Yes, physical and social systems may
be modeled with similar tools! (pdf here)
There is a strong aversion to building and using mathematical models among many
heterodox economists. They correctly criticise the infatuation with complicated
mathematics in the mainstream, which use advanced math to tinker with models
that have little relevance for the real world, or are plain wrong. The ironic
label "physics envy" is often heard, and this is quite appropriate in
my opinion. Among many in the heterodoxy, this leads to an attitude that
economics in a meaningful sense have to be done verbally.
Since I am very critical of the neoliberal mainstream in economics, I
sympathise with these critics. But I disagree with their attitude against
mathematics and modeling in economics. In my opinion, their aversion against
neoclassicals' infatuation with "modeling" and (wrongly applied)
maths, leads them to throw out the correct modeling and relevant maths baby
with the bathwater.
In my world (modeling of dynamical systems), both social science research
objects and physical science research objects have several traits in common.
This allows us to approach social (including economic) systems with similar
mathematical and simulation tools as for physical systems, with one crucial
caveat which will be discussed further below.
But first, a brief definition of a "system": It is a collection of
units which interact which each other, and is also influenced by the system's
surroundings. The characteristics of the different units, of their
interconnections, of the connections to the outside and of the signals
influencing the system through these outside connections, decide the movements
of the system over time -- its dynamics.
Some basic points when working with models of systems are:
The above holds for both physical and social
systems! This indicates that one should -- as stated above -- be careful not to
throw the modeling baby out with the neoliberal bathwater. That said,
... there is one crucial difference
between physical and social systems:
The latter category contains "components" (in fact: humans) that are conscious!
If these "components" understand the system that they are a part of,
they will adjust their behaviour, which again means that the system will get
changed dynamics -- in many cases, dramatically so.
To illustrate the difference we may use the example of a dangerous pandemic
among animals as opposed to humans. In the animal pandemic they will infect
each other regardless of dramatic developments with mass death. In a human
similar pandemic people will change their behaviour because they are made aware
of the infection mechanisms, and mass death will be (mostly) avoided. Both
systems have the same infective mechanisms: contact rate, infectivity
(= infection probability when in contact), incubation time, etc. In that
sense they may be modeled in quite similar ways (the reader may google SI
and SIR models). But they differ because of the system insight of
its units. Thus a valid model of a system containing humans (including economic
systems) also has to incorporate changes in behaviour because of communication
between system "components" and their understanding about how the
system that they are part of, works. In the pandemic model this means that,
while having the same structure, parameters and variables as the version for
animals, one must add connections from the amount of infected units to
parameters -- such as contact rate and infectivity (both will be reduced
because people -- as opposed to animals -- start to avoid others during a
pandemic, and they also try to reduce infectivity in situations where contact
cannot be avoided).
Note however that some sort of system insight is not an exclusive human trait.
It also exists to a certain degree in animals. An example is pack hunting
(wolves), where individuals behave based on knowledge of the workings of the
group. But there is a difference from humans in that group behaviour in animals
is mostly hard-wired and a result of evolutionary selection, while humans can
deliberately construct societal systems and then adjust their behaviour to
achieve the system's goals. Or they can do the opposite: try to exploit
weaknesses of the system for own gain. In both cases system insight is
required. Perhaps we could distinguish between system insight (humans)
and system awareness (humans and animals)? (On could possibly include a
third and even lower level of individual behaviour that exploits membership of
a system: Ants
use chemical signals to communicate with one another, and through this
establish beneficial trails for foraging. But here it is probably more
reasonable to consider the system of ants to be one big organism, so we exclude
it from the discussion here.)
The general conclusion is that dynamical modeling of social systems with
tools from modeling of physical systems is perfectly meaningful, but only if
one accounts for (the big consequences of) the system insight of the human
"components".