|
home page
PAE
Review index
|
sanity, humanity and science
post-autistic economics review ( formerly "newsletter")
Issue no.
10; 7 December 2001 back issues at www.paecon.net
subscribers in over 100 countries latest economic
journalism at GEN
Subscriptions
are free, To subscribe, email "subscribe". To unsubscribe,
email "unsubscribe". To
subscribe a colleague, email"
subscribe colleague" and give their email address. Send
subscriptions
to: pae_news@btinternet.com
If
you wish, we
will resend this issue to you as an attached document. Just send us the
message "resend".
In this issue:
- Anne
Mayhew, Some
Old But Good Ideas
- Bruce Edmonds, Against: a priori theory.
For: descriptively adequate computational modelling
- Jason Potts,
John Nightingale,
An Alternative Framework for Economics
- Alan Shipman,
Ignoring Commercial Reality
- Steve Keen, The Russian Defeat of Economic Orthodoxy
Some
Old But Good Ideas
Anne Mayhew
(University of Tennessee, USA)
As
Post-Autistic Economics moves beyond criticism and on to the task of building
a more
relevant and robust economic science, one challenge is to develop a theoretical
framework
that will guide pluralistic borrowing from a variety of disciplines and
approaches. Some
useful guidelines for development of such a framework may be found in the
history of
American economic thought as it
developed and flourished in the first half of the 20th
century. During the first five decades
of that century a group of economists who taught at
a number of the major American Universities created the reasonably coherent,
pluralistic
and non-autistic approach to the study of economies and economic issues known
as
institutionalism, an approach that dominated American economic thought during
the
interwar years.
Four basic themes characterized this approach:
(1) Regularities
in the organization of both production and distribution are the same as all
other social regularities in that they are human creations and are subject to
change by
human intervention. In other words, there is no “natural economy”
and there is no reason to
assume that an idealized market system is historically or morally prior to
other social
systems. This perception was rooted
in American pragmatic philosophy which saw
individuals as recipients of inherited ideas, but also as active agents
capable of perceiving
problems and imagining new possibilities.
The basic autistic assumption of isolated
individuals interacting from the beginning of human history through exchange,
but little
changed by it, was rejected in favor of the notion
that humans are always social beings.
Mind, thought, and consciousness are products of active processes of human
interactions,
processes that do not end, but evolve through time.
This understanding of the social and inquiring nature of humans is crucial to
two tasks that
must confront post-autistic economic analysis: the understanding of variation
in economic
organization across time and space, and
variation in human understanding and behavior
across the lifetime of individuals.
The idea that we all start with a set of inherited ideas and
perceptions is crucial to explaining economic and all other forms of social behavior. A
simple example: young American children learn at an early age that food can
be acquired
by spending money and that money is acquired by “hard work and
thrift.” They may learn
that beggars without money for food are victims of hard luck; they are as
likely to learn that
such beggars are undeserving of receiving money because they have not worked
hard or
been thrifty. In this process the idea
of a market economy with justified and even desirable
income inequality is instilled. Young
children in other times and places have learned
different things and have different understanding of distribution and its
relationship to
production.
What the pragmatists and institutional economists also stressed is that all
people are
capable of questioning the ideas that they inherit. We all know that many Americans
come to question the conventional wisdom that the poor have earned their own
economic
fate, but note that the questioning itself is via a social process of
questioning, of contact
with others with different ideas (contact that is now global as well as
local), and of formal
learning. In the process, ideas of
what constitutes justice and injustice are changed, as
are ideas of how to achieve justice.
It is this active process that produces the evolution
of thought and consciousness and that leads to change in human culture and
organization.
(2) It
follows from #1 that as humans create their economies, they can change those
economies to solve perceived problems.
A central part of economic analysis should
therefore be the identification of problems, which is to say to patterns of
production and
distribution that do not accord with the goals of society. This analysis should lead to
reasoned advocacy of reform through normal political and social
processes. This aspect
of pragmatism underlay the reform activities of the 1920s and 30s in the
United States,
activities that included creation of the Federal Trade Commission, the Social
Security Act
that provided income security to the elderly, unemployment compensation,
regulation of
securities trading and much, much more.
(3) While the Institutional economists saw their
role as one of criticism and advocacy,
they did not purport to offer permanent solutions or design of utopias. They were reformers,
not revolutionaries who could advocate permanent solutions. Instead, the pragmatic
solutions to problems were offered with the sure knowledge that these
solutions would
create new problems, and with the sure knowledge that as science and
technology
changed the interaction of humans with the physical world so too would that
change alter
the relationship of humans with each other.
Central to institutionalist thought was the
perception that the advent of industrial as opposed to craft production had
altered the
relationship of producers of products and of producers to consumers. New rules,
regulations and patterns of interaction were required and those very rules,
regulations and
patterns of interaction themselves created new conflicts that would lead to
more change
via a process of cumulative causation.
Not only was the path of change difficult to predict,
but it was impossible to formulate an ideal toward which such change
tended. In other
words, it was futile to speculate on the conditions that would prevail in an
ideal economy.
(4) In
order to understand the processes of ongoing change, and in order to
understand the
human organization of production and distribution, a variety of tools were
found to be useful.
Wesley Mitchell, one of the most active of institutionalists
and founder of the National
Bureau of Economic Research was a strong advocate of descriptive statistics
and of
statistical analysis as a way of discovering the actual (as opposed to
idealized) patterns of
economic behavior.
Others borrowed the methods of anthropology and sociology to
discover patterns of behavior through rough
observation and participation. Studies
of the legal
system as a working system of evolving human rules was central to the
approach taken by
John R. Commons and his students. The study of economic history was vital for
understanding patterns and processes of change. In all of the institutionalist
work, the
tools were just that: ways to achieve the goal of understanding the patterns
of human
behavior and how they changed. The tools did not define the
discipline.
There is much to be learned about the early 20th century American
economy from reading
Thorstein Veblen, John R.
Commons, Wesley C. Mitchell, John Maurice Clark, Rexford
Tugwell and the others who brought the pragmatist
approach to the study of economics.
What is more important is that these authors and others offer rich examples
of how to
build an economic science that would, in the words of Tony Lawson, describe
and explain
event regularities. They can teach us
much about how to do non-autistic economic science.
SUGGESTED CITATION:
Anne Mayhew (2001) “Some Old But Good
Ideas”, post-autistic economics review : issue no. 10, December,
article 1. http://www.btinternet.com/~pae_news/review/issue10.htm
|
Advertisement
New from Routledge's
econo0mics
as social theory
Intersubjectivity in Economics:
Agents and Structures
£22.99 / $36.95
Editor: Edward Fullbrook
Contributors: Frank
Ackerman, John B. Davis, Jean-Pierre Dupuy, Armin Falk, Ernst Fehr,
Edward Fullbrook, Shaun P. Hargreaves Heap, Geoffrey M. Hodgson, Frédéric Lebaron, Thierry
Levy, Paul Lewis, Roger Mason, Anne Mayhew, Paul Ormerod,
Ralph William Pfouts, Jochen
Runde, S. Abu Turab Rizvi, Laurent Thévenot,
Peter Wynarczyk
Readers' Comments:
”All the contributions of this book
share the same theoretical conviction: if we want to understand economic
interactions, we need to go beyond the opportunistic and superficial
approach that has dominated the discipline for half a century or more. The result of the book is full of promises
for the future.” André Orléan, École Normale Supérieure/CEPREMAP
”Edward Fullbrook has edited an excellent
set of essays in which economic concepts are debated in terms of their
intellectual significance. The authors
show a rare capacity to use, in clear language, the most advanced outcomes
of economics theory. In this way
they develop a critique that touches upon the very assumptions sustaining
the body of conventional economics.
Human needs and desires emerge as stronger concepts that the notion
of commodities-based utility.”
Joseph Halevi, University
of Sydney and Université Pierre Mendès, France
“This collection is a major contribution to intersubjectivity
studies. Veblen
would applaud, but so too must all those interested in the psychology of
economic activity and the methodological problems and opportunities of a
world comprised of problematic, relativist, and combined deliberative and nondeliberative activities.” Warren J. Samuels,
Michigan State University
”If you are an economist you need to read this book, because
economics needs to start treating its “agents” and
“actors” as people. The
“Prudence-Only” model we’ve had since Bentham
gets better as science when it acknowledges life. Without controls on Love and Justice and
Courage the “Prudence-Only” agent is just bad economic
science. Be a good scientist: get
the book.” Deirdre
McCloskey, University of Illinois at Chicago
This volume tackles the most important issue facing the theoretical foundations
of economics, namely the need to go beyond the tools and concepts
bequeathed to us by the early neoclassicals. It’s very much about
time.” James K. Galbraith,
University of Texas at Austin
Available Online at:
Amazon.com
Amazon.co.uk
WHSmith.co.uk
Blackwells
(includes summary and contents list)
Barnes
& Noble US
Routledge.co.uk
|
Against: a priori theory
For: descriptively adequate computational modelling
Bruce
Edmonds (Center for Policy Modelling,
UK)
Introduction
Autistic
economics is rightly held in disregard by an increasing number of people.
Unfortunately it has sullied the reputation of all kinds of formal social
modelling by
association. On the other hand there
is sociology and discursive social theory but here
there is a huge gap between its thorough and detailed observation and its
abstract
theoretical terms. I suggest that the
way forward is not to abandon all types of formal
modelling but rather to use expressive computational systems to build descriptive
models
of observed dynamic processes. This
aims to combine the relevance and realism of social
observation with the rigour of formal computational models [6]. This is
a bottom-up attempt
to bridge the gap and move towards a science of social phenomena
(see [4] for a discussion
of this). This is a consequence of accepting that economics will have to be
more like biology,
which employs lengthy observation and description before modelling, than
physics (or, at
least, than the economist’s perception of physics). This is what some
of the researchers in
the new field of social simulation are attempting to do (for an insight into
this field see
JASSS [1]).
Modelling complex systems
Complex systems are precisely those for which it is extremely difficult
to deduce its
behaviour from first principles. For example, it is extremely unlikely that
one would be able
to predict the behaviour of a particular animal purely from a priori
principles, rather one
would have to spend a lot of time observing and describing its actions to get
a hold on the
intricate contingencies of its actual behaviour. With complex systems,
observation and
description must come first and only much later (when the detailed
behavioural mechanisms
are well understood) is it sometimes possible to encapsulate some of
these in a predictive
model. It seems likely that much economic behaviour is complex in this way.
This would not
be surprising since it arises as the consequence of the intricate
interactions between
members of a species that is characterised by the variety and contingency of
its behaviour.
But if we are
to give up the chimera of numerical predictive models built using a priori
principles, doesn’t that mean we have to give up formal models and
rigour? I would say that
we do not. What it does mean, however, is that we have to use formal and
computational
models that are capable of capturing the detailed behaviour as it is
observed. We then need
to constrain these models as much as possible using observations of
the relevant
phenomena, both in terms of the trajectories of the causal processes as well
as the
outcomes; in terms of qualitative information (such as anecdotal accounts) as
well as
quantitative data. Pinning down our models using only the verification of
predictive outcomes
and an insistence on formal simplicity will not be enough. We will need to
capture the
workings of the processes stage by stage as they are observed.
In order to
perform this feat we will need systems that are up to the task of expressing
the
qualitative cognitive and social processes that economic phenomena are rooted
in. These
more expressive systems come at a price, they are not simple and they allow
for multiple
representations of the same outcomes. However there is no need for them to be
any less
formal than a set of differential equations.
I am
suggesting that we should attempt to construct models of quite specific sets
of
observations that are more akin to a description than a theory. It is, of
course, impossible
to lose all assumptions in the construction of any model, but the
point is to move towards
using fewer and less drastic a priori assumptions and use more
qualitative and quantitative
constraints derived from observation the processes under study. The purpose
is to provide
an unambiguous framework for the exploration of the possible processes within
these
constraints so as to inform the direction of further observation and
modelling (I attempt this
in [5]). This is not merely static description, for we are not concerned
with static phenomena,
but dynamic description of particular sets of observations using the
techniques of
computational and cognitive modelling. The extent to which such models are generalisable to
other phenomena will only become apparent when it is compared with other
descriptive
models, just as the general characteristics and markings of a species of
animal may only
become clear when several descriptions of the animals are compared.
To many my
position will seem too pessimistic. They may be still hoping for some
brilliant
‘short-cut’ to a predictive model, that will allow them to miss
out the laborious business of
observing and describing the underlying processes. However, I would point out
that the
science of biology has become enormously successful using the methods I am
suggesting
and, once we have accepted the amount of field work that our subject matter
entails, equal
success might be achieved in economics.
Using agent-based models
The move to agent-based models in economics can be seen as part of a
transition to a more
descriptive style of modelling. An agent-based model must, by its very
nature, model a real
actor with a computational agent (in some way), so there should be a
one-one correspondence
between actors and agents. It is not necessary to assume that the law of
large numbers will
iron out the messy details. The model can allow the global properties to
emerge (or not)
without having to assume these details away. Real economic actors are
(almost always)
encapsulated, i.e. they will have an inside where the decision making is done
which is largely
hidden from view, and a series of ways in which they interact with the
outside environment
which are more easily observable. The agents that are used to model these
actors are
encapsulated in a directly analogous way.
However, many
agent-based modellers do not see the need for any greater descriptive
accuracy than this. Thus when inspecting the learning, inference and decision
making
processes that an agent uses in such a model, one often finds something as
unrealistic as
a simulated annealing algorithm or standard genetic algorithm. These are
algorithms that
have been taken from the field of computer science, regardless of their
descriptive
appropriateness for the actual economic actors being modelled. Now it is
possible that in
some circumstances such algorithms will give acceptable results for some
purposes, but
at the moment we can only guess whether this is the case. It is not only that
we do not
know the exact conditions of application of each algorithm, we do not know of
even a single
real circumstance where we could completely rely on any of these
‘off-the-shelf’ algorithms
to give a reasonable fit.
To be clear, I
am not criticising looking to computer science for ideas, structures and
frameworks that might be used in modelling. Being a bounteous source of
possible types
of process is one of the computer science’s great contributions to
knowledge. What I am
criticising is the use of such algorithms without either any justification of
their
appropriateness or modification to make them appropriate.
Thus many
agent-based models fail to escape the problems of more traditional models.
They attempt to use some ensemble of interacting agents to reproduce some
global
outcome without knowing if the behaviour of the individual agents is at all realistic.
The wish
for the ‘magic’ short-cut is still there.
Constraining our models
Clearly what is needed is some way of modelling the behaviour of economic
actors by
computational agents in a credible way. As noted above, real economic actors
are probably
complex in the sense that it is unlikely that we will be able to deduce their
actions using a
priori principles. What we can do is to constrain our models as much as
possible from what
we do know. There are several sources of such knowledge.
1. We can ensure that the global outcomes of the model match the global
outcomes of real
actors in the standard way.
This is a start, but when one is using a more expressive formal system like a
agent-based
computational one then this is unlikely to sufficiently constrain the
possible models. In other
words, there are likely to be many computational models which produce the
same global
outcomes.
2. Ensure that the actions of the individual actors match those of our
agents’ behaviour as
they learn and interact.
Axtell and Epstein [2] set out some criteria for the performance of
multi-agent simulations
in [6] In this: level 0 is when a model caricatures reality at
the global level through the use
of simple graphical devices (e.g. animations or pictures); level 1 is
when the model in is
qualitative agreement at the global level with empirical macro-structures; level
2 is when
the model produces qualitative agreement at the agent level with empirical
micro-structures;
and level 3 is when the model exhibits quantitative agreement at the
agent level with
empirical microstructures. The constraint I am suggesting corresponds to
their level 3 with
an emphasis on the agreement over time.
3. Look to the emerging guidelines coming from cognitive science as to the
sort of learning
and decision processes humans might use.
Now the task of the cognitive scientist is difficult, but such scientists are
able, at least, to
exclude some mechanisms for modelling behaviour and make suggestions for the
mechanisms derived from a lot of observation. It is notable that many
successful sciences
take their ultimate grounding for the behaviour of their components from
outside their
discipline (e.g. chemistry is grounded in physics).
4. Simply
ask the actual actors why they made the decisions they did and how they
learnt
what they learnt, i.e. use some of
techniques of business history.
This method has its known drawbacks, but can be successfully used, especially
when
confirmed by other methods. In any case it is likely to produce more useful
and accurate
information about the real behaviour of actors than is implicit in many of
the assumptions
used in economics. Edmund Chattoe has recently written a more thorough catalogue of
the ways in which we can collect social data to properly constrain our modeling [3].
Conclusion
Bad science starts with a technique and changes the problem to fit it,
good science starts
from the problem and chooses the appropriate technique. With the advent of cheap
computational power and flexible modelling software we have the appropriate
techniques for
performing that essential abstraction task called description. In this case it is a description
that captures the dynamic, emergent and complex cognitive and social
processes we
observe to be involved in economic exchange.
References
1. Journal of Artificial Societies and Social
Simulation (JASSS), http://jasss.soc.surrey.ac.uk.
2. Axtel, R.L. and J.M. Epstein, Agent-based
Modelling: Understanding Our Creations. The Bulletin of the Sante
Fe Institute, 1994. Winter 1994:
p. 28-32.
3. Chattoe, E., Building
Empirically Plausible Multi-Agent Systems - A Case Study of Innovation
Diffusion, in
Socially Intelligent Agents -
creating relationships with computers and robots, K. Dautenhahn,
et al., Editors.
In press, Kluwer. p. Chap. 13.
4. Conte, R., et al., Sociology and
Social Theory in Agent Based Social
Simulation: A Symposium. Computational
and Mathematical Organization Theory, In
press. http://www.cpm.mmu.ac.uk/cpmrep82.html.
5. Edmonds, B., Towards a Descriptive
Model of Agent Strategy Search. Computational Economics, 2001. 18(1).
http://www.cpm.mmu.ac.uk/cpmrep54.html.
6. Moss, S., Relevance, Realism and
Rigour: A Third Way for Social and Economic Research. 1999, Centre for
Policy Modelling, Manchester Metropolitan University: Manchester. http://www.cpm.mmu.ac.uk/cpmrep56.html.
SUGGESTED CITATION:
Bruce Edmonds (2001) “Against: a priori theory For: descriptively adequate computational
modelling”, post-autistic economics review : issue no. 10,
December, article 2. http://www.btinternet.com/~pae_news/review/issue10.htm
An Alternative Framework For Economics
John Nightingale, (University
of New England, Australia)
Jason
Potts, (University of Queensland,
Australia)
The award of the Nobel Prize in Economics for Information
Economics gives an opportunity
to illustrate why this form of economic analysis is a dead end. The theories
advanced by the
Prize winners, Akerlof, Stiglitz
and Spence, are ad hoc auxiliary assumptions tacked onto
the neoclassical, and neowalrasian, hard core. The
work of these auxiliaries is mainly ex
post rationalisation rather than prediction or explanation.
Is modern economic theory just a morass of special cases? It is important
that some
alternative framework be found to allow valid generalisation to once again
characterise
economic theory, and this time, not fail to provide robust empirical results
in the absence
of ad hoc auxiliaries. Is there such
an alternative? We can report that
there is, and that it
promises all that is missing from orthodoxy.
The autism of
orthodoxy stems from its treatment of the human agent, who is mindless and
does not interact with other agents.
The broad solution then is to develop a framework in
which agents carry knowledge and interact with other agents to use and create
knowledge.
This is the essence of the new evolutionary economics (e.g. Loasby, Knowledge, Institutions
and Evolution in Economics, 1999).
In The New Evolutionary Microeconomics, Potts (2000)
argues that all heterodox thought shares a common ontological foundation in
the view that
the dynamics of evolving economic systems are in the space of
connections. An economy
is a complex system of interactions, and the dynamics of an economic system
involve
change in the connective structure of the system. Three main themes can be
found to share
this common foundation.
The first is the evolutionary economics revived by Nelson and Winter
(1982). This builds on
Book IV of Marshall’s Principles, and on Schumpeter’s
theories of cycles and innovation,
creative destruction and greed for monopoly profit. Market capitalism is a
restless system
of experimentation in pursuit of sustainable rents based on private
knowledge. This is
fundamentally a neo-Darwinian approach.
It has been argued in Nightingale and Laurent
(Darwinism and Evolutionary Economics, Edward Elgar,
2001), that social and cultural
theory is ultimately swallowed by Darwin’s ‘universal
acid’, as Dennett so tellingly put it
(Dennett, Darwin’s Dangerous Idea, 1995). Complexity and self-organisation theory is
the
most recent advance of the neo-Darwinian project (Foster and Metcalfe, Frontiers
of
Evolutionary Economics, 2001).
The second is the New “Old Institutionalism”, which is about how
agents with minds
construct and use complex systems of rules.
Current orthodoxy has largely ignored the
cognitive dimension of human behaviour.
This strand of course began with Veblen,
finding
new life in the development of both evolutionary thought and its application
to human
institutions. American Institutionalism saw the difficulties of Veblen’s imprecision and
contradictions, and neglected the biological metaphor introduced by Veblen in favour of a
vague developmental notion of institutions as historical determinants of
economic outcomes.
Current research on Veblen’s themes often
ignores his contribution, but continuity of ideas
remains clear. Organisational ecology,
and other resource and systems based views of the
firm, is one such well-defined field on inquiry. Evolutionary psychology is another (L.
Cosmides and J. Tooby,
(1994) ‘Better than Rational’ AER,
84: 327–32). Both these are
converging in the economist’s sphere, seeking explanations of selection
processes and
system regularities in habits, routines and the causes for
organisations’ and other institutions’
persistence as well as entry and exit. The means by which knowledge is
conserved as well
as transformed and created is at the centre of this program.
The third is the complex systems view of economic systems. Methodological
Individualism
is one of the principles on which modern orthodox economics is based, as an
article of faith,
and a justification for the reductionism that has bedevilled areas such as
macroeconomics.
The antithesis of this is an organic approach that can be traced to, among
others, the
American pragmatist philosopher Charles Sanders Peirce. In essence, the concept of a
system rather than some atom within an aggregation of atoms, as the entity of
interest,
distinguishes the organic approach from MI.
Geoff Hodgson’s Economics and Evolution
(Polity Press, 1993) has an extended exposition of the importance of this
branch of theory.
Reductionism, one of the fundamentals of MI, insists on ‘micro
foundations’ for any
explanation. An organic, systems or
hierarchical approach insists that this demand is not
only irrelevant but misleading. Such a demand results in attempting to use
inappropriate
theory, and has long been abandoned in the physical and life sciences (ever
heard of a
sub-atomic theory of ocean waves?).
This range of heterodox economic theories, all of which are close relatives
of very orthodox
theories in other fields of science, are united against the neowalrasian orthodoxy, even with
the ad hoc auxiliaries added by this year’s Nobel prize winning
information economists, by
a single critical feature. They are all theories of connections between
knowledge carriers,
be these individuals (in a theory of intra-household decisions), firms (in a
theory of market
structure), or sectors or national economies (in a theory of macroeconomic
performance).
They are all dynamic theories of systems evolving endogenously, subject to
external
shocks, of course. They are theories in which knowledge rather than
information is key.
They are not Newtonian field theories, in which every point is connected to
every other.
They can all be subsumed analytically as elements and the connections between
them.
These dynamic systems theories of evolutionary organisation are all graph
theory constructs.
In other words, using the language of graph theory, the geometry of elements
and connections
provides a unifying frame with which to develop these alternative economic
theories.
This, then shows there is a progressive alternative to autistic neoclassical/neowalrasian
economics. The emerging synthesis of evolutionary and self-organizational
approaches into
a framework of complex systems theory is a solid basis upon which to build.
It connects
evolutionary biology and evolutionary psychology to evolutionary economics
(for a popular
science account, see, for example, Stuart Kauffman's At Home in the
Universe, 1995). It
provides analytic methods in discrete mathematics and multi-agent simulation
models. It
is the study of the emergence of order, rather than continuous equilibria. It is
ontologically
well-founded in a growth of knowledge framework where connections are the
prime variables
in an economic system. Such a unified heterodox synthesis may underpin a
broad front of
research advances that do not close off alternatives, but open more to
scientific development.
___________________
Jason Potts is the author of The New
Evolutionary Microeconomics: Complexity, Competence, and Adaptive
Behaviour (2000).
John Nightingale is the co-editor of Darwinism
and Evolutionary Economics, Edward Elgar, 2001.
SUGGESTED CITATION:
Jason Potts and John Nightingale (2001)
“An Alternative Framework for Economics”, post-autistic
economics review : issue no. 10, December, article 3. http://www.btinternet.com/~pae_news/review/issue10.htm
Ignoring Commercial Reality
Alan Shipman
Consumers confronted with a legal monopoly shop around for cost-effective
alternatives.
Rival producers innovate around the patent to supply them. They are helped by
the
monopolist’s growing distance from competitive reality, leaving it to
churn out, ever less
efficiently, products ever fewer people want. If mainstream economists still
bought this
‘Austrian’ story, they’d see their own monopoly in a
starring role. People seeking to
survive in the economy look to journalists for information, financial
commentators for
advice and business schools for education. Academic economists, finding
little market
for their tales of the market, are left chasing shrinking public subsidy
– or privately
dispensing consultancy and forecasts built on different principles from those
they teach
in class.
Inside business schools, the research and teaching for which companies and
students
willingly pay looks very different from those economists peddle. Management
courses and
journals mix their economics with sociology, psychology, natural and computer
sciences,
ethics, and any other discipline whose information and ideas help undertake
or understand
the running of enterprise. Their presentation ranges from macro- and
micro-econometrics
and statistically strip-mined survey data to cross-disciplinary syntheses,
case studies,
anecdotes and sectoral straw polls. Their authors
are an equally diverse mix of full-time
researchers, practising managers, consultants with a foot in each campus and
gurus with
their heads in the sky. They probably resemble the economics departments of
fifty years
ago, with research posts and products accessible to anyone with informed
interest,
however convoluted their career path or maverick their method.
Yet while business literature has much to say on the corporate strategy,
organisational
and consumer behaviour, technology choice, expectation and regulation which
drive the
modern economy, mainstream economists pay it little attention - even when published in
journals as rigorously refereed as their own. Dialogue has died because
neoclassical
economists speak an increasingly exclusive language. Like early
industrialists, they have
found a way of discussing the enterprise by its financial flows, in splendid
isolation from
human and physical stocks. Accounting made it possible to run a company by
numbers,
tracking money and materials to avoid touring plants and talking to
employees. In the
pioneer industrialisers (and de-industrialisers)
Britain and the US, accountants still
outnumber engineers in middle and senior management, and
‘strategy’ offshoots of the
big accounting/auditing firms have wrested the consultancy market from those
who once
practised what they preach.
In the same way, mainstream economists seek knowledge through numbers to stop
the
messy reality of people, processes and politics dirtying their invisible
hands. Missing or
hard-to-measure variables are conveniently proxied
(e.g. model-consistent predictions for
expectations, volatility for risk). Unmeasurable
variables, if theory requires them, are
hammered into measurable shape (e.g. aggregate capital derived from a
whole-economy
‘production function’, bounded rationality recast as rationally
chosen rule-of-thumb). More
usually, what’s not in the National Accounts doesn’t count. In
the neoclassical division of
labour, theorists condense the economy into algebraic symbols, opening its
components
(firms, households, governments) to much more apparently precise analysis
than that of
classical theorists, who debated these phenomena in the raw. Applied
economists can
then ‘calibrate’ the models and ‘compute’ the general
equilibrium, their forecasts’
correctness to two decimal places somehow forgiving their incorrectness when
reality
catches up.
A diplomat posted to a new country studies its history, language, political
system and
social conventions, often taking years to acclimatise before daring to make
big decisions.
An economist flown in by donor government or multilateral lender studies its
national
accounts, and is often dispensing expert advice a lunch-hour after stepping
off the plane.
Just as airline pilots take their cockpit gauges as accurate summaries of
external
conditions, the more ambitious economists claim to fly an economy by
financial newswire
– leaving seat-of-the-pants driving to ‘less developed’
social disciplines, and blaming any
wrong turns or crashes on faulty statistics, or failure of political
passengers’ nerve.
Models have helped the mainstream clarify key concepts (like output gaps and
imperfect
information), explain away anomalies (persistent unemployment becoming
‘voluntary’),
and turn vague tendencies into quantified causal links. By nailing conflicting
approaches
to a common framework, they pinpoint deductive mistakes, and pare down
complex debates
(‘Keynesian’ vs
‘monetarist’, mark-up vs marginal
pricing) to disputes over parameter values.
They establish a standard reporting style [reassuringly close to that of
natural science]
which makes papers easy to read and write, for those who’ve mastered
the maths. Most
importantly, they establish a common debating language. Alternative
contributions remain
imprecise, incomprehensible and dispensable, until ‘formalised’
into a neoclassical model
(and, preferably, estimated from available data).
Thus Marxism can re-enter mainstream debate if formalised as a macro-model
with ‘rational
choice’ foundations (indeed, Bowles’ and Gintis’
AER-published model of capitalist labour
incentives was one of the foundation stones of orthodox principal-agent
theory). March and
Simon’s ‘bounded rationality’ moved from marginalized
management science to mainstream
microeconomics once reformulated as a ‘transaction cost’ to be
optimised alongside
production cost. But such heresies as Austrian economics (tarring the
rational-expectations
modelbuilder with the same brush as the all-knowing
central planner), post-Keynesianism
and Sraffianism (with non-marginalist
price theories), the Cambridge criticism (dismantling
marginalism’s aggregate capital),
institutionalism (denying that all social structures can be
traced to repeated game-play), or classical Marxism (where capitalists’
individual rationality
sums to collective disaster) fall outside the mainstream’s logic,
despite tackling its central
topics.
Economists’ retreat into private language explains their neglect of
relevant information and
explanation outside their model-based world. Anthropologists, ethnographers,
historians
and philosophers have much to say about origins and varieties of
individualism, altruism,
profit maximisation; but these are unnecessary interrogations of
neoclassicism’s ‘a priori’
assumptions, irrelevant if they support these and inconvenient if they
challenge them.
Sociology, psychology and politics give equally rich insights into internal
and external
pressures on (and problems with the outcome of) people’s economic
choices. But unless
(like Jonathan Bendor in sociology, Steve Brams in politics or Kahneman
and Tversky in
psychology) they spell out their ideas in rational-choice, repeated-game
language – so as
to publish in mainstream economics journals – they are firmly repelled
beyond the
disciplinary border.
Instead of engaging with alternatives on their terms, the mainstream tries to
refashion them
into its own. So where such emerging (and emergent) phenomena as social
capital,
market-mediating institutions, interdependent expectations and path-dependent
technical
change appear at all, they do so in selectively interpreted,
model-translated, neoclassically-
readable form. This complicates the presentation (to anyone unschooled in
neoclassical
language and its unspoken assumptions), while often oversimplifying the
argument, by
ditching what cannot be distilled to simultaneous equation.
This ‘imperial’ battle has reached its height in the
confrontation between neoclassical
economics and evolutionary psychology (EP). Like neoclassicism, EP offers an
all-embracing
explanation for unrestricted individual action having functionally efficient,
‘natural’ outcomes;
and for all attempts to guide or manipulate that action being doomed to
inflict collective as
well as individual damage. But whereas neoclassical ‘competitive
selection’ works in the
market period, ensuring that behaviour persists where best suited to the
present time, EP
appeals to paleontological periods, resulting in
persistence of behaviour better suited to
prehistorical than post-industrial times. To turn
EP from usurper into ally, neoclassicists
must assume that the traits ‘hard-wired’ into evolved human minds
are fully consistent
with individual rational choice and rational expectation. Hence the current
quest for game-
based models and simulations equating ‘evolutionary stable
strategy’ with winning
noncooperative game strategy, ensuring that such EP
phenomena as altruism and group
selection amount to nothing more than clever manifestations of
humanity’s universally selfish
streak.
While economists play these games, management schools continue capturing
staff,
students, and research funds from them, because what they teach and publish
is what
their sponsors and customers want to know. They do so without narrowing the
syllabus
down to neoclassical nostrums – because underconsumption
crises, technological
upheavals and panics and persistent disequilibrium are real threats to those
working in
the economy, even if irrelevant to those working on it, and Marx’s
assessment is as
acceptable as Samuelson’s if it helps to steer a way through. Most
bookshops have
emptied their Economics shelves to make room for a bulging Business section.
Business
research passes a ‘market test’ which mainstream market champions
know they would
fail – and so prefer to pass up, in favour of ‘peer review’
which judges quality by conformity
to accepted method, rather than usefulness of results. The consequent
financial rationing
helps neoclassical department heads restrict recruitment to researchers in
their own image.
But it means the mainstream’s abstract art is painting itself into an
ever more (literally)
marginal corner.
___________________
Alan
Shipman is the author of Transcending Transaction: The Search for
Self-Generating Markets (Routledge, Nov. 2001)
SUGGESTED CITATION:
Alan Shipman (2001) “Ignoring Commercial Reality”, post-autistic
economics review : issue no. 10, December, article 4. http://www.btinternet.com/~pae_news/review/issue10.htm
The Russian
Defeat of Economic Orthodoxy
Steve Keen (University of Western Sydney, Australia)
Many
armies have followed a triumphant march into Russia with an ignominious
withdrawal. Orthodox economics is merely the latest invader to succumb to
this
dismal tradition. But this theory did more damage to the Russian Bear than
most
military invaders.
Neoliberals
were jubilant at the fall of the Berlin Wall. Not only had capitalism proved
superior to communism, but the economic theory of the market economy had, it
seemed,
proved superior to Marxism. A task of transition did lie at “the end of
history”—though not
from capitalism to communism as Marx had expected, but from state socialism
back to
the market economy.
Such a transition was clearly necessary. In addition to the clear political
and humanitarian
failures of centralized Soviet regimes, economic growth under central
planning had failed to
maintain its initial promise. Once impressive performances gave way to
stagnant economies
producing dated goods, whereas the market economies of the West had grown
more rapidly
(if unevenly), and with far greater product innovation.
As the most prominent intellectual advocates for the free market over central
planning,
neoclassical economists presented themselves as the authorities for how this
transition
should occur. Above all else, they endorsed haste. In a typical statement,
Murray Wolfson
argued that
market systems are much more stable than most people who
have been brought
up in a command economy can imagine. The flexibility of market systems
permits
them to absorb a great deal of abuse and error that a rigidly planned system
cannot
endure. (Wolfson 1992, “Transition from a
command economy: rational expectations
and cold turkey”, Contemporary Policy Issues, Vol. 10, April: p. 42).
The terms “abuse” and
“error” were unfortunately prophetic—for the rapid
transition imposed
a great deal of abuse and error on the peoples of Eastern Europe. A decade
later, incomes
have collapsed, unemployment is at Great Depression levels, poverty is
endemic. The
transition has in general been not from Socialist to Capitalist, but from
Socialist to Third World.
Wolfson is far from being a leading light of neoliberal economics. But his arguments in
favour of a rapid transition are indicative of the naivety of those whom
Joseph Stiglitz would
eventually blame for abetting the theft and destruction of Russia’s
wealth. Their key failing
was a simplistic belief in the ability of market economies—even
proto-market economies
—to rapidly achieve equilibrium. This led them to recommend haste in
the transition, and
especially in privatization of state assets—a haste which effectively
handed over state
assets to those in a position to move quickly, the old Party appartachiks and organized crime.
Reading these pro-haste papers one decade after the transition debacle, one
can take little
comfort in realizing how different the outcome of this rapid transition was
to the expectations
economists held:
“Even though we
favour rapid privatization, we doubt that privatization will produce
immediate, large increases in productivity... Nonetheless, we believe that in
order
to enjoy these enormous long-term gains, it is necessary to proceed rapidly
and
comprehensively on creating a privately-owned, corporate-based economy in
Eastern
Europe” (Lipton & Sachs 1990: “Privatization in Eastern
Europe: the case of Poland”,
Brookings
Papers on Economic Activity, 2: 1990, p. 295)
“The motivation for comprehensiveness and speed in
introducing the reforms is clear
cut. Such an approach vastly cuts the uncertainties facing the public with
regard to
the new ‘rules of the game’ in the economy. Rather than creating
a lot of turmoil,
uncertainty, internal inconsistencies, and political resistance, through a
gradual
introduction of new measures, the goal is to set in place clear incentives
for the new
economic system as rapidly as possible. As one wit has put it, if the British
were to
shift from left-hand-side drive to right-hand-side drive, should they do it
gradually
… say, by just shifting the trucks over to the other side of the road
in the first round?”
(Sachs, 1992. “The economic transformation of Eastern Europe: the case
of Poland”,
The American Economist, Vol. 36 No. 2: p. 5)
It might be thought that, since speed
was such a key aspect of the recommendations
economists gave for the transition, they must have modeled
the impact of slow versus fast
transitions and shown that the latter were, in model terms at least, superior.
But in fact the
models economists took their guidance from completely ignored time: they were
equilibrium
models that presumed the system could rapidly move to a new equilibrium once
disturbed.
The period of transition coincided with the peak influence of the concept of
“rational
expectations” in economic theory. This theory argues that a market
economy is inhabited
by “rational agents” who have, by some presumably evolutionary or
iterative learning
process, developed complete knowledge of the workings of the market economy
and who
can therefore confidently predict the future (at the very least, they know
what will happen
in response to any policy change by the government). The workings of the
market economy
happen to coincide with the behavior of a
conventional neoclassical model, so that the
economy is always in full employment equilibrium.
When this theory is put into a mathematical model, it results in a dynamic
system known
as a “saddle”, because the system dynamics are shaped like a horse’s
saddle.
In conventional dynamic modeling, a saddle is an
unstable system: the odds of the system
being stable are the same as the odds of dropping a ball on to a real saddle
and having it
come to rest on the saddle, rather than falling off it. But if you were so
lucky as to drop the
ball precisely onto the saddle’s ridge, and it stayed on that ridge, it
would ride up and down
it for quite a while until it finally came to rest.
In rational expectations modeling, the saddle
system that sensible dynamic models would
say is unstable becomes stable but cyclical. The “rational
agents” of the models all know
the precise shape of the saddle, and jump onto its crest instantly from
wherever they may
have been displaced by a government policy change. Then the economy cycles up
and
down the ridge of the saddle, eventually coming to rest in full employment
equilibrium once
more. This is how devotees of rational expectations explain cycles, given
their belief in the
inherent equilibrium-seeking nature of a market economy: the system cycles up
and down
the sole stable path until coming to rest until it is once again disturbed.
These perspectives on individual behavior, the
formation of expectations, and the behavior of
a market economy, are dubious enough in their own right. Rational
expectations “logic” is
truly worthy of the moniker autistic, since it is based on a proposition
that, if properly handled,
negates its own predictions. This is the proposition that, as Muth put it:
Information is
scarce, and the economic system generally does not waste it. (John
Muth, “Rational Expectations and the Theory
of Price Movements”: )
Since in neoclassical economics,
scarcity is the basis of value, then information should
according to this theory have a cost. If it has a cost, then agents should
economize on its
use—they will not use “all available information” but only
the subset of information that
they can afford, given their preferences for knowledge. Therefore individual
agents will not
know the full character of the economy, and most will certainly not know its
“stable manifold”.
Rational agents therefore cannot be expected to jump immediately to the
equilibrium path
of the economy unless they are irrational enough to expend the enormous
amount of
revenue that would be necessary to buy all the scarce information.
The foundations of “rational expectations” economics are thus
internally inconsistent, and
the fact that they were taken seriously in the first place is a clear sign of
how truly autistic
economic theory has become.
But if it was autistic to give this theory credence in the West, how much
more so was it to
apply this model to the behavior of people in an
economic system in transition between
central planning and market capitalism?
How can the “agents” in a transitional system develop a mental
model of a market economy
with which they predict the future behavior of the
actual economy, if they have not previously
lived in a market economy? Are we to presume instead that people can
instantly develop the
understanding of something as complex as a market economy—and are we to
grace this
belief with the adjective “rational”?
Lest this seem an overly harsh rhetorical flourish, consider the following
discussion of how
fast the transition should be from Wolfson’s
1992 paper. He begins with a statement that a
sensible person might expect would lead towards the conclusion that people
must be given
time to learn how to react to market signals:
“Indeed, when
government actions become so large that their effect on prices causes
wide divergence from individual choices, one cannot determine what those
choices
would have been. As a result, no reliable guidelines exist for government
choice. Even
with the best of intentions, unlimited collective choice destroys the very
information
base for rational decisions.” (Wolfson 1992:
37).
But instead, he immediately follows
up this apparently sensible statement with the following
proposition:
Central planners seemingly should at once resign their
posts and close their offices.
Their departure simply would signal the market to move immediately to
equilibrium.”
(Wolfson 1992: 37)
What
market? But oblivious to logical contradictions, he elaborates:
“For example, suppose the government were planning a
gradual transition from a
regime of administered prices to market prices to take place a year from now.
What
would happen 364 days hence? Obviously, people would refuse to make any but
the
most urgent transactions at the old prices, or an illegal market would immediately
jump to the new prices. Those individuals who would have to sell their goods
and
services at a lower price on day 365 would find no legal customers on day
364.
Similarly, those who would receive higher prices at day 364 would not sell
legally on
day 363, 362, 361, and so on. The economy would either come to a complete
stop
or would legally or illegally anticipate the future. In the face of rational
and reasonably
knowledgeable economic agents, delay invites disaster.” (Wolfson 1992: 37)
“Rational and reasonably
knowledgeable economic agents”? Where did they come from,
and how did they acquire so profound a knowledge of the market system they
have not as
yet lived in that they can predict its behavior (and prices in it a year into the future)
before
they experience it? Yet presuming their existence and their intimate
knowledge of the
behavior of an economic system that does not yet
exist, Wolfson advises that
A rational
expectations conclusion is that quitting communism Cold Turkey is the
only way to get from A to B. In practice, governments must make the national
currency convertible and allow it to float on legal as well as black markets,
abolish
the system of subsidies and direct plans and quotas, close plants that cannot
compete, come quickly to a privatization of industry even if some inequities
result,
strictly control the money supply, and allow goods and services to find their
own
price on national and international markets. (Wolfson
1992: 39; Wolfson does qualify
his arguments with some concessions to reality, but in the end his
recommendations
are all for speed on the basis of a belief in the self-adjusting properties
of the market
economy)
While there were significant
differences in how the program of transition was implemented,
in general this rapid and complete exposure of the once relatively closed
economies of the
East to the West was the rule. Away from the fantasies of rational
expectations economics,
what this rapid exposure to international competition did was give
ex-socialist consumers
instant access to Western goods, and expose Eastern European factories to
open
competition with their Western counterparts.
As Janos Kornai details
so well, the soft budget constraints of the Soviet system had
resulted in “cashed up” consumers on the one hand, and
technologically backward and
shortage-afflicted factories on the other. The consumer financial surpluses,
accumulated
during the long wait between placing orders for consumer durables under the
Soviet system
and actually receiving the goods, were rapidly dissipated on Western consumer
goods. The
Eastern businesses, now forced to compete with technologically far superior
Western firms,
were rapidly destroyed, throwing their workers into unemployment. With
accumulated buying
power dissipated and freely floating currencies, exchange rates
collapsed—for example,
Romania’s Lei has gone from about 1,000 to the US dollar in 1993 to
32,000 to the dollar today.
A sensible dynamic analysis of the plight of the ex-socialist
economies—one that really did
take time into account—would have predicted this outcome from a too
rapid transition. Even
if the technological advantages of the market system over Soviet-style
industrialization had
amounted to just a one percentage difference per annum in productivity, the
forty five year
period of socialism would have given market economy firms a 55 per cent cost
advantage
over their socialist counterparts. And of course, the product development
aspect of
technological innovation had made far greater differences than this merely
quantitative
measure of costs—Western firms would have decimated socialist ones on
product quality
alone, even without a cost advantage.
A time-based analysis would therefore have supported a gradual transition,
with substantial
aid as well to assist Eastern factories to introduce modern production
technology and
process control methods. It should also have been obvious that for a market
economy to
develop, one needs the minimum distributive systems of a market: systems of
wholesale
and retail distribution, respect for written contracts, systems for consumer
protection, laws
of exchange—all things which take a substantial time to put in to
place.
With the obscene haste with which the actual transition was implemented, the
only
non-market systems that could rapidly develop were those that were already in
place in the
preceding socialist system—the systems of organized crime that had
always been there to
lubricate the wheels of the shortage-afflicted Soviet system, just as market
intrusions once
permeated the feudal systems out of which capitalism itself evolved in
Europe.
It is of course too late now to suggest any alternative path from socialism
to the market for
these no longer socialist economies. The new transition they must make is
from a
de-industrialized Third World state back to a developed one, and that
transition will clearly
take time.
__________________
Steve Keen is the author
of Debunking Economics: The Naked
Emperor of the Social Sciences
(Zed Books
[US/UK] & Pluto Press).
SUGGESTED CITATION:
Steve Keen (2001) “The Russian Defeat of Economic Orthodoxy”, post-autistic
economics review : issue no. 10, December, article 5. http://www.btinternet.com/~pae_news/review/issue10.htm
____________________________________________________________________________________________________________________________
EDITOR: Edward Fullbrook
CORRESPONDENTS: Argentina: Iserino;
Australia: Joseph Halevi, Steve Keen:
Brazil: Wagner Leal Arienti;
France: Gilles Raveaud, Olivier Vaury;
J. Walter Plinge; Germany; Helge Peukert; Japan:
Susumu Takenaga;
Spain: Jorge Fabra; United
Kingdom: Nitasha Kaul;
Michael Murphy; United States: Benjamin Balak,
Daniel Lien, Paul Surlis: At large: Paddy
Quick
____________________________________________________________________________________________________________________________
Proposals
and suggestions for articles
should be sent to the editor at pae_news@btinternet.com
__________________________________________________________________________________________________________
Subscribe a colleague(s) to this journal by
sending their email address to
pae_news@btinternet.com
Back issues of this journal and other material
related to the pae movement
are available at www.paecon.net
To subscribe to this journal, send an
email with the message "subscribe" to
pae_news@btinternet.com
To unsubscribe to this journal, send
an email with the message "unsubscribe" to
pae_news@btinternet.com
|
|