Guidelines for a study of whole human beings,
not just homo oeconomicus.
Methodological guidelines to the description
of societies and economies, renouncing to methodological individualism.
The fundamental difference between evolutionary
and neoclassical economics relies on the concept of time.
Building on the former, the paper allows for
opening new venues of data analysis such as temporal
4. The unity of economic disciplines
Specialization in University departments and
chairs, nurtured by and reflected in the hyperspecialization of
scientific journals, is hiding the underlying unity of economics
(macroeconomics, industrial economics, regional economics, microeconomics,
labour economics, international economics, etc.) and business (marketing,
organization, administration and control, corporate finance, etc.).
Such disciplines are in a matrix structure with vertical disciplines
referring to the institutional sectors (e.g. public finance), industries
(e.g. banking, manufacturing, tourism, networks etc.), types of
countries (e.g. economics of development) and issues so important
that would require an ad-hoc approach (income distribution and inequality,
innovation, sustainable development, etc.). Innovation economics
seems to be a small niche, whereas it is the core of the evolutionary
We object to such separation and we have systematically
built the research and the teaching at the Economics Web Institute
as an hyper-text connecting key concepts
across nominal disciplinary barriers.
Just as for an example, we think that cutting-edge
advancement in business sciences, such as social marketing and Living
Labs, highlight issues that should be tackled also by microeconomics.
5. Substantive examples of intertwined micro,
meso and macroeconomic theory embedding key methodological insights
of evolutionary economics
A sharp systematic list of differences of the
consumer theory under neoclassical and evolutionary economics. it
is an entry point to many key concepts that economics share with
marketing and other disciplines.
5.2. Agent-based models: a structured set
of consumer rules and a testbed for general routines
The most typical formal tool in evolutionary
economics is agent-based modelling, by which all agents are
individually modelled and emerging properties can arise. In
this paper, an extensive treatment of consumers in agent-based
possible models is provided. In
this other paper, the key concept of "routine" is
introduced and you are given a testbed for comparing results from
the implementation of routines with real data in an interpersonal
validation procedure for agent-based models.
5.3. Companies dynamics
with competition on a multiplicity of leverages (technology,
product differentiation, prices,
advertising,...) and persistent
profits, more or less turbolent market shares, etc. are common presence
in evolutionary industrial dynamics.
In this paper, an exploration of
modelling about companies is provided, introducing issues of structural
fragility between real and financial markets. The dual problem of
labour market and micro-macro success
is a key concern. A comprehensive view of market structure is presented
5.4. Macroeconomic dynamics in a graph representation
With time delays and varying elasticities, macroeconomic
variables are interconnected and they can be usefully represented
by network graphs. We have applied this visualisation to a more
traditional model here; however,
this graphical language should be used also for the "Schumpeter
meets Keynes" macroeconomic evolutionary tradition.
6. The distance of economics from physics
and biology, the connections to history and geography
Economics for too long has been drawing from
natural sciences, and even from theories that became obsolete in
their respective science. The neoclassical atomistic view of consumers
and firms draws on a rational mechanics before the XX century new
physics (with the theory of relativity, quantum physics and the
principle of indetermination). It reflect a pre-Freudian psychology.
Since economics should rooted in the analysis of human beings, the
reference to natural science should be weakened. This applies to
physics (where atoms do not have a will and do not evolve) but also
to biology (which has been approached by evolutionary economics
but need to be taken not too literally). People and companies do
have a birth, development and death, but the lack of any goal in
biological actions is at odds with humans' projects (which build
upon the past and have a tension towards the future).
By contrast, we think that economics need to
speak a language which can have a dialogue with history and with
(anthropic and bioclimatic) geography. We need to upgrade from the
Methodenstreit in the XIX century, where a vision of history totally
deprived of inner logics and alternatives was skipped in favour
of a type of mathematics that seemed to promise tractability and
generality. Today we need to recognize that our models generate
alternative histories and patterns that contain both random and
non-random components (drawing from necessity, will and power distribution).
Conversely, we expect from historical analysis to draw lessons,
find patterns, rules of change, and be conducted under value judgement,
helping us in coping with the key issue of our age.
6.1. Sources of inspiration and metaphores
Useful metaphores and analogies for describing,
understanding, and modelling economic actions should draw on everyday
life, not come from physics. Biology can be a very interesting source,
provided one does not overstretch specific keywords.
6.2. Comparing history-friendly evolutionary
models with empirical realities
book, a chapter is devoted to the way emerging properties in
both real and artificial worlds (including history-friendly
models) become the main line of conjuction between the two (ch.
16). At the micro-level, our golden
rule is that agents should be given rules that can be enquired
in surveys with real human beings.
7. Which causality? What's
an acceptable explanation for evolutionary economics
In evolutionary economics, you explain a certain
situation (e.g. a configuration of values and structures) by taking
a step back in time, describing a historical state, offer certain
dynamics (laws of motion) which generate the current and future
(alternative) states and a "final stage", chosen with
some criteria. You don't regress back ad
infinitum; you accept that there was a certain past and
you detect and demonstrate modifications of it. The explanation
is the way things change. This is in contrast with neoclassical
explanation that relies on the equilibrium concept. Explanation
is the formal demonstration that the state is optimal (in the sense
of Nash, Pareto, etc.). It's an instantaneous equilibrium (e.g.
between demand and supply), where all agents are maximising something
and don't want to introduce further changes. If something exogenously
(thus unexplainable) change, a new equilibrium is reach instantaneously
(indeed: timelessly, since it's just the crossing point of curves
and the solution of a system of equations where time is out). Even
when there is a talk of time and
the utilization of differential equations gives the appearance of
time, everything is reversible.
Instead, in the evolutionary paradigm all events
take time; they cumulate and multiply over an irreversible time,
with an arrow from the burden of the
past to the tension towards the future. Their inertial development
and delays in transmission from a variable to another, thanks to
agent-to-agent microdynamics, provide a "time window"
in which the observer (an analyst
empowered by the theoretician's production) can understand and
envisage what is going to happen, while recognising that the multiplicies
of factors at play and dynamic influences engender key uncertainties.
The actions of humans can change the future. A forecast can lead
to action that avoid the forecasted events. It's falsification is
not a failure, but a scientific success. In this sense, we are anti-Popperian.
For instance, in consumer theory, an important explanation
of current purchases is rooted in the cumulative
bundle of past purchases. On a broader scale, cities are historically
stratified built and non-built environments, deriving from past
investment and current activities, including urban
regeneration. In a simple formula, Past + innovation
= current state.
8. Multi-dimensional representations of parametres
and outcomes of simulation models
book, a few chapters are devoted to graphical methods to represent
10+ parametres in the same sheet to provide ways to give insights
on the high non-linearities typical of our modelling way (ch. 12-15).
9. Emerging properties and stylized facts
in models and in empirical data as a way to validation
morphogenesis is an innovative approach to generate all possible
states-of-the-world and changes in a micro-meso-macro system as
well as all possible shifts in the emerging distribution of entities.
Here we provide a
well-defined context in which the problem is sensible and meaningful.
By generating a morphospace that is exhaustive of
all possible shapes, you get a structured container to which both
real (empirical) and artificial (model-generated) data structures
can be mapped. Thus you will have precise indications about what
distinguish real from non-real shapes (ie. shapes that are possible
but not empirically detected), as well as how extensively models
can replicate real structures. Comparison of models can be based
on how many (and which) real structures can be generated by them.
We have proposed a specific method of a sub-class of evolutionary
agent-based models here.
Moreover, discovery of new structures become a possibility
for models, substantiating their power. Scientific knowledge gets
a venue for cumulativeness, in the sense that new models may be
directed to generating structures not yet generated by current models
but that exist or that might exist.
10. Qualifying the quantitative and not quantifying
Since Galileo, science has been oriented to measure
and quantify empirical events, in the perspective of finding mathematically
simple relationship across such values, capable of predicting future
values in dependence from variable somehow under the human control.
This approach has mixed technological advancements with the abstract
tools of mathematics, including calculus and systems of differential
equations, with an extension to stochasticity and more sophisticated
However, human experience is qualitative and decisions
are taken without such heavy apparatus, which is the competence
domains of specialists, not of the normal person. Accordingly, economics
and social sciences should give priority to qualitative methods
of investigation on real flows of human
actions. Group decision-making, including interactions (conflict,
cooperation, coalitions, veto powers, etc.), characterise most of
key decisions and their implementation (from dreams to products
and infrastructure, including their cumulative
For humans and human systems, there is a conflict
between precision and truth: the more precise a guess, the higher
the probability of missing the true. If you have to guess the age
of a person on the street, you'll certainly be able to distinguish
an adult from a child. With good chances you will fit the generation.
But the exact year - or day of the year in which he or she was born
become unattainable, with a collapse of methods and of the likelihood
of fitting the right answer. If the precision level goes down to
the minute and second of the birth, the same individual concerned
might not have the answer and no record kept in official registers
could provide it.
Conversely, in agent-based evolutionary models,
a lot of variables appears with their actual numerical values, in
a "deluge" of data that can only be interpreted
in pattern, clusters and qualitative terms. Especially when discussing
policies, the relationships across variables and the right sequence
of instruments should take into account the nonlinearities, the
cumulative and bifurcation effects that make history.
11. Teaching evolutionary economics
Cutting-edge research and teaching should be
connected, in contrast to the easy trick of the neoclassical economics
in which textbooks contain a very unrealistic description that,
if challenged by any reasonable student, is then skipped in favour
of extremely advanced (and unreadable) papers, which do never trickle
down to textbooks back. In this way, a circular reasoning prevents
any objection and closes the paradigm.
By contrast, teaching at EWI alternates the presentation
of the key concepts of economics, redefined
along evolutionary economics lines, and the distribution of real
data (long time series for most countries in the world), so
that the student can detect whether the
overall indications are matched by data. This implements the fundamental
difference between theoreticians
(the teacher) and the would-be analyst (the student). In so
doing, we are aiming at a critical reader who can articulate a long
reasoning, as envisaged in this
book, who literally enters into models (human
participated simulations), and develop an actively critical
attitude, ready to read and react to media coverage of the real
world, aware of interpreting fraameworks and support (or reject)
certain policies to change the
More in general, evolutionary economics puts emphasis
on interactivity in teaching, openness to a plurality of opinions,
dialogue with history and geography more than with natural sciences.
We still need to devise ways to test students and
give marks in a way that is systematically different from the neoclassical
paradigm, since teaching methods, drills and evaluation criteria
are conducive to the establishment to an agreed "normal science"
in T. Kuhn's terms.
12. Evaluation criteria for publication
Normal science needs criteria to orient reviewers
to evaluate, judge and suggest revisions to submitted papers. A
body of formal knowledge is thus constituted. What's important for
evolutionary economics is that papers should offer tools for others
to think, understand and act upon. They can broadly refer:
1. to theory, as a somewhat abstract set of key
concepts, typical connections, tentative hypotheses that hold until
disproofed in a specific case;
2. to history (ages, centuries, and years), geography
(thus countries, sub and supra national regions), and institutions,
including business history, as empirical entities to be understood
and changed (if present and future);
3. to alternatives, from realistic to utopian
and dystopians, as far as goals, policies, tools, attitudes, values
and other similar items are concerned.
A paper does not need to cover all of these aspects;
it can well refer just to one (and even be narrower). Methods do
not need to demostrate usefulness in specific instances (for being
accepted to publication). They only need to demonstrate correctness
under explicit assumptions. We are aware that papers are not monads
(in Leibniz terms): they are not self-sufficient closed worlds.
In another direction, for economics (and other
sciences) to be relevant to policymaking, papers need to be intelligible
and accessible. The typical journal is burdening papers with the
mandatory jargon, equations, and other distancing devices. This
is why at the Economics Web Institute we typically publish very
13. Ethics for evolutionary economics
In the multiple and dynamic outcomes of evolutionary
models and argumentations, where a plurality of agents have a plurality
of interests, including conflictual ones, the economist should take
side and make explicit value judgements, before providing advice
on policies. There is no unified optimization procedure that
may allow her or him to evaluate ours as the best of all possible
worlds. On the contrary, we are always at the crossroad of development
pathways that can be better or worse than the starting point.
Moreover, it may well turns out that a pathway leading to advantages
for a group is damaging
others. Pareto optimality cannot be the ethical guiding principle
of evolutionary economics. On the contrary, we are insisting on
the full responsibility of the agents for the direct and indirect
development pathways connected with their choice, their lack of
it, and of events that require reactive and pro-active action on
14. Connection with world class evolutionary
Some of the reference websites of evolutionary
economics are the Journal
of Evolutionary Economics, Industrial
and Corporate Change and the Sant'Anna
repository of papers. For teaching, see the Journal
of Pluralism and Economics Education.
Fundamental books are the following:
R. R. and Winter S. G., Evolutionary theory of economic change (1982);
Nelson R. R., Dosi G., Helfat C. E., Pyka A., Saviotti P. P., Lee
K., Dopfer K., Malerba F. Winter S. G., Modern evolutionary economics
- An overview (2018)
Shiozawa, Masashi Morioka, Kazuhisa Taniguchi, Microfoundations
of Evolutionary Economics (2016)
paradigm of social complexity: an alternative way of understanding
societies and their economies
Gonzalo Castañeda (2020)
* and, in policy terms, Piana
V. et al. Innovative economic policies for climate change mitigation
15. A strategy for paradigm shift away from
In line with Thomas Khun epistemology, we need
to identify not only logical and empirical flaws in the neoclassical
paradigm but also key anomalies (empirical facts of high
historical importance that stubbornly refuse to be explained with
their paradigm). As unemployment was in the 1930s a key anomaly,
giving rise to the Keynesian revolution (which Hicks tried to capture
back into the neoclassical paradigm and post-Keynesian have succeeded
in fostering), so innovation is an anomaly that cannot be
explained by the hyperrationality and determinism of neoclassical
paradigm. Evolutionary economics has successfully occupied the best
explanation for innovations and their diffusion, paving the way
for a new paradigm.
Our own contribution is to consider climate
change as key anomaly, whose urgency for the XXI century cannot
be underestimated. For it, the simple elements of the neoclassical
paradigm (quantities and prices),
which lead to the neclassical suggestions being limited to quantity
policy (cap-and-trade) and price policies (CO2 taxes) are way too
weak and ineffective. By suggesting innovative policies to cope
with climate change (including innovation-centred but also going
beyond), we are providing a leverage for the paradigm shift.
We need to introduce new key concepts (e.g. Simon's
"bounded rationality", Dosi's "technological trajectory"
or our cumulative bundle)
and demostrate how they improve the capability to explain empirical
and theoretical "facts". We need to have our own default
values for certain functions or schedules (e.g. in terms of costs,
by which we reject the neoclassical default value of increasing
marginal costs in the short run). We need to have our own formal
methods and to avoid the mistakes that we criticize in the neoclassical
approach (e.g. the abuse of mathematics).
Obviously important as they are as departure points,
criticisms to neoclassical paradigm will not suffice for the shift
unless we have convincing alternatives on which the young generation,
the ultimate judge, can draw for insight and guidance.
Embedded in theory, we need to develop scenarios
for the XXI centuries, point at critical juctions across alternative
futures and identify policies and historically powerful subject
capable, if organized, to deviate certain trajectories in favour
of others, evaluated by an explicit set of values but without artificially
forcing utopies on the historical movement of forces.