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Slightly brusque if you don't mind me saying so Scott. I thought Leigh's
example was a useful one in this thread as it offers a concrete example
of the way simulation has offered insight in a research process. I will
not enter a discussion of the merits or otherwise of the insights it
offers as these are well outside my domain. I have found this thread
interesting since it seems to bring home one aspect of 'simulation' that
has not been talked about much to my knowledge - that is that it clearly
offers a meeting ground for a very diverse community of researchers with
different approaches to theorising about society. We may all disagree on
methodology, epistemology and paradigm positions, but at least
simulation seems to offer a common ground for a substantive conversation
about what we do and how we work.

Alan

> -----Original Message-----
> From: News and discussion about computer simulation in the social
sciences
> [mailto:[log in to unmask]] On Behalf Of Scott Moss
> Sent: 25 November 2003 09:43
> To: [log in to unmask]
> Subject: Re: Simulation and Explanation
>
> Leigh Tesfatsion wrote:
>
> > The labor market experiment I reported in an earlier email is a case
> > in point.  As discussed in more detail in that earlier email, a key
> > **observation** in empirical labor studies is "excess heterogeneity"
> > -- substantial unexplained variation in wage earnings that persists
> > even after attempts are made to control for all relevant structural
> > factors (gender, industry type, schooling, etc.).    Recently
> > (Econometrica 1999), using very long panel data (observations!),
John
> > Abowd et al. uncovered a surprising effect:  Simply adding workers'
> > names to the list of regression variables led to substantial
reduction
> > in the unexplained variation in wage earnings across workers who
> > appeared to be in structurally similar circumstances.  These
> > *empirical observations* then led me to wonder whether personal
> > non-price interaction effects on the work-site could -- even in
> > principle -- sustain persistent variance in wage earnings among
> > workers whose observed structural characteristics were absolutely
> > identical.   I set up a simple experiment to test this conjecture,
and
> > received a strongly affirmative answer.   More to the point, I was
> > able to see two distinct sources for the persistent wage variation
> > (behavioral effects and network effects).   I was also able to see
> > that outcome distributions for any given treatment did not take a
> > "normal" central tendency form (a common social science a priori
> > assumption) but instead were spectral (multiple peaked) in nature.
> > These findings, while understandable after the fact, were certainly
> > not anticipated by me in anywhere near this specificity.
> >
> > As I now continue on with my agent-based computational modeling work
> > focusing on unemployment benefit programs (e.g., in Iowa), and on a
> > reliability study of New England's restructured electricity market
as
> > a consultant for the Los Alamos National Lab,  I take with me from
> > these simple labor market experiments the cautionary warning that
> > non-price behavioral and network interaction effects can be very
> > strong indeed, leading to spectral rather than central tendency
> > distributions of outcomes even for similarly structured entities, so
I
> > should be extremely careful not to engage in inappropriate pooling
> > purely on the basis of a priori structural categorizations (e.g., a
> > priori lumping together data for all generators of a certain size
and
> > fuel type).
> >
> > In short, observation led to theorizing which in turn is changing
the
> > way I am organizing observed data in subsequent empirical studies,
and
> > so it goes in an endless feedback process.
>
> Leigh uses a prisoners' dilemma game theoretic formulation.  Either
this
> was an arbitrary design choice based only on its use in other
similarly
> arbitrary model designs or she validated the design against some
> evidence about the behaviour of workers.  She does not say that she
has
> validated the spectral distribution of outcomes.  In the worst case,
> therefore, Leigh has a wholly unvalidated model inspired by an
empirical
> observation.  However inspirational she finds the results, I do not
> understand how she could use such a model with confidence to formulate
> social policy.
>
> > By the way, I believe your original question asked for "excellent
> > examples of simulation providing explanation in any field."
Somehow,
> > in all the email that has ensued from your original email, I have
seen
> > general dismissive remarks and abstract discussion but not a
response
> > to your request per se -- which I interpret as a request for
*specific
> > constructive examples*.
> >
> > How about it, other readers?  How about engendering more
constructive
> > discussion on the basis of *specific* examples?
>
>
> Off the top of my head, there is the VDT model produced by Ray Levitt
> and colleagues at Stanford, the models of the Anisazi by George
Gumerman
> and colleagues, models of domestic water demand produced for the UK
and
> Catalonia as part of the European FIRMA project, I'll chuck in one of
my
> papers on critical incident management in JASSS a few years ago, a
model
> of electricity usage by Jan Treur's team in Amsterdam (reported I
think
> in ICMAS-98), Kathleen Carley's recent work on biological weapons use.
> What these all have in common is that they are descriptive first.  It
is
> also the case that some generalisable techniques have been developed
in
> the course of mplementing these models.
>
> regards,
> Scott