VALUE CHAIN ANALYSIS OF THE EGYPTIAN AQUACULTURE SECTOR

Abstract

Egypt's aquaculture production (921,585 tonnes in 2010) is by far the largest of any African country and places it 11 th in terms of global production. Despite the fact that the aquaculture sector in Egypt is now a mature one having developed over a period of more than 30 years, the economic performance of the sector is not well understood or documented. To help improve this understanding WorldFish Centre conducted a value-chain study for the sector in September 2011. The study completed individual interviews and focus group discussions with fish farmers, traders/wholesalers, and retailers in four of the most important governorates in terms of aquaculture production: Kafr el Sheikh, Behera, Sharkia, and Fayoum. The study mapped the value-chain, and generated a wide range of quantitative data for each link in the value-chain on operational and financial performance (e.g. gross output values, variable and fixed costs, operational and net profit margins, value-added generation), and on employment creation (by gender, age and full-time/part-time). Qualitative information on the critical factors impacting on the performance of each sub-sector of the value-chain was also collected, and this enabled recommendations to be made about necessary actions both by those within the value-chain and by those outside of it (i.e. government), to improve value-chain performance. The study showed how value-chain analysis can be a useful tool to describe sector performance and to make evidence-based recommendations for improvements. INTRODUCTION Egyptian fish production is sourced from capture fisheries (inland and marine) and aquaculture. Total fish production increased from 724,300 tonnes in 2000 to 1,304,794 tonnes in 2010. These increases were primarily obtained from significant increases in aquaculture which represented 70% of total production in 2010 compared to 47% in 2000 [1]. Total aquaculture production in Egypt reached 919,585 tonnes in 2010 with a total market value of USD 1,546 million. Egyptian aquaculture is the largest of any African country, and ranked 11 th in terms of global aquaculture production [2]. Eighty-five percent of aquaculture production comes from earthen ponds, with the rest produced in fish cages, rice fields and intensive farms [1]. Aquaculture production is strongly concentrated in low lying land around the northern lakes (Manzala, Brulous, Edko and Maryout). According to official statistics, tilapia accounted for 55.5% by volume of aquaculture production in 2010, mullets 29.9%, carp 10.5%, African catfish 2.5%, and European seabass and gilthead seabream 1.5% [1]. Although the aquaculture sector in Egypt is now mature, having developed over several decades, the financial and social performance of the sector is not well understood or documented. Value-chain analysis is potentially a useful tool to address this gap. It has become increasing prominent as a form of analysis in the fisheries and aquaculture sectors [3, 4]. The increasing interest in value-chain analysis is due to the fact that it provides an excellent means to:  assess the relative importance of factors affecting competitiveness, and the costs and earnings of those involved in the value chain;

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VALUE CHAIN ANALYSIS OF THE EGYPTIAN AQUACULTURE SECTOR
Ahmed Nasr-Alla1, Graeme Macfadyen2, Malcolm Dickson1,
Diaa Al–Kenawy1, Mohamed Fathi1, Gamal El-Naggar1
1The WorldFish Center, Abbassa, Abou Hammad, Sharkia 44662, Egypt.
2Poseidon Aquatic Resource Management Ltd, 308 Rue d’Arbere, Divonne les Bains, 01220, France
Corresponding Author:
Ahmed Nasr-Alla
Tel: +20 10200 43126
Email: a.allah@worldfishcenter.org
Postal address: PO Box 1261, Maadi 11728, Cairo, Egypt
ABSTRACT
Egypt’s aquaculture production (921,585 tonnes in 2010) is by far the largest of any African country and places
it 11th in terms of global production. Despite the fact that the aquaculture sector in Egypt is now a mature one
having developed over a period of more than 30 years, the economic performance of the sector is not well
understood or documented. To help improve this understanding WorldFish Centre conducted a value-chain
study for the sector in September 2011. The study completed individual interviews and focus group discussions
with fish farmers, traders/wholesalers, and retailers in four of the most important governorates in terms of
aquaculture production: Kafr el Sheikh, Behera, Sharkia, and Fayoum. The study mapped the value-chain, and
generated a wide range of quantitative data for each link in the value-chain on operational and financial
performance (e.g. gross output values, variable and fixed costs, operational and net profit margins, value-added
generation), and on employment creation (by gender, age and full-time/part-time). Qualitative information on
the critical factors impacting on the performance of each sub-sector of the value-chain was also collected, and
this enabled recommendations to be made about necessary actions both by those within the value-chain and by
those outside of it (i.e. government), to improve value-chain performance. The study showed how value-chain
analysis can be a useful tool to describe sector performance and to make evidence-based recommendations for
improvements.
Keywords: Value-chain analysis, Egypt, aquaculture
INTRODUCTION
Egyptian fish production is sourced from capture fisheries (inland and marine) and
aquaculture. Total fish production increased from 724,300 tonnes in 2000 to 1,304,794 tonnes
in 2010. These increases were primarily obtained from significant increases in aquaculture
which represented 70% of total production in 2010 compared to 47% in 2000 [1].
Total aquaculture production in Egypt reached 919,585 tonnes in 2010 with a total market
value of USD 1,546 million. Egyptian aquaculture is the largest of any African country, and
ranked 11th in terms of global aquaculture production [2]. Eighty-five percent of aquaculture
production comes from earthen ponds, with the rest produced in fish cages, rice fields and
intensive farms [1]. Aquaculture production is strongly concentrated in low lying land around
the northern lakes (Manzala, Brulous, Edko and Maryout). According to official statistics,
tilapia accounted for 55.5% by volume of aquaculture production in 2010, mullets 29.9%,
carp 10.5%, African catfish 2.5%, and European seabass and gilthead seabream 1.5% [1].
Although the aquaculture sector in Egypt is now mature, having developed over several
decades, the financial and social performance of the sector is not well understood or
documented. Value-chain analysis is potentially a useful tool to address this gap. It has
become increasing prominent as a form of analysis in the fisheries and aquaculture sectors [3,
4]. The increasing interest in value-chain analysis is due to the fact that it provides an
excellent means to:
 assess the relative importance of factors affecting competitiveness, and the costs and
earnings of those involved in the value chain;

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 focus on distributional issues and pro-poor and gender equitable growth [5,6,7], and on
global linkages in the context of globalization;
 benchmark changes over time;
 identify gaps/weaknesses in value chain performance; and to
 identify ‘levers’ and targeted action programmes to ‘upgrade’ and improve value chain
performance.
A value chain is a sequence of related enterprises conducting activities to add value to a
product from its primary production, through its processing and marketing to the final sale of
the product to consumers. The functions of each link in the chain involve sourcing inputs,
making/producing, and then delivering/selling product to the next link in the chain. Value
chain analysis seeks to understand and describe the enterprises involved in the value-chain
and their financial performance [8].
Value chain analysis was first popularized by Michael Porter in the mid-1980's [9], and forms
of analysis with many similarities have been undertaken since then by others [10] on value-
streams, and [11] on power relations in value-chains. However, it is only more recently that
value chain analysis has become increasingly mainstream in development circles.
An important component of value-chain analysis is the recognition that support and action for
improving performance throughout the value chain can be achieved both by those within the
value chain itself such as private sector operators, and by those outside it including
governments and other parties external to the value chain.
This paper presents the outputs of a value-chain analysis completed during September 2011.
The research was funded by the Swiss Agency for Development and Cooperation (SDC) as a
preliminary study leading to a project proposal for a three-year aquaculture development
project; Improving Employment and Income through Development of Egypt’s Aquaculture
Sector, the IEIDEAS project.
The objectives of the study were to better understand, and document, the pond fish farming
value-chain in Egypt. In particular the study aimed to:
 map the value-chain for pond farmed fish to describe the main stakeholders and the flow
of product through the value-chain;
 understand the costs and earnings profiles and financial performance of the different sub-
sectors/links of the value-chain, and compare the financial performance of the sub-
sectors in four regions of Egypt (governorates);
 consider the employment generated by the sector; and
 identify the key constraints and problems impacting on different actors in the value-chain.
MATERIALS AND METHODS
The study was based on collecting production and financial information from 2010 and was
limited to pond farming (which accounts for 85% of the total Egyptian aquaculture
production) in four governorates, which together account for 74% of total national production
from ponds; Kafr el Sheikh, Behera, Fayoum and Sharkia. Figure 1 shows the geographical
distribution of the study areas across the country.
The mapping and financial analysis of the pond farming value-chain started at the fish farm
and ended with retail sales to consumers. Fish seed was viewed as a farm input along with
other key inputs such as fish feed, labour, capital etc. The study was also limited to the retail
sector, and did not cover the food service sector.
Two detailed study questionnaires covering both qualitative and quantitative issues were
drafted, for fish farmers, and the post-harvest sub-sector (traders/wholesalers and retailers).
They were then piloted with a fish farmer and a fish trader/wholesaler which resulted in small
changes to the questionnaires, before being finalised and printed.

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Individual interviews and focus group discussions were held with fish farmers,
traders/wholesalers, and retailers. In order to maximise the number of interviews, small
groups of stakeholders met at a central location in each governorate. This provided an
opportunity to introduce the study and to hold a focus group discussion in plenary before
individual interviews were then conducted with the participants. The number of interviews
per governorate was decided on stratified basis according to the available statistics on the
number of farms in the target governorates. The introductory comments and focus group
discussions, which concentrated mainly on key stakeholder problems and potential solutions,
generally lasted around sixty to ninety minutes, as did the individual interviews. Table 1
provides information on the number of individual questionnaires completed in each
governorates and the number of participants at the same meetings that were involved in the
focus group discussions.
Figure 1. Geographical distribution of study areas
Data obtained from the questionnaires were entered into a Microsoft Excel spreadsheet and
analyzed to generate the results which were considered in light of, and informed by, the
qualitative focus group discussions.
The data collected during the study have allowed the estimation of a number of key indicators
for each link in the value chain. The indicators were calculated both separately for each of the
four governorates by taking averages of the data provided by the respondents in each
governorate, and for the sample frame as a whole.
Table 1: Sample frame used during the study
Governorate
Fish Farmers
Fish Traders and/or Wholesalers
Fish Retailers
Kafr el Sheikh
22 individual questionnaires
3 focus groups (total of 24
participants)
6 individual questionnaires
1 focus group (8 participants)
5 individual
questionnaires
Behera
14 individual questionnaires
1 focus group (15 participants)
5 individual questionnaires
1 focus group (9 participants)
-
Fayoum
16 individual questionnaires
1 focus group (29 participants)
4 individual questionnaires
7 individual
questionnaires
Sharkia
9 individual questionnaires
1 focus group (12 participants)
6 individual questionnaires
1 individual
questionnaire
Totals
61 individual questionnaires
6 focus groups (total of 80
participants)
21 individual questionnaires
2 focus groups (total of 17
participants)
13 individual
questionnaires

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The financial indicators calculated included: gross output values per kg; operational profits
(sales value-operational cost) in Egyptian Pounds (LE) per tonne of fish (LE1=$5.96) and as a
percentage of sales; net profits (revenue- (operational + fixed cost)) in LE per tonne of fish
produced or sold and as a percentage of sales; total value-added (net profit + wages) per
tonne of fish sold; and the percentage of the total operational profits, net profits, and value-
added made throughout the chain derived from the different links in the value-chain. The
questionnaires generated data on sales volumes and values, operational costs and fixed costs,
and which allowed for the construction of costs and earnings models for each respondent.
Operational costs were defined as costs which vary depending on the amount of fish being
produced. For fish farmers these typically include costs for feed, fertiliser, fry, power,
transport, ice, sales commission paid to traders/wholesalers, and labour. For
traders/wholesalers and retailers, operational costs typically relate to transport of fish from
markets, boxes, labour and ice.
Fixed costs do not vary depending on production volumes. For the fish farming value-chain,
they typically include government licences, repair and maintenance costs, rents paid for land
and buildings, and the depreciation costs of assets. Depreciation costs have been estimated by
obtaining information on the replacement costs of fixed assets, and depreciating these costs
over standardised lifespans for different items e.g. buildings over 25 years, nets over 3 years,
water pumps over 5 years, generators over 10 years, vehicles over 10 years.
The study outputs generated data on the number of people employed and on the nature of that
employment, whether employment is full-time, part-time or seasonal, whether employees are
men or women and over or under the age of 30. The data collected were converted into Full-
Time Equivalent (FTE) jobs for the various employment categories.
In addition to these quantitative calculations, the focus groups and some sections of the
questionnaires allowed for the collection of more qualitative information, particularly on the
key factors impacting on value-chain performance and on some potential solutions to these
problems.
RESULTS AND DISCUSSION
The farmed fish value-chain
Mapping of the value chain revealed it to be very short and simple with three main actors;
producers, wholesaler/traders and retailers (Figure 2). There are virtually no exports or
processing of Egyptian farmed fish so almost all the fish is sold in whole form (either live,
fresh on ice, or fresh without ice).
Figure 2. Egyptian Aquaculture Value Chain

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Fish is harvested by fish farms, bought by traders/wholesalers who either collect fish from the
farms or have fish delivered to them by the fish farms, and then sold on to retailers and
restaurants (sometimes, but not often, through a second trader/wholesaler). Some product,
especially in Kafr el Sheikh, Behera and Sharkia Governorates, passes through wholesale
markets, while other product is transported directly by traders/wholesalers to retailers. It
appears that much of the largest size-grade of tilapia (>350 g, known locally as ‘super’) is
sold through the wholesale markets in Kafr el Sheikh, Behera and at El-Obour close to Cairo,
while smaller fish may by-pass these markets and be sold closer to the farms, where
purchasing power of the local population is weaker, and greater demand for smaller, cheaper
fish.
Most fish farms reported that they produce and sell a mix of fish species, dominated by sales
of tilapia, but also including sales of mullet, catfish, and carp. The average size of fish being
harvested was 265 g for tilapia, 409 g for grey mullet, 216 g for thinlip mullet, and 1,481 g
for catfish. Eighty-seven percent of the total volume and 81% of the total value covered by
the survey was accounted for by tilapia. Mullet represented 9% of volume and 18% of value,
carp 0.2% of volumes and 0.1% of values, and catfish 1.7% of volume and 1.3% of value.
All catfish was sold live, while other species (tilapia, mullet, carp) were generally sold either
fresh on ice (in summer months or if markets were relatively far from farms) or fresh with no
ice (in winter months or if markets were relatively close to farms). There appears to be a
growing trend for the sale of live tilapia, particularly for fish produced in Fayoum
Governorate, which is transported in drums or tanks with oxygen by traders to wholesalers
and retailers.
Key features of the value-chain included a very short time-period (1-2 days) from harvest to
final consumption by the consumer and very low post-harvest losses (in contrast to many
wild fisheries value-chains) reflecting an efficient distribution system with production located
close to major population centers.
Operational and financial performance
Fish producers
Average operational data for fish farms in the four governorates, and average operational data
for the entire sample as a whole are shown in detail in Table 2.
Although most of the interviewees have been involved in fish farming for many years, those
from Kafr el Sheikh were, on average more experienced and those from Fayoum, less
experienced.
The lowest average farm size was in Fayoum, perhaps because there is a shortage of suitable
land for fish farming compared to the three Nile delta governorates.
Stocking densities depended on farming strategies and varied from 14,000 to 70,000 per
hectare for tilapia. The average stocking rate in farms in Behera Governorate was the highest
compared to other governorates at 45,000 per hectare.
Tilapia represented an average 87% of fish stocked, ranging between 78.7% in Sharkia to
95.4% in Fayoum.
Average production rates (tonnes.ha-1) were highest in Behera. This may be because many of
the fish farms included in the Behera sample frame were located close to Lake Idko where
there is good water availability.
The average quantity of feed used was 14.3 tonnes per hectare, with highest feed application
rates in Behera, and lowest in Sharkia. The best Feed Conversion Ratios (FCRs) were in
Behera and Sharkia compared to Kafr el Sheikh and Fayoum.
Relatively low fish prices in Behera were due mainly to the small harvest size of fish
(average tilapia size is 235 g) and the relatively high prices in Fayoum were due to the
dominance of the live fish trade and the high average size of tilapia at harvest 283 g.

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Table 2: Operational data for the fish farming sub-sector
Operational data
Kafr el
Sheikh
Behera
Fayoum
Sharkia
Total
Number of farms interviewed
21
13
16
9
59
Years involved in the sector
20
18
16
18
18
Total hectare of interviewed farms under
prod'n
223
188
83
143.2
637
Average area under production (ha)
11
14
5
16
11
Average stocking density /ha
34,388
44,972
34,070
33,329
35,864
Tilapia % of stocking rate
88.5%
92.6%
95.4%
78.7%
87.1%
Average size of tilapia when stocking (gr)
10
4
11
10
9.05
Average growth period (months)
9.6
8.7
8.3
7.7
8.7
Average feed used (tonnes / ha)
14.46
15.13
12.41
9.91
13.34
Average production (tonnes / ha)
7.76
11.46
7.53
7.42
8.46
Average FCR
1.86
1.45
1.65
1.34
1.62
Average size tilapia at harvest (gr)
276
235
283
252
265
Average % of total production from tilapia
86%
94%
93%
79%
89%
Average FTE / ha
0.50
0.54
0.91
0.54
0.63
Average FTE / 100 tonne.yr-1
6.99
5.31
12.59
7.98
8.31
Table 3 provides information on the financial performance of the fish farms.
The overall average fish price was around 10 LE/kg (1.68 $/kg), ranging from 8.26 in Behera
to 11.79 LE/kg in Fayoum. Higher prices in Fayoum resulted from selling live tilapia,
allowing the fish farmers to generate a price premium of around 2 LE/kg higher than other
farmers.
Fish farms had positive financial performance in all governorates in terms of average net
profits (average LE 247,172), net profits per tonne of fish (average LE 2,329), and net profits
as a percentage of sales (average 22%). Fish farmers in Fayoum displayed the highest profits
even though they had the highest production cost per tonne, due largely to high prices. Other
factors may be the skill level of farmers as they have been the beneficiaries of more training
than farmers in other Governorates. In general, farms in Kafr el Sheikh had the worst
performance of the four governorates;
The average total production cost across all farms was LE 7,769/tonne ($1,303/tonne), which
represents the break-even weighted sales price, so fish should be sold at higher than LE
7,769/tonne if the farm is to make a profit. Highest average production costs were in Fayoum
(LE 8,392/tonne) and lowest in Behera (LE 6,688/tonne);
Operational costs per hectare varied between governorates ranging from 68,500 LE/ha in
Behera to 45,000 LE/ha in Sharkia. In contrast, operational costs per tonne of fish produced
were lowest in Behera, as they produced the highest fish yields (4.81 tonne/ha).
Fish feed represented the largest operational cost (average 67% of operational costs) followed
by fish seed (13%), followed by labour (8%), sales commission (5%), and
fuel/electricity/power (3%).
Operational costs made up 91.5% of total costs. Fixed costs were low because many farms
are on rented land with short lease periods, which decreases the incentive for farmers to
invest in fixed assets. Land rents are the highest single fixed cost (average 62% of fixed
costs) with depreciation and repair/maintenance costs both contributing 17% of total fixed
costs. Very few farms have any formal fixed finance costs in the form of interest payments on
loans, as there is virtually no formal bank lending to the sector;

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The total value-added by the sub-sector i.e. net profits plus wages paid to labour, was LE
2,989 ($501) per tonne of fish produced with the highest value added in Fayoum and the
lowest in Kafr el Sheikh.
Table 3: Financial performance of fish farms
Financial performance data
Kafr el
Sheikh
Behera
Fayoum
Sharkia
Overall
Average
Average sales price (LE*/kg)
9.70
8.26
11.79
9.87
9.98
Average sales revenue (LE)
804,447
1,385,487
427,841
1,267,517
885,964
Average operational costs (LE)
563,226
1,008,630
286,703
720,814
600,242
Average operational costs / ha (LE)
55,150
68,473
55,301
45,296
55,350
Average feed costs as % of operational
costs
72%
66%
68%
57%
67%
Average op. costs / tonne produced (LE)
7,020
6,405
8,011
6,692
7,115
Average operational profit (LE)
253,551
410,652
141,138
546,703
301,357
Average operational profit / tonne (LE)
2,724
2,243
3,402
3,179
2,997
Average fixed costs (LE)
68,612
52,593
13,498
87,933
51,343
Average total production cost (LE/tonne)
8,051
6,688
8,392
7,442
7,769
Average net profit (LE)
182,036
356,410
127,639
458,770
247,172
Average net profit / tonne (LE)
1,640
1,914
3,402
2,429
2,329
Average net profit as % of sales
16%
20%
29%
24%
22%
Average labour costs / tonne produced (LE)
516
486
948
768
660
Average total value-added / tonne (LE)
2,155
2,400
4,350
3,198
2,989
* (LE5.96=$1)
Trader/wholesaler sub-sector – operational and financial performance
Table 4 provides the outputs of the data collected and analysed for trader/wholesaler sub-
sector of the value-chain. Traders/wholesalers are key players in the value-chain, especially
in terms of determining prices. The one exception to this is in Fayoum, where fish farmers are
reported to have a much stronger influence on farm gate prices than in other Governorates.
The traders/wholesalers play a key role in providing finance to many of the fish farms (along
with feed mills/traders in many cases), and most of them finance their operations out of their
own finance (often earned from other economic activities). This provides an indication of the
overall financial position/wealth of such individuals, and their influence in the value-chain.
Even though final profit margins (3.9% on average) and profits per tonne of fish sold (LE
422) are both low compared to the farming sub-sector, given the large average value of sales
made by individuals each year (LE 11.9 million on average), profits in absolute terms were
significant, with individuals typically earning around LE 400,000 ($67,114) per year.
The earnings made by traders/wholesalers are generated from a sales commission, 3-6% of
fish sales value, which is paid to them by the fish farmers. This margin is typically lower (e.g.
3%) when farmers deliver product to them, and higher (5-6%) if they collect fish from the
farms and therefore have to pay for transportation and ice, and if they have provided finance
to fish farmers. Individual questionnaire responses revealed that net profits and net profit as
percentage of sales were generally higher when traders/wholesalers collected fish from the
farms, because the costs they incur on ice and transport are less than the difference between
the commission they take for collecting fish at the farms, and the commission they get if fish
is delivered to them.

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Table 4: Operational and financial performance data for fish traders/wholesalers
Kafr el
Sheikh
Behera
Fayoum
Sharkia
Overall
Operational data
No. of traders/wholesalers
interviewed
6
5
5
6
22
Total annual sales volume of
interviewees (tonne)
9,588
7,749
2,697
6,072
25,566
Total annual sales value of
interviewees (LE)
105,948,000
75,463,200
36,026,210
51,739,588
269,176,998
Average FTE / '00 tonnes of sales
0.40
0.62
0.92
1.56
0.87
Average sales price (LE/kg)
10.83
9.86
12.95
10.23
10.66
Financial performance
Average annual sales value (LE)
17,658,000
12,577,200
7,205,242
8,623,265
11,930,954
Average operational costs (LE)
17,158,250
12,172,752
6,800,911
8,226,058
11,510,701
Average operational profit (LE)
499,750
404,448
404,331
397,206
420,254
Average operation profit / tonne
(LE)
293
265
822
413
440
Average labour costs / tonne (LE)
42
96
98
91
80
Average fixed costs (LE)
34,454
13,517
9,532
7,918
17,377
Average net profit (LE)
465,296
390,931
394,799
389,288
402,877
Average net profit / tonne (LE)
268
252
804
400
422
Average net profit as % of sales
2.3%
3.7%
6.4%
4.4%
3.9%
Average total value-added / tonne
(LE)
310
347
903
491
503
Farm gate fish prices were higher in Fayoum than in other governorates but average annual
sales values for individual traders/wholesalers operating within Fayoum were lower than in
other Governorates, due to the lower level of total farm production in Fayoum.
Operational costs were comprised almost entirely of fish purchases. Other operational costs
included labour, truck rental/transport, ice, and fuel/power, but none of these items made up
more than one percent of the value of sales.
Fixed costs were generally very low, and more evenly distributed across a range of items
such as rents/leases (32% of total fixed costs), depreciation of buildings, fish boxes and
vehicles (30% of fixed costs), and repairs and maintenance of buildings and vehicles (15% of
fixed costs).
The individual average earnings for traders/wholesalers across the four governorates were
very consistent, with those in Fayoum similar to those in other governorates even though
sales volumes and values are lower, due to the higher margins being achieved.
The average value-added (net profits plus wages) per tonne of fish sold was LE 503, and was
highest in Fayoum and lowest in Kafr el Sheikh.
Retailer sub-sector – operational and financial performance
There are two main types of farmed fish retailers in Egypt. The first group engage in
‘informal’ street sales. This is usually carried out by individual operators who purchase fish
from wholesale markets or traders, and then set up shop by the roadside to sell their product.
Sales facilities and equipment is minimal, often comprising just a shelter from the sun.

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Labour is generally not employed, and these types of retailers aim to make LE 0.5-1.0 profit
on each kg of fish they sell.
Table 5: Operational and financial performance data for fish retailers
The second group is more formalised, with sales taking place from retail shop facilities.
These retailers may also have fridges and or freezers for storing unsold fish for following day
and often employ labour to clean and prepare fish. As a result their operational and fixed
costs tend to be higher than the informal street traders.
The data presented in Table 5 shows that retailers typically have low fixed costs, and a high
percentage of operational costs comprising fish purchases (with other operational costs being
primarily for transport of fish from markets, and ice). This suggests that as long as retailers
can sell their product for a small standard margin over and above the purchase price, there is
little ‘risk’ inherent in the business. The higher fish prices in Fayoum exhibited in earlier
links in the value-chain were maintained in the retail sub-sector.
Net profit earnings fluctuated among governorates with the lowest in Fayoum, while Kafr el
Sheikh and Sharkia were similar. Average net profit per individual business owner was LE
58,778 ($9,862), still considerably above national average earnings. The retail sub-sector
creates an average of LE 1,131 value added for every tonne of fish sold.
Employment creation through-out the value-chain
Table 6 demonstrates that employment was entirely male in the fish farming sub-sector and
was fairly evenly divided between those over and under 30 years of age. It was mostly full-
time work, and generated 8.3 jobs for each 100 tonnes.yr-1 of fish produced.
For the trader/wholesaler sub-sector, employment was also almost exclusively male, even
more full-time in nature than in the farming sub-sector, and generated a lower percentage of
jobs for the under 30’s. The trading/wholesaling sub-sector generates just under 1 FTE job
for each 100 tonnes.yr-1 of fish being sold.
Kafr el
Sheikh
Behera
Fayoum
Sharkia
Overall
Operational data
No. of retailers interviewed
5
0
6
1
12
Total annual sales value of
interviewees (LE)
5,244,300
n/a
4,998,210
1,056,600
11,299,110
Average FTE / 100 tonnes sales
1.34
n/a
7.79
2.02
4.62
Average sales price (LE/kg)
12.51
n/a
15.75
10.67
13.98
Financial performance
Average annual sales value (LE)
1,048,860
n/a
833,035
1,056,600
941,593
Average operational costs (LE)
972,648
n/a
786,268
974,880
879,644
Average labour costs /tonne (LE)
0
n/a
333
170
181
Average operational profit (LE)
76,212
n/a
46,767
81,720
61,948
Average operation profit / tonne
(LE)
916
n/a
1,091
825
996
Average fixed costs (LE)
-
n/a
5,557
4,700
3,170
Average net profit (LE)
76,212
n/a
41,210
77,020
58,778
Average net profit / tonne (LE)
916
n/a
1,008
778
951
Average net profit as % of sales
7%
n/a
6%
7%
6.8%
Average total value-added /
tonne (LE)
916
n/a
1,341
948
1,131

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It is only at the retail sub-sector that any meaningful quantities of female employment were
being created. This employment tends to be full-time in nature, and with a low proportion of
total employment being for the under 30’s. The retail sector created 4.6 jobs per 100
tonnes.yr-1 of fish sold.
Every 100 tonnes.yr-1 of fish produced by fish farms resulted in almost 14 FTE jobs through
the value-chain. Total Egyptian aquaculture pond production was estimated at 716,801 tonnes
in 2010, indicating that were a total of almost 100,000 FTE jobs in the sector as a whole. This
study did not attempt to estimate multiplier employment impacts from pond farming, or
employment from other production methods e.g. cage farming.
Wages paid to those working in the sector were typically around LE 800-900/month ($134-
151/month) for full-time labour, and LE 30-50/day ($5-8.4/day) for part-time and seasonal
labour.
Table 6: Employment creation in the Egyptian aquaculture value chain
Employment
Full time equivalent jobs per 100 tonnes.yr-1 sold
Kafr el
Sheikh
Behera
Fayoum
Sharkia
Overall
Average
farmers
6.99
5.31
12.59
7.98
8.31
traders/wholesalers
0.40
0.62
0.92
1.56
0.87
retailers
1.34
n/a
7.79
2.02
4.62
Total
8.73
5.93
21.29
11.57
13.80
% of FTE days contributed by men
farmers
100%
100%
100%
100%
100%
traders/wholesalers
100%
100%
100%
94%
98%
retailers
60%
n/a
80%
50%
69%
% of FTE days for full-time employment as opposed to part-time or seasonal work
farmers
70%
86%
63%
73%
72%
traders/wholesalers
83%
91%
97%
92%
91%
retailers
100%
n/a
100%
100%
100%
% of FTE days contributed by those under 30 years of age
farmers
71%
41%
52%
56%
57%
traders/wholesalers
35%
52%
36%
28%
37%
retailers
50%
n/a
16%
100%
37%
Fish prices across the value chain
Mapping the value chain and constructing costs and earnings models for each link in the
value chain as presented above, allowed for a comparison across the various sub-sectors in
the value chain. The average fish prices of products sold by each link in the supply chain in
each governorate are summarized in Table 7. This indicates that fish farmers obtained a
relatively high percentage of the final price. This is due to the lack of any exports, the short
supply chain, and the lack of value-addition through the chain.
Table 7: Fish prices in the farmed fish value-chain
Sub-sector
LE/kg (all species, Average price)
Average price compared to consumer price
K el Sh
Beh
Fay
Sha
All
K el Sh
Beh
Fay
Sha
All
farmers
9.70
8.26
11.79
9.87
9.98
78%
n/a
75%
92%
71%
traders/
wholesalers
10.83
9.86
12.95
10.23
10.66
87%
n/a
82%
96%
76%
retailers
12.51
n/a
15.75
10.67
13.98
100%
n/a
100%
100%
100%

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Finally, Table 8 provides information on the total value-added created through the value-
chain i.e. the net profit, plus the wages earned by those working in the sector. The data show
that on average across all governorates, a total of LE 4,619 value-added is generated for each
tonne of fish produced by the farming sub-sector. Again, the levels of value-added created
were highest in the fish farming sub-sector (LE 2,985/tonne), and those in Fayoum (LE
6,594/tonne) were higher than in other governorates.
Table 8: Value-added in the farmed fish value-chain
Sub-sector
LE/tonne
% total value-added
K el Sh
Beh
Fay
Sha
All
K el Sh
Beh
Fay
Sha
All
farmers
2,155
2,400
4,350
3,198
2,989
63.7%
87.4%
66.0%
69.0%
64.7%
traders/whol
esalers
310
347
903
491
503
9.2%
12.6%
13.7%
10.6%
10.9%
retailers
916
n/a
1,341
948
1,131
27.1%
n/a
20.3%
20.4%
24.5%
Total
3,381
2,748
6,594
4,637
4,623
The data presented in Table 7 and 8 serve to benchmark performance by the sub-sectors of
the value-chain in different governorates and demonstrate the superior performance of those
in Fayoum governorate. The emphasis on live fish trade, on which Fayoum’s superior
performance appears to be largely based, also seems to be a strategy that is increasingly being
pursued in other governorates.
This study did not collect information to allow for a quantitative comparison of the changes
in performance within the sub-sectors of the value-chain over time. However there was an
attempt to generate some findings of a more qualitative nature by asking interviewees to
comment on their perceptions about changes in key variables over the last three years. A
relatively uniform picture was provided by respondents in terms of the perceived changes in
the operational and fixed costs incurred in the fish farming sub-sector, with a dominant view
being that most individual cost items e.g. feed, labour, rents, power, etc., have increased over
recent years. Given that fish prices have declined in real terms in recent years, this suggests
that profitability has been declining in recent years. Sector performance may now be under
threat, especially due to increases in the feed costs, which have increased by 200-250% over
the last 6-7 years.
Critical factors impacting on value-chain performance
Critical factors affecting the farmed fish value chain were explored through during the study
and classified into three groups; input, production and post harvest and marketing factors.
Critical input factors included; access to credit; high cost of fish feed; poor quality of tilapia
fry; poor water quality of inlet water; limited land available for future expansion; and high
cost power and fuel.
Critical production factors included; limited growing season for tilapia; farm layout and
design; variable knowledge of Best Management Practice (BMP) about feed use and fish
health management; low stocking densities; the weak structure of sector and subsector
organization; and limited number of cultured species (tilapia and mullet).
Post harvest and marketing critical factors included daily and seasonal price fluctuations due
to changes in supply volume; poor health and hygiene in wholesale and retail markets;
limited experience and knowledge about export markets; lack of value-addition and
processing; and steady increases in fish supply coupled with poor consumer perceptions of
farmed fish quality leading to declining consumer prices.
All of these issues represent potential areas for action by stakeholders in the aquaculture
value-chain itself and by other relevant actors including government, NGOs and donors.
Many of these are now being addressed by the SDC funded IEIDEAS project.

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12
Conclusions
The Egyptian aquaculture sector generates very considerable levels of value-added, results in
profitable businesses at each stage of the value-chain, and provides employment for many
thousands of people. In spite of that, the sector now faces number of significant challenges.
The historical strength of the sector, coupled with recent challenges, and indeed opportunities
for further improvements in value-chain performance, provide a strong argument for action
by private sector within the value-chain, and by government in the form of supportive policy
and legislation. Such action would serve both to safeguard the current financial and
employment benefits being generated in the sector, and to increase such benefits in the future.
Value-chain analysis has not been widely adopted in the aquaculture sector, with a continuing
focus instead in research and interventions on technical production issues. This paper has
demonstrated that value chain analysis is a useful tool for understanding the social and
economic benefits generated by the aquaculture sector, and for identifying the critical factors
affecting its performance. Value chain analysis should be considered as an essential first step
in planning necessary action and innovations to bring about sustainable development of this
key sector.
Acknowledgements
This work is a contribution to the CGIAR Research Program on Livestock and Fish and was funded
by the Swiss Agency for Development and Cooperation. The authors would like to thank Malcolm
Beveridge and Patrick Dugan from the WorldFish Center for their efforts to bring this study and the
subsequent project to fruition.
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