Modern Economy, 2011, 2, 569-574
doi:10.4236/me.2011.24063 Published Online September 2011 (http://www.SciRP.org/journal/me)
Our Economy
Christian Müller*
Zurich University of Applied Sciences, School of Management and Law, Winterthur, Switzerland
Received April 8, 2011; revised May 30, 2011; accepte d J une 12, 2011
Abstract
I discuss the strengths and weaknesses of the current predominant approach to macroeconomic modelling of
asset prices and suggest an alternative perspective. This alternative rests on the insight that the economy is
the result of individual decisions. The industry standard has it, however, that individual action is ruled by
objective, general laws instead. Changing the point of view allows to reconcile numerous puzzles and paves
the way for a promising new research agenda.
Keywords: Fundamental Uncertainty, Subjectivity, Finan cial Crisis
1. Introduction
Many years ago the ancient Greek coined the term “eco-
nomics” which defines the principle research agenda
until today. Today we are still concerned with decision
making for enhancing society’s welfare. However, two
thousand years cannot pass leaving the world unchanged.
While in ancient Greece decisions allocated the scarce
resources of the oikos (the household) comprising the
master, his family, slaves, and the land, today’s nomos
(custom) of efficient action concerns thousands of
households, countries and the world as a whole.
The basic objective of economic analysis has never-
theless remained largely unchanged. Economists are still
looking for laws that can guide our behaviour to the bet-
ter of the society. The most important difference—in my
view—between then and now certainly is the degree of
complexity of today's issues. In a relatively little world
with well-defined roles for individuals, a judgment of the
effects of one's action in the future appears reasonably
reliable. We can thus imagine that the optimal decision
can be made considering all relevant combinations of
action and reaction.
Interestingly, economists still apply the same strategy
for advancing theories when describing human behaviour,
or prescribing the best possible choice. The umbrella
term for this procedure is usually called rational choice.
Individuals are assumed to decide on the basis of rational
expectations abou t the future state of the economy. In its
probably most restrictive version th is approach posits the
existence of the so-called homo oeconomicus. This hy-
pothetical agent is, among other things, completely self-
ish, profit oriented and processes an unlimited amount of
information in no time. Not surprisingly, this methodo-
logical approximation of real humans becomes more and
more outdated as more and more evidence is gathered
which proves the limits o f humans beyon d doub t. A main
driver of this more recent development certainly are al-
ternative analyses of decision making pioneered by re-
searchers like [1,2], for example.
Recognising the limits of the rationality concep t many
authors have begun to consider plausible deviations from
the rationality paradigm including (rational) learning,
incomplete information and sentiments (see e.g. [3-5]) or
ambiguity [6,7] to name but a few. Generally speaking,
results derived by neighbouring sciences such as psy-
chology which explain cognitive processes have entered
economics and have helped to better understand individ-
ual choice under more realistic assumptions [8,9].
Despite the significant augmentation of our under-
standing of efficient decision making, numerous prob-
lems remain. Many of them are known as puzzles be-
cause the theoretical predictions are not matched by ac-
cording observations. The puzzles I am referring to in
particular are those in which the outcome of individual
decisions seem not to be in line with considerations re-
lated to the aggregate of information available. Popular
examples are all sorts of exchange rate puzzles and asset
price puzzles such as price bubbles. Typically, these
puzzles feed on the seemingly mismatch of theoretically
plausible prices and their actual counterparts. In the fol-
lowing I will relate these puzzles to the predominant
*I do thank participants of the 2009 Berlin--Copenhagen conference for
many helpful comments. All mistakes are mine.

C. MÜLLER 570
concept of rationality. I then put the problem in the con-
text of the traditional economists’ research program and
finally, I will suggest a new research agenda.
2. The Dark Side of Rationality
Recent research into the limits of rational behaviour can
be compared to investigations of the moon by means of
powerful telescopes. Prior to the invention of optical
assistance the moon appeared more or less plain and
bright whenever the sky was clear. The same was true for
the concept of the rational agent. Ever since, however,
we do know there are craters, mountains, and a whole lot
of different structures on the moon’s surface, pretty
much as there are serious scratches on the surface of the
homo oeconomicus. After a while astronomers also
learned that there was a dark side of the moon too, they
would never be able to observe while looking from the
earth. It was not until the first lunar explorers which left
our planet that we finally got to kn ow the more complete
story of the earth’s satellite.
In my opinion, economists still await a similar en-
deavour. What remains unknown to us is the “true” story
behind economic agent’s decisions. This story is untold
because we can only advance theories aiming at explain-
ing behaviour but we can never know whether or not
these theories reflect reality. Of course, there is empirical
research which compares observations to what theories
imply, but as mentioned earlier, key aspects of the
economy such as exchange rate determination and asset
pricing consistently defy satisfactory modelling giving
rise to so-called puzzles. Why, then, can we compare
these puzzles to lunar exploration? We can do so, be-
cause, speaking allegorically, the main appro ach to solve
those puzzles rests with the development of ever better
telescopes. What we would really need, however, is a
glance at the dark side of the moon.
2.1. Better Telescopes, or 
To understand this claim one may dissect the currently
dominant empirical approach into two major parts. The
first part comprises the collection of observations and
their comparison to what has been expected on theoreti-
cal grounds. This part alone provides enough issues for
discussion to fill volume after volume of high ranking
journals. Th e major source for the stream of publications
has already been identified by [10] as follows. The re-
searcher develops a model that uses (individual) expecta-
tions about the future states on the economy. The corre-
sponding empirical test
 can be carried out only conditional on the behav-
ioural model . This means that conclusions concern-
ing the expectations process will not be invariant to the
choice of the underlying behavioural model [10, p.22].

Moreover, as almost always the choice of empirical
data (definition, level of aggregation, transformations)
itself is subject to discussion, researchers can regularly
produce more insight based on variations of the model or
the choice of the data. The choice of econometric tech-
niques also nourish the publication stream. Directing a
telescope towards the moon and taking notes is an as
comparably transparent and competitive process of
knowledge generation as this first part of the current ap-
proach in economics.
2.2. Lunochod? 
The second constituent element of the current approach
attracts far less attention, however. This element is the
(tacit) assumption of the existence of an objective sto-
chastic probability distribution of the future states of the
economy. Notice, as theory defines a theoretic standard
against which actual data is to be compared to, we must
assume that such a means of comparison exists, and
maybe more important, this standard must be independ-
ent of the agents who are supposed to act on it. More
precisely, objectivity is obtained by either imagining a
representative agent or finite numbered groups of het-
erogeneous agents. As the number of agents increases the
total outcome tends towards some objective optimal de-
cision which cannot be influenced by an individual. The
formal condition is called ergodicity with respect to the
number of individuals. For example, to render the fol-
lowing equation meaningful from the point of view of an
applied economist, its error term, [epsilon], has to follo w
some ergodic stochastic process:

=.yfx


Here, y represents the observation, ()
f
the func-
tional form and x all conditioning information that helps
explaining y.
Loosely speaking, the assumption of ergodicity with
respect to the number of agents of any unexplained por-
tion of y, that is

, can be regarded the dark side of the
moon. We would still not know the full story of our
earth’s companion had we not escaped the gravity of
convenience: the familiarity with the traditional telescope
equipment. Likewise, unless we carefully scrutinise the
implications of ergodicity, or rather non-ergodicity we are
unlikely to fully appreciate human behaviour from an
economist’s poi nt of vi ew.
3. Off Remote Control
Let us reflect for a moment on the meaning of a repre-
sentative agent. Any representative agent would find out

C. MÜLLER571
that y must equal

f
x up to some agent specific mar-
gin. Considering the repr esentative agent provides a han-
dle for coping with the individual specific effect by as-
suming that all individual effects follow some statistical
law. In other words, there is a given probability that the
individual specific margin does not exceed some upper
and lower bound. Taking this assumption literally im-
plies, however, that the subject is somehow ruled by a
law that dominates his or her own will. Consequently, we
cannot talk about subjects any more, the representative
agent turns into an object. Considering heterogeneous
agents instead does not change the principle as long as
the degree of heterogeneity is finite.
The representative agent approach yields a bizarre re-
sult when applied to asset markets. Before turning to this
issue let me first remind the reader that concepts like
bubbles, and exuberance, and so on and so forth all tac-
itly assume the existence of a correct, or true, or rational,
or fundamental value of some financial asset. Unless we
know this true price we cannot, h owever, attach the label
“bubble” to prices exceeding this rational price, for ex-
ample. According to the standard approach, any trader
would agree on the price y. However, this price is deter-
mined completely independent of the trader’s opinion.
Therefore, when striking a deal this very trader is ulti-
mately supposed to work on a kind of remote control. In
my view, this is a totally misl eading, ev en b izarre picture
of what is really going on.
4. The New Null
Let me therefore suggest an alternative. This alternative
starts with the simple observation that prices are set by
humans. These subjects act on the basis of certain ex-
ogenous conditions and their own will. Prices are thus
the result of subjective judgements but not the outcome
of some independent, objective process. Secondly, for a
price to be quoted at least two subjects must interact. In
1836 David Ricardo already argued that a deal will only
be beneficial when the parties involved are different, not
identical. The same is true for asset prices. There is
scope for a deal if the traders differ in their judgment
about the perspectives of the future asset price. If we let
the number of market participants increase, we should
therefore expect that the degree of disagreement in-
creases but not decreases like the representative agent
approach has it.
This increase in the degree of disagreement leads di-
rectly to a new null hypothesis under which we may have
a second look on existing empirical findings. If it was
true that the number of agents in a market matters fo r the
price process we should observe that the variance of the
observed price increases the more agents are active. By
contrast, the representative agent approach would sug-
gest that the variance of the average price decreases.
5. Reconciliation
If there ever was a chance to measure directly the rela-
tionship between the number of agents and the variance
of the asset price, for example, we would easily be able
to reject or accept this hypothesis. However, there are
considerable hassles to overcome because it is very dif-
ficult to control for the number of people interacting. In
my opinion, experiments are the potentially most pow-
erful tools in that respect. Therefore, I scanned the exist-
ing literature in order to look if a suitable experiment has
ever been conducted. Unfortunately, I did not find any.
What I found instead are numerous examples where it
has been demonstrated how irrational price setting can
become.
So-called irrational behaviour can now be considered a
stylised fact in artificial asset markets (see inter alia [1,
11]). It has also be demonstrated ([12-14]), however, that
experienced traders can push the market price towards its
fundamental value and hence eradicate irrational prices.
Notably, all these experiments use a design where an
(implicit) objective price process is induced. For exam-
ple, the traded asset may yield a return with a given
probability each period. Therefore, irrationality in such a
situation might be used as an argument against the new
null. I prefer a different interpretation, however. The
participants in these experiment behave exactly as they
would have done in the real world: they trade as if there
was no objective price process. By contrast, expert trad-
ers are able to discover the induced pricing rule and
hence tend to behave rationally. Therefore, these ex-
periments do not lend support to the standard approach.
The decisive question is how do experts trade in the ab-
sence of an objective price process? In sum, standard
experiments, that is those in the vain of [1], use objective
price processes whose very existence is hence not test-
able.
Because suitable experimental evidence is not (yet)
available one may wonder if there are other bits and
pieces of evidence for or against the new null hypothesis.
In the following, I will focus on support while leaving
the search for contradictions to future research. As long
as direct tests of the relation between number of agents
and variance have not been conducted we have to resort
to various kinds of approximations. There are two kinds
of approximation which I consider helpful. These are in
the case of asset prices volume traded and size (length)
of the order book. For example, [15] point out that the
forward market is far less liquid than the spot market for
foreign exchange to the effect that price volatility on the
former is much smaller than on the latter market. There-
fore, any regression of changes in spot rates on changes

C. MÜLLER 572
in forward rates (or forward-spot differences) can yield
any result and is ultimately meaningless. Similarly, [16]
report per-minute-data of the deutschmark—USD market
where volume and volatility are clearly positively asso-
ciated.
The use of order book data has been popularised by
[17]. These authors show that the regression fit of ex-
change rate models increases dramatically when order
book information is included. At the same time signifi-
cance of “fundamentals” decreases considerably, or dis-
appears completely. The regression fits the data better
because the variance of the price is better captured. Us-
ing the size of the orde r book as an approximation to the
number of traders active allows us to understand this
effect in terms of the subjective pricing process.
In a further analysis, I have also run several regres-
sions of share price volatility on the number of ticks per
ten-minute-time interval as an approximation to the
number of agents [18]. Again, the result is a clear posi-
tive link between these two variables.
Finally, I would like to hint to the notorious intra-day
seasonality of financial market data. It is a well-estab-
lished fact [19,20] th at share price volatility drops arou nd
noon. This effect has been labelled lunch break puzzle.
Under the new null hypothesis this puzzle disappears,
however. The solution is straightforward: when traders
have lunch they are not active on the market any more.
We should therefore expect volatility to drop. It might be
worth emphasising that the lunch break puzzle is so use-
ful in support of the new null hypothesis because en-
dogeneity bias is out of the question. Lunch is an exoge-
nous event and any feedback from volatility to the oc-
currence of lunch time can be safely excluded.
6. The Unexpectable
In the light of the tentative evid ence let us operate under
the assumption that the new null hypothesis holds and
have a look at its implications. One implication affects
the use of the term rationality of agents. If certain events
are generic in the sense that subjective judgements de-
termine their outcomes such as the pricing of assets, we
would rationally conclude that an objective solution for
determining these outcomes does not exist. Hence look-
ing (only) in the direction of rational, representative
agent models for predicting those outcomes becomes
irrational itself.
Secondly, because the outcome of human interaction
on markets is ultimately subjective and not objective,
objective probability distribution functions are of very
limited use in general. Lack of any such probability dis-
tribution implies that there are things which are not only
very difficult to expect but which are even unexpectable.
Is this conclusion worrisome? I don’t think so. First of all,
life is life-threatening anyway. In othe r words, the future
is open and no-one really knows, what it will bring. De-
spite this fact the human race has been able to survive
some one or two billions of years. Most of this time hu-
mans were happy without the concept of rational deci-
sion making in the modern economists' sense. Therefore,
humans must have developed some tools for coping with
the unexpectable which hence still await their discovery
by economists.
7. Our Economy
Economic agents somehow have to cope with the unex-
pectable. These unexpectable events are in turn the re sult
of the very subjects’ judgements and actions. In one
word, the economy is shaped by ourselves and we do
create the reality we live in ourselves. After all, it is our
economy and nothing else. This statement is, of course in
stark contrast to the many attempts of modelling ex-
change rates, share prices, and the whole economy as
chains of ev ents following objective prob ability distribu-
tions. Provided the existence of the unexpectable we
might wonder what the implication for economic analy-
ses may be. In the following, I will raise some aspects I
consider worth a more detailed investigation.
First of all, I do not think that under the new null hy-
pothesis representative agent models, or their ambigu-
ity-augmented versions are totally useless or wrong al-
together. The only adjustment that I deem necessary is
the way we look at the respective findings and at what
else we might be able to find. Let us reconsider the idea
of the future being open. When things are fundamentally
unexpectable while our day-to-day decisions are still
based on guesses of what tomorrow will bring, we real-
ize that individuals must use some mechanisms to either
formulate those guesses or to find some other way to
cope with the same problem. The principal agent ap-
proach can thus be regarded as one single option out of a
whole arsenal of weapons which arm us for coping with
the unforeseeable. In this particular case, we try to ra-
tionalise our actions and decisions to the greatest possi-
ble extent on the basis of statistical analyses of past
events.
Once we take comfort in accepting the traditional ra-
tional expectation—representative agent approach as one
out of many possibilities for understanding economic
decisions, the next obvious question is: what are the
other tools? In my opinion, the search for these alterna-
tives is the true challenge of future economic research.
Luckily, economics has already become a very well di-
versified science. Therefore, many mechanisms which
help us making efficient use of resources when events
are unexpectable have probably already been investi-
gated. Those mechanisms could therefore simply been

C. MÜLLER573
reconsidered as part of the larger arsenal. There is no
reason any more, however, to give priority to one par-
ticular line of argument like rational expectations of a
representative agent.
In order to illustrate the last point consider the popular
competition between so-called fundamentalists and so-
called chartists. The traditional rational expectation ap-
proach would clearly favour the analysis of fundamentals
for explaining stock prices. If we take into account,
however, that chartist create as much reality as do fun-
damentalists, there is no reason to consider the analysis
of fundamentals a priori more reasonable than the con-
clusions drawn by chartists. Instead, we should search
for arguments as to why either method is more suitable
to handle the unexpectable; the answer to which is yet to
be found.
To provide another example, the thought that agents
create the reality they have to deal with themselves
brings back a number of issues economists have long
regarded more or less settled. Consider for instance
[21]’s case for flexible exchange rates. Six out of seven
reasons Friedman gives for the determination of ex-
change rates can directly be used as arguments in favour
of flexible foreign exchange prices. The reasons are al-
ways that exchange rates adjust to external, macroeco-
nomic imbalances and vice versa which re-establish
macroeconomic equilibrium. The assumption of such a
bi-directional feedback mechanism is at the heart of
many exchange rate puzzles, however. Under the new
null hypothesis, a straightforward feedback from macro-
economic conditions to exchange rates does no longer
exist. Therefore, any short-cut to favouring flexible rates
becomes doubtful. Again, there is no a priori reason ei-
ther to jump to the conclusion that fixed rates are better.
But we certainly have to consider the whole issue again
under the new null hypothesis.
8. Points of Departure
Returning to the subjectivity notion one might remember
that psychologists have long noticed that decision mak-
ing is a complex process which does not only involve
those areas of the brain that are responsible for calcula-
tion and thorough reasoning. In fact, humans can lose
their ability to make a decision completely once the af-
fective part of the brain is seriously damaged. It might
very well be that the evolution has reserved a decisive
role for emotions exactly because they equip us with the
ability to cope with unexpectable events.
Further relevant, seemingly irrational influence on de-
cision making can be attributed to a tendency of neglect-
ing information which runs against one’s initial convic-
tions (see Section 5, third paragraph), using irrelevant
“anchor” information, being more considerate when in a
sad mood, being overwhelmed by too much information,
and many more. Obviously, once we confront these be-
havioural pattern with well-defined problems of stochas-
tic optimisation we tend to find them utterly ridiculous.
What we disregard in those comparisons, however, is the
simple fact that well-defined problems rarely exist in real
life. Therefore, economists should look at seemingly
irrational patterns in the ligh t of un expectable events.
Coming finally back to the initial example of an an-
cient Greek household, one possible answer to the unex-
pectable might have been given by societies which as-
sign very well-defined roles to certain members of the
society such as women, men, children, craftsmen, priests,
aristocrats, and so on. Assigning these roles limits the
possible outcomes of human interaction and hence re-
duces the occurrence of unexpectable events. Therefore,
such a strategy might benefit the society by making un-
wanted unexpected events impossible. At the same time
desirable unexpectable events such as economic devel-
opment are also restricted. Hence, a classical trade-off
results. If the outcome of a strategic choice is fundamen-
tally uncertain, or unexpectable, non-classical tools for
analysing this choice must be developed and applied.
9. Summary and Conclusions
The outcome of human decisions and actions is as di-
verse as humans are different from one another. There-
fore, the outcomes are inherently subjective and system-
atically defy mo delling by means of o bjective, stochastic
processes. Observable human behaviour might hence be
optimal in the sense that it is efficient given the occur-
rence of unexpectable events while appearing at the same
time “irrational” in laboratory settings.
Traditional economic modelling can be regarded an
approximation to the actual optimisation behaviour under
the restriction that events are following some objective
rules. However, to fully appreciate economic decision
making we have to scrutinise individuals’ behaviour
given that they also have to cope with the unexpectable.
The results of these investigation will potentially yield
important implications for policy making and theoretical
research alike.
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C. MÜLLER 574
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