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Value-chain analysis —An assessment methodology to estimate Egyptian
aquaculture sector performance☆
Graeme Macfadyen ⁎, Ahmed Mohamed Nasr-Alla
1
, Diaa Al‐Kenawy
1
, Mohamed Fathi
1
, Hussien Hebicha
1
,
Ahmed Mohammed Diab
1
, Samy Mohmed Hussein
1
, Ramadan Mohamed Abou-Zeid
1
, Gamal El-Naggar
1
The WorldFish Center, Abbassa, Abou Hammad, Sharkia 44662, Egypt
abstractarticle info
Article history:
Received 15 December 2011
Received in revised form 11 April 2012
Accepted 21 May 2012
Available online 20 July 2012
Keywords:
Value-chain analysis
Egypt
Aquaculture
Tilapia
Egypt's aquaculture production (705,490 tonnes in 2009) is by far the largest of any African country and
places it 11th in terms of global aquaculture production. The aquaculture sector in Egypt is now a mature
one having developed over a period of more than 30 years, but the financial performance of the sector is
not well understood or documented, even though value-chain analysis provides a methodological tool to
do so. To provide a better understanding of the sector, a WorldFish Center study completed in September
2011 and funded by the Swiss Agency for Development and Cooperation, conducted a value-chain analysis
of the pond fish farming sector. The sector concentrates on the production of tilapia with additional produc-
tion of mullet, catfish and carp from earthen ponds. The study mapped the value-chain and showed that there
is no processing and virtually no export of farmed fish, a short time-period from harvest to final consumption
by the consumer (typically around one day) due to the live/fresh nature of all sales, and very low rates (b1%)
of post-harvest losses. Quantitative data were collected 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). The results
showed that theindustry generates a combined LE 4619 ($775) of value-added (i.e. profits plus wages/earnings)
for farmers,traders and retailers for each tonne of fish produced. Employment generation is also significant with
around 14 full-time equivalent jobs generated for every 100 tonnes of fish produced. However, the sector as a
whole is under increasing financial pressure. Critical factors impacting on the performance of the
value-chain relate to inputs (most importantly to rising feed costs and the poor quality of fry), to production
(most importantly to poor practices with regard to feed management, farm design and construction, fish
health management, and stocking densities), and to the marketing, transportation and sale of product
(most importantly to declining fish prices in real terms, consumer preference for wild fish and a distrust
of filleted/processed products, fluctuating seasonal prices, poor hygiene and handling practices, the lack
of value-addition through processing, and the lack of exports). This paper highlights the benefits of
value-chain analysis as a useful tool to understand sector performance and argues for its wider use in iden-
tifying critical factors and actions to support aquaculture sector improvements.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
The main sources of fish production in Egypt include marine fish-
eries, inland capture fisheries and aquaculture. Total production in-
creased from 724,300 tonnes in 2000 to 1.1 million tonnes in 2009.
These increases were primarily obtained from significant increases
in aquaculture production, and the share of total production provid-
ed by aquaculture had risen to 65%, up from 47% in 2000 (GAFRD,
2011).
Egypt's aquaculture production was 705,490 tonnes in 2009
(GAFRD, 2011), which is the largest of any African country. According
to FAO statistics (FAO FISHSTAT) Egypt ranks 11th in terms of global
aquaculture production. Eighty-four percent of aquaculture production
comes from earthen ponds, with the rest produced in fish/rice fields,
Aquaculture 362–363 (2012) 18–27
Abbreviations: LE, Egyptian pounds (LE1 = $5.96); FTE, full time equivalents; Av.,
average; g, grammes; FCR, Feed Conversion Ratio; BMPs, Best Management Practices;
Fed, Feddan (1 ha =2.381 feddan).
☆All authors listed above were part of the study team which planned and executed
the fieldwork which generated the data and information used and presented in this
paper.
⁎Corresponding author at: 308 Rue d'Arbere, Divonne les Bains, 01220, France. Tel.:
+33 450 20 68 05.
E-mail addresses: Graeme@consult-poseidon.com (G. Macfadyen),
a.allah@cgiar.org (A.M. Nasr-Alla), d.kenawy@cgiar.org (D. Al‐Kenawy),
m.fathi@cgiar.org (M. Fathi), hhebisha@yahoo.com (H. Hebicha),
ahmeddiab_clar@yahoo.com (A.M. Diab), samyhussien1@yahoo.com (S.M. Hussein),
abouzied2004@yahoo.com (R.M. Abou-Zeid), g.naggar@cgiar.org (G. El-Naggar).
1
Tel.: +20 553404227; fax: +20 553405578.
0044-8486/$ –see front matter © 2012 Elsevier B.V. All rights reserved.
doi:10.1016/j.aquaculture.2012.05.042
Contents lists available at SciVerse ScienceDirect
Aquaculture
journal homepage: www.elsevier.com/locate/aqua-online
and intensive cage farms (GAFRD 2011). Aquaculture production is
strongly concentrated in the delta region to the north of Cairo. Tilapia
(Oreochromis niloticus) accounts for 55.5% of national aquaculture
production by volume, grey mullet (Mugil cephalus) and thinlip mullet
(Liza ramada) for 29.9%, common carp (Cyprinus carpio), grass carp
(Ctenopharyngodon idella), and silver carp (Hypophthalmichthys molitrix)
for 10.5%, North African catfish (Clarias gariepinus) for 2.5%, and Europe-
an seabass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata)
for 1.5% (GAFRD 2011).
With a production of over 700,000 tonnes in 2011 and more
than 120,000 people estimated to be employed in the sector
2
Egyptian aquaculture makes an important contribution to income,
employment creation and food security, all of which are national
policy priority areas given low per capita income levels (LE1 2556
or $2107 in 2010),
3
a population that has been growing in recent
years at a constant rate of about 1.48 million per year, worsening
food security indicators, and official unemployment levels which
have remained at around 10% for the last ten years (CAPMAS,
2011).
However, despite the fact that the aquaculture sector in Egypt
is now mature, having developed over a period of more than
30 years, the financial and social performance of the sector are
not well understood or documented. This is a little surprising
given the existence of value-chain analysis as a useful tool to as-
sess performance, and its increasing prominence as a form of anal-
ysis in the fisheries and aquaculture sectors (Veliu et al., 2009;
Christensen et al., 2011). The increasing interest in value-chain
analysis is due to the fact that it provides an excellent means of
assessment to:
•Focus on distributional issues and pro-poor and gender equitable
growth (Mayoux and Mackie 2008;Rubin et al., 2009;USAID
2011), and on global linkages in the context of globalisation;
•Benchmark changes over time;
•Assess the relative importance of factors affecting competitive-
ness, and the costs and earnings of those involved in the value
chain;
•Identify gaps/weaknesses in value chain performance; and to
•Identify ‘levers’and targeted action programmes to ‘upgrade’and
improve value chain performance.
This paper presents the outputs of a value-chain study completed
during September 2011. The study was funded by the Swiss Agency
for Development and Cooperation and completed by a team from
the WorldFish Center and CARE Egypt, supported by an international
expert in value-chain analysis.
The objectives of the study were to better understand, and report
on, 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;
•Consider the employment generated by the sector;
•Understand the costs and earnings profiles and financial perfor-
mance of the different sub-sectors/links of the value-chain; and
•Identify the key constrains and problems impacting on different ac-
tors in the value-chain.
This paper focusses on presenting the results of the first three of
these bullets, and only presents in summary form some of the key
constraints and problems identified during the study as impacting
on the value-chain.
2. Material and methods
2.1. Study scope
The scope of the study presented in this paper was limited to
earthen pond farming (which accounts for 85% of the total Egyptian
aquaculture production) in four governorates, which together ac-
count for almost 74% of the total national production from ponds,
namely: Kafr el Sheikh, Behera, Fayoum and Sharkia (see Fig. 1).
Pond farms in Egypt are generally considered as ‘semi-intensive’, al-
though there are a range of different strategies used by fish farmers
in terms of stocking densities and the use of feed.
The mapping and financial analyses of the pond farming value-
chain start at the fish farm and finish with retail sales to the consumer,
with fish fry/fingerlings viewed as a farm input along with other key
inputs such as fish feed, labour, capital etc. Hatchery operations and
the quality and quantity of fry being produced were considered by
the study in terms of the critical challenges and problems facing the
sector, but costs and earnings data for hatcheries were not collected
as part of the study. The study was also limited to the retail sector,
and did not cover the food service sector (e.g. restaurants).
All data on the financial performance of the value chain collected
and presented in this paper pertain to the full calendar year 2010,
and are yearly averages. The data for each link in the value-chain
presented for the four governorates covered by the study are aver-
ages, and hide nuances in performance between individual operators.
2.2. Study phases
The study was completed in three main phases.
During the first phase, two study questionnaires covering both qual-
itative and quantitative issues were drafted, one for fish farmers, and
one to cover the post-harvest sub-sector i.e. traders/wholesalers and re-
tailers. The two questionnaires were then piloted at the WorldFish Cen-
ter office in Abbassa with one fish farmer and one fish trader/
wholesaler. This piloting resulted in some small changes to the ques-
tionnaires, which were then finalised and printed for the field work.
In Phase 2, individual interviews and focus group discussions were
held with fish farmers, traders/wholesalers, and retailers. In order to
maximise the number of interviews possible during the time
available for the field work, the study team (the authors of this
paper) arranged to meet small groups of stakeholders at a central lo-
cation in each governorate. This provided an opportunity to introduce
the study and to hold a focus group discussion in plenary before
individual interviews with those participating in the focus groups
were then conducted with the participants (each member of the
study team sat with a different participant and went through the
questionnaire). The introductory comments and focus group discus-
sions, which concentrated mainly on key stakeholder problems and
potential solutions, generally lasted around 60 to 90 min, as did the
individual interviews.
Table 1 provides information on the number of individual ques-
tionnaires completed in each of the four governorates and the num-
ber of participants that were involved in the focus group discussions.
During Phase 3, data from the questionnaires were entered into a
Microsoft Excel spreadsheet and then analysed to generate the re-
sults. The quantitative results were considered in light of, and in-
formed by, the qualitative focus group discussions which had also
taken place during Phase 2.
3. Theory/calculation
3.1. Value-chain analysis
A value chain is a sequence of related enterprises conducting ac-
tivities so as to add value to a product from its primary production,
2
Figures estimated by the General Authority for Fisheries Resource Development.
3
Most financial/economic figures in this paper are provided in Egyptian pounds
(LE). LE 1= US$ 5.96.
19G. Macfadyen et al. / Aquaculture 362–363 (2012) 18–27
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 enter-
prises involved in the value-chain and their financial performance.
Value chain analysis was first popularised by Michael Porter in the
mid-1980s (Porter, 1985), and forms of analysis with many
similarities have been undertaken since then by others (Womack
and Jones, 1996 on value-streams, and Gereffiet al., 2005 on power
relations in value-chains). However, it is only more recently that
value chain analysis has become increasingly mainstream in develop-
ment circles.
An important component of value-chain analysis is recognition
that support and action for improving performance throughout the
value chain can be achieved both by those within the value chain it-
self i.e. the private sector operators, and by those outside of it i.e. typ-
ically governments. For businesses in the chain, they can improve
performance by reducing costs, increasing output, and/or increasing
the prices of their products (see Riisgard et al., 2010 for more infor-
mation on ways to upgrade the value-chain). Typically mechanisms
to do so involve being more efficient at what they do, and improving
the quality or form of product being sold to the next link in the value
chain. Improvements in value chain performance can also be
supported by governments and other parties external to the value
chain. For example, policy, institutions and infrastructure all impact
on the ability of businesses in the value chain to source the inputs
that they need, to make or engage in their primary activity, and
then to sell and deliver their product to their customers. Govern-
ments may therefore have an impact on value-chain performance
through their influence on policy, subsidies, licensing, standards,
transport infrastructure and related costs, property rights, enforce-
ment of regulations, government charges/rent collection, and other
impacts on factor costs (e.g. labour, capital, land, utilities).
3.2. Calculations
The data collected during the study have allowed us to estimate a
number of key indicators for each link in the value chain. 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.
Fig. 1. Map of the study area.
Table 1
Sample frame used during the study.
Governorate Fish farmers Fish traders and/or wholesalers Fish retailers Total
Kafr el Sheikh 22 questionnaires
1 focus group with 9
1 focus group with 7
1 focus group with 8
6 questionnaires
1 focus group with 8
5 questionnaires 33 questionnaires
Focus group discussions with 32
Behera 14 questionnaires
1 focus group with 15
5 questionnaires
1 focus group with 9
–19 questionnaires
Focus group discussions with 24
Fayoum 16 questionnaires
1 focus group with 29
4 questionnaires 7 questionnaires 27 questionnaires
Focus group discussions with 29
Sharkia 9 questionnaires
1 focus group with 12
6 questionnaires 1 questionnaire 16 questionnaires
Focus group discussions with 12
Totals 61 questionnaires
6 focus groups with total of 80
21 questionnaires
2 focus groups with a total of 17
13 questionnaires 95 questionnaires
8 focus group discussions with a total of 97
20 G. Macfadyen et al. / Aquaculture 362–363 (2012) 18–27
The financial indicators calculated include: gross output values per
kg (i.e. prices); operational profits
4
in LE per tonne of fish produced
or sold and as a percentage of sales; net profits
5
in LE per tonne of
fish produced or sold and as a percentage of sales; total net
value-added
6
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. Calculat-
ing these indicators was possible because of the detailed questions in
the questionnaires which asked for data on sales volumes and values/
prices, operational costs, and fixed costs, and which allowed for the
construction of costs and earnings models for each respondent.
Operational costs are those costs which vary depending on the
amount of fish being produced. For fish farmers these typically in-
clude costs for feed, fertiliser, fry, power, transport, ice, sales commis-
sion 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 are those costs which do not vary depending on pro-
duction volumes i.e. they need to be paid each year irrespective of
production/sales. For the fish farming value-chain, they typically in-
clude government licences, repair and maintenance costs, rents paid
for land and buildings, and the depreciation costs of assets. Depreciation
costs have beenestimated by obtaining information onthe 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 were not just limited to financial indicators
however. Individuals were asked to provide information on the num-
ber of people employed and on: whether employment is full-time,
part-time or seasonal; the number or working days per year for
part-time and seasonal workers; whether employees are men or
women; whether employees are over or under the age of 30; and
where labour comes from. The data collected were analysed and
converted into full-time equivalent (FTE) jobs based on the number
of days usually worked in the different sub-sectors as reported in
our interviews. This allowed for the calculation, for each link in the
value-chain (and per governorate), of: the FTE jobs per 100 tonnes
of fish sold; the percentage of FTE jobs that are men and women;
the percentage of FTE jobs that are full-time as opposed to
part-time or seasonal; and the percentage of FTE jobs that are created
for those over- and under-thirty years of age.
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.
4. Results and discussion
4.1. The value-chain for farmed fish from earthen ponds
There are virtually no exports of farmed fish, and so the value-chain
is a short and simple one compared to aquaculture value-chainsin some
other countries. This is especially true given that there is no processing
at all of farmed fish i.e. all fish is sold in whole form (either live, fresh on
ice, or fresh without ice),
7
and there is no value-addition either through
primary processing into fillets or into other secondary processed prod-
ucts (e.g. ready meals, etc.).
Fish is harvested by fish farms (typically but not exclusively be-
tween September and December, with stocking having taken place
in March/April), 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, may pass 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
Al-Obour close to Cairo, while smaller fish may by-pass these market
establishments and be sold closer to the farms, where purchasing
power of the local population is weaker, and where there is thus a
greater demand for smaller and cheaper fish.
Once fish has been harvested, there are no distinct value-chains
for different species i.e. individual traders/wholesalers and retailers
deal in all fish species, rather than in particular ones. All 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 is 265 g for tilapia,
409 g for grey mullet, 216 g for thinlip mullet, and 1481 g for catfish.
Eighty-nine percent of the volume and 81% of the value of farm pro-
duction in 2010 covered by our survey were accounted for by tilapia.
Mullet represented 9% of farm volumes and 18% of farm values, carp
0.2% of volumes and 0.1% of values, and catfish 1.7% of volumes and
1.3% of values.
All catfish is sold live, while other species (tilapia, mullet, carp) are
generally sold either fresh on ice (in summer months or if sales are
made relatively far from farms) or fresh with no ice (in winter
months and/or if sales are made relatively close to farms). There is a
growing trend in the country for the sale of live tilapia. This is partic-
ularly the case for tilapia being produced in Fayoum governorate,
which is almost all sold live, and transported in drums/tanks with ox-
ygen by traders to wholesaler and retailers. This live fish is typically
held in pens/cages in the Nile in Giza and Beni Suef and sold as
‘wild’fish from the Nile. In other governorates in the delta, live fish
may also be held in irrigation channels, and sold as wild fish, indicat-
ing a consumer preference for wild fish over farmed fish.
Interesting features of the value-chain and the flow of product
through it include: the very short time-period from harvest to final
consumption by the consumer due to the live/fresh nature of all
sales, with fish generally sold to consumers the same day as the har-
vest or the day after; and almost zero post-harvest losses (which is in
contrast to many wild fisheries value-chains, where significant post
harvest losses often occur in developing countries). These features
are reflective of an efficient distribution system and production locat-
ed close to major areas of population.
4.2. Employment creation through the value-chain
Table 2 demonstrates that in the fish farming sub-sector, employ-
ment is entirely male, is fairly evenly divided between those over and
under 30 years of age, is more strongly made up of full-time work,
and generates 8.3 jobs for each 100 tonnes of fish produced.
Non-full time employment is associated with the seasonal nature of
some fish farming activities e.g. stocking and harvesting, weed clear-
ance, etc. Seasonal activities on farms e.g. harvesting, are an unskilled
activity which can be completed by younger people with fewer skills
(at a low cost to the farmers), hence the relatively high rate of em-
ployment for the under 30s. Employment creation in Fayoum gover-
norate is probably higher than in other governorates due the small
average farm size in this governorate (12 fed), and the resulting in-
ability to generate economies of scale.
4
Sales revenues less operational costs.
5
Sales revenues less operational costs and fixed costs.
6
In national accounts, net value-added is the sum of remuneration of labour plus
capital i.e. pre-tax profits to owners net of depreciation, plus wages.
7
Some tiny quantities of farmed fish may be sold frozen by retailers if they are un-
able to sell product on a particular day, and deteriorating quality requires them to
place fish in home/shop freezers and then to sell it frozen. There is however no mass
freezing of product at the wholesale/trading stage of the value-chain.
21G. Macfadyen et al. / Aquaculture 362–363 (2012) 18–27
For the trader/wholesaler sub-sector, employment is also almost
exclusively male, even more full-time in nature than in the farming
sub-sector, and generates a lower percentage of jobs for the under
30s. Employment is generally associated with loading and unloading
of fish. The lower percentage of employment for those under 30s
compared to the farm sub-sector is probably explained by the fact
that traders/wholesalers represent key players in the value-chain, re-
quiring considerable amounts of capital (generally from their own
sources) which the young are likely to find less able to provide. The
trading/wholesaling sub-sector generates just under 1 FTE job for
each 100 tonnes of fish being sold —much lower than for the farming
sub-sector due to the short-time traders have the product in their
possession and the fact that they are in the business of distribution,
rather than processing.
It is only at the retail sub-sector that there are any meaningful quan-
tities of female employment being created, sometimes as managers/
owners of small businesses but more commonly as employees. This em-
ployment tends to be full-time in nature, and with a low proportion of
total employment being for the under 30s, again probably because of
the need to have capital and/or facilities to commence such an activity.
The retail sector creates 4.6 jobs per 100 tonnes of fish sold.
Data on FTE creation per tonne of fish passing through the
value-chain, allow us to estimate that for every 100 tonnes of fish
produced by pond fish farms, once the product has travelled through
the value-chain, it has resulted in almost 14 FTE jobs being created.
For the total production from ponds in Egypt (591,296 tonnes in
2009), a total of around 82,000 FTE jobs can thus be estimated in
the sector as a whole at the national level.
8
For the sector as a whole, and for all sub-sectors within it, almost
all labour is sourced from within the governorate in which the busi-
ness is based. However, our interviews did identify some limited num-
bers of people, especially from Kafr el Sheikh, who work in other
governorates. Wages paid to those working in the sector are 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.
4.3. Fish farming sub-sector —operational and financial performance
Table 3 provides the average operational data for fish farms in
each of the four governorates, and average operational data for the
sample frame as a whole.
Some interesting points to highlight from these results are:
•The relatively low average farm size in Fayoum, explained by the
fact that Fayoum is an oasis to the south-west of Cairo, and there-
fore suitable land for farming and fish farming is less available
than in the other governorates;
•The fact that most interviewees have been involved in the fish farm-
ing business for many years;
•The relatively uniform stocking size for tilapia (around 10 g), ex-
cept in Behera where stocking size is lower;
•Feed Conversion Ratios (FCRs) that are similar in Kafr el Sheikh and
Fayoum, but not as good as in Behera and Sharkia (which also have
similar FCRs to each other). Differences in the FCR rates are likely to
be the result of a number of different factors such as: the size of fish
at stocking; the extent to which fertiliser is also used; feed manage-
ment techniques and relative efficiencies; the quality of the feed
being used, which varies considerably between farms and gover-
norates; and the extent of water exchange;
•Production per fed that is comparable in Kafr el Sheikh, Fayoum and
Sharkia, but highest in Behera. This is perhaps due to fact that many
of the fish farms included in the sample frame in Behera are located
close to lake Idku, and so water availability and exchange is partic-
ularly good in this area;
•Relatively low fish prices in Behera due mainly to a smaller percent-
age of total production consisting of ‘super’(largest) grade tilapia in
that governorate, and the relatively high prices in Fayoum due to
the dominance of the live fish trade in that governorate;
•Tilapia ‘super’prices in Fayoum which are higher than the average
price for total production in Fayoum, due to the low percentage of
total production consisting of mullet compared to other governor-
ates —because mullet prices are higher than prices for tilapia, in
other governorates mullet production means that the average
price for all production is higher than the price for ‘super’tilapia;
•Stocking densities that are quite uniform across governorates, but
which can vary hugely between farms, depending on farming strat-
egies. Stocking rates reported during interviews range between
6000 and 30,000 per fed for tilapia. However most farms stock be-
tween 10,000 and 15,000 tilapia per fed; and
•Fairly consistent average size of fish at harvest in the four
governorates.
Table 4 provides information on the financial performance, and
the costs and earnings, of the fish farms.
Key points of interest from the results are:
•The positive financial performance in all governorates in terms of
average net profits (LE 247,172), net profits per tonne of fish (LE
2329), and net profits as a percentage of sales (22%). Fayoum is
the best performing governorate even though it has the highest
production cost per tonne, due largely to the high prices of fish
paid for their live product. Other reasons may be the level of skills
and good management practices in the governorate due to the
fact that farmers in Fayoum in particular have been the beneficiaries
of considerable amounts of training in the past, and more so than
farmers in other governorates. In general farms in Kafr el Sheikh
have the worst performance of the four governorates;
•An average total production cost across all farms of LE 7769/tonne,
which represents the break-even weighted sales price i.e. the aver-
age price of all fish sold by a farm must be more than LE 7769/tonne
if the farm is to make a profit;
•The consistently high percentage in all governorates of operational
costs which consist of feed costs (67% across all farms). Fish fry con-
stitute the next most important input (13% of operational costs),
followed by labour (8%), sales commission (5%), and fuel/electricity/
power (3%);
•The high percentage (91.5%) of total costs which consist of operation-
al costs, as opposed to fixed costs. Fixed costs are low due to the
8
This study did not attempt to estimate multiplier employment impacts from pond
farming, or employment from other production methods e.g. cage farming.
Table 2
Employment creation in the value chain.
Employment Kafr el Sheikh Behera Fayoum Sharkia Overall average
Full time equivalent jobs per 100 tonnes sold
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%
22 G. Macfadyen et al. / Aquaculture 362–363 (2012) 18–27
nature of the fish farming business, and also because many farms are
on rented land with short lease periods, which decreases the incen-
tive for farmers to invest in fixed assets;
•Land rents are the highest single fixed cost, representing 62% of
fixed costs for our sample as a whole, 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;
•Total value-added by the sub-sector i.e. net profits plus wages paid
to labour, is LE 2989 per tonne of fish produced. Again, this figure
is the highest for fish farms in Fayoum.
4.4. Trader/wholesaler sub-sector —operational and financial performance
Table 5 provides the outputs of the data collected and analysed for
this 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 gov-
ernorates (although the influence of traders/wholesalers is still signif-
icant in Fayoum also). 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 activi-
ties). 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 inabsolute terms are sig-
nificant, with individuals typically earning around LE 400,000 per year.
The earnings made by traders/wholesalers are generated from a
sales commission, usually of between 3 and 6% on the sales of fish,
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 a) they collect fish from the farms and therefore have to
pay for transportation and ice, and/or b) they have provided finance
to fish farmers. Individual questionnaire responses reveal that net
profits and net profit margins are generally higher when traders/
wholesalers collect fish from the farms, because the costs they incur
on ice and transport are less than the difference between the commis-
sion they take for collecting fish at the farms, and the commission
they get if fish is delivered to them.
Other interesting observations which can be drawn from the data
in the table are:
•The higher farm gate price for fish in Fayoum continues to be passed
through the value-chain, with higher average prices of fish sold by
traders/wholesalers in Fayoum compared to other governorates;
•Average annual sales values for individual traders/wholesalers sold
within Fayoum are lower than in other governorates, due to the
lower level of total farm production in this governorate;
•Operational ‘costs’consist almost entirely of the fish traders/
wholesalers buy from farms or sell for them. Other operational
cost items include labour, truck rental/transport, ice, and fuel/
Table 4
Financial performance of fish farms.
Financial performance data Kafr el Sheikh Behera Fayoum Sharkia Overall Average
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 feed costs as % of operational costs 72% 66% 68% 57% 67%
Average labour costs per tonne produced (LE) 516 486 948 768 660
Average op. costs per tonne produced (LE) 7020 6405 8011 6692 7115
Average operational profit (LE) 253,551 410,652 141,138 546,703 301,357
Average operational profit per tonne (LE) 2724 2243 3402 3179 2997
Average operational profit as % of sales revenue 27% 24% 32% 31% 29%
Average fixed costs (LE) 68,612 52,593 13,498 87,933 51,343
Average total production cost (LE/tonne) 8051 6688 8392 7442 7769
Average net profit (LE) 182,036 356,410 127,639 458,770 247,172
Average net profit per tonne (LE) 1640 1914 3402 2429 2329
Average net profit as % of sales 16% 20% 29% 24% 22%
Average total value-added per tonne (LE) 2155 2400 4350 3198 2989
Table 3
Operational data for the fish farming sub-sector.
Operational data Kafr el Sheikh Behera Fayoum Sharkia Overall
Total fed of interviewed farms under production 531 448 198 341 1517
Average years involved in the sector 20 18 16 18 18
Average area under production (fed) 25 34 12 38 26
Average size of tilapia when stocking (g) 10 4 11 10 9.05
Average FTE per fed 0.21 0.23 0.38 0.23 0.26
Average FTE per 100 tonnes 6.99 5.31 12.59 7.98 8.31
Average production (tonnes/fed) 3.26 4.81 3.16 3.12 3.55
Average FCR 1.89 1.44 1.71 1.38 1.66
Average sales price (LE/kg (all species)) 9.70 8.26 11.79 9.87 9.98
Average sales price tilapia ‘super’(LE/kg) 9.59 8.75 11.88 9.34 10.14
Average % of total production from tilapia 86% 94% 93% 79% 89%
Average stocking density tilapia/fed 12,786 17,500 13,656 11,012 13,790
Average stocking density mullet M. Cep/fed 700 784 858 788 776
Average stocking density mullet M. Cap/fed 1600 1354 1466 2167 1676
Average stocking density catfish/fed 200 317 n/a 844 332
Average growth period (months) 9.6 8.7 8.3 7.7 8.7
Average size tilapia at harvest (g) 276 235 283 252 265
Average size mullet M. Cep at harvest (g) 421 342 453 402 409
Average size mullet M. Cap at harvest (g) 223 206 500 177 216
Average size catfish at harvest (g) 1321 1333 n/a 1340 1481
23G. Macfadyen et al. / Aquaculture 362–363 (2012) 18–27
power, but none of these items alone comprise more than one per-
cent of the value of sales;
•Fixed costs are 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 vehi-
cles (15% of fixed costs);
•The individual average earnings for traders/wholesalers across the
four governorates appear very consistent, with those in Fayoum
similar to those in other governorates even though average total
sales values are lower, due to the higher margins being achieved;
and
•The average value-added (net profit plus wages) per tonne of fish
sold is LE 503, with almost double that being generated in Fayoum.
4.5. Retailer sub-sector —operational and financial performance
There are two main types of farmed fish retailers in Egypt. The first
group engages in ‘informal’street sales, which take place usually 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/equipment is minimal, often comprising just a shelter
from the sun. Labour is generally not employed, and these types of re-
tailers aim to make LE 0.5–1.0 profit on each kg of fish they buy/sell.
The second group is more formalised, with sales taking place from
retail shop facilities, and retailers may also have fridges and or
freezers for storing fish if it cannot be sold the same day it is pur-
chased. These businesses often employ labour to clean/prepare fish.
As a result their operational and fixed costs tend to be higher than
the informal street traders. However, this simplistic description and
division is not always entirely accurate or obvious in reality. For ex-
ample some formal retail businesses may employ people to sell fish
(generally of lower quality of or particular species) informally on
the street outside or nearby their shop. Equally, many formal retailers
also engage in some elements of the food service/restaurant business,
and use grills to cook fish for consumers.
The data provided in Table 6 does not distinguish between the two
types of operation, due to the small sample size achieved during the
study. Nevertheless, some confidence can be gained from the consis-
tency shown in the data between governorates, and the data are in-
teresting in that they show:
•Businesses 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;
Table 6
Operational and financial performance data for fish retailers.
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 per 100 tonnes of sales 1.34 n/a 7.79 2.02 4.62
Average sales price (LE/kg (all species)) 12.51 n/a 15.75 10.67 13.98
Average sales price tilapia ‘super’(LE/kg) 10.83 n/a 13.38 11.50 12.19
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 per tonne sold (LE) 0 n/a 333 170 181
Average operational profit (LE) 76,212 n/a 46,767 81,720 61,948
Average operation profit per tonne (LE) 916 n/a 1091 825 996
Average operational profit as % of sales 7% n/a 7% 8% 7.1%
Average fixed costs (LE) –n/a 5557 4700 3170
Average net profit (LE) 76,212 n/a 41,210 77,020 58,778
Average net profit per tonne (LE) 916 n/a 1008 778 951
Average net profit as % of sales 7% n/a 6% 7% 6.8%
Average total value-added per tonne (LE) 916 n/a 1341 948 1131
Table 5
Operational and financial performance data for fish traders/wholesalers.
Kafr el Sheikh Behera Fayoum Sharkia Overall
Operational data
No. of traders/wholesalers interviewed 6 55622
Total annual sales value of interviewees (LE) 105,948,000 75,463,200 36,026,210 51,739,588 269,176,998
Average FTE per 100 tonnes of sales 0.40 0.62 0.92 1.56 0.87
Average sales price (LE/kg (all species)) 10.83 9.86 12.95 10.23 10.66
Average sales price tilapia ‘super’(LE/kg) 10.17 9.67 12.80 10.17 10.5
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 labour costs per tonne sold (LE) 42 96 98 91 80
Average operation profit per tonne (LE) 293 265 822 413 440
Average operational profit as % of sales 2.6% 3.9% 6.5% 4.5% 4.1%
Average fixed costs (LE) 34,454 13,517 9532 7918 17,377
Average net profit (LE) 465,296 390,931 394,799 389,288 402,877
Average net profit per 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 per tonne (LE) 310 347 903 491 503
24 G. Macfadyen et al. / Aquaculture 362–363 (2012) 18–27
•Higher prices for fish in Fayoum exhibited in earlier links in the
value-chain are maintained in the retail sub-sector;
•Average net profits per individual business owners are LE 58,778,
still considerably above national average earnings; and
•The retail sector creates an average of LE 1131 for every one tonne
of fish sold.
4.6. Summary data on financial performance
Mapping the value chain and constructing costs and earnings
models for each link in the value chain as presented above, allows
for a comparison across the various sub-sectors in the value chain.
Table 7 shows how the average price of product both for all sales
sold by each link the value-chain (i.e. the basket price), and separate-
ly for tilapia ‘super’grade, increases as farmed fish moves through the
supply chain in each governorate. It also shows for the basket price of
fish the percentage of the final consumer price achieved by each link
in the value-chain. The data in the right-hand column of this table
show that the farmers are obtaining 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.
Tables 8 and 9 show the operational and net profit per tonne re-
spectively for each link in the value chain. These two tables also
show the operational and net rates of return on sales values for
each link in the value chain, and the percentage contribution of
each link in the value-chain to total profits created. The tables show
that operational and net profits as a percentage of own sales, and in
absolute terms per tonne of fish sold, are highest in the farm
sub-sector.
Finally, Table 10 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 4619 value-added is generated
for each tonne of fish produced by the farming sub-sector. Again,
the levels of value-added created are highest in the fish farming
sub-sector (LE 2985/tonne), and in Fayoum (LE 6594/tonne).
The data presented in Table 7 to Table 10 serve to benchmark perfor-
mance by the sub-sectors of the value-chain in different governorates,
and demonstrate the superior performance in Fayoum governorate.
Table 7
Gross output values i.e. fish prices for the farmed fish value-chain.
Gross output values LE/kg (all species basket price) LE/kg (tilapia ‘super’price) All species basketprice as % offinal consumer price
K el Sh Beh Fay Sha All 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 9.59 8.75 11.88 9.34 10.14 78% n/a 75% 92% 71%
Traders/wholesalers 10.83 9.86 12.95 10.23 10.66 10.17 9.67 12.80 10.17 10.50 87% n/a 82% 96% 76%
Retailers 12.51 n/a 15.75 10.67 13.98 10.83 n/a 13.38 11.50 12.19 100% n/a 100% 100% 100%
Table 8
Operational profits created in the farmed fish value-chain.
Operational profit LE/tonne % of own sales % of value-chain operational profit creation
K el Sh Beh Fay Sha All K el Sh Beh Fay Sha All K el Sh Beh Fay Sha All
Farmers 2724 2243 3402 3179 2997 27.2% 24.5% 32.0% 31.5% 28.8% 69.3% 89.4% 64.0% 72.0% 67.6%
Traders/wholesalers 293 265 822 413 440 2.6% 3.9% 6.5% 4.5% 4.1% 7.4% 10.6% 15.5% 9.4% 9.9%
Retailers 916 n/a 1091 825 996 7.3% n/a 6.8% 7.7% 7.1% 23.3% n/a 20.5% 18.7% 22.5%
Total 3933 2508 5315 4418 4432
Table 9
Net profits created in the farmed fish value-chain.
Net profit LE/tonne % of own sales % of value-chain net profit creation
K el Sh Beh Fay Sha All K el Sh Beh Fay Sha All K el Sh Beh Fay Sha All
Farmers 1640 1914 3402 2429 2329 15.8% 20.4% 28.8% 23.8% 21.8% 58.1% 88.4% 65.2% 67.3% 62.9%
Traders/wholesalers 268 252 804 400 422 2.3% 3.7% 6.4% 4.4% 3.9% 9.5% 11.6% 15.4% 11.1% 11.4%
Retailers 916 n/a 1008 778 951 7.3% n/a 6.3% 7.3% 6.8% 32.4% n/a 19.3% 21.6% 25.7%
Total 2824 2166 5215 3607 3702
Table 10
Total value-added created in the farmed fish value-chain.
Total value-added LE/tonne % of value-chain value-added creation
K el Sh Beh Fay Sha All K el Sh Beh Fay Sha All
Farmers 2155 2400 4350 3198 2989 63.7% 87.4% 66.0% 69.0% 64.7%
Traders/wholesalers 310 347 903 491 503 9.2% 12.6% 13.7% 10.6% 10.9%
Retailers 916 n/a 1341 948 1131 27.1% n/a 20.3% 20.4% 24.5%
Total 3381 2748 6594 4637 4623
25G. Macfadyen et al. / Aquaculture 362–363 (2012) 18–27
The emphasis on live fish trade, on which Fayoum's superior perfor-
mance appears to be largely based, also seems to be a strategy that isin-
creasingly being pursued in other governorates.
Our fieldwork 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 in any one governorate (i.e. benchmarking
sub-sector performance against itself over time). However we did at-
tempt 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 pro-
vided by respondents in terms of the perceived changes in the opera-
tional 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 with only small in-
creases in nominal terms, this would suggest that profitability has
been declining in recent years. Sector performance may now be under
threat, especially due to increases in the costs of feed, with feed prices
havingincreasedby200–250% over the last 6–7 years.
To the best of our knowledge, a detailed costs and earnings survey
of the sub-sectors of the farmed fish value-chain similar to the one
presented in this paper has not previously been completed in Egypt.
While our data cannot therefore be used to quantitatively assess
changes in value-chain performance in recent years, the data
obtained during this study may be useful as baseline data to be used
for future benchmarking of changes over time. In particular, the
data may be helpful in the monitoring and evaluation of any subse-
quent interventions in support of the sector.
4.7. Critical factors impacting on value-chain performance
In seeking to explore how value-chain performance could be im-
proved, our study qualitatively explored with questionnaire respon-
dents and focus groups the critical factors impacting on value-chain
performance. We have chosen in this paper to focus primarily on
presenting the financial performance of the value-chain, rather than
to discuss in detail the myriad of factors determining value-chain per-
formance. However Table 11 provides a brief summary of the key is-
sues impacting on the sector. All of the issues included in the table
represent potential areas of action by the value-chain itself and by
those relevant factors outside of it (e.g. government), to improve
value-chain performance.
5. Conclusions
Egypt is by far the largest aquaculture producer in Africa and the
world's second largest producer of farmed tilapia, and the sector is a
pioneering and vibrant one. When one considers the attempts by
other African countries to develop aquaculture and the small produc-
tion volumes that have resulted, the success achieved in Egypt is all
the more impressive. This paper has demonstrated that the sector
generates very considerable levels of value-added, results in profit-
able businesses at each stage of the value-chain, and provides em-
ployment for many thousands of people (who in turn have many
others in their households dependent on their earnings). Most people
who work in the sector have been doing so for many years, and our
study suggested that this is largely, but not exclusively, due to the
sustainable nature of the value-chain rather than due to a lack of al-
ternative livelihood opportunities.
However, the sector now faces a number of significant challenges,
and it is noteworthy that the yearly percentage increase in the vol-
ume of aquaculture production in 2009 (1.7% above 2008) was the
lowest yearly percentage increase for the last 10 years. The historical
strength of the sector, coupled with recent challenges, and indeed op-
portunities for further improvements in value-chain performance,
provides a strong argument for action by private sector businesses
within the value-chain, and by government in the form of supportive
policy and legislation (on issues such as land tenure, access and qual-
ity of water, infrastructure, and human capacity development). Such
action would serve both to safeguard the current financial and
Table 11
Summary of critical issues and factors constraining the sector.
Critical issue or factor
Input factors •Access to capital and finance from the banking
sector is virtually non-existent, due to perceptions
of risk held by the banking sector and the collateral
requirements demanded
•Feed costs have risen dramatically in the past
6–7 years, and the quality of feed is very variable
between feed producers
•Fry quality for tilapia is often poor with fry sold as
mono-sex reproducing, and in some geographical
areas there are shortages of mullet fry
•Water quality can be poor from using agricultural
drainage water, and availability limited at some
times of the year due to agricultural requirements
•Expansion of farming into new areas would re
quire considerable human capacity development to
train labour
•Access to land for expansion is increasingly prob
lematic, and many farmers operate on land rented
from government without any option to buy and
with short lease periods and low security of tenure
•Power/fuel costs have risen in recent years and
many farms do not have access to mains electricity
Production factors •While the environmental conditions in Egypt are
generally favourable for fish production, the colder
winter months from January through April place
constraints on the fish farming sub-sector, due to
the lack of cold tolerance of fish and a growth peri
od that is limited to around 8 months
•For some farms, pond size, layout and design is not
optimal
•There is very variable knowledge about Best
Management Practices (BMPs) for feed use
•Many farms are thought to use sub-optimal
stocking strategies
•BMPs for fish health management are not always
followed
•Sector and sub-sector organisation is very weak.
Only in Fayoum is there any form of representative
organisation that is functioning in a meaningful way
•Over-reliance on a small-number of fish species
(i.e. tilapia and mullet)
Post-harvest distribution
and marketing factors
•Pressure on fish prices due to increasing
aquaculture production over the last decade,
consumer preference for meat as a source of
protein, the presence of significant quantities
(although declining) of imports of competitor
products (often of poor quality), and a consumer
preference for wild fish due to health concerns
about fish produced by farms because of water
quality issues
•Fish prices can exhibit considerable daily and
seasonal fluctuations, primarily due to changes in
the volume of supply on particular days, or between
different months.
•Health and hygiene conditions in wholesale and
retail markets, and in the transportation/
distribution network are poor
•There are virtually no exports, but not enough
knowledge about Egypt's competitive position vis a
vis other suppliers, about comparative prices in
Egypt and in overseas markets, and about the steps
that would have to be taken to expand exports, in
order to make an informed opinion about the merits
of a push to try to access export markets
•There is no processing for value-addition, with all
fish sold in whole form
•Poor road networks to farms in some areas impact
on the ability of farmers/traders to get fish to
markets
26 G. Macfadyen et al. / Aquaculture 362–363 (2012) 18–27
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 aquacul-
ture sector, with a continuing focus instead in research and interven-
tions on technical production issues. This paper has showed that
value chain analysis is a useful tool for understanding the financial
and social benefits that are generated by the aquaculture sector, and
for identifying the critical factors that affect the financial and social
performance of the value chain. Better understanding of these critical
factors can inform the necessary actions and innovations to increase
the financial and social benefits created by the sector.
Acknowledgements
The authors would like to acknowledge the important contribu-
tions and suggestions made by Dr. Malcolm Beveridge from the
WorldFish Center to a first draft of this paper. The authors also grate-
fully acknowledge the support of the Swiss Development Corporation
in funding this work. The paper also represents an output of the
CGIAR Livestock and Fish Research program.
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