Download 1 On invisible trade relations between Mesopotamian cities

On invisible trade relations between Mesopotamian cities
during the third millennium B.C.*
Audrey Bossuyt
Université Libre de Bruxelles
Laurence Broze
GREMARS, Université de Lille 3 and CORE, Université Catholique de Louvain
and
Victor Ginsburgh
Université Libre de Bruxelles and CORE, Université Catholique de Louvain
August 1998
Revised February 2000
Abstract
The idea that the emergence of writing was a necessity due to both the increasing
number of economic transactions and political complexity has been recently
emphasized by Matthews who also underlines that writing acted as a feedback in
enabling and encouraging the growth of ever more complex modes of exchange.
The intertwinment of trade and writing suggests that clay tablets left by the
civilizations from the third millenium B.C. in Mesopotamia (where writing was
invented) may be considered as traces of trade links and transactions between cities.
We estimate a gravity model based on clay tablets, as if they represented trade
flows. The parameters lead us to conclude that Mesopotamia formed a strongly
integrated market.
Published The Professional Geographer 53 (2001), 374-383.
1
Introduction
The idea that the emergence of writing was a necessity due to both the increasing number
of economic transactions and political complexity is emphasized by Matthews (1997) who
writes that "the economically driven expansionism of the Late Uruk [latter half of the
fourth millenium] culture system can without difficulty be seen as the natural context for
the origin and early development of proto-cuneiform writing [...]. We have the undeniable
presence of the imported commodities at the site of Uruk, just as we have their attestation
in the earliest written documents." Matthews also underlines that writing acted "as a
feedback loop in enabling and encouraging, through accuracy and accountability in
economic transactions, the growth of ever more complex modes of exchange and
redistribution."
The intertwinment of trade and writing suggests that clay tablets left by the
civilizations from the third millenium B.C. in Mesopotamia (thus about five to ten
centuries after the emergence of writing) may be considered as the visible traces of the
(otherwise invisible1) trade links that existed between cities.
Though these texts do not allow reconstructing even approximate trade data, one
may think of using the number of tablets found in a given city and the information this
provides on other cities to represent the intensity with which trade was carried out. The
essential idea of the paper is to exploit the information given by the number of citations of
a given city in the texts found in other cities and to test whether these traces of transactions
are consistent with a simple but suggestive model of trade relations. This is the so-called
gravity model in which trade relations between two regions (countries, cities) are related to
the importance of each region, the "distance" between the two regions, and other
characteristics such as the existence of trade agreements or other trade enhancing (or
restricting) factors.
The paper is organized as follows. First, we describe very briefly the geographic,
historic and economic environment in which the civilizations of the third millennium B. C.
evolved, stressing the importance of trade relations, though transportation must have been
difficult to carry out, given the geographical conditions. We then turn to the model used, to
the database that we constructed with this aim in mind and to the results obtained by
estimating a gravity equation which tries to explain intercity "trade." The fit that we obtain
is surprisingly good and shows that distance and transportation difficulties did not seem
to play any restrictive role in trade relations.
2
Geographic, historic and economic background
The Euphrates and the Tigris rivers constitute the backbones of the vast region with which
we are concerned; both rivers spring up in the north (Armenia). The Euphrates flows
through Turkey, and bends south-east, the Tigris flows directly south-east. They end up
joining in the south, forming the so-called Shatt-el-Arab delta, before flowing into the
Persian Gulf. The various subregions of this very large territory which became known as
Mesopotamia2 are also linked by rivers which flow into the Euphrates and the Tigris.
During the fourth millennium B.C., the Uruk civilization emerges and the first
signs of cities becoming larger can be observed. One of these is the city of Uruk. The
large architectural monuments and palaces that survive--and are today the subject of our
admiration--as well as the earliest manifestations of writing date back to this era.
Urbanization grows and cities are founded in the land of Sumer, in Babylonia, as
well as along the Tigris and the Euphrates. A few more cities are located west of the
Euphrates, not far from the Mediterranean sea. Around 2370 B.C., Sargon unifies
Mesopotamia, but his empire collapses around 2230 B.C. when the powerful city-states
take over again. Anarchy prevails for over a century thereafter. Then, between 2100 to
2003 B.C., political control succeeds in centralizing once more, under the dominance of
the city of Ur (third dynasty) which rules over the whole region of Sumer. The written
evidence that is used in our paper was left by these two civilizations.
Archeological excavations in these areas have however been far from systematic.
The information available for certain periods and cities is therefore scarce, especially in the
case of cities in the delta which were regularly flooded. Even when found, tablets have not
all been read and/or translated. The tens of thousands of texts written before and during
the Akkadian empire and the third Ur dynasty are essentially records of transactions,
contracts and inventories, established by scribes who may be considered as the
bookkeepers of the temple or the palace in each city. These texts are, nowadays, the only
visible signs of the growing commercial and trade activities that took place during the third
millennium.
Such activities were essentially undertaken by priests (the temple) and, later under
the third dynasty, by the state (the palace)--though, according to Crawford (1973), it is not
always possible to dissociate both--and probably3 by private merchants as well. Among
the goods traded between the various regions, there is copper from Anatolia, tin from
Persia, silver from Armenia, gold found in several mines between India and Egypt, wood
from Lebanon, stone from Zagros and many luxuries, including precious stones, oils and
slaves. These commodities were probably exchanged for textiles (wool), leather (including
hides), fish and grain produced in surplus in the fertile river basins. Bronze, invented at the
end of the fourth millennium, has by then become a commodity of important trading. The
3
potter's wheel, also invented during that period of time, made it possible to produce
earthenware in a more efficient way.
Transportation was mainly ensured by boats, built in shipyards to be found in
almost every city located along a river. Donkeys were used on land, when rivers were
impossible to navigate, and, obviously, to cross deserts. Two main roads connected the
southern delta and the west. The first led from Sippar to Mari and then, crossing the
desert, it reached Qatna and the Phenician ports on the Mediterranean sea. Though longer,
the second one was safer as it did not go through a desert; it also started in Sippar,
followed the Tigris to Nineveh and then turned west towards the sea, through Nagar and
Harran. Because of the mountains, communications with the eastern part of the country
were much more problematic.4 See Fig. 1 for a map of the region, which gives the
locations of the main cities and illustrates the main landroutes.
The problem and the database
We chose some thirty cities that were active during the last centuries of the third
millennium. They cover relatively well the whole region: the northwest, the southern delta,
and the center along the Tigris river (see map). We also limited our choice to cities for
which the precise location is known, as distance beween cities will be one of the factors
explaining the intensity of trading relations.
Since trade flows between cities are unknown and cannot be retrieved, we thought
of proxying them by the number of times each city is quoted in the documents discovered
(as well as translated and classified) in every other city. These documents cover four types
of activities: letters exchanged between the king and his diplomats or other monarchs;
texts related to the administration of the city itself (population censuses, tax collections,
stocks of raw materials and agricultural produce, etc.); texts dealing with the administrative
management of the provinces (letters from the king to his agents and administrators); and
finally, texts concerned with the administration of the king's palace (including inventories
of cellars and storerooms).
This research was somewhat facilitated by the existence of compendia5 which
make it possible to determine the number of times a city is mentioned in the archives of
other cities.6 In the case of the third dynasty of Ur, however, provenance of the documents
is unknown in many cases. Excavations conducted in cities from this period were often
illegal and the documents found were sold (even to museums) without any mention of
provenance.7 For these cases, we followed the expertise of assyriologists and attributed
provenance to four cities (Lagash and Ur (30% each) and Umma and Uruk (20% each)).
Note that we have documents quoting 30 cities, but discovered in 11 cities only; this
means that there are many missing "trade flows," a situation that we will have to take into
4
account in our estimation. Moreover, we decided to distinguish between two subperiods
(the Pre-sargonic period and the third dynasty of Ur), since some of the cities did only
exist during one or the other subperiod, and we wanted to avoid "creating" trade relations
that could obviously not exist between cities that were not contemporaneous. Fortunately
enough, the compendia mentioned above draw the distinction between tablets belonging to
either of the two subperiods.
We also need distances between cities but simple geographical distances would be
poor indicators of the time it took to travel, using different transportation means in the very
heterogeneous areas existing in Mesopotamia: there are inaccessible mountains, deserts
which cannot be crossed, unless there exist sweet waterwells on the way, etc. Therefore, we
computed distances in days of travel, either walking or sailing. We started with kilometric
distances for plausible8 routes and then assumed that donkeys would be able to travel 25
km per day, while a boat would sail 50 km per day. Distances vary from half a day
(between two neighboring cities in the delta) to over 80 days (between Eridu in the delta
and Qatna in the west). Archeologists also helped us to construct several indicators related
to the intensity with which excavations were carried out in each city and to the accessibility
of the documents: were the excavations thorough or rather superficial (intensity); how
deep had excavations to go in order to find documents related to the third millenium
(accessibility).9
Table 1 gives an overview of the data for each city considered. The indications 1
and 2 which follow the name of the city (for example Assur 1, Assur 2) refer to the two
subperiods (1 for Pre-sargonic and 2 for the third dynasty of Ur). The other columns
describe location (North, Center, South), area of the city, whether the city was sited in the
southern delta (1 for yes, 0 for no), whether it housed a harbour (1 for yes, 0 for no),
whether it was located on a river (1 for yes, 0 for no), the values describing the intensity of
excavations and the accessibility of the remains from the third millenium B. C. (1 for high,
2 for medium, 3 for low10). Finally, the last columns give the number of citations relative
to a city; the number of self-citations (i.e., citations of a city found in the city itself) is not
included in the former count, and is given separately for those cities in which tablets were
found.
Our objective is to check whether intercity trades (i. e. citations) can be explained
by a certain number of factors thought to be at the root of such commercial relations. The
point of departure is the classical gravity model, based on Newton's well known gravity
law: The attraction force xij between two bodies i and j is directly related to mi and mj, the
masses of the two bodies and inversely related to the (square of the) distance dij between i
and j:
(1)
xij = α0mimjd-ij2,
5
where α0 is a physical constant. Clearly, one does not expect this law to hold as such for
trade relations. In particular, mi and mj could be raised to some power, different from one,
and distance could appear with an exponent that is different from minus two. Therefore,
the previous equation (in logarithmic form) is usually written as:11
(2)
log xij = logα0 + α1log mi + α2log mj + α3log dij + uij.
Here the αi are parameters to be estimated and uij is an error term assumed to be endowed
with the usual assumptions. Interpreting (2) for the case of trade relations, is
straightforward. The dependent variable xij is the trade flow (exports) from j to i, while mi
and mj represent wealth or income in regions i and j, respectively; dij is a measure of the
"distance" between i and j; this is of course not necessarily the simple physical distance,
but could, for example, be the physical distance weighted by the fact that both regions
belong to a common market, speak the same language, are located on the same continent,
etc.12 Then, (2) postulates that the trade flow from j to i can be explained by wealth in both
regions and (negatively) by some measure of the distance that separates them. In many
applications, mi and mj are simply defined as total imports of i:
(3a)
mi = Σkxik
and total exports of j:
(3b)
mj = Σkxkj.
Note that xii = xjj = 0, since there can be no exports (or imports) from a region to itself.
This very simple model has been criticized on many grounds, since, beside distance, it
does not take any spatial patterns into account, failing to model accurately relationships
between destinations (Fotheringham, 1984) as well as possible hierarchical intarcations
(Fik and Mulligan, 1990). This has been taken into account by estimating a separate
equation for each origin and by introducing for each destination, a variable which
measures its accessibility with respect to all alternative destinations. Though this is much
more elaborate than the approach underlying eq. (2), we could not implement the
refinements suggested for two reasons.
First, a large number of observations on origin-destination links is needed, and as
can be checked from Table 1, this is not the case with our database. In several cases, we
have only one or two destinations for a given origin, making it impossible to estimate
separate equations. We could of course have estimated separate equations only for those
6
cases where enough observations were available, but this would have led us to ignore an
important part of the already scant information. Second, we have to deal with the issue of
possible missing observations, because tablets describing origins have not been found yet
(no excavations, excavations not intensive enough, etc.), or have been destroyed or lost
(e.g. by floods). Therefore, we are led to estimate a unique equation of type (2), combining
all pairs of origins-destinations, together with an equation which explains missing
observations. This would be hard to tackle if we were to estimate one equation for each
origin.
In our case, xij is readily defined as the number of times city j is cited in the
archives found in city i. There are several ways to define mi and mj. One possibility is to
use ranks given to cities, based on archeological expertise. Another possibility is to follow
the international trade simile (3a-b), implying that the attractiveness or importance of i, the
"importing" city is defined by the total number of citations found there (including or
excluding self-citations xii, which unlike in (3a) are not necessarily equal to zero), while
the importance of j, the "exporting" city is based on the number of citations of j, found
elsewhere.
After some preliminary experimentation, we performed our work with mi and mj
defined as in (3a-b) and dropped the ranking of cities as a measure of their importance
since it did not come out significantly. In the count of mi, we kept self-citations separate
from other citations so that the "self-citation" variable (xii) can also pick a coefficient
which may therefore be different from the one picked by mi. We added four extra
variables to those defined in the previous section:
(a) A dummy variable (ri) which takes the value one if city i (the one in which tablets are
found) was located on a river, and zero otherwise; this variable is supposed to capture the
negative effect of floods on the number of archives found in a city located on a river.
(b) A dummy variable (Ii) which takes the value 1 if excavations in city i were intensive
(and zero otherwise); the expected sign for the regression coefficient is positive.
(c) A dummy variable (ai) which takes the value 1 if the documents from the third
millenium found in city i were easy to access (and zero otherwise); again, the regression
coefficient is expected to be positively signed.
(d) A dummy variable (pj) which takes the value 1 if city j housed a harbour from which
goods could be redirected to other cities (and zero otherwise); if so, one may expect this
city to be quoted more often.
(e) The area of city i (si); the expected sign could be positive (larger cities were more
likely to have larger libraries) or negative (the likelihood to find tablets is inversely related
to the area of the city).
7
The equation that we estimate is thus written as follows:
(4)
log xij = logα0 + α1log mi + α2log mj + α3log dij + α4log xii + α5ri + α6Ii +
α 7ai + α 8pj + α 9si + uij.
Estmating (4) by ordinary least squares would lead to biased results since some xij
are missing (and are thus equal to zero) in a systematic way, for various reasons: no
intensive archeological excavations in city i, no tablets found, etc. We are therefore faced
with censored data.13 Equation (4) should thus be supplemented by a second equation
which determines an unobserved variable Ti such that if Ti is larger than an unobserved
threshold T, then xij > 0, otherwise xij = 0; observations for which xij = 0 (transformed
accordingly, since we have to take logarithms) have thus to be added to the database. Ti is
unobserved, but there are observations on some variables that are assumed to determine Ti,
and this is the additional equation the coefficients of which have to be estimated:
(5)
T i = δ 0 + δ 1 r i + δ 2 I i + δ 3 a i + δ 4 s i + vi .
According to this equation, Ti is not observed (latent), but determined by city floodings
(ri), the intensity of excavations (Ii), the accessibility of third millenium remains (ai) and
the area of the city (si). The simultaneous model which is estimated consists of equations
(4) and (5), where xij is observed only if Ti > T, where Ti and T are unobserved.
We assume that the errors (uij, vi) are independently normally distributed with zero
means, variances σu2 and σ 2v respectively and covariance ρσuσv. Equations (4)-(5) are
estimated simultaneously by maximum likelihood. To ensure identification of all the
coefficients in (4)-(5), one of the variables in (5) should be absent in (4).14 Details on the
model and the estimation method can be found in the technical appendix.
Results
We first estimated (4) using ordinary least squares, and found that the area of the
city in which tablets were found (si) did not come out significantly. It looked as a good
candidate to be excluded from (4) and included in (5)--where it will appear to contribute in
a significant way. The reason for which it does not contribute in (4) is that, as was pointed
out earlier, the sign can go either way, and the negative and positive effects do probably
cancel out. The results obtained by using maximum likelihood methods to estimate
simultaneously (4) and (5) are given in Table 2. As can be seen from the pseudo-R2 for
eq. (4), the fit is quite high (R2 = ***). All variables contribute to the explanation with the
expected sign, though three coefficients are not significantly different from zero at the
8
conventional 5% probability level (self-citations, the presence of a river--again because of
the two effects which go in opposite directions--, and the intensity of excavations).
Intercity distance picks the expected negative sign, showing that the elasticity of the
number of citations with respect to distance is approximately one fifth, with a small
standard error. This is in sharp contrast with the value of 0.7 to 0.8 found today in
international trade or intercity travel studies (see e.g. Fotheringham (1983) or Fik and
Mulligan (1990)), suggesting that distance seemed to be less of a problem in
Mesopotamia five millenia ago, than it is today even in developed regions, despite the
progress made in transportation facilities. Cities, often very far from each other,
maintained close contacts, implying that Mesopotamia formed a quite strongly "integrated
market." This was obviously mainly due to the lack of raw materials such as timber,
minerals and other raw materials, which had to be imported from other regions, and paid
for by exports of textiles and grain produced in the south-eastern delta region (see above).
Trade was thus an absolute necessity.15
The total number of citations in i and j contribute positively to intercity citations,
though citations of city j (origin) have a much larger impact on xij than the number of
tablets found in i. Self-citations have a small and not significant impact. The existence of a
river, and therefore the possibility of frequent floods, has a strong negative, though not
significant effect, indicating that floods concurred to destroy archives. Accessibility of
remains and the fact that city j happened to be a harbour from which goods could be
redirected to other cities both generate a large increase in the number of citations.
The quality of the fit of equation (5) is more questionable. The coefficient of the
river in city i variable has the wrong sign (note again that the coefficient is not significantly
different from zero). The other coefficients have the expected (positive) sign, but
acessibility has no significant impact.
Conclusions
Since the information contained in Mesopotamian tablets essentially collects and describes
economic transactions (management of supplies, trade flows, etc.), the number of citations
concerning a city in the tablets discovered in other cities can be thought of as indirectly
representing trade flows. We show that this number of citations can be consistently and
quite accurately explained by a simple model that has been often used to analyze trade
flows between countries or regions.
Our most interesting finding is that distance did seem to matter less in ancient than
it does in modern times, implying that autarky was not more, and perhaps even less
sustainable five millenia ago. It would of course be interesting to reproduce such results
9
for other parts of the ancient world and give more direct evidence of the intensity of
commercial links even between very distant locations.
References
Crawford, Hariett E. (1973), Mesopotamia's invisible exports in the third millennium,
World Archeology 5, 232-241.
Fik, Timothy J. and Gordon F. Mulligan (1990), Spatial flows and competing central
places: towards a general theory of hierarchical interaction, Environment an Planning A
22, 527-549.
Fotheringham, A. Stewart (1981), Spatial structure and distance-decay parameters, Annals
of the Association of American Geographers 71, 425-436.
Fotheringham, A. Stewart (1984), Spatial flows and spatial patterns, Environment and
Planning A 16, 529-543.
Maddala, G.S. (1983), Limited-Dependent and Qualitative Variables in Econometrics,
Cambridge: Cambridge University Press.
Matthews, Roger (1997), The emergence of writing in the ancient Near East, in En Syrie,
Aux Origines de l'Ecriture, Bruxelles: Brepols.
Nelson, Forrest D. (1977), Censored regression models with unobserved censoring
thresholds, Journal of Econometrics 6, 309-327.
Oppenheim, A. Leo (1954), The seafaring merchants of Ur, Journal of the American
Oriental Society 74, 6-17.
Potts, Timothy F. (1993), Patterns of trade in third-millenium BC Mesopotamia and Iran,
World Archeology 24, 375-402.
10
Table 1 Characteristics of the cities quoted
____________________________________________________________________
City
Period*
Location
Area
Delta
Harbour Intensity Accessib. No.cit.
of excav. of excav.
____________________________________________________________________
Alalakh
1
N
30
0
0
1
2
7
Assur
1
C
100
0
1
1
2
6
Assur
2
C
100
0
1
1
2
6
Ebla
1
N
55
0
0
1
1
7
Ebla
2
N
55
0
0
1
1
18
Emar
1
N
35
0
1
2
1
217
Eridu
1
S
30
1
0
1
2
26
Eridu
2
S
30
1
0
1
2
34
Eshnunna 1
S
60
1
0
1
2
5
Eshnunna 2
S
60
1
0
1
2
36
Halab
1
N
60
0
0
3
3
22
Harran
1
N
30
0
0
3
3
14
Isin
1
S
60
1
0
2
2
21
Isin
2
S
60
1
0
2
2
32
Kanesh
1
N
30
0
0
1
1
3
Karkemish 1
N
30
0
1
3
3
5
Kish
1
S
200
1
0
1
2
69
Kish
2
S
200
1
0
1
2
29
Lagash
1
S
300
1
0
1
1
60
Lagash
2
S
300
1
0
1
1
413
Larsa
1
S
80
1
0
2
2
21
Larsa
2
S
80
1
0
2
2
5
Mari
1
C
120
0
0
1
1
202
Mari
2
C
120
0
0
1
1
45
Nagar
1
C
50
0
0
1
2
2
Niniveh
1
C
50
0
1
2
2
73
Niniveh
2
C
50
0
1
2
2
97
Nippur
1
S
60
1
0
1
2
67
Nippur
2
S
60
1
0
1
2
625
Nuzi
1
C
4
0
0
1
3
19
Qatna
1
N
100
0
0
2
2
2
Shuruppak 1
S
60
1
0
2
2
17
Shuruppak 2
S
60
1
0
2
2
74
Sippar
1
S
35
1
0
2
2
6
Sippar
2
S
35
1
0
2
2
24
Suse
1
S
150
0
0
1
3
19
Suse
2
S
150
0
0
1
3
284
Terga
1
C
35
0
0
2
2
3
Tuttul
1
N
35
0
0
2
2
9
Tutub
1
S
40
1
0
1
2
1
Tutub
2
S
40
1
0
1
2
3
Umma
1
S
150
1
0
2
2
128
Umma
2
S
150
1
0
2
2
351
Ur
1
S
200
1
0
1
2
43
Ur
2
S
200
1
0
1
2
229
Uruk
1
S
400
1
0
1
2
121
Uruk
2
S
400
1
0
1
2
179
Zabalam
1
S
30
1
0
3
2
32
Zabalam
2
S
30
1
0
3
2
65
____________________________________________________________________
* 1 is for the Pre-sargonic period; 2 is for the Third Dynasty of Ur.
11
Table 1 (cont.) Characteristics of the cities
where tablets were found
___________________________________________________________________________
City
Period* Location
Area
Delta
Harbour
River
Intensity Accessib. No.cit.
of excav. of excav.
Self-cit.
___________________________________________________________________________
Assur
1
C
100
0
1
1
1
2
1
1
Ebla
1
N
55
0
0
0
1
1
499
37
Eshnunna 1
S
60
1
0
1
1
2
17
3
Eshnunna 2
S
60
1
0
1
1
2
3
0
Lagash
1
S
300
1
0
1
1
1
471
469
Lagash
2
S
300
1
0
1
1
1
720
155
Nippur
1
S
60
1
0
1
1
2
109
17
Nuzi
1
C
4
0
0
1
1
3
5
19
Shuruppak 1
S
60
1
0
1
2
2
72
2
Suse
1
S
150
0
0
0
1
3
7
4
Umma
2
S
150
1
0
1
2
2
509
87
Ur
1
S
200
1
0
1
1
2
47
32
Ur
2
S
200
1
0
1
1
2
765
98
Uruk
1
S
400
1
0
1
1
2
1
2
Uruk
2
S
400
1
0
1
1
2
555
45
___________________________________________________________________________
* 1 is for the Pre-sargonic period; 2 is for the Third Dynasty of Ur.
12
Table 2
Estimation results
________________________________________________________________________
Coefficient
St. error
________________________________________________________________________
Equation (4)
Intercept (α0)
Importance of city i (α1)
Importance of city j (α2)
Distance between cities j and i (α3)
Self-citations in city i (α4)
River in city i (α5)
Intensity of excavations in i (α6)
Accessibility of remains in city i (α7)
Port in city j (α8)
-2.9292*
0.3483*
0.7897*
-0.2062*
0.1178
-0.4186
0.2388
0.4204*
0.4468*
0.6005
0.0672
0.0431
0.0546
0.0848
0.2590
0.2314
0.2191
0.2196
Equation (5)
Intercept (δ0)
River in city i (δ1)
Intensity of excavations in i (δ2)
Accessibility of remains in city i (δ3)
Area of city i (δ4)
-1.0008*
0.1309
0.4146*
0.2978
0.0049*
0.3248
0.2924
0.2111
0.2729
0.0008
0.7138*
0.3349
0.0660
0.4467
Other parameters
St. error of eq. (4) (σ)
Correlation between eqs. (4) and (5) (ρ)
No. of observations
Log. of the likelihood function
Pseudo-R2 for equation (4)
282
-324.3
________________________________________________________________________
Note. The dependent variable is the number of citations of city j in documents found in city i.
* indicates that the coefficient is significantly different from zero at the usual 5% probability level.
13
Footnotes
* We are grateful to Marc Lebeau, Chairman of the European Centre for Upper Mesopotamian Studies
and Codirector of the Syro-european excavations at Tell Beydar, and to Philippe Talon, professor of
Assyriology at Université Libre de Bruxelles for many enlightening discussions. We also thank J.
Waelbroeck, three anonymous referees and the editor of the Journal for extremely useful comments.
1 We borrow this term from Crawford (1973), though he uses it in a different context.
2 Mesopotamia means "between rivers" in ancient Greek.
3 According to Crawford (1973, p.237), "it is almost impossible on present evidence to know whether
private enterprise also undertook trading ventures."
4 See Oppenheim (1954) and Potts (1993) on detailed descriptions on commodities traded and on how
trade was undertaken.
5 Répertoires géographiques des textes cunéiformes, Beihefte zum Tübinger Atlas des Vorderen Orients,
Reihe B, 7, Wiesbaden: Dr Ludwig Reichert (various authors and dates of publication).
6 These compendia mention every city quoted in a tablet, together with the tablets in which it is quoted.
Knowing the city where each tablet was discovered makes it possible to construct the "intercity flows."
7 Note that this has very often been the case in the past, and it is only very recently, that archeologists,
and museums have come, at great pains, to decide that no museum would any longer buy, accept as
donations or bequests, any archeological artefact if provenance is not explicitly known. Note also that this
agreement has already been breached by at least one museum.
8 With the help of archeologists Lebeau and Talon.
9 The difficulty of accessing the documents from the third millenium depends on whether the city had
been inhabited after the third millenium. If so, the older archeological strata from the third millenium will
be covered by more recent dwellings and this will make third millenium tablets less accessible.
10 In the computations, the three categories were eventually regrouped into two classes: high (1) and low
(2+3).
11 See e.g. Fotheringham (1981).
12 Obviously, more variables could also be introduced in this equation, which take into account several
other factors linking countries i and j.
13 The model we use is due to Nelson (1977). See also Maddala (1983).
14 This is a sufficient condition for identification. See Nelson (1977).
15 We are grateful to J. Waelbroeck for having pointed out this very important conclusion.
14