26
manner. For such a system, there is no deterministic model that can predict
its future development. Instead, scientists use prospective models of socioeconomic metabolism to compute future trajectories of the system that are
considered possible but not necessarily likely continuations of historic
development. Such possible future trajectories are called scenarios .
Prospective models use a trick to compute future scenarios for an indeterminate system: First, a number of exogenous parameters, assumptions, and
model drivers are defi ned, and then these are fed into a dynamic model of
socioeconomic metabolism that is deterministic relative to the exogenous
parameters. Parameters like fertility or effi ciency improvement rates, model
drivers like GDP or population trajectories, and assumptions like “ceteris
paribus” or “business as usual” describe the possible future development of
certain indicators and system properties on the macro-scale. In a second
step, the prospective model applies the exogenous assumptions to the system description and generates a detailed scenario for society’s future metabolism. Specifi cation of exogenous parameters not only eliminates
indeterminacy from the model, it also reduces the complexity of the system
description by fi xing those system variables that one else would have to
determine by modeling poorly understood feedback mechanisms or those
where suffi cient empirical data are not available. Scenario analysis is therefore an important way to handle our ignorance of human-environment systems in a productive and transparent way.
2.2 Credible, Possible, and Likely Scenarios
To decide what is a possible future and what is a credible scenario, scientists have
established criteria that prospective models and their results need to fulfi ll.
Exogenous assumptions need to be plausible and consistent. Often, they follow a
certain scheme or idea that is called story line . Criteria for prospective models
include process balancing constraints such as monetary, mass, or energy balances;
the assumption that certain parameters, like effi ciency improvement rates, do not
leave empirically determined ranges; assumptions on human behavior; or the ability
of the model to correctly determine the actual development from a given starting
point in the past, using macro-indicators such as GDP as driver.
Criteria for plausibility, consistency, and properties of exogenous assumptions
and prospective models differ across modeling fi elds, mainly because of different
academic traditions. This scientifi c inconsistency has repeatedly led to criticism
across modeling disciplines, like our criticism of integrated assessment models
from an industrial ecology perspective presented below.
Are scenarios, or possible futures, also likely outcomes of future development?
This often-raised question about the predictive capability of scenarios needs clarifi -
cation. Strictly speaking, there cannot be a connection between possibility and likelihood in an indeterminate system, and a scenario can never be a prediction of the
S. Pauliuk and E.G. Hertwich
manner. For such a system, there is no deterministic model that can predict
its future development. Instead, scientists use prospective models of socioeconomic metabolism to compute future trajectories of the system that are
considered possible but not necessarily likely continuations of historic
development. Such possible future trajectories are called scenarios .
Prospective models use a trick to compute future scenarios for an indeterminate system: First, a number of exogenous parameters, assumptions, and
model drivers are defi ned, and then these are fed into a dynamic model of
socioeconomic metabolism that is deterministic relative to the exogenous
parameters. Parameters like fertility or effi ciency improvement rates, model
drivers like GDP or population trajectories, and assumptions like “ceteris
paribus” or “business as usual” describe the possible future development of
certain indicators and system properties on the macro-scale. In a second
step, the prospective model applies the exogenous assumptions to the system description and generates a detailed scenario for society’s future metabolism. Specifi cation of exogenous parameters not only eliminates
indeterminacy from the model, it also reduces the complexity of the system
description by fi xing those system variables that one else would have to
determine by modeling poorly understood feedback mechanisms or those
where suffi cient empirical data are not available. Scenario analysis is therefore an important way to handle our ignorance of human-environment systems in a productive and transparent way.
2.2 Credible, Possible, and Likely Scenarios
To decide what is a possible future and what is a credible scenario, scientists have
established criteria that prospective models and their results need to fulfi ll.
Exogenous assumptions need to be plausible and consistent. Often, they follow a
certain scheme or idea that is called story line . Criteria for prospective models
include process balancing constraints such as monetary, mass, or energy balances;
the assumption that certain parameters, like effi ciency improvement rates, do not
leave empirically determined ranges; assumptions on human behavior; or the ability
of the model to correctly determine the actual development from a given starting
point in the past, using macro-indicators such as GDP as driver.
Criteria for plausibility, consistency, and properties of exogenous assumptions
and prospective models differ across modeling fi elds, mainly because of different
academic traditions. This scientifi c inconsistency has repeatedly led to criticism
across modeling disciplines, like our criticism of integrated assessment models
from an industrial ecology perspective presented below.
Are scenarios, or possible futures, also likely outcomes of future development?
This often-raised question about the predictive capability of scenarios needs clarifi -
cation. Strictly speaking, there cannot be a connection between possibility and likelihood in an indeterminate system, and a scenario can never be a prediction of the
S. Pauliuk and E.G. Hertwich