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I used to say of him that his presence on the field made
the difference of forty thousand men.
Arthur Wellesley, 1. Duke of Wellington
1.
Introduction
Though centuries have passed since the rise and fall of
Napoleon, his military performance continues to fuel
discussion among scholars of history and military science.
Scientific discourse about him and the battles and campaigns
fought during his age are extensive, nevertheless most
research on this topic can broadly be divided into two
approaches: historical and from a practical perspective
employed by military science. Without conflicting the other,
these complement one another, as they independently attempt
to explore very different aspects of Napoleonic warfare.
The first approach is the historical perspective,
practiced among many others by the likes of Blanning
1
or
Smith
2
. Scholars focus on the broad lines of the military
encounters and the grand strategy
3
as the central theme,
interpreted in light of social and cultural aspects as well. A
work of such breadth would usually be written by a historian
and would be culminating in a good descriptive impression
and an overview of most of the aspects of the Napoleonic
times. Due to the nature of historical science, empirical data
would normally only be used in a qualitative way without
employing in-depth quantitative analysis.
4
Moreover the
broader perspective is normally emphasized at the expense of
1
Blanning (1996).
2
Smith (2005).
3
In this thesis I will use the definitions of grand strategy, strategy, grand tactics
and tactics as proposed by Chandler (2001).
4
E. g. statements along the lines of ,he fielded more troops' or ,he had a higher
amount of artillery at his disposal'. These statements, although backed by
numbers, do not give insight into the size of the effect or the nature of it and
therefore can not qualify as quantitative analysis.
- 2 -
detailed aspects and so only statistics of the highest
importance are included so not to obscure the leitmotif of
history.
Military scientists and practitioners using the second
approach usually focus on campaigns and describe the course
of them and the important battles that took place during them.
Their work is highly detailed and covers many different
aspects of Napoleonic warfare. Logistics, infantry tactics,
cavalry attacks and artillery bombardments are explained in
great detail and their effects are scrutinised. These works
usually contain high amounts of empirical data about all the
different subjects and facets of contemporary warfare.
Nevertheless the focus is on the strategy and the tactics and
although numbers are taken into account, their exact impact is
not worked out in detail through a quantitative and
methodical analysis. Their focus on the military factors
furthermore prevents these works to give a comprehensive
view of the Napoleonic times but makes them dependent on
the general approach discussed before.
Although both approaches can be combined for a very
detailed qualitative description of Napoleonic warfare, history
and times there is an evident lack of thorough empirical
analysis of Napoleons military efficiency. Recent research in
economic science has seen an increasing number of papers,
books and theories addressing the subject of conflict from an
economical and rational choice perspective. Starting with the
analysis of `rent seeking' by Gordon Tullock, several other
important theorists
5
have ventured out to study the different
aspects of conflict that border both social sciences and
economics. This thesis attempts to apply their theories of
5
I especially owe much to the work of Hirshleifer, who studied conflicts for years
and always encouraged other economists to apply the economic theories to
other field of scientific work.
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conflict to the battles of the Napoleonic age and to test several
assumptions derived from the so called Contest Success
Functions that have been put forth as models for the
prediction of conflict outcomes. Although these concepts have
been around for several years and sparked frequent
discussion, there are only some works that actually try to
verify these theories by applying them on actual data.
Hence this thesis seeks to explore the following two
working hypotheses: Firstly, that Napoleon's alleged military
superiority in terms of skill and battlefield competence over
his peers can be empirically quantified and proven. Secondly,
that the results of Napoleonic warfare can be predicted by
applying the theory of Contest Success Functions to these
battles.
6
To address these claims this paper is organized into this
introduction and four different sections, with eleven chapters
in total as follows:
Theory
The first of the conceptual sections summarizes the
theoretical underpinning behind the economical
understanding of conflict. This so called `second approach'
7
6
Interestingly, a similar approach was chosen by two research teams before. In
1962 the Research Analysis Corporation conducted a study on the Lancaster
Equations for the United States Department of Defence. [The Lancaster
Equations being early developments of Contest Success Functions there are
some similarities in the approach, especially in the use of regressions. Willard
concluded that the Lancaster Equations only had a poor predictive value for his
data. Compare Willard (1962) for further information.
The second research work is the so-called Quantitative Judgment Method
Analysis developed by Colonel Dupuy. [Dupuy(1985)] This analysis started from
a historical perspective by manually fitting curves until the conduct of a battle
could be predicted. Although this method has high value for predicting the
outcome of battles, this is only accomplished by using dozens of variables to
increase the predictive value. Although some of the curves are variants of the
Logit-Function this thesis relies on as well, the method used and the sheer
magnitude of explaining variables makes comparison only possible for small
aspects.
7
Hirshleifer (1994).
- 4 -
and its merits are outlined and the history of these theoretical
concepts is explained. Chapter three introduces the Ratio
Contest Success Function (RCSF) put forth by Tullock and the
Difference Contest Success Function (DCSF) employed by
Hirshleifer, the concepts for predicting probabilities of success
in conflict theory.
History
The fourth and fifth chapters are used to outline the
actual conditions during the Napoleonic wars and the data
used for this study. The focus of this part is especially what we
actually do now about these battles and how it may be used.
The fourth chapter gives a brief report on warfare during the
Napoleonic ages. A special emphasis lies on an analysis that
evaluates if the key parameters have been homogenous over
the time and what kind of technology was employed during
these battles. The results are then compared with the demands
of conflict theory. The fifth chapter then explicates the data
set. The different variables that could be obtained are
introduced and at last the scope of the further analysis is
specified. This is done by picking the variables that actually
can be used for an in-depth quantitative.
Modelling
The third part of the thesis is of especial importance, as
the focus of this work is to answer the two hypotheses by
empirical work. In the four chapters that deal with the actual
modelling, the theory is applied on the historical data to yield
the results we need to verify the working hypotheses. After the
two different estimators used have been introduced in chapter
six, the chapters seven and eight deal with utilising each of the
estimators to answer these questions. The results from the
estimates are interpreted and are compared in chapter nine. In
addition, chapter nine attempts to weigh the explanatory value
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of the two approaches and places them in the historical
perspective.
Résumé
The last section of my thesis contains two
chapters. Chapter ten answers comments on Napoleon's
personal worth on the battlefield and applies the findings of
the empirical work on three short case studies.
8
The
subsequent summary then merges the results of the whole
study and concludes with follow-up questions for future
research.
8
The case studies then should answer if Napoleon really had the impact of
40,000 soldiers, like Wellington attributed it to him.
- 6 -
I Theory
There are but two powers in the world, the sword and
the mind. In the long run the sword is always beaten by
the mind.
Napoleon Bonaparate
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2.
The Economy of Conflict The Second Approach
To understand how economist approach conflict, we
first have to master one very important concept of modern
economics, that forms the centre of economic science as we do
know it. This is the fictive homo oeconomicus. This conceptual
person takes everything into account and then tries to
maximise its utility
9
by deciding what to do. Possibilities can
include such trivial decision like the one between going to
work or staying at home
10
or between buying a car or saving
the money. In the later case the homo oeconomicus would buy
a car if he values owning and using it more than the money he
has to pay for it. We always assume that this individual would
make a rational choice, based on its assumptions about the
different possibilities. Conventional economics do know only
one method for this person to make a living: producing useful
goods or services and trade.
11
Although this constitutes by far
the biggest part of economic transactions it nevertheless does
not catch these in total and omits the other side of human
nature and behaviour.
Interestingly, this strict focus on producing goods
evolved only over time. The works that founded economic
science did refer quite often to a very different aspect of
economic behaviour:
"The efforts of men are utilized in two different ways:
they are directed to the production or transformation
of economic goods, or else to the appropriation of
goods produced by others." Vilfredo Pareto
9
The concept of utility will not be detailed here, as it is common economic
knowledge. For our uses it should be sufficient to understand utility as the
amount one does value a specific situation.
10
But even these decisions can be quite hard when the structural conditions are a
bit more complicated e. g. when welfare could be paid out.
11
Compare the definition of economics of most standard textbooks, e. g. Marshall
(1977).
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Adam Smith
12
and Vilfredo Pareto both made many
references to conflicts and how these shaped human
interactions and especially decisions. The merit for
reintroducing this dualism to economic acting goes to Thomas
Schelling, who in his book The Strategy of Conflict
13
outlined
many concepts
14
that nowadays are part of the standard
economic curriculum, after they for some time had been of no
importance
15
. Especially the game theory
16
profited from his
works, which mainly deal with the underlying concepts of
behaviour. Several later scientists then started to sketch out a
theory of conflict interactions. During the 1970es Tullock
17
"was [...] the first to employ standard analytical building
blocks [...] for dealing with conflict interactions".
18
By this
inventive and new approach it was for the first time possible to
conduct a thorough analysis of conflicts from an economic
perspective and to foster a better understanding of how
conflicts actually do work.
But conflict theory is not so very one sided to explain
only how conflict evolves it even does not predict that all the
time clashes have to occur. Nash-equilibriums not only include
the best amount of input for a conflict, but can explain
cooperation as well. To show how the parts of conflict theory
interact, we have to distinguish four aspects that together
explain what happens before, during and after:
19
12
Adam Smiths ,,The Wealth of Nations" cites war and conflict regularly.
13
Schelling (1960).
14
The most widely known of these is the concept of commitment, where one side
constrains the options of its adversary by binding itself.
15
Nevertheless these mostly ,conflict-less' times saw the development of the
Lancaster Laws, which were early special cases of the Ratio Contest Success
Function which will be discussed later.
16
The game theory attempts to capture behaviour in strategic situations by
mathematical terms.
17
Tullock (1974).
18
Hirshleifer (2001), p. 4.
19
These four aspects are presented in Hirshleifer (2001), p. 13.
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Sources of Conflict
These can range from different preference sets up to
totally irrational reasons for conflicts, e.g. hate, distrust or
love. They are the starting point for the whole affair.
Depending on their shapes they can make conflicts more
intense or make it easy to bridge the gap and cooperate.
20
Because this thesis analyses the battles and their outcomes,
the sources of conflict during the Napoleonic ages are not to be
discussed here in depth. Suffice to say that there are several
brilliant books written by historians that cover these conflicts
and how they evolved.
21
For our analysis it is only necessary to
assume that there is conflict and that during the battles it can
not be solved by any kind of cooperation or agreement short of
a surrender, so that the battles have to be fought out.
Technology of Conflict
This category includes the analysis of the technology
actually used to fight out the conflict either in a
metaphorical way where leaflets or television campaigns could
be the technology, or when these measures are actually used to
have fights and wars. The importance of the tools used to wage
a conflict lies within the differences of them. Without
distinguishing between them, a rational choice is not possible.
Therefore it is not only necessary to differentiate among these
instruments, but for every choice it has to be considered how
to get this kind of technology, how to use it, what the costs are
and what the impact upon the conflict will be.
20
Amazingly it can even happen, that intense sources of conflict can ease
cooperation, e. g. when both parties involved are willing to give everything up
for the fight and both parties know this and do not want to take the chance.
21
Although all the books in the references should be able to shed some light on the
sources of the Napoleonic wars, especially ,,The Napoleonic Wars: Rise and Fall
of an Empire" by Barnes and Fisher (2004) gives a good first impression of
them.
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In contrast to conflicts with diverging sources, it is not
always possible to compare conflicts them when the
technologies are not the same among them. Each set of
technology offers a unique set of choices and possibilities to
the actors. Hence different conflicts can only be compared if
some of consistency holds true for the situations that are to be
analysed. It will be of importance to have a closer look at the
technology used during the Napoleonic wars to make sure that
the battles can be compared without blurring the results.
Modelling of Conflict
The actual modelling of the conflict tries to put the
interactions during it into a theory, which most of the time is
expressed at least partially through mathematics. This is
generally a problem of "optimization on the decision-making
level",
22
where we are interested in how probable it is to win a
certain conflict or how big a share of the booty we can expect.
During the modelling several aspects have to be taken
into account. Technology, resources, the intensity of the
conflict all these are variables that might influence the result
and therefore have to be checked for their impact. There are
umpteen different approaches to actually modelling a conflict,
from black-box-models, where no assumptions are made
about what actually happens, to the highly complex war games
of the military, where thousands of variables are taken into
account. Small level, multi party conflicts with homogenous
technologies among the parties are of a special interest. These
approaches include the Contest Success Functions (CSF),
which model the probability of winning a certain contest or
conflict subject to the inputs by the parties involved and which
shall be used later on.
22
See Hirshleifer(2001), p. 18.
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Consequences of Conflict
Consequences can range from getting no or less money
to very grave ones like getting killed or defeated in a military
struggle even cooperation and peace are possible. Military
battles often not only yielded partial results in the style of a
won battle, but could lead to crushing defeats of whole
countries. These consequences have to be taken into account
when the actual modelling takes place, although some
interesting results can be obtained about them during
modelling as well.
It would be beyond the scope of this work to include all
the different consequences into the analysis of the battles. For
this thesis the consequences of a certain battle are either to
hold one's ground or the retreat from the battlefield and hence
the loss of terrain, initiative and cohesion among the forces.
Conclusion
But in how far is this of reference for the two working
hypotheses? The first hypothesis states, that the presence of
Napoleon had an impact on the French probability of winning
a battle. This is actually both an amendment to the technology
of conflict and the modelling. By making the presence of
Napoleon possible, the technology set is augmented with one
more option and this addition has to be integrated into the
modelling as well.
The second hypothesis postulates that the battles of that
era can be modelled via the Contest Success Functions. These,
like we shall see in the next chapter, say that the input of the
competitors the committed forces in military terms can be
- 12 -
used to predict the outcome of such a conflict situation.
Therefore this hypothesis augments the technology set as well
by introducing the input of forces and makes a statement
about the kind of modelling actually to be used.
The most important aspects of conflict for testing these
hypotheses therefore are the actual modelling of the conflict
and to a much smaller degree the technology of the
conflict.
- 13 -
3.
Modelling Contest via the Contest Success Functions
It is important to understand some basic concepts
about Contest Success Functions in general before moving on
to the special Contest Success Functions by Tullock and
Hirshleifer. Hence this chapter will first introduce basic
aspects of Contest Success Functions, before the two special
ones are introduced and analysed. At last it will be discussed
when which function might be applicable.
a.
Contest Success Functions in General
The concept of economic contest evolved, when Tullock
introduced a new approach to measuring the welfare costs of
monopolies.
23
In his paper he argued that the traditional
approach to calculate the costs of a monopoly for society were
flawed, because they omitted the costs that are connected with
the struggle about the monopoly. In principle the patrons are
overreached in a monopoly case, as the producer can charge
them prices that are higher then they would be in the case of
competition. Therefore the monopolist can make a higher
profit then he could have by selling the same amount on a
competitive market which is highly desirable for him.
Additionally to these burden to the consumers, there is
another burden to society: the costs of the struggle for this
desirable case of being the monopolist. These costs can be
varied and can include lobbying costs, marketing, new
facilities or even bribes - to name only a few. Tullock showed
that these costs also have to be taken into account when
calculating the costs a monopoly had for society. Starting with
this problem of the so-called `rent-seeking'
24
, many more
conflicts were recognised.
23
Tullock (1967).
24
This term was actually coined by Krueger (1974).
- 14 -
Hirshleifer then put forth the argumentation that these
thoughts should be broadened and that the models that had
been designed to describe rent-seeking compromised only a
small part of a much bigger family of Contest Success
Functions. He argued that these Contest Success Functions
could be applied to every conflict situation to provide it with a
theoretical background. Furthermore his impression was, that
on the border of social sciences and economics these Contest
Success Functions would offer new opportunities to shed light
on how conflicts evolve and especially on who will be the
winning party.
25
During further research it emerged, that there
are some characteristics that all Contest Success Functions
have to share and which can be stated with an axiomatic
character.
26
As these are best expressed in mathematical terms, we
first need to define the variables we are going to use:
let
n
be the finite number of contestants in this
contest;
let
c
i
be the amount of effort the i
th
contestant puts
into winning this conflict measured in cost units;
let
p
i
(c
i
) be the probability of the i
th
contestant to emerge
as the winner of this conflict.
Then we can express the three absolutely needed
axioms about Contest Success Functions this way:
25
Compare Hirshleifer (1989) for more information.
26
For a formal analysis check Skaperdas (1994). For the sake of simplicity only the
three most important axioms will be discussed here. It will become evident, that
only these will be needed to create econometric models by which to estimate the
exact CSF later.
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A1.
p
i
(c
i
)
=1
i
=1
n
and
p
i
(c
i
)
0 for all i
and
p
i
(c
i
)
> 0 if c
i
> 0.
A2.
p
i
(c
i
)
c
i
0 for all i
and
p
i
(c
i
)
c
j
0 for all j i.
A3. For any permutation
of the n contestants
p
(i)
(c)
= p(c
1
)
= p(c
2
)
= ... = p(c
n
)
will hold
true.
27
Axiom 1 states that all the probabilities sum up to one in
the end, the probability of winning of every contestant is at
least zero and that if you put any kind of effort into the contest,
your probability of succeeding will not be zero. Axiom 2 dilates
this with the presumption that if you put more effort into the
contest your probability of succeeding will rise and that it will
fall if any other contestants decides to invest more. The
anonymity property statement of Axiom 3 then predicates,
that the probability of winning for every contestant does only
rely on his effort, not on who he his.
Any kind of function that tries to model contest has to
fulfil these requirements to give predictions that are at least
conceivable. Nevertheless, these axioms are only the lowest
bar every kind of economic modelling has to take. In no way
do they differentiate good models from bad ones - but only
models that could describe reality from those models that
never could do so. During research two families of Contest
Success Functions evolved, which dominate conflict economics
27
This approach owes greatly to Skaperdas (1994), who was among the first to
point out these fundamentals in such a clear manner.
- 16 -
nowadays. Both have unique features and fulfil all the three
axioms introduced above, so that they can be used for
modelling. Named after their most striking characteristics
these are the Ratio Contest Success Function and the
Difference Contest Success Function, which will be discussed
and explained now.
b.
The Ratio Contest Success Function
In Tullock's basic model of `rent-seeking' the probability
of winning for a contestant
28
was determined by the ratio of
the own effort and all efforts together. For the case of only two
players this can be expressed as:
p
1
=
c
1
c
1
+ c
2
.
This fairly basic model was in turn amended by several
papers
29
and evolved by adding a factor m , the so called `mass-
effect-parameter', and a factor k
i
which measures how
efficient the effort of the i
th
player is.
30
The amended and
generalized Tullock function then evolves into the generally
applicable Ratio Contest Success Function:
p
i
=
(k
i
c
i
)
m
(k
j
c
j
)
m
j
=1
n
.
The Ratio Contest Success Function obviously fulfils all
the three axioms we established during the general approach
to Contest Success Functions and therefore does not conflict
with reality per se.
31
Furthermore, it has a special attribute
that characterises it: p
i
(
c
i
)
= p
i
(c
i
) for all i . This implies that
28
Contestant and player will from now on be used as synonyms.
29
Hirshleifer (1994) credits among others Hillmann and Katz (1984), Corcoran
and Karels (1985) and Hillmann and Samet (1987) with the improvement of the
Tullock model.
30
This factor
k
i
can be the same for all players a special case when it looses it
meaning but we can not assume this without proof.
31
Proof for this is trivial and can be found in Skaperdas (1994).
- 17 -
if all the inputs are multiplied by a fixed amount
, no results
and probabilities will change.
32
Using the Ratio Contest
Success Function the probability of winning a conflict does
only depend on the ratio of the efforts involved, the `mass-
effect-parameter' ( m ) and the efficiency of the individual
players ( k
i
). If all players increase their efforts with the same
ratio, no effects will occur. The contrary happens when the
players increase their efforts by the same amount the
probabilities will change then.
33
Interestingly the behaviour of the Ratio Contest Success
Function depends only on the `mass-effect-parameter' m when
only one player changes his efforts. Regardless of the level of
m
it always holds true that p
i
= p
j
if k
i
c
i
= k
j
c
j
. For m
1 the
player will face diminishing returns to his efforts all the time.
When m
>1 increasing returns to effort are possible at the
start, with diminishing returns later on. This is illustrated by
Figure 1.
32
Proof:
(
k
i
c
i
)
m
(
k
j
c
j
)
m
j
=1
n
=
m
(k
i
c
i
)
m
m
(k
j
c
j
)
m
j
=1
n
=
m
m
(k
i
c
i
)
m
(k
j
c
j
)
m
j
=1
n
=
(k
i
c
i
)
m
(k
j
c
j
)
m
j
=1
n
= p
i
(c
i
)
.
33
Except for the special case when all the players invest the same effort and are
equally effective in applying it.
Figure 1.
Ratio Contest Success Function
- 18 -
c.
The Difference Contest Success Function
Although Tullock's model obviously has its merits for
instance it is easy to understand and work with - there are
nevertheless several flaws that can render it less usable for
some applications. Hirshleifer criticises, that "there is an
enormous gain when your side's forces increase from just a
little smaller than the enemy's to just a little larger".
34
Especially when the efforts of both sides are high the Ratio
Contest Success Function will not award further input with a
considerable increase in the probability of winning
35
but does
predict only a very small effect on the probabilities. Instead of
amending the Ratio Contest Success Function to compensate
for these flaws, he proposed another sort of model that is
based not on the ratio of the efforts but on the differences
between them.
36
Keeping in mind the axioms A1 to A3 and further
postulating that success in contest depends upon the
difference between the resources committed, he offered the
following model, which is now known as the Difference
Contest Success Function:
p
1
=
1
1
+ e
(c
2
-c
1
)
.
This formula is a specific case of the family of the
logistic functions, where
is the `mass-effect-parameter' for
the difference form. This family of functions has several
special features that make them very attractive for describing
probabilities. The most important of these attributes in the
case of the Difference Contest Success Function is the returned
34
Hirshleifer (1994), p. 93.
35
This is because of the diminishing returns to effort.
36
It can be argued that amending the Ratio Contest Success Function would not
have been possible at all.
- 19 -
value, which always is between 0 and 1. Similarly to the case of
the Ratio Contest Success Function, this simple case with two
contestants can be generalized by introducing an efficiency
parameter k
i
for the individual players and by raising the
amount from 2 to n. The result is the general form of the
Difference Contest Success Function:
p
i
=
e
k
i
c
i
e
k
j
c
j
j
=1
n
.
37
Where the Ratio Contest Success Function was not
affected by proportional increases of all efforts, the Difference
Contest Success Function is not affected when all players
increase their efforts by the same absolute amount.
38
Contrary
to the Ratio Contest Success Function, in this case the `mass-
effect-parameter'
does not change the general shape of the
returns to efforts curve but does influence how steep these
effects are.
37
The proof that the Ratio Contest Success Function does comply with A1 to A3 is
trivial. See Skaperdas (1994) for further information.
38
Mathematically this can be expressed as
p(c
+
) = p(c)
, where
is a vector
of the same dimension as
c
and
i
=
j
holds true for all
i, j
.
Figure 2.
Difference Contest Success Function
- 20 -
d.
Choosing the Right Contest Success Function
A visual comparison of the two Contest Success
Functions shows us, that under some circumstances both can
look remarkably alike. This is the case when the players
commit nearly the same amount of effort. For every Ratio CSF
there exists then a Difference CSF that has exactly the same
increase in probability for a further unit of effort.
39
Hence it can be complicated to differentiate between
the two kinds of Contest Success Functions practically,
especially when the measured efforts of the contestants do not
vary much among each other and among the contests. In cases
where either the efforts among the contestants or among the
contests do vary more it gets easier to differentiate and to
decide upon the function with the greater explanatory value.
Theoretically we would expect the RCSF to be of higher
value if the contest is conducted under optimal circumstances
where total information for all the players and perfect
39
To get the same slope in this point
=
m
c
has to be fulfilled. For proof of this
skip to Appendix A.
Figure 3.
DCSF (
= 0.04
) and RCSF (
m
= 4
)
- 21 -
homogeneity of the efforts can be assumed, the RCSF is
normally chosen. When we expect frictions to happen and
decisions problems for the players to arise, we would assume
that the DCSF would prevail.
This is a result of the way the functions are modelled
and is much easier to understand, if one assumes the analogy
of a battlefield. The RCSF would describe the battle pretty
accurately if the battlefield were flat, had no fog, offered no
places to hide and we could use all our units simultaneously
and wherever we wanted them to be right at this moment. We
then would expect the larger force to use its superior numbers
for a concentrated assault. It would be logical for the
defending force to concentrate as well, as smaller units would
have even smaller chances of winning. Therefore we expect an
all-out battle of attrition that concentrates in one spot with all
the forces.
The DCSF describes a totally different battlefield, on
which movement, dispersion and knowledge about the enemy
are all limited. We then can interpret the difference between
the two parties involved as reserves that the superior force still
can use, after the whole enemy force has been engaged. This
force then could be used to fight only at certain spots and not
against all of the enemy force. Hence we expect this kind of
battle to be divided into smaller encounters where different
units fight each other, with one side having reserves in the
backhand. This model hence should provide to be a better fit if
we try to analyse battles that only lasted a certain time and so
could not evolve into battles of attrition.
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II History
History is the version of past events that people have
decided to agree upon.
Napoleon Bonaparate
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4.
The Essentials about Napoleonic Warfare
During the discussion of economic conflict theory it
emerged, that there are four aspects to every analysis of
conflict on which light has to be shed. We established before,
that the sources of conflict and the consequences do not
belong to the topics of this thesis. In the last chapter we
examined a way of modelling the conflict via the Contest
Success Functions. Nevertheless there still does remain the
question of the technology of conflict. Necessarily this
question could not be answered in an abstract way, as
everything can belong to it. We therefore need to discuss it
directly along the lines of the conflict explored. The following
chapter is based upon several historical works that are listed in
the references in detail. Two of these were of special
importance: The Art of Warfare on Land by David Chandler
40
and Tactics and the Experience of Battle in the Age of
Napoleon by Rory Muir
41
.
As a battle only forms a small cut-out of a war, war itself
constitutes only one way of conflict. During a war everything
can be an instrument to be turned against the enemy
together they make the technology of this war. From the more
subtle ones to the brutish attacks all have to be taken into
account, when deciding what constitutes the technology.
Recurring on the working hypotheses, we do not need to deal
with the technology of these wars in total, but only with what
could be applied during the battles that formed the
culminations of warfare in these times. We now will have to
examine the technology of Napoleonic era battles and will start
with the armament of these times. The soldiers that could be
fielded, the organisation of the armies and their tactics are
examined afterwards.
40
Chandler (2001).
41
Muir (1998).
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