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## Causality and diagrams for system dynamics

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Title: Causality and diagrams for system dynamics

1
Causality and diagrams for system dynamics
Chile martin_at_utalca.cl
• Students have a hard time learning to correctly
use polarity.
• Most approaches use causality between events, not
behavior. System dynamics focuses on behavior,
but intuitive thinking focuses on events the
relationship between them is not clearly defined.
• System dynamics has several definitions of
polarity
• the popular one is simple but allows false
statements
• the complete one avoids false statements, but
is hard to learn and ambiguous with respect to
the relationship between behavior and event.
• Causal loop diagrams (CLDs)
• allow to model fast-and-dirty
• can represent mental models that contradict basic
system dynamics truths
• cannot represent some of the basic system
dynamics truths.
• CLDs are easy and risky to use
• the expert dynamicist does not need external help
to avoid errors and can use CLDs safely
• the beginner needs external help but resists the
effort of learning stock-and-flow modeling before

2
Causality in different approaches
1
Approach Main use Nodes Links Driving force Degree of abstrac-tion
Concept mapping Structure knowledge in form of propositions Concepts in general Any type Undefined Low
Cognitive mapping Uncover, structure and analyze problem accounts Constructs Qualitative causal links, negative and positive type Events, actions Low
Causal mapping Represent beliefs about the causal structure. Variables Qualitative, including popular polarity Undefined High
Causal diagrams Determine causes of events or consequences of actions Variables with discrete values Quantified causal links Events High
System dynamics Structure decision policies Variables with continuous values Quantified causal links Behavior High
3
What is behavior (that it is not an event)?
2
Quantitative
Computer
the sequence of quantities
the trend (quality of behavior)
Levels of description
Specialization
first descends, then grows
decreases
Event
the change of the trend
switches from decreasing to growth
Qualitative
Modeler
Behavior
4
The popular definition (between behavior and
event)
3
when the independent variable changes, then the
dependent variable changes in the same direction
positive
when the independent variable changes, then the
dependent variable changes in the opposite
direction
negative
dV1
- dV2
Change
Change dV
Behavior as change of quantities
Behavior as change of the quality of behavior
(event)
5
The complete definition (between behavior and
event)
4
when the independent variable changes with a
particular sign ( or -), then the following
values of the dependent variable will be above
(or less) than what they would have been.
positive
when the independent variable changes with a
particular sign ( or -), then the following
values of the dependent variable will be less(or
above) than what they would have been.
negative
Behavior as change of quantities
Behavior as change of the quality of behavior
(event)
6
Famous example population dynamics
5
-

population

-

births
deaths

This part of the CLD is used to critique the
causal loop diagram language as a tool for
systems thinking in pedagogical contexts.
natality
mortality

birth control policy
public health policy
?See the population case.itm model in the
7
What a CLD can say (but should not)
6

population
Popular definition
Complete definition
Is the moment of bifurcation an event?
?
births
?
?
?
If births decrease, then population will
decrease.
If births decrease, then population will be less
than what it would have been.
Complete definition seems to avoid
contradiction. However, less than what would
have been does not imply no absolute decrease.
8
What a CLD should say (but cannot)
7

population
Any definition
births
0
0
No flow variables that are inflow or
outflow, no quantities
No bounds on quantities (like a negative inflow).
No stock variables that maintain values
A constant independent variable can lead to a
growing dependent variable.
No flow-stock integration
9
8
Famous example once more population decreases!
What does ceteris paribus then mean
population has no other influences or all
other influences on population remain as they
are?
Population depends on various variables and also
influences them. births ? population is too
reduced.
-

population

-
births
deaths

natality
mortality

birth control policy
public health policy
?Experiment with the population case.itm model
10
Concluding arguments (cog.map)
9
CLDs allow event-oriented (intuitive) thinking.
CLDs have few implied concepts.
CLDs allow to go fast and do not require much
previous study.
Use of CLDs does not educate proper systems
thinking.
Thinking with CLD is popular.
We generally cannot avoid to make behavioral
interpretations
CLDs allow false behavioral interpretations.
A beginner is likely to think in terms of
constructs and events. He is not aware of the
hazard zones.

An expert can think in terms of variables and
behavior he embodies the rules and will not err
CLDs as shorthand.
Use by experts OK.
Only disciplined use in teaching!
11
Concluding arguments (cog. map)
10
A beginner is likely to think in terms of
constructs and events. He is not aware of the
hazard zones.
System dynamics has several complicated
concepts.
We generally cannot avoid to make behavioral
interpretations
-
Learning stock-and-flow thinking and modeling
takes time.
Adults have few time to learn.
Improve definition of relationships with event
thinking approaches.
Start teaching earlier.
An expert can think in terms of variables and
behavior he embodies the rules and will not err
CLDs as shorthand.
12
System dynamics references
11
1. Booth-Sweeney, L. and Sterman, JD., 2000. Bathtub
dynamics initial results of a systems thinking
inventory, System Dynamics Review 16(4) 249286
2. Coyle, G. 1998. The practice of system dynamics
milestones, lessons and ideas from 30 years
experience. System Dynamics Review 14(4), (Winter
1998) 343365
3. Homer, J. and Oliva, R. 2001. Maps and models in
system dynamics a response to Coyle, System
Dynamics Review Vol. 17, No. 4, (Winter 2001)
347355
4. Moxnes, E. and Saysel, A. Misperceptions of
Global Climate Change Information Policies
5. Moxnes, E., 1998, Overexploitation of renewable
resources The role of misperceptions, Journal of
Economic Behavior Organization Vol. 37 (1998)
107-127
6. Moxnes, E., 2000. Not only the tragedy of the
commons misperceptions of feedback and policies
for sustainable development, System Dynamics
Review 16(4)325348
7. Moxnes, E., 2004. Misperceptions of basic
dynamics the case of renewable resource
management, System Dynamics Review 20(2) 139-162
8. Pedercini, M. 2006. Whats behind the blue arrow?
- The notion of causality in System Dynamics
Proceedings of the 24th International Conference
of the System Dynamics Society, Nijmegen
9. Richardson, 1991 Feedback thought in social
sciences and systems theory. Pegasus
Communications
10. Richardson, G. P. 1997 Problems in causal loop
diagrams revisited, System Dynamics Review Vol.
13, No. 3, (Fall 1997) 247252
11. Richardson, G. P. 2006 Concept Models.
Proceedings of the 24th International Conference
of the System Dynamics Society, Nijmegen
12. Richmond, B., 1993, Systems thinking critical
thinking skills for the 1990s and beyond, System
Dynamics Review Vol. 9, no. 2 (Summer
1993)113-133
13. Sterman, JD. 1989. Modeling managerial behavior
misperceptions of feedback in a dynamic decision
making experiment. Management Science 35(35)
321-339
14. Sterman, John, 2000. Busyness Dynamics systems
thinking and modeling for a complex world, John
Wiley
15. Warren, Kim, 2004. Why has feedback systems
thinking struggled to influence strategy and
policy? Systems Research and Behavioral Scienc
Jul/Aug 2004 21, 4 pg. 331
16. Wheat, David. 2007. The Feedback Method - A
System Dynamics Approach to Teaching
Macroeconomics, PhD thesis, University at Bergen,
March 2007
17. Wolstenholme, E. 1990. Systems Enquiry. Wiley

13
Other references (selcted)
12
• General sources
• Hume, D. 1984 Enquiry concerning the human
Understanding Investigación sobre el
conocimiento humano, (Translated by Jaime de
• Gopnik, A. Glymour, C. Sobel, David M.
Schulz, L. E. Kushnir, T. and Danks, D. 2004.
A theory of causal learning in children Causal
maps and Bayes nets. Psychological Review, 2004,
111, 1, 1-30
• Allan. L. and Tangen, J. 2005. Judging
Relationships Between Events How Do We Do It?
Canadian Journal of Experimental Psychology Mar
2005 59, 1 pg. 22
• Heider, F., 1958. The Psychology of Interpersonal
Relations. New York Wiley
• López, F., Cobos, P. and Caño, A. 2005.
Associative and causal reasoning accounts of
causal induction Symmetries and.asymmetries in
causal predictions and diagnostic inferences,
Memory Cognition Dec 2005 33, 8 pg. 1388
• Kahnemann, D. 2002. Maps of bounded rationality
a perspective on intuitive judgment and choice,
Nober Prize Lecture, December 8, 2002
• Kelley, H. H. 1973. The processes of causal
• Causal diagram sources
• Halper, J. and Pearl, J. 2005a. Causes and
Explanations A Structural-Model Approach. Part
I Causes, Brit. J. Phil. Sci. 56 (2005), 843887
• Halper, J. and Pearl, J. 2005b. Causes and
Explanations A Structural-Model Approach. Part
II Explanations, Brit. J. Phil. Sci. 56 (2005),
889911
• Pearl, J. 1955. Causal diagrams for empirical
research, Biometrika (1995), 82,4, pp. 669-710
• Cognitive mapping
• Eden, C. 1990. Using cognitive mapping for
Strategic Options Development and Analyses
(SODA), in J. Rosenhead (Ed.), Rational Analysis
for a Problematic World, Wiley Chchester
• Howick, S. Ackermann, F. and Andersen, D., 2006.
Linking event thinking with structural thinking
methods to improve client value in projects,
System Dynamics Review Vol. 22, No. 2, (Summer
2006) 113140
• Mental model sources