Social Sciences for the Support of a World of Solidarity Peter Fleissner, Vienna, Austria

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 describestherelationshipbetween Utopia and Science in a morepreciseway, itsays „fromutopiatoscience“) • „(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 Therefore we should not use outdated and failed concepts of neither Socialism nor Nature.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 politico-economic 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.

°^^‚#* ~$}[% .:->>| §x“?+* Cycle of Change: nature-society-nature Reflection = Portraying and Designing the world „the world“ Diffusion Reifying the concepts Interaction Reification

Economic Reality – A Complex Construction Contemporary Capitalism market prices (observed) 7 6 5 4 3 2 1 commodification of information goods/services Information Society: information as commodity, communication as commercial service Public sector taxes, subventions transfers, social insurance Globalized economy International financial capital markets for money, credit, stocks, derivatives Capitalism with perfect competition and fixed capital prices of production labor market Commodity production of self employed exchange values prices ~ labor values commodity/service markets Physical basis 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”).

°^^‚#* ~$}[% .:->>| §x“?+* Cycle of Change: mathematical modeling included Reflecting = Portraying and Designing „the world“ Diffusion Reification Reflection Reification

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 Equationconservation laws; e.g. input-output-tables, national accounting schemes L := l1 + l2 + l3 + l4 R := r1 + r2 + r3 l3 „Unequal quantities of equal qualities sum up to a quantity of equal quality“ l1 l2 l4 r1 r2 „Only the unequal becomes equal“ „Equal quantities must consist of unequal qualities“ r3 L = R

Mathemathic codification 2: Dynamic Balance Equationinventory 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 reality is constructed by „stocks“ and „flows“ Basis for the mirroring of dynamic processes (difference and/or differential equations) x(t) x(t+Dt) t -> t +Dt

+ - y y y x x x Mathemathic codification 3: Behavioral equations cause-effect-schemes; e.g. multi-variate Blalock-model, econometric equations, neural networks x1 D y(t) = f [ x1(t), x2(t),…] y D x2 • Modifications: • linear • nonlinear • stochastic • delays • Feedback -> D

Causal Loop Diagrams Negative feedback: goal seeking, oscillations (D) Target value State value D Positive feedback: exponential growth reaction discrepancy wages Demand for higher wages cost pressure prices

Examples:Input-Output-Model Econometric model D D

Combined Example: Input-Output and Econometric ModelBMWF (Ed.) Mikroelektronik - Anwendungen, Verbreitung und Auswirkungen am Beispiel Österreichs, Wien 1981

Jay Forrester‘s System Dynamics: Basic elements(Software: Dynamo, Stella, Vensim …) Stella Verhulstequation: 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

How to treat Randomness?Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics Randomness essential Randomness non-essential Statistical laws of nature (H. Hörz) In econometrics/ regression analysis treated as residual or error term No randomness

Randomness in Regression Analysis Equation y = y + e y(x) e y y x

„true“ y e residual stochastic part . y forecast y deterministic part How to treat Randomness?Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics Randomness essential Randomness non-essential Statistical laws of nature (H. Hörz): In econometrics/ regression analysis treated as residual or error term No randomness

How to treat Randomness?Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics Randomness essential Emergence of stable structures by changing the properties of randomness (prob. distr. variable) Randomness non-essential Statistical laws of nature (H. Hörz): In econometrics/ regression analysis treated as residual or error term No randomness „true“ y „true“ y e residual stochastic part . y forecast y deterministic part

Austrian Pension Schemes in Comparison Private pension schemes Demographic data and Sccial statistics Amount of pension Creation Of Individuals Social Insurance Pension schemes Amount/type of pension Individual cases HTML-files

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/brownian/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

How to treat Randomness?Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics Randomness essential Emergence of stable structures by changing the properties of randomness (prob. distr. variable) Randomness non-essential Statistical laws of nature (H. Hörz): In econometrics/ regression analysis treated as residual or error term No randomness „true“ y „true“ y e residual stochastic part . . y forecast y deterministic part

How to treat Randomness?Zero Order Cybernetics First Order Cybernetics Second Order Cybernetics Randomness essential Emergence of stable structures by changing the properties of randomness (prob. distr. variable) Randomness non-essential Statistical laws of nature (H. Hörz): In econometrics/ regression analysis treated as residual or error term No randomness „true“ y „true“ y e residual stochastic part . . . y forecast y deterministic part

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) 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 http://members.chello.at/gre/springer/

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:fleissner@arrakis.es

Economic Reality – A Complex Construction Contemporary Capitalism market prices (observed) 7 6 5 4 3 2 1 commodification of information goods/services Information Society: information as commodity, communication as commercial service Public sector taxes, subventions transfers, social insurance Globalized economy International financial capital markets for money, credit, stocks, derivatives Capitalism with perfect competition and fixed capital prices of production labor market Commodity production of self employed exchange values prices ~ labor values commodity/service markets Physical basis use values collective production/appropriation

Layer 1: Use values, collectively produced and appropriated • Mathematicaldescriptionin 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 matrixnotation • Ax + Cx + Sx = x , • where C, and S represent matrices of consumption coefficients and surplus coefficients respectively.

Social Sciences for the Support of a World of Solidarity Peter Fleissner, Vienna, Austria