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# Economics crisis

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## Abstract

Economic theory failed to envisage even the possibility of a financial crisis like the present one. A new foundation is needed that takes into account the interplay between heterogeneous agents.
2 nature physics | VOL 5 | JANUARY 2009 | www.nature.com/naturephysics
commentary
Economics crisis
Thomas Lux and Frank Westerhoff
Economic theory failed to envisage even the possibility of a nancial crisis like the present one. A new
foundation is needed that takes into account the interplay between heterogeneous agents.
O
nce viewed as mystic monetary
engineer, Alan Greenspan, former
Chairman of the US Federal
Reserve, has been re-cast as irresponsible
villain, one who laid the ground for the
present worldwide nancial catastrophe.
him to make decisions he now regrets,
Greenspan confessed
1
that he would have
deemed impossible the ongoing disruptions
to the nancial system and that “his belief
He is not the only one who has been
taken entirely by surprise. Most economists
did not in any way foresee the depth of
the current crisis, or even consider it
possible. Even those who warned
2
of over-
exuberance in the US housing market did
not have any clue about the impending
meltdown, which, to the shocked public,
looks as if some Dr Strangelove on Wall
Street had pushed the button on a nancial
Doomsday Device. Greenspans supposed
ideology certainly coincided widely with
that of mainstream economists who believe
in the self-regulating forces of unrestrained
nancial markets, the ‘eciency’ of
asset-price formation, and the increased
eciency in risk allocation and sharing
through the introduction of ever more
nancial instruments.
All of this is just the nance version
‘homo economicus, who has unlimited
insightfulness and capability of deliberation
(economists typically speak of ‘rationality’).
nancial aairs as a side-aspect of his
utility maximization problem, taking into
account all potential future happenings
with the correct probabilities. As there
is only one way to be perfectly rational,
this agent is usually the lone actor in
economic models — a representative
Robinson Crusoe.
Of course, this Crusoe has been oen
derided as a straw-man illustration of
non-mainstream economists, unbelieving
natural scientists and a similarly
unbelieving public. Still, the straw man
is alive, and was well — at least until the
current nancial crisis started to unfold.
Although the principles outlined above
are still the basis of most contemporary
scholarly activity in economics, there are
other trends. ese include innovative
work in ‘behavioural economics’ and
experimental work with human subjects —
recognized in the award of the 2002
Nobel Prize to Daniel Kahneman and
Vernon L. Smith — which have revealed
a plethora of behavioural patterns that
rational behaviour.
However, these developments still occupy
only a marginal position. e widespread
perception within our profession is that
behavioural research delivers a curious set of
anomalies or exceptions that lack coherence,
and whose impact gets washed out in the
aggregate. In contrast, the mainstream
paradigm is seen as a more solid and
consistent framework. Economic policy
will therefore typically be based on a set of
axioms and hypotheses derived ultimately
from the Robinson Crusoe scenario. As
the prevailing nancial crisis cannot be
explained using these standard tools,
economic theory basically oers policy
makers little guidance about what to do in
the current situation.
A major problem is that despite many
renements, this is not at all a system based
on and conrmed by empirical research
(as the naive believer in ‘positive science
might expect). e vision (or ideology)
encapsulated in the mainstream approach
is of a more ‘pre-analytical’ nature and is
supported mainly by elegant but idealistic
models of the economy. Perfect rationality
and optimizing behaviour are used so
pervasively in economics education that
their basic tenets are taken for granted
as the principles ruling the real world,
despite all of the anomalies and exceptions
discovered in empirical research.
For instance, it would be hard
to nd supporting evidence for the
rmly held belief that more derivative
instruments — which should allow agents
to insure themselves better against the
stochastic wheels of fortune lead to a
better allocation of resources and thus
an increase in market eciency. is
assertion is based entirely on the benets
of contingent claims in the textbook
general-equilibrium model. Derived in
the abstract, the eciency gain through
derivatives is only a hypothesis, yet this is
not how economists are used to thinking
of such theorems: it is the mathematical
proof within the model economy that is
considered its validation, rather than any
empirical evidence.
A glance at real-life operations in
derivative markets easily shows why the
theory fails: instead of hedging away risk,
many market participants use derivatives
in an ‘anomalous’ way, to build up
speculative positions so as to prot from
higher returns, as long as the downside
risk does not materialize. e near disaster
brought about in the late 1990s by the
collapse of notorious hedge fund Long-
Term Capital Management (intellectually
based on modern derivative theory) should
have raised some doubts. If that was not
compelling enough, the present crisis
should constitute its ultimate rejection.
e dominance of the rational-agent
an even more cumbersomeconceptual
reductionism. As there can only be one
way to act fully rationally, everyone
should display exactly the same behaviour.
erefore, a representative agent would be
sucient. Taking both aspects together,
the typical format of current economic
models is that of a single household or rm
maximizing its utility or prot over a nite
or innite lifespan. Technically, this is a
dynamic programming problem.
To the shocked public, it looks
as if some Dr Strangelove
the button on a nancial
Doomsday Device.
nature physics | VOL 5 | JANUARY 2009 | www.nature.com/naturephysics 3
commentary
is methodological preference excludes
the study of interaction among economic
agents. However, most of what is relevant
and interesting in economic life has to do
with the interplay and connection between
diverse economic actors. e current crisis
is a perfect example of the importance of
interactions at various levels. It was the
interaction between highly connected
international nancial markets that has
generated the spillover from the US
subprime-mortgage problem to other layers
of the nancial system.
Securitization of credit risks enabled
lenders to sell various parts of their
mortgage portfolios to other nancial
institutions thus creating new links with
these buyers as well as, indirectly, among
them. Other new asset classes, such as
entities. is gives us a glimpse of how
nancial innovations have increased
the degree of connectivity within the
nancial system. It is well known that
highly connected systems might be ‘robust
yet fragile
3
, but such important aspects
have been out of reach of the mainstream
approach to economics.
In fact, the ubiquitous notion of
systemic risk’ signals that current events
concern the nancial system at an aggregate
level. For natural scientists, the distinction
between micro-level phenomena and those
originating on a macro-, system-wide scale
from the interaction of microscopic units
is clear. e overall systemic features of
the crisis would be seen as an emergent
phenomenon of the dispersed micro-
activity. To reduce these macro events to
the outcome of the decision process of a
single agent seems to be missing the point.
As with systemic risk, the notion of
coordination failure (a term oen used
to characterize the endogenous nature
of economic slumps and recessions)
in itself encapsulates a perspective of
4
, an
involuntary negative collective outcome
of a system of dispersed activity. Rather
than looking for the explanation in a
particularly odd case of a microscopic
dynamic programming problem, it would
seem much more plausible to investigate
the ‘logic of collective activity’ on the
macroscopic scale. However, due to the
conceptual reductionist philosophy,
macroeconomics has been entirely reduced
to microeconomic theory in the past few
rational agents. at the overall system
is dierent from its parts is plainly
incomprehensible from the viewpoint of
the ruling school of thought.
Economics has thus, by its methodology,
tied its own hands and prevented the
analysis of vital aspects of economic
systems. For example, despite the recent
surge of research in network theory, the
now apparent linkages between banks have
received scant attention. In the few papers
that have been published, the analyses are
of a static nature based on equilibrium
concepts and do not easily lend themselves
to empirical applications. e even smaller
number of studies using empirical data or
realistic models come from authors with
a background in physics
5
. Unfortunately,
the study of anything at a systemic level
has been dened away from economics by
the insistence on micro-foundations that
simply set the macro sphere equal to the
microscopic base unit.
What could be the way out of this
dilemma? In our view, a change of
methodological orientation in economics
is needed, to take into account the ‘more
is dierent’ paradigm. On the one hand,
economists need to take seriously the
various deviations from ‘rationality’
revealed by behavioural research. On the
other hand, however, to avoid getting lost
in a patchwork of behavioural biases and
anomalies, a new empirically based type of
micro-foundation is necessary — one that
stresses more the links between boundedly
rational agents rather than the agents
internal processes. It would, therefore,
also not be enough to replace the current
actor (as has sometimes been done in
recent literature).
e experience of the natural
sciences in coping with complex
systems would suggest a parsimonious
stochastic approach. Because agents
in large economic systems will display
heterogeneity in terms of their dierent
micro motives, degrees of deliberation and
information-processing capabilities, one
might hope that this variability of human
behaviour can be quantied in a tractable
way using statistical laws. Ongoing work
inspired by statistical physics shows that
relatively simple models with plausible
behavioural rules have the potential to
replicate key empirical regularities of
nancial markets
6
. In these models, direct
and indirect local and global interactions
between market participants are important
ingredients in understanding the dynamics
of nancial markets. Currently, similarly
simple stochastic models are being
developed in the study of the distribution
of income and wealth
7
, and some
economists have even taken this approach
to macroeconomic models
8
.
e apparent systemic vulnerability
of our globalized nancial markets has
brought to the fore another carelessly
neglected facet of economic interactions.
Most economic problems are emergent
phenomena of complex societies that
require a systemic perspective. A new
micro-foundation based on interactions
would be the missing macro counterpart
to the microeconomic regularities
revealed in behavioural economics. To
develop a proper perspective on systemic
phenomena, economics as a science should
take stock of the experience of the natural
sciences in handling complex systems with
strong interactions. A partial reorientation
in modelling principles and more
methodological exibility would enable
us to tackle more directly those problems
that seem to be most vital in our large,
globalized economic systems.
omas Lux is in the Department of Economics,
University of Kiel, Olshausenstraβe 40, D‑24118
Kiel, Germany, and is a member of the research
group ‘Risks in the Banking Sector’ of the Kiel
Institute for the World Economy.
e‑mail: lux@bwl.uni‑kiel.de
Frank Westerho is in the Department
of Economics, University of Bamberg,
Feldkirchenstraβe 21, D‑96045 Bamberg, Germany.
e‑mail: frank.westerho@uni‑bamberg.de
References
1. Andrews, E. L. Greenspan concedes error on regulation.
e New York Times online 23 October 2008.
2. Shiller, R. Irrational Exuberance 2nd edn (Princeton Univ.
Press, 2005).
3. Watts, D. J. Proc. Natl Acad. Sci. USA 99, 5766–5771 (2002).
4. Anderson, P. W. Science 177, 393–396 (1972).
5. Iori, G., Jafarey, S. & Padilla, F. J. Econ. Behav. Organ.
61, 525–542 (2006).
6. Lux, T. in Handbook on Financial Economics (eds Schenk-Hoppé, K.
& Hens, T.) (Elsevier, in the press).
7. Chatterjee, A., Yarlagadda, S. & Chakrabarti, B. (eds) Econophysics
of Wealth Distributions (Springer, 2005).
8. Aoki, M. & Yoshikawa, H. Reconstructing Macroeconomics:
A Perspective from Statistical Physics and Combinatorial Stochastic
Processes (Cambridge Univ. Press, 2007).
Acknowledgement
e authors are grateful to Mishael Milakovic for inspiring discussions.
Economics should take stock
of the experience of the
natural sciences in handling
complex systems with strong
interactions.
Economic theory offers
policy makers little guidance
about what to do in the
current situation.
... The fundamental weakness in current macroeconomic theory is the absence of a consistent micro level foundation. Here we present a new microeconomic theory where the macro state of a system is the aggregate of states of the micro units as proposed by Lux and Westerhoff (2009) in the spirit of classical analytical mechanics. Throughout our framework, we define and apply a consistent unit system for economics presented by De Jong (1967), comparable to that of physics. ...
... As e.g. Lux and Westerhoff (2009) state, the neoclassical economic theory is widely known of its inability to model the behaviour of real economic phenomena. The most fundamental shortcoming in the prevailing neo-classical framework, acknowledged e.g. by Mas-Colell et al. (1995), is that it is essentially static in nature, whereas real economic systems are always dynamic. ...
... Our theory can explain observed dynamic economic phenomena also outside optimum states. Therefore, it can be used to simulate economic systems in a realistic way such as economic crises that the neo-classical framework is unable to forecast or handle, see Lux and Westerhoff (2009). Our theory has been tested with extensive simulations and two empirical evaluations, and it has been found consistent with real data, as shown in Estola and Dannenberg (2012); Estola (2015). ...
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