The idea of a
steady state economy has a long history. It was discussed by
Adam Smith,
John Stuart Mill,
John Maynard Keynes,
Nicholas Georgescu-Roegen,
E.F. Schumacher,
Kenneth Boulding, and
Herman Daly (all discussed
here). Basically, the
theory of economic growth describes the conditions under which an economy will grow (I've discussed the neoclassical growth model
here) and steady-state economy theory describes the conditions under which the economy will stop growing (without collapsing). Both of these theories are flawed for reasons described by the theory of
complex dissipative systems. I'll introduce some of these ideas in this post, but my major objective is to introduce the concept of
steady state.
The fundamental insight from the steady state economy model is displayed in the graphic above taken from Herman Daly's (1977)
Steady State Economics (San Francisco: Freeman) on page 35. Economic growth theory takes up the right-hand box in the figure. The economy, in Daly's view, produces stocks of artifacts (capital goods and stocks of knowledge) that not only deplete the Ecosystem (the left-hand box) but also generate pollution (even knowledge production does this, think of your University's power plant). Compared to the Ecosystem, which is open to Solar Energy and accepts heat pollution, the Economic system is closed. From my earlier discussion of economic growth theory (
here), the economy is typically thought to be open to population growth and technological change. Daly includes both those stocks (the stock of population and the stock of knowledge) within the economic system.
If we split the drawing in half, the economy is open to input from the Ecosystem and the Ecosystem is open to pollution and depreciation from the economy as well as solar input. The
theory of open systems shows that only
closed systems can reach a permanent steady state. An open system is always forced into another state by its inputs. So unless solar energy becomes an input to the Economy and, at the same time, regenerates the Ecosystem which is being depleted but the Economy, the combined system cannot reach a permanent steady state at a high level of economic development. Basically, the
Second Law of Thermodynamics holds that all closed systems run down due to dissipation of energy (the theory of
complex dissipative systems).
What is lurking under all this theory is the concept of
openness. The subtleties are easier to understand by considering the general open system
S(t) = A S(t-1) + B X(t-1) where
t is time,
S is the state of the system,
A and
B are matrices of coefficients and
X is a matrix of inputs from the environment (the open part of the system). The characteristic behavior of the
state-space representation is determined by properties of the
A matrix, specifically its
stability (all
eigenvalues of
A less than one). If the system is stable it will reach a steady state only when
X becomes zero, that is, when the inputs are dissipated (think of
X as the environment) or when
X becomes a constant, that is, the environment reaches a steady state. If the system is unstable, it will growth forever, even without inputs--which is impossible. So, real world systems must ultimately become stable.
But, imagine a world which is
radically open. There are all sorts of systems, some stable, some unstable (think of normal cells in the human body and cancer cells, the cancer cells are growing unstably). Each system is interacting with other systems. In this disorderly world, change over time is determined by the
unstable systems. Unless the unstable systems are stabilized, they take over the stable systems. In the case of cancer cells, without killing the cancer cells (one type of steady state) they eventually kill the host system.
The view of the ecological system and the economic system advanced by the theory of steady state economics involves mildly open, stable systems. What if they are not? What if they are more like the human body? What if the Economy and the Ecological system are radically open? This will be a topic for a future post.
The theory of
radically open systems possess serious problems for all attempts to specify the steady state or even the growth path of an economy. All the conclusions from economic growth theory, steady-state economic theory and simple open systems theory depend on being able to specify the state
S of the system. In radically open systems, if the state is misspecified then some
unmeasured, unstable force in the environment (e.g., a caner pathogen) can disrupt the system and make forecasting the future impossible. In a world of radically open systems, all systems are
weakly state determined and strongly driven by the environment. For theorists and model builders, accustomed to specifying system states, specifying the entire environment is an impossible task. For us consumers of theories and models, we need an answer to the question of how open our real word systems are
before we an have much faith in the conclusions of theoreticians and model builders.
The one question that the debate between economic growth theorists and steady-state economists has brought into the open is whether any of our economic systems are moving toward a steady state. And, if an economic system is moving toward a steady state (an empirical question) what might happen after that (a speculative question). The resolution of this question is important because it impacts the Ecosystem on which the Economy depends. I will present historical data from and test actual economics systems in future posts (something that is seldom done in ECON 101).
HISTORICAL NOTE
The concept of a Steady State Economy was dropped from ECON 101 after WWII as was much of what had been developed by Classical Economists in the Nineteenth Century (except
David Ricardo).
For example, in the graph above is the output from a Steady-State Malthusian System model produced by the code below, if you would like to experiment yourself. Note, this model is a closed system.
Code
A Steady-state Malthusian Model. Models have a compact R-code in
dse and can be run easily
https://rdrr.io/snippets/. Cut-and-paste the following code into the Snippets editor window. When you run it, it should produce the shock decomposition diagram and the forecast in the graphic above.
#
# MALTHUS
#
require(dse)
require(matlab)
f <- matrix( c( .8, 0, 0.09478143,
0, .8, 0.09238426,
0.000000000, 0.00000000, 1.000000000
),byrow=TRUE,nrow=3,ncol=3)
h <- eye(2,3)
k <- f[1:3,1:2,drop=FALSE]
TRM <- SS(F=f,H=h,K=k,
z0=c(0.09478143, 0.09238426, 1.00000000),
output.names=c("N","QA"))
stability(TRM)
TRM
TRM.data <- simulate(TRM,sampleT=20,
,start=1,freq=1,noise=matrix(0,20,2))
TRM.model <- l(TRM,TRM.data)
#tfplot(TRM.model)
shockDecomposition(toSSChol(TRM))
tfplot(forecast(TRM.model,horizon=20))