98-23
Purchasing Strategies: The Case
of the Royal African Company
Ann Carlos
Yongmin Chen
University of Colorado, Boulder
and
Ron Smith
Birkbeck College, London
1. INTRODUCTION.
To produce, a companyoften needsto useintermediate goodsthat are the output of
other firms. A key business decision for the company, therefore, is how to acquire such
production inputs. In some situations, there may be a need for relationship-specific
investment (Williamson, 1985). Such investment can prevent the buyer from making
purchases directly from a competitive market, making it desirable to select and contract with suppliers before production starts. At the same time, a buyer may want to
establish relations with more than one supplier as a safeguard against potential opportunistic behavior by a single supplier (Riordan, 1996; Shepard, 1987). To encourage
relationship-specific investment, commitments may be made either through market
contracts (Noldeke and Schmidt, 1995) or through the assignment of ownership rights
(Grossman and Hart, 1986). Since contracts are often incomplete, parties to a relationship may also rely on mechanisms such as reputation to deter opportunistic
behavior (cf. Dybvig and Spatt, 1980; and Shapiro, 1983).
Although theories on optimal purchasing arrangements have been well developed,
few studies have empirically evaluated companies' actual purchasing strategies. The
lack of empirical analysis is not entirely surprising, since contemporary companies
are usually unwilling to provide the information which we would need to judge the
efficiency of their purchasing decisions. The purpose of this paper is to provide some
empirical evidence, based on the records of the Royal African Company (HAC), on
whether and how companies use efficient purchasing strategies in response to the
potential problem of opportunism under relationship-specific investment and incomplete contracts.
Although RAC is no longer in operation, its business records and
purchasing arrangements are available. The RAC is a good case study because it
typically purchasedmore than one hundred different types of goods in a year, and so
offers us an opportunity to study empirically the purchasingstrategiesof a company.
2
trade was complex, in that firms had to predict the demand there for European
commodities. The trade required the HAC to purchase rougWy 150 types of goods in
England ranging from pewter pots of different sizes, textiles of various sorts, iron bars,
beads and various other goods (Davies, 1957, p234). Not only did different regions
along the coast have different requirement, but Africans were also very discerning
buyers and would not trade if the goods were unsuitable. Mistakes were very costly.
As Davies (1957, p232) points out "goods that were unwanted or unsalable, or goods
of the right kind but the wrong color, ...had either to be sent home or left to rot in
a Gold Coast warehouse." For many of these goods, since the RAC had specialized
needsa supplier to the RAC had to make specific investment to meet them. At the
same time, since demand changed rapidly, it was difficult for the HAC to specify
exactly all aspects of a product or even the quantity needed early on.
While the nature of demand could mean specialized investment by a supplier, the
company itself faced the constraint of potential hold-up by its suppliers.
In the
African trade, the timing of ship departures was critical to the success or profitability
of that year's trade.
The journey from England to West Africa took on average
seventy days, with a median length of stay along the African coast of three and a
half months. During this time ships would travel along the coast looking for Africans
willing to trade.l
The ships would then proceed back to England or to the West
Indies. The median journey to the West Indies took about nine weeks, (Galenson
1986, p35). 'ftaders, however, did not want to be on the African coast or to pick up
slavffi during the rainy season which ran from June through August, because disease
was rampant resulting in higher mortality for all. Nor did captains want to arrive in
the Wffit Indiffi during the hurricane seasonwhich runs from August to October. The
RAC agent in Barbados wrote that the best time to arrive in the islands was from
"December to June, being a healthy time and affording plenty of provisions, and ye
1The company also had some posts but the bulk of the trade was a ship-based one.
4
rest of ye year being ye reverse." (August 30, 1715, Galenson 1986, p35). As a result
ships needed to leave London by the end of September and definitely no later than
the end of November.
The RAC had therefore to ensure both that it had its supplies on time to allow the
ships to leave London in the appropriate window and that the supplies were of the
appropriate nature and quality. A breakdown of control over either of these would
impose large costs and could potentially
were thus crucial.
inventories,
Uncertainty
bankrupt
the company. Delivery
about delivery could be mitigated
and quality
to some extent by
which the company did hold, but storage costs could be high particularly
for perishables.
In addition,
in order to decide which of the many items to accumulate
the company had to predict demand which was difficult
when demand for particular
items could change rapidly2.
Theoretical
Background
The fact that there was a deadline by which RAC ships had to leave for Africa
and that contracts were likely to be incomplete
due to demand uncertainties
suggests
the possibility of a "hold-up" problem: without competition from others, a supplier
might refuse to deliver the good unless he was paid a price higher than agreed upon
earlier;
or a supplier
Because timing
considerations
might
and quality
deliver goods of lower quality
consideration
for minimizing
perpetuanas
were once again
wee and bought
of it",
Davies
precludes
but that
we conjecture
caused by such opportunistic
telling the Company
behavior
that after a four year hiatus,
"the Dutch had notice of it a month
of perpetuanas
that
heare before we knew anything
sooner than
of the reason
(1957 p235).
31f there was a competitive
hold-up
in demand
up greate quantitiys
affected profitability,
the inefficiency
21n 1686, the agent at Cape Corso Castle wrote
than had been agreed.3
problem
would
the existence
spot market
not arise.
from which the buyer could obtain
The need for an ex ante relationship-specific
of such a competitive
market.
5
the goods, then this
investment
often
were important in determining how RAC made its purchasing arrangements.
One mechanism to overcome opportunism is, of course, to vertically integrate with
upstream suppliers (Grossman and Hart, 1986; Williamson, 1985). However, the
range of products demanded and the changing patterns of demand precluded up-
stream vertical integration as a solution in most cases.RAC did vertically integrate
downstream where there was a more limited range of specialistskills involved, specialist skills which it acquired in the course of its business. A second mechanism to
attenuate opportunism would be a joint venture where the RAC and supplier share
the profits of the eventual sale. Although the company did allow some of its suppliers
small amounts of space on its ships for their own trade, given the large number of suppliers and the difficulty suppliers would have in monitoring RAC's performance, such
joint-ventures were not feasible. However, as an alternative to a joint-venture, suppliers could buy shares in the HAC and below we investigate the empirical importance
of this route to achieveefficient purchasing.
A third mechanism by which a buyer can prevent hold-up is to establish purchasing
relationships with several suppliers. Riordan (1996), for instance, shows that it might
be optimal for a buyer to qualify two suppliers by making redundant relationshipspecific investment and then purchasing only from one of them. Riordan's model is
based on the assumption that one supplier can produce the entire output demanded
at an observable constant marginal cost and that the buyer makes the specific investment. In a more general context, we might expect that a buyer with a higher demand
would tend to purchase from more suppliers, for the following reasons. With higher
output demanded, there would be higher ex-post rents, provided that the buyer's
valuation for the product exceedsthe marginal cost of production. Thus the loss
to the buyer is also higher if suppliers have more market powerex post. Therefore,
the higher relati6nship-specificinvestment associatedwith purchasingfrom more suppliers may be justified when the total amount of purchasesis high, since with more
6
suppliers there will be more competition among them and the buyer will have a higher
share of the ex-post rents.4
A fourth mechanism, and the one we think most important, is the possibility that
repeated interactions and reputation effects would help overcome the opportunism
problem under incomplete contracts. This could be especially important for maintaining product quality, over which it is often difficult to contract (Shapiro, 1983).
For reputation to work, there should be a proper rewarding and punishing mechanism. To the extent that suppliers can obtain rents from selling to the buyer, one
such mechanism is to reward good performance with more future business and to
punish bad performance with no future business. Thus, if reputation is at work, we
would expect that a supplier with whom the buyer has longer relations to have relatively more business. Of course, sellers may have different incentives in establishing
and maintaining a reputation, they may behave differently and their relations with
the buyer may last different lengths, as one would expect from the theory of quality
cycles developed by Gale and Rosenthal (1994). For reputation effects to work, the
expected value to the supplier of continuing the relationship must be greater than the
value of opportunism.
supply uncertainty.
These expected values will depend on exogenous demand and
Even if the supplier did not behave opportunistically, future sales
may not materialize either becausethe supplier went out of business (e.g. because of
death) or because the HAC did not need that particular product due to changes in
tastes in Africa.
41£suppliers compete in the Bertrand fasion, then the buyer will only needtwo suppliers in order
to prevent hold-up by a supplier and to capture the entire rents in the production stage. More
gererally, however, suppliers may still obtain positive rents with competition due to factors such as
increasing marginal costs, capacity constraints, and imperfect information.
7
3. EMPIRICAL
ANALYSIS
Below we describe the data, examine the importance of demand uncertainty, consider market structure5 and examine the effects of the length of the relationship on
the market share of a supplier.
We are primarily concemed here with describing
the extent to which the patterns in the RAC purchases followed efficient purchasing
practices, rather than to estimate structural models of their decision making process,
which \vould be conditioned on much more information than is available to us.
The Data
The original data comprise a set of about 6000 warrants issued to over 2,000 suppliers by the RAC over the period 1672-1699.6 These record the date, the name of
the supplier, the amount paid, and the items purchased. The data are described in
more detail in Carlos and Key (1996). The basic data are then Vijt, the value of the
payments in Pounds Sterling made to supplier i of product j in period t. Thus there
are no price data, just expenditures on the purchase. The specification of i, suppliers;
j, products, and t, time periods, each raise issues.
Identification of suppliers is not always straightforward because of different spellings
for last names7 and because of changes in the person within a family named, e.g. due
to death. We have identified i on the basis of last name, so the family rather than
the individual is regarded as the supplier which we feel is appropriate as we are
interested in reputation.
The distribution of purchases is highly skewed. The global
arithmetic mean of Vijt is £228, the geometric mean is £60. The range is £0.5-23,240,
5We use the term market structure to describe the supply structure that the Company chose.
The true market for these products is much wider than the Company's demand.
6Minute Books, Royal African Company Records,Public Record Office, Kew, England.
7At this time period there was not yet uniformity of spelling. Different clerks could and did spell
the same name differently.
8
the coefficient of skewness is 15.1 and of kurtosis is 404; the skewness and kurtosis
of a normal distribution are 0 and 3. The logarithm of purchases, Vijt8 is roughly
normal, with skewness coefficient of 0.0 and kurtosis of 2.6. Notice that this sample
is truncated in that we have no information on potential competitors who did not
make any salesto HAC and as a result we do not have measuresof the degreeof
competition in the wider market for the product.
The products purchased by the company are diverse: over 150 separately identified
items were purchased. These we have grouped into 15 product categories, partly
based on current SIC categories, though this division is inevitably arbitrary given the
historical nature of the data. Table 1 lists the product categories. The Miscellaneous
category includes what were called East India goods and Guinea stuffS.9 Ship services
include supplying, hiring and building ships. Lumber etc. includes building products
and stone, clay and brass products. Chemicals includes oil and coal products. Textile
mill products included a wide variety of types of cloth. Primary metals include mainly
iron bars which were used as currency in parts of Africa. Fabricated metals includes
other manufacturedmetal products.1O
Choice of t, the frequency of the data, matters. The ideal frequency would be to
match purchases to ships sailings, but this is difficult and would require the ship's
manifest for each ship. Since there is a natural annual cycle of selling, we use a
calendar year, thus t = 1, ..27 (1672-1699, leaving out 1693 when there were no
purchases at all because ofwar).ll
Within a year there are often multiple payments to
8We shall use lower caseletters to denote logarithms.
9East India goods are goods purchased from the East India company such as cowry shells and
textiles, while Guinea stuffs were a particular classification of textiles destined for the coast of
Guinea.
10Davies,1957, in his Appendices provides an annual list of the major products shipped by the
RAC.
llThere is a minor ambiguity about calendar years. Until England switched from Julian to
Gregorian calendars in 1752, English years began on March 25. We treat them as beginning on
9
individual suppliers. These were treated as staged payments for a single contract and
aggregated to a single observation. After aggregation there are 4056 observations.
We define ~t as total purchases of product j in year t; then the market share of
supplier i (the shareof supplier i in total purchasesof that product by the Company)
is ~jt
= \lijt/Vjt.
Summary statistics for the 15 products are shown in Table 1.
It gives the definition of the product, the number of transactions,the total value in
pounds of the purchasesoverthe whole period; the numberof years (other than 1693)
when purchases of that product were zero (Vjt = 0) and the number of years when
all the purchases were made from a single supplier (~jt
= 1). For most commodity
groups, we can see that HAC purchased from more than a single supplier.
The nature of these data are such that, while we are not in a position to estimate
a structural
model of HAC decision-making process due to lack of information
on
the wider market, we can examine the importance of those factors most discussed
in the theoretical literature.
In particular, we examine the role played by demand
uncertainty, the purchase structure of the company and the role played by the length
of the relationship. We also examine the significance of share ownership on the part
of the vendors in enhancing the value of the relationship.
January 1
10
6
Table 1. Summary Statistics for product groups
Product
Nj
~
1
Beads
128
24142
4
2
Miscellaneous
135
108120 1
5
3
General Services
428
40650
1
0
4
Ship Services
358
444697 0
2
5
Freight
350
101460 4
5
6
Food
382
31420 a
1
7
Alcohol & Tobacco
183
26850
2
1
8
Textile l\,fill Products
778
302130 0
1
9
Apparrel
97
5190
7
3
259
13153
2
1
11 Printing and Publishing 59
2138
5
5
12 Chemicalsetc.
82
11519
5
0
13 Primary Metals
202
112770 2
3
14 Fabricated metal etc
405
46629
0
2
15 Ordnance
210
56431 0
3
Total
4056
927310 35
36
10 Lumber etc.
Demand
~t =0
~jt = 1
uncertainty
The value of a continuing relationship will fall and the incentives for supplier opportunism will rise with the probability that the HAC may not need the product in
the future, in other words demand uncertainty. The fact that for ten of the 15 products, there were some years when no purchases of the product were made illustrates
the extent of uncertainty of demand during this period. Another way to illustrate
the degree of uncertainty is to ffitimate a regression for each product of the form:
V;t = Qj +,BjVi + fj Vj,t-l + bjt + Ujt; t = 2, ...,27; j = 1, ..., 15
11
and ask how much of the variation in p.urchasesof a particular product can be explained by total demand in that year, Vi, purchases of the product in the previous
year and a time trend.12 This can be regarded as a proxy for the forecasting model
that suppliers might use to estimate likely demand, given knowledge of previous years
purchases of the product and the state of the African market as a whole, though it
uses data for the whole sample which would not be available to them. The fit of these
regressions is poor. The R2 ranges from 0.05 (product 11) to 0.72 (product 1), with
seven of the fifteen products having R2 below 0.5. The regression overestimates the
predictability of demand, since much of the variability is introduced by total demand,
which probably could not be predicted easily by suppliers. When Vi is excluded, leaving a first order autoregression with trend, the range of R2 is -0.06 (product 11) to
0.63 (product 1) with 13 of the 15 products having an R2 below 0.5. Thus, demand
unpredictability
Purchase
for these products was an important factor in purchasing strategy.
Structure
A simple way to define the purchase or market structure is the reciprocal of the
Herfindahl index:
Ijt
RHjt = (l::: Wi;t)-l
i=l
where I jt is the number of firms supplying product j to RAC in year t and ~jt
is
the share of supplier i in purchases of the product by the Company in that year.
This can be interpreted as the "representative" number of firms supplying RAC. For
instance, if there is a single supplier, a "monopolist", RH = 1. Although we will call
single suppliers monopolists, single suppliers may not have monopoly power if there
is competition in the wider market for the product. This measure has limitations, but
12Thisformulation does not take into account that someobserveddata are censoredat zeroobservations. However, a standard Tobit model would not be appropriate becauseone of the regressors,
the lagged dependent variable, is also censored.
12
15
is probably the best available single summary measure of purchase structure.
The
distribution of RH is shown in Table 2.
Table 2. Distribution of Reciprocal of Herfindahl
RH
1
> 1 < 1.5
1.5 -2
2 -2.5
No
36
35
46
26
2.5 -3
3-3.5
3.5-4
4-4.5
36
23
18
13
4.5-5
5 -5.5
5.5- 6
6-6.5
16
15
14
20
6.5-7
7 -7.5
7.5-
No
No
2
11
8
>8
44
The RAC data has 405 "product years" (tj = 27x15). These405 casescan be split
into four categories. The first category is no demand: in 35 cases(8.6%), RH = 0,
becausethere were no purchases. The second category is effective monopoly. In
36 of the casesthe value of RH was unity, a single supplier, while in a further 35
casesRH lay between 1 and 1.5. An RH = 1.5 coversa two firm market with the
dominant firm having just under 80% of the market and its competitor having just
over 20%; or a market with the dominant firm having 66%, competing against a large
number of very small competitors.
If RH<1.5 is taken as an indication of effective
monopoly, 17.5% of the product years fall into this category. Notice that although
we call sourcing all purchasesfrom a single suppliermonopoly, it may also arise when
the market is competitive and there are no capacity constraints, so that buying from
a single supplier minimizes transactions costs. The third category is a small number
of competitors. In 149 (36.8%) casesthe RH lay between1.5 and 4. A RH of 4 could
be produced by two firms with 35% of the market and a large competitive fringe each
firm of which has negligible sales. The fourth categoryis a very dispersed supplier
13
13This
base, with a RH > 4, which covers, 150 cases (37.0%).
Quite a lot of the variation in RH jt can be explained by total demand for the product and product and year effects. Using the 370 product-year observations where sales
were not zero, a logarithmic13 two way fixed effects model with separate intercepts
for each product and year of the form:
rhjt = aj + at + .fJVjt+ Ujt
gave an estimate of /3 of 0.17 with a t ratio of 7.4 and :R2 = 0.60; with both product
and year effects significant This confirms that when demand is larger the HAC
tended to buy from more firms which is what one would expect if there were either
capacity constraints on some suppliers or there were trade-offs between relationshipspecific investment and the market power of suppliers. The estimate of at is very low
in the first year, 1672, when the RAC could not yet have established a wide supplier
base and so bought from relatively few firms; fairly flat at a higher level thereafter
till about 1690 and then lower and more erratic during the war years. The estimates
of Qj are low relative to the mean for products 2, 12 and 13; high for 3, 8 and 10.
A low value means that they bought that product from fewer firms than would be
expected overall given the level of demand. This may partly reflect the degree of
heterogeneity in the product categories, which in some cases, e.g. general services
product 3, aggregate a range of rather different activities.
Relationships
We also record Kijt, the number of years that supplier i of product j sold to the
company. This measure does not, of course, capture whether the relationship was
continuous. Kijt = 5 could mean that the supplier had sold for the previous 4 years
or had not sold for the previous two years, but had sold for the 4 years before that. But
dominated a number of other functional forms that were tried.
14
15
it does provide gross information on the length of relationships. The largest value of
Kijt is 21 out of a possible 27 (ignoring 1693 when the RAC bought nothing because
of war).
This firm which supplied general services, product 3, began supplying in
1673, the second year, and supplied in the final year 1699, but did not supply in 8 of
the intervening years including 1693. The annual amounts supplied varied between
£10 and £536 and its market share was always under 25%.
Considering all suppliers, the mean value of Kijt over the whole sample is 3.1, but
the distribution
is highly skewed. Nearly half the Company's purchases were made
from suppliers with whom it had no previous relationship as was suggested by the
reciprocal of the Herfindahl index: for 46% of the 4056 cases Kijt = 1; and for a
further 16% Kijt = 2. The frequencies continue to decline rapidly. So a relatively
small percentage of the purchases were made from suppliers with whom the Company
had a long relationship; 17% from suppliers from whom the Company had purchased
in 5 previous years. To describe the pattern of the relationships Table 3 gives the
Hazard rates, hk : the percentage of suppliers who have supplied k years who do not
subsequently supply RAC.
Table 3. Hazard Rates.
4
5
6
k
1
2
3
hk
53
66
41 29 24 23
k
7
8
9
hk
21 22 24 22 18 22
k
13 14 15 16 17 18
hk
25
10 11 12
18 11 37 30
There are very high failure rates in the first three years. Fifty three percent of those
who sell once do not sell again and 66% of those who sell twice do not sell again.
may reflect sorting by reputation, with the RAC punishing poor performance. After
four years the hazard stabilizes at just over 20%. This rate most likely reflects the
15
This causes a relatively small improvement in fit.
Model 4 is a three factor fixed
dummies for the length of the relationship, allowing a completely flexible functional
form for relationship length:
Wijt = aj + at + ak + (3Vjt+ 6kjt + Uijt.
This produces little improvement over the logarithm of the length of the relationship.
Model 5 is modell,
with all the coefficients allowed to differ across products:
Wijt = Ctj+ .BjVjt + 'Yjkijt + 8jkjt + l1jt + Uijto
The effect of Vjt is negative for all products, with a range -0.06 to -0.5, with 6 of
the 15 coefficients significant. The effect of kijt is positive for all products, with a
range 0.06 to 0.94, with 12 of the coefficients significant. All the kjt are negative with
13 significant.
All but one of the coefficients of t are positive and 7 are significant,
though not the negative coefficient.
Product 15, ordnance, seems something of an
outlier with the negative time trend and the largest coefficient of kijt. The estimates
reported in the Table are the Swamy (1971) precision weighted averages of the 15
individual coefficients. Theseare similar to the OLS and fixed effectestimates though
the standard errors are rather larger.
The assumptions of homoskedasticity and
homogeneity across groups, implicit in the OLS and fixed effect models, may bias the
standard errors downwards.
This linear formulation does not take account of the fact that Wijt is censored
above
at zero.
upper limits.
Model 6 gives Tobit estimates of Modell,
taking account of the
These axe almost identical, which is not surprising given that only
a small proportion (36 of 4056) of the observations axe censored. However, these
explanatory variablffi are not particularly good at predicting monopoly. This is not
surprising since the variablffi will reflect supplier characteristics such as the degree of
18
competition and capacity constraints. Model 7 gives probit estimates for a dependent
variable which equals one if ~jt
> 0.8, 0 otherwise14. The probit coefficients have
been renormalised using the Amemiya (1981) approximation (multiplied by 0.38) to
make them comparable with the other coefficients. The MLL is not comparable with
the other estimates.
Own and average reputation have the correct signs and are
significant but market size is now positive and insignificant and this model classifies
only 38 of the 70 monopolists correctly15. Finally, given the possibility that product
sales are endogenous this was excluded, and model 8 is model 2 without Vjt.
Most of the implied restrictions would be rejected by Likelihood Ratio tests at
conventional significance levels, but this is partly a product of the large sample size
and it is not obvious how one should trade off fit and parsimony in large panels. If one
used the Schwarz model selection criterion16, which penalizes over-parameterisation
more heavily than classical tests, Modell
would be chosen. However, in this case
model selection is not an issue, since the estimates of the parameters of interest are
very similar across the alternative specifications. Across the eight specifications the
coefficient of kijt varies only between 0.48 and 0.54. The effect of demand is slightly
larger and the effect of average relationship slightly smaller, both in absolute value,
when time-dummies are included. The effect of average relationship is slightly larger,
when Vjt is excluded.
14When monopolist
was defined Wijt = 1 nothing was significant,
probably the result of the
small number of cases. There are, of course, econometric difficulties associated with partitioning
the
sample on the basis of an endogenous variable.
15A logistic form did slightly worse.
16The MLL
minus the number of parameters estimated times half the logarithm of the sample
SIZe.
19
(0.02)
(0.03)
17This
Table 4 Alternative
1
2
Vjt
kijt
kjt
M LL
R2
.LVOP
-0.22
0.53
-0.76
-7220
0.333
.5
-0.29
(0.03) (0.04)
0.53
-0.73
-7186
-0.32
0.344 19
(0.05)
(0.04)
3
specifications of the effect of relationships.
0.53
-0.65
-7177
0.347 45
-7174
0.348 59
(0.04) (0.03) (0.07)
4
5
-0.32
-0.65
(0.04)
(0.07)
-0.27
0.48
-0.74
-7029
75
-7205
5
(-141)
5
(0.07) (0.08)
6
7
8
-0.22
0.04
0.53
-0.79
(0.03)
(0.04)
0.54
-0.68
(0.06)
(0.06)
0.54
-0.97
(0.03)
(0.05)
-7208
0.337 18
Despite the large amount of unexplained heterogeneity in market share, the effects
of demand, reputation and average reputation are relatively precisely measured and
broadly in accord with the theory of efficient purchasing. In accord with the theoretical literature on shareholding, a dwnmy variable was included for whether the
supplier was a shareholder in the RAC in that year. This had a positive sign, as
one might expect if shareholding was a way to build a relationship, but the coefficient was very small and not significant in any of the models with a t ratio around
0.3.17 Satisfactory purchasing experience with a supplier is more important than
result is in accord with the results presented ~n Carlos, Key and Dupree which found
20
shareholding.
4. CONCLUSIONS
The empirical patterns of purchases by the RAC fit reasonably well with the qualitative account. Of the 405 product years, about a third of the cases were from many
suppliers; about a third of the purchases were from a few suppliers; just under 20%
were from one dominant supplier and in the rest of the casesthere were no purchases.
The hazard rates showed the pattern we would expect from sorting by performance:
in the first few years of the relationship there were high probabilities of not getting
repeat business from the RAC as poor performance was punished. Subsequently, the
probability of not getting repeat business stabilised around 20%, reflecting exogenous
ending of the relationship.
Expected market share increased with the length of the
relationship and fell with the average length of the relationship for all suppliers of
that product in that year. Expected market share fell with the size of the market
for the product.
These results appear robust to econometric specification, though
they may not be robust to market definition. Although these effects are strong and
significant, there remains a large amount of unexplained heterogeneity; in particular
monopoly, purchase from a single supplier, is poorly predicted.
phasized that the models used here are not "structural',
It should be em-
rather they are designed
to describe the pattern of purchases by the Royal African Company. Despite these
caveats, the patterns found within this very large data set fits rather well with the
theory of efficient acquisition and provides someempirical support for a previously
almost wholly theoretical literature.
vendors to be a small percentageof total shareholders.
21
REFERENCES
1] Amemiya, T (1981) "Qualitative Response Models: A Survey", Journal of Economic
Literature, 19, p481-536.
[2] Carlos, A.M. and J. Key (1996) "Asset Specificity and Contracting Structure:
The
Royal African Company, 1672-1692," unpublished University of Colorado at
Boulder.
[3] Carlos, A.M. and Kruse, J. (1996), "The Decline of the Royal African Company:
Fringe Firms and the Role of the Charter," Economic History Review; Vol. 49,
pp. 291-313.
[4] Carlos, A.M., J. Key and J. Dupree (1998), "Learning and the Creation of Stock market Institutions:
Evidence from the Royal African and Hudson's Bay Companies,
1670-1700", Journal of Economic History, Vol. 58, 318-344.
[5] Davies K.G. (1957) The Royal African Company, London, Longmans
[6] Dybvig, Philip and Spatt, Chester (1980), "Does it Pay to Maintain a Reputation,"
Mimeo.
[7] Eltis, D.(1994) "The Relative Importance of Slaves in the Atlantic Trade of Seventeenth Century Africa", Journal of African History, 35, 337-49.
[8] Galenson, D. W. (1986) Traders, Planters and Slaves: Market Behaviour in Early
English America, Cambridge, Cambridge University Press.
[9] Gale, Douglas and Rosenthal, Robert (1994), "Quality Cycles for Experience Goods,"
Rand Journal of Economics, Vol. 25,590-607.
22