capitalistic
production and the dialectics of nature still represent the basis of
left scientific thought, allowing us deeper understanding of the
fabrics of history and nature.
• But: History did not stop with Marx and Engels, nor did all kinds of
sciences and research. History showed qualitative new features and
relations and enriched our understanding of the world.
• Therefore we should not use outdated and failed concepts of
neither Socialism nor Nature.
• We should not repeat the mistakes of the past. We have to apply the
best methods, most efficient concepts, and the deepest insights
human mind has discovered.
• Also it is necessary that the new ideas are not only utopian, but are
also scientific, based on the most developed insights available.
Introduction (3/5)
For a socialism of the 21st century imho four issues have to be taken into
account:
• Concrete pathways towards the “emancipation of labor” (see the
interview with Karl Marx in the Chicago Tribune, 5 January 1879) –
with a focus on ALL kinds of labor, may it be paid or unpaid, male or
female, formal or informal, manual or mental.
• Pathways towards socio-economic and gender-equality
• Establishing a culture of democracy, participation, solidarity,
recognition, inclusion, and conviviality.
• Protecting natural environment, transforming production and its
energy base towards sustainability.
Introduction (4/5)
• We should not work with simplified solutions like to adopt outdated
concepts of society, based on authoritarian rule, or destroying our
social and natural environment. Marx’ demand for emancipation is
not compatible with it.
• Also, a change of our personal life style is needed, foremost in the
wealthy countries of our planet, to be based on a changed mindset.
• But one of the most important areas of change is still the politicoeconomic system. Although there is no ideal way towards a society of
solidarity, there is definitely no hope to reach such goal without a
political transformation of the economy.
• In his paper “Dynamic Modeling towards a Society of Solidarity“ at
the WARP conference Carsten Stahmer described basic features of a
new economic order in Germany. He proposed adequate methods
and tools how to do research along these lines. I will elaborate on
some of these methods.
Introduction (5/5)
• One of the methods where great progress was reached is
mathematical modeling and computer simulation.
• My suggestion is to use this method as a tool to get a clearer and
more consistent picture of the transformation process and the
desired structure and dynamics of the economy of the future.
• Of course, do not focus only on simulation! We have to apply it in
close connection with other methods and tools of social sciences,
political economics, mathematics and statistics in general.
• In the following I illustrate where political economics and computer
simulation can be located within the “cycle of change”, within a
transformative and reflexive practice of changing society.
• In my perspective, computer simulation is a special way of rule
based reflection of specific structures and dynamics of the world.
Cycle of Change: nature-society-nature
Reflection = Portraying and
Designing the world
§x“?+
*
„the world“
°^^‚#*
.:->>|
Reification
Interaction
Reifying the concepts
Diffusion
~$}[%
Economic Reality – A Complex Construction
7
Contemporary Capitalism
6 Information Society:
information as commodity, communication as commercial service
5 Public sector
Globalized economy
4 International financial capital
Capitalism with perfect competition
3 and fixed capital
Commodity production
2 of self employed
Physical
1 basis
market prices
(observed)
commodification
of information
goods/services
taxes, subventions
transfers, social insurance
markets for money,
credit, stocks, derivatives
prices of production
labor market
exchange values
prices ~ labor values
commodity/service markets
use values
collective production/appropriation
Human beings as elements of the Cycle of Change
reflecting their practice (“Widerspiegelung”)
• Reflection = „Portraying“ and „Designing“ the world, based on human
practice, striving for survival/a better life, in cooperation and/or in
competition.
• Human beings are embedded in the “world” and are part of it, but at
the same time they are changing it according to their needs.
• In changing their environment they they change also themselves.
• Lenin: metaphor for the brain: camera portraying the world in a
rather passive way. It is essential to stress also the active (“design”)
part of the reflexion process: Even the coat of the photographic
paper will not map all the incoming electromagnetic waves, but
selects certain frequencies and intensities of light. Only those
selected leave their marks on the photo and are visible to other
people. The same is true for a mirror (this is another analogy
frequently used – compare the German term “Widerspiegelung”).
•
Cycle of Change: mathematical modeling included
„the world“
Reflecting = Portraying and
Designing
§x“?+
*
°^^‚#*
.:->>|
Reification
Reflection
Reification
Diffusion
~$}[%
Cycle of Change: mathematical modeling included
• Simulation models are
–
–
–
–
–
–
–
–
Based on human thinking and projection
In a social framework
Symbolic or physical reification/codification
Complementary to experiments
More than induction
More than deduction
More than reduction
Between theory and application
• Types of simulation models
•
•
•
•
•
Econometric (based on emprical data)
Input-output (patterns of economic interaction)
Neural networks (highly nonlinear)
Systems dynamics models (world consists of stocks and flows)
Agent based models/microsimulation (macro&micro levels)
Basic Relations in simulation models
Strictly deterministic relations
(inspired by Rainer Thiel; Germany)
 Definition equations
 Static balance equations
 Dynamic balance equations
 Behavioral equations
Stochastic relations
(inspired by Herbert Hörz, Germany)
 Randomness as residual/error
 Randomness essential, but constant
 Randomness essential, but variable
Mathemathic codification 0: Definition equations
Main element: “variable” with an associated quality/dimension and a
certain quantity
Types of definition equations:
A: A new variable of same dimension is constructed by other variables
of the same dimension, but different quantities
Example: Circumference of a triangle is equal to the sum of the length
of the three sides.
B: A new variable of new dimension is constructed by other variables
of the same dimension, but different quantities
Example: Area of a rectangle is the product of its length and width.
C: A new variable of new dimension is constructed by other variables
of the different dimension and different quantities. wir
Example: Labour is force times distance, turnover equals unit price
times volumes.
Although definition equations look simple, their identification was a
cumbersome and erroneous process (like “energy” or “force”)
Mathemathic codification 1:
Static Balance Equation
conservation laws; e.g. input-output-tables, national accounting schemes
L := l1 + l2 + l3 + l4
l3
„Unequal quantities
of equal qualities
sum up to a
quantity of equal
quality“
l1
l2
l4
R := r1 + r2 + r3
r1
r2
„Only the unequal
becomes equal“
r3
L = R
„Equal quantities
must consist of
unequal qualities“
Mathemathic codification 2: Dynamic Balance Equation
inventory equation, dynamic population balance, capital accumulation,
dynamic accounting schemes
Dx(t, t+1)
x(t+Dt) = x(t) + Dx(t, t+1)
The only qualitative
difference between left and
right: Position in time
x(t)
x(t+Dt)
t
->
t +D t
reality is constructed by
„stocks“ and „flows“
Basis for the mirroring of
dynamic processes
(difference and/or
differential equations)
Mathemathic codification 3: Behavioral equations
cause-effect-schemes; e.g. multi-variate Blalock-model, econometric
equations, neural networks
x1
D
+
y
y(t) = f [ x1(t), x2(t),…]
D x2
Modifications:
•
y
y
linear
•
nonlinear
•
stochastic
•
delays
•
Feedback ->
y
x
x
x
D
Causal Loop Diagrams
Negative feedback: goal
seeking, oscillations (D)
Target value
Positive feedback:
exponential growth
discrepancy
wages
Demand for
higher wages
cost pressure
prices
State value
D
reaction
Examples:
Input-Output-Model
Econometric model
D
D
Combined Example: Input-Output and Econometric Model
BMWF (Ed.) Mikroelektronik - Anwendungen, Verbreitung und Auswirkungen am Beispiel Österreichs,
Wien 1981
Jay Forrester‘s
System Dynamics:
Basic elements
(Software: Dynamo, Stella, Vensim
…)
STOCK VARIABLE
INFLOW VARIABLE
OUTFLOW VARIABLE
Stella
AUXILIARY VARIABLE
Verhulst equation:
dx / x = alfa (1 –x ) dt
Forrester‘s World Dynamics:
Causal Loops Diagram
Forrester‘s World Dynamics (1971):
Dynamo-Diagramm
Forrester‘s World Dynamics:
Stella Diagram
Mathematical Simulation Models:
Paradigm Shifts and Reification
Cybernetics 0. Order
Cybernetics 1. Order
Cybernetics 2. Order
linear
nonlinear
nonlinear
static
dynamic
dynamic
unidirectional
feedback
feedback
aggregated
aggregated
individuals (variable
numbers of agents)
deterministic
deterministic/nonessential randomness
essential
randomness/changing
prob distributions
very abstract
less abstract
more realistic
Mathematical Simulation Models:
Paradigm Shifts and Reification
Cybernetics 0. Order
Cybernetics 1. Order
Cybernetics 2. Order
linear
nonlinear
nonlinear
static
dynamic
dynamic
unidirectional
feedback
feedback
aggregated
aggregated
individuals (variable
numbers of agents)
deterministic
deterministic/nonessential randomness
essential
randomness/changing
prob distributions
very abstract
less abstract
more realistic
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
Randomness nonessential
Statistical laws of
nature (H. Hörz)
No randomness
In econometrics/
regression analysis
treated as residual or
error term
Randomness essential
Randomness in Regression Analysis
Equation y = y + e
y(x)
e
y
y
x
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
Randomness nonessential
Statistical laws of
nature (H. Hörz):
No randomness
In econometrics/
regression analysis
treated as residual or
error term
„true“ y
.
y
e
residual
stochastic
part
forecast y
deterministic part
Randomness essential
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
No randomness
Randomness nonessential
Randomness essential
Statistical laws of
nature (H. Hörz):
Emergence of stable
structures by changing
the properties of
randomness (prob.
distr. variable)
In econometrics/
regression analysis
treated as residual or
error term
„true“ y
.
y
e
residual
stochastic
part
forecast y
deterministic part
„true“ y
Private
pension
schemes
Amount of
pension
Demographic data and
Sccial statistics
Austrian Pension Schemes in Comparison
HTML-files
Social
Insurance
Pension
schemes
Amount/type
of pension
Individual cases
Creation
Of Individuals
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
No randomness
Randomness nonessential
Randomness essential
Statistical laws of
nature (H. Hörz):
Emergence of stable
structures by changing
the properties of
randomness (prob.
distr. variable)
In econometrics/
regression analysis
treated as residual or
error term
„true“ y
.
y
e
residual
stochastic
part
forecast y
deterministic part
„true“ y
Einstein’s explanation of Brownian motion
• The big particle can be considered as a dust particle while the smaller
particles can be considered as molecules of a gas.
• On the left is the view one would see through a microscope.
• To the right is the supposed explanation for the jittering of the dust
particle
• http://galileoandeinstein.physics.virginia.edu/more_stuff/Applets/brownia
n/brownian.html
People leave a room
Leaving a room without panic: velocity v0 = 1 m/s.
• Efficient because of good coordination
• http://angel.elte.hu/~panic/pedsim/sim/No_Panic.html
Leaving a room with panic: velocity v0 = 5 m/s.
• Irregular and inefficient due to arching and clogging at the bottleneck (door)
• http://angel.elte.hu/~panic/pedsim/sim/Panic.html
Leaving a room with injured (Stampede): Verletzten: velocity v0 = 5 m/s.
• If a critical "squeezing" force of 1600N/m is exerted, a person is injured. (The
squeezing force is measured as the sum of the magnitudes of radial forces acting
on the pedestrian). Injured people block the exit.
• http://angel.elte.hu/~panic/pedsim/sim/Stampede_N0200_Fc1600.html
An asymmetrically placed column in front of the door can avoid injuries.
http://angel.elte.hu/~panic/pedsim/sim/Column_5.html
Overview of outcomes
Simulation
200 Persons
Escaped before Injured
t=45s
before t=45s
No Panic:
No column,
No injured
90
-
Panic:
No column,
no injured
65
-
Stampede:
No column,
Injured do not move
44
5
With column:
72
0
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
No randomness
Randomness nonessential
Randomness essential
Statistical laws of
nature (H. Hörz):
Emergence of stable
structures by changing
the properties of
randomness (prob.
distr. variable)
In econometrics/
regression analysis
treated as residual or
error term
„true“ y
.
y
e
residual
stochastic
part
forecast y
deterministic part
„true“ y
.
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
No randomness
Randomness nonessential
Randomness essential
Statistical laws of
nature (H. Hörz):
Emergence of stable
structures by changing
the properties of
randomness (prob.
distr. variable)
In econometrics/
regression analysis
treated as residual or
error term
„true“ y
.
y
e
residual
stochastic
part
forecast y
deterministic part
„true“ y
.
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
No randomness
Randomness nonessential
Randomness essential
Statistical laws of
nature (H. Hörz):
Emergence of stable
structures by changing
the properties of
randomness (prob.
distr. variable)
In econometrics/
regression analysis
treated as residual or
error term
„true“ y
.
y
e
residual
stochastic
part
forecast y
deterministic part
„true“ y
..
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
No randomness
Randomness nonessential
Randomness essential
Statistical laws of
nature (H. Hörz):
Emergence of stable
structures by changing
the properties of
randomness (prob.
distr. variable)
In econometrics/
regression analysis
treated as residual or
error term
„true“ y
.
y
e
residual
stochastic
part
forecast y
deterministic part
„true“ y
How to treat Randomness?
Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics
No randomness
Randomness nonessential
Randomness essential
Statistical laws of
nature (H. Hörz):
Emergence of stable
structures by changing
the properties of
randomness (prob.
distr. variable)
In econometrics/
regression analysis
treated as residual or
error term
„true“ y
.
y
e
residual
stochastic
part
forecast y
deterministic part
„true“ y
agent based models
Example: „The blind and the lame“
Two interacting worlds …
• world A: physical world
(classical mechanics)
• world B: world of information and symbols
(words without meaning)
agent based models
…and two interacting agents
agent 1: the blind
• Is able to
–
–
–
–
jump
hear
Interpret sound he/she hears
And act accordingly (jump)
http://members.chello.at/gre/springer/
agent 2: the lame
• Is able to
– See the width of the obstacle
– Produce sound (with a trumpet)
– Can link the width of the obstacle to the pitch of the sound
An invitation to cooperation
• We should start a global network of scholars
• accompanying political processes of change towards new
forms of socialism of the 21st century
• by adequate mathematic modeling tools,
• also taking advantage from already existing groups or
activities (see e.g. GINFORS, an Anglo-German Foundation
research policy initiative: Creating sustainable growth in
Europe, http://www.agf.org.uk/currentprogramme/CreatingSustainableGrowthInEurope.php).
• starting with parallel work on a national basis,
• later on combining national models to regional,
• finally global ones.
Tentative research agenda (1/3)
• Collecting existing ideas of types of socialism of 21st century.
I do not believe in a unique model of socialism, although
various features have to be in common. Each country has its
own history, tradition and institutions of social decision
making and co-operative forms. Nevertheless it would be
useful to have a kind of standardized description of each
model type, and also a list of pros and cons to make
comparisons and evaluation easier.
• Collecting existing transition concepts towards socialism - in
particular, if they are controversial -, elaborating, investigating
and comparing them within specialized satellite research
groups, maybe linked to existing research units or research
projects.
Tentative research agenda (2/3)
Examples of controversial or open questions resp. ill
defined areas of research:
• Commodity markets vs. moneyless transfer methods
• Redistribution process: minimum wage vs. basic income - in
money terms or in kind
• Working time regimes and remuneration concepts for simple
and complex labor
• Price structures guided by labor values, prices of production
or other community targeted pricing?
• How to preserve the natural environment and transform the
carbon based production towards a more sustainable system?
• How to design and organize political participation and
democratic control?
Tentative research agenda (3/3)
• Identifying adequate software tools and creating a pool of
platforms for free use/open source (e.g. VENSIM, NETLOGO,
FABLES, PAJEK). Probably the methods should include system
dynamics, agent based and network types of modeling.
• Developing national simulation models of socialism in each of the
countries, documenting them in a standardized way, making the
simulation models available to other researchers for testing and
improving. If applicable the simulation models should be updated
according to progress in implementation of socialist features in the
individual countries.
• Collecting models, comparing and trying to integrate them.
• Feeding the results back to the actual political process in various
countries, updating the model structure according to practical
experiences in the concrete socialist implementation process.
Institutional context (proposal)
• Discussions and meetings in real life could be organized by the
World Advanced Research Project (WARP) and the Center for
Transition Sciences (CTS).
• The annual World Conferences on Political Economy (WAPE)
could be a suitable forum for discussion and support of these
activities.
• The network could become a global platform of elaboration,
discussion and exchange of concepts, methods and models of
economies in transition towards a society of solidarity, the
socialism of 21st century.
Thanks for your attention!
Contact:
[email protected]
Economic Reality – A Complex Construction
7
Contemporary Capitalism
6 Information Society:
information as commodity, communication as commercial service
5 Public sector
Globalized economy
4 International financial capital
Capitalism with perfect competition
3 and fixed capital
Commodity production
2 of self employed
Physical
1 basis
market prices
(observed)
commodification
of information
goods/services
taxes, subventions
transfers, social insurance
markets for money,
credit, stocks, derivatives
prices of production
labor market
exchange values
prices ~ labor values
commodity/service markets
use values
collective production/appropriation
Layer 1: Use values, collectively produced and appropriated
•
•
•
•
Mathematical description in terms of Leontief’s input-output scheme to
represent the economy in terms of use values.
Each row and each column represent one branch of production or firm
It reflects the degree of division of labor.
The matrix of technical coefficients A represents the technology of the
economy. The element aij gives the amount of goods of industry i needed
to produce one unit of output of industry j.
x (output vector) contains all use values produced. It can be split by kind of
use of goods into Ax (demand for intermediate goods) and y (final demand).
The following famous formula is called the primal problem
Ax + y = x
y (final demand) can be split it into c (consumption) and s (surplus product =
capital investment)
y = c + s.
or in matrix notation
Ax + Cx + Sx = x ,
where C, and S represent matrices of consumption coefficients and surplus
coefficients respectively.
Layer 2: Labour values, small commodity production
The dual Leontief model deals with
the unit prices
pA + q = p
p …row vector of unit prices q …
unit value added.
After substitution of q by life unit
labor input l we get the basic formula
how to compute Marx’ labor values v
vA + l = v.
We can split l into wages, w, and
profits p and get
l = w + p.
Marx used different symbols
W = C + V + M,
where W is the labor value,
• C constant capital,
• V variable capital and
• M surplus value.
In our notation:
v = vA + w + p.
Production
Consumption
Labor
Money
Self-employed
laborers
Commodities
&
Services
Structure of „classical“ labour values
all industries are value producers
c - constant capital, v - variable capital, m - surplus value
Austria 2003: 57 industries (percent), r= 0.883
m
v
c
Nr
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Industry
Agriculture, hunting
Forestry, logging
Fishing, fish farms
Mining of coal and lignite
Extract. o. crude petrol. a. nat. gas, min. o. metal ores
Other mining and quarrying
Manufacture of food products and beverages
Manufacture of tobacco products
Manufacture of textiles
Manufacture of wearing apparel
Manufacture of leather, leather products, footwear
Manufacture of wood and of products of wood
Manufacture of paper and paper products
Publishing, printing and reproduction
Manufacture of coke, refined petroleum products
Manufacture of chemicals and chemical products
Manufacture of rubber and plastic products
Manufacture of other non-metallic mineral products
Manufacture of basic metals
Manufacture of fabricated metal products
Manufacture of machinery and equipment n.e.c.
Manufacture of office machinery and computers
Manufacture of electrical machinery and apparatus n.e.c.
Manufacture of radio, television equipment
Manuf. of medical, precision, optical instruments, clocks
Manufacture of motor vehicles and trailers
Manufacture of other transport equipment
Manufacture of furniture; manufacturing n.e.c.
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
Recycling
Electricity, gas, steam and hot water supply
Collection, purification and distribution of water
Construction
Sale and repair of motor vehicles; automotive fuel
Wholesale and commission trade
Retail trade, repair of household goods
Hotels and restaurants
Land transport; transport via pipelines
Water transport
Air transport
Supporting a. auxiliary transport activities; travel agencies
Post and tele-communications
Financial intermediation, except insur.
Insurance and pension funding, except social security
Activities auxiliary to financial intermediation
Real estate activities
Renting of machinery and equipment without operator
Computer and related activities
Research and development
Other business activities
Public administration; compulsory social security
Education
Health and social work
Sewage and refuse disposal,sanitation and similar act.
Activities of membership organizations n.e.c.
Recreational, cultural and sporting activities
Other service activities
Private households with employed persons
Stucture of labour values
no surplus of services, variable exploitation rates
c - constant capital, v - variable capital, m - surplus value
Austria 2003: 57 industries (percent)
m
m
v
v
c
c
Layer 3: prices of production, capitalist economy at perfect
competition
Capital
Investment
Production
Consumption
Labor
workers
capitalists
Profits
Wages
Commodities
&
Services
Layer 3: prices of production, capitalist economy at perfect
competition
Marx provided us with the following solution for p:
p = v (K + C) (1 + r), where r = v (I - A - C) x / v (K + C) x and v = l (I – A)-1
K…matrix of capital coefficients per unit of output, I …identity matrix with ones in
its main diagonal, otherwise zeros, and r is the average rate of profit.
This method can be generalized to an iteration process which leads us to the
solution proposed by von Bortkiewicz in the beginning of the 20th century (which is
equal to the solution of an eigenvector/eigenvalue problem). The generalized
iteration scheme inspired by Marx is:
pi (K + C) (1 + ri) = pi+1 where ri = pi (I - A - C) x / pi (K + C) x,
ri … average profit rate at iteration step i. (Different turnover times neglected,and
assume they are all equal to one.
The link to labor time is kept up because the iteration scheme starts from the
solution of equation (3) for v
p0 = v = l (I – A)-1, where r0 = p0 (I - A - C) x / p0 (K + C) x
Marx‘ solution: Prices of production
c - constant capital, v - variable capital, m - surplus value
Austria 2003: 57 industries (percent), r=0.901
m
v
c
von Bortkiewicz: Prices of production
c - constant capital, v - variable capital, m - surplus value
Austria 2003: 57 industries (percent), r=0.952
m
v
c
Layer 3: prices of production, capitalist economy at perfect
competition
Marx provided us with the following solution for p:
p = v (K + C) (1 + r), where r = v (I - A - C) x / v (K + C) x and v = l (I – A)-1
K…matrix of capital coefficients per unit of output, I …identity matrix with ones in
its main diagonal, otherwise zeros, and r is the average rate of profit.
This method can be generalized to an iteration process which leads us to the
solution proposed by von Bortkiewicz in the beginning of the 20th century (which is
equal to the solution of an eigenvector/eigenvalue problem). The generalized
iteration scheme inspired by Marx is:
pi (K + C) (1 + ri) = pi+1 where ri = pi (I - A - C) x / pi (K + C) x,
ri … average profit rate at iteration step i. (Different turnover times neglected,and
assume they are all equal to one).
The link to labor time is kept up because the iteration scheme starts from the
solution of equation (3) for v
p0 = v = l (I – A)-1, where r0 = p0 (I - A - C) x / p0 (K + C) x
Layer 4: Real capital, financial capital
Capital
Investment
Production
Consumption
Labor
Profits
Wages
workers
capitalists
credits
financial
earnings
Financial capital
credits
financial
earnings
Commodities
&
Services
Layer 4: Real capital, financial capital
In Layer3 the following equilibrium conditions were assumed
Wages equal consumption: wx = pCx = pc
Profits equal capital investment: πx = pSx = ps.
If we want to reflect money explicitly in the economy, we need to get rid of such
equilibria. Therefore we replace them by the following savings equations:
Money savings/increase of debt of households, shh , are given by the following
relations
shh,t = w t – 1’C t + rl ,t mhh,t
if mhh,t > 0
shh,t = w t – 1’C t + rb,t mhh,t
if mhh,t < 0
m…money stocks, rl …interest rate for lending money to banks, rb … interest
rate for borrowing, rl < rb
Similarly, we have money savings/increase of debt of firms, sf , as a result of
profits, minus capital investment and borrowing/lending money (time indices
suppressed)
sf = π – 1’S + rl mf
if mf > 0
sf = π – 1’S + rb mf
if mf < 0
Layer 4: Real capital, financial capital
The financial assets/debts of firms, households and state are held by the
banks. Assets are rewarded by banks with an interest rate r_borrowing, credits
have to be paid for with an interest rate r_lending (r_lending > r_borrowing).
The payments of interest are deducted from / added to the surplus variables or
wage income. Of course, the redistribution does not change the amount of
total GDP.
In this simplified version the income of banks is given by the sum of all interest
payments of all sectors including the household and government sectors minus
all interest payments of the bank for deposits of firms, households of
government (if any):
{ -rl mhh. (if mhh. > 0)
xbanks = S.
-rl mf. (if mf. > 0) }
+
{ -rb mhh. (if mhh. < 0)
-rb mf. (if mf. > 0) }
Including a financial sector creates a secondary distribution of income.
Layer 4: Real capital, financial capital
Dynamic equations
The dynamics for physical capital is given by
K a,t+1 = K a,t + Sn = K a,t + (S - Sd),
where Sn is the matrix of net capital investment per time unit, and Sd the scrap
matrix (or depreciation matrix) of capital. The relation between gross and
net investment is given by
Sn = S - Sd
The money capital stock of firms, banks and the government debt can be
represented by a row vector mf,t , the one of households by mhh,t
Money(+)/Debt(-) stocks of households, mhh,t , at time t, is given by:
mhh,t+1 = mhh,t + shh,t
Money(+)/Debt(-) stocks of firms, mf,t, at time t:
mf,t+1 = mhh,t + sf,t
Layer 5: Real capital, financial capital, public sector
Produktion
Investition
UnternehmerInnen
IndustrieProfite
ArbeiterInnen
Angestellte
Löhne
Gehälter
credits
financial
earnings
Konsum
credits
Financial capital
Taxes
subsidies
financial
earnings
Taxes
transfers
Public sector
Layer 5: Real capital, financial capital, public sector
For a simplified mathematical model one could include the following
variables to represent activities of the state :
• t_ind
tax rate of indirect taxes
• t_profits
tax rate of profits
• t_wages
tax rate on wages
• indirect taxes
• direct taxes (wage tax, profit tax)
• public consumption
• public investment
• contributions to the social insurance system
• transfers to households
• subsidies to enterprises
•
Including a public sector creates a tertiary distribution of income
Layer 6: Information society:
Commodification and Commercialization of cultural activities
•
As already has happened in history with land and work, under the
headline of „information society“ the market conquers the sector of
cultural activities, writing, singing, dancing, chatting, performing any
kind of arts, doing research etc.
•
This is done by an efficient interaction of the economy, technology
and law.
•
Technology allows for freezing volatile information on a carrier of
digital or analogue data and also reviving it. It transforms cultural
activies into information goods, knowledge goods and cultural goods.
•
By Law (e.g. Intellectual Property Rights) copying is forbidden.
Therefore all properties of commodities are created and they can be
exploited by private capital.
•
Three kinds of markets have been established:
• A market of data carriers with content (CDs, DVDs, tapes etc)
• A market of communication services (mobile communication,
Internet)
• A market of devices (PCs, Laptops, TV-sets etc)
Economic Reality – A Complex Construction
7
Contemporary Capitalism
6 Information Society:
information as commodity, communication as commercial service
5 Public sector
4 Globalized economy
International financial capital
3 Capitalism with perfect competition
and fixed capital
2 Commodity production
of self employed
1 Physical
basis
market prices
(observed)
commodification
of information
goods/services
taxes, subventions
transfers, social insurance
markets for money,
credit, stocks, derivatives
prices of production
labor market
exchange values
prices ~ labor values
commodity/service markets
use values
collective production/appropriation
Layer 7: Contemporary capitalism
To approximate the system of contemporary capitalism, a dynamic input
output model on stylized facts was constructed on two JAVA-based
simulation platforms: ANYLOGIC (proprietary) and FABLES (free of
charge). As a next step the model will be filled with actual data.
The following control variables allow for a change of the distribution of
value added:
•
•
•
•
•
•
•
•
r_b
r_l
t_ind
t_profits
t_wages
deprec_rate
interest rate for credits
interest rate for assets at banks
tax rate of indirect taxes
tax rate of profits
tax rate on wages
depreciation rate (for the moment related to
output, not to fixed capital).
leverage_factor
limits the maximum amount of credits given by
banks with respect to their financial assets.
fraction of public investment on total investment
Output, savings, prices of six sectors of the economy and
savings of households (preliminary results)
Capital stock and money/debt stock of each of the six sectors
of the economy and of households (preliminary results)
Thanks for your attention
Contact:
[email protected]
http://transform.or.at
Wassily W. Leontief, Scientific
American, Sept.1982, pp.152-164;
Nobelpreis für
Ökonomie1973
10-years forecast/comparison with actual data 1990
fast diffusion of micro-electronics in Austria
Indikator
GDP prices 1976
1990 actual
1990 1990 forecast
standard with melectronics
1051 Mrd ATS
1113 Mrd ATS
1190 Mrd ATS
unemployed
165.795
220.000
386.000!
Wage labour
2.925.396
3.221.000
3.056.000
male
1.716.754
1.883.000
1.802.000
female
1.208.642
1.338.000
1.254.000
39,4
39,6
39,9
Exports
526 Bill ATS
619 Bill ATS
624! Bill ATS
Imports
470 Bill ATS
631 Bill ATS
648! Bill ATS
Working hours
Hours/week
Status 0
Status 1
Status 2
Status 11
Status 12
Status 21
Status 22
neither employed not retired
blue collar
white collar
blue collar ret by invalidity
blue collar ret by age
white collar ret by invalidity
white collar ret by age
11
1
12
abroad
birth
0
dead
21
Transition
diagram
2
22
Total Population Austria
2003-2050
8600
8550
8500
8450
8400
8350
Yellow line: life expectancy
up to 90 yrs by 2050
8300
8250
8200
8150
8100
2003
2008
2013
2018
2023
2028
2033
2038
2043
2048
Retirement Age
(Invalidity) White Collar Workers, male
62
60
58
56
54
52
50
2003
2008
2013
2018
2023
2028
2033
2038
2043
2048
Interactive Simulation
A Combined
System Dynamics/
Econometric Model
G. Bruckmann/P. Fleissner:
Controlling the National Economy
(Am Steuerrad der Wirtschaft)
Springer 1989