Snapshot Africa Kenya
Snapshot Africa - Kenya
Benchmarking FDI Competitiveness
Multilateral Investment Guarantee Agency
Government of Madagascar in association with
the Private Sector Development Project II
of the International Development Association
Swiss State Secretariat for Economic Affairs
Austrian Development Agency
United States Agency for International Development
JANUARY 2007
SNAPSHOT AFRICA - KENYA
Copyright © 2006
World Bank Group/MIGA
1818 H Street, NW
Washington, DC 20433
All rights reserved
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November 2006
Available online at www.fdi.net/snapshot_africa
For more information, contact:
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Washington, DC 20433
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The material in this publication is copyrighted.
Requests for permission to reproduce portions
of it should be sent to MIGA Operations at the
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The Multilateral Investment Guarantee Agency (MIGA) of the World Bank Group was established
in 1988 to promote the flow of private foreign investment to developing member countries.
MIGA offers political risk insurance coverage to eligible investors for qualified investments
in developing member countries. MIGA also offers technical assistance programs to develop
and implement effective strategies for attracting and retaining foreign direct investment. This
hands-on technical assistance focuses on three primary areas: dissemination of information on
investment opportunities and business operating conditions in developing member countries
through online services; capacity building of the organizations and institutions involved in the
promotion of foreign investment; and, investment facilitation activities supporting the efforts of
developing countries to identify and attract investment.
Research for the sub-Saharan Africa benchmarking study was conducted and carried out by The
Services Group, one of MIGA’s principal contractors for the global Enterprise Benchmarking
Program.
SNAPSHOT AFRICA - KENYA
Snapshot Africa-
Kenya
Benchmarking FDI Competitiveness
Foreign Direct Investment Cost and Conditions for the Textile, Apparel,
Horticulture, Food and Beverage Processing, Shared Services and Tourism
Industries
Ghana
Kenya
Lesotho
Madagascar
Mali
Mozambique
Senegal
Tanzania
Uganda
FIFTH IN A SERIES
OF SECTOR ANAlYSES
NOVEMBER 2006
SNAPSHOT AFRICA - KENYA
Table of Content
Sector
Textile .......................................................................................................................9
Apparel ...................................................................................................................13
Horticulture ...........................................................................................................17
Food and Beverage Processing .............................................................................21
Shared Services .....................................................................................................25
Tourism ..................................................................................................................29
Appendices
I. Acronyms and Abbreviations .............................................................................34
II. Data Definitions and Sources ..........................................................................35
III. Tables and Findings .........................................................................................44
IV. The Kenya Investment Authority (KIA) ...........................................................63
The Multilateral Investment Guarantee Agency is not, by means of this publication, rendering
accounting, business, financial, investment, legal, tax, site selection, or other professional advice
or services, and shall not be responsible for any loss sustained by any person who relies on this
publication as a substitute for such professional advice or services. Before making any decision
or taking any action that may affect your business, you should consult a qualified professional
advisor.
SNAPSHOT AFRICA - KENYA
Introduction
As part of MIGA’s global Enterprise Benchmarking Program (EBP), a study was
conducted in sub-Saharan African countries among six industries to compare the
operating costs and conditions for investors located in nine sub-Saharan African
countries: Ghana, Kenya, lesotho, Madagascar, Mali, Mozambique, Senegal,
Tanzania and Uganda. This report summarizes the study’s findings, and presents
Figure: Phases of research
the result of the sub-Saharan Africa EBP, adhering to the location benchmarking
methodology
approach commonly used by foreign investors to evaluate alternative global
investment sites. As an analytical tool, location benchmarking enables an investing
Desktop research - Phase I
company to narrow its site selection options to a short-list of locations best suited
to the requirements of the investment project. Countries were evaluated based
r Identify source
r Compile data
on the actual costs and operating conditions reported by existing investors with
r Enter data into model
facilities in these countries.
The study was conducted by the Multilateral Investment Guarantee Agency of the
World Bank Group, with the financial support of the Government of Madagascar
Field research – Phase II
in association with the Private Sector Development Project II (International
Development Association [IDA]), the Swiss State Secretariat for Economic Affairs
r Interviews with foreign investors
r Fine-tune costs and conditions
(SECO), the Austrian Development Agency (ADA), United States Agency for
r Compile results
International Development (USAID) and Japan Policy and Human Resources
r Enter data into model
Development Trust Fund (World Bank).
The Africa EBP was designed to deliver on several specific components, many with
associated outputs integral to the participating countries’ investment promotion
Findings – Phase III
strategies, capacities and processes. Its key objectives were to:
• Compare the operating costs and conditions associated with the selected
r Normalize data
r Benchmarking analysis
industries in each country in order to identify industries with a strong com-
r SWOT analysis
petitive position, relative to competing locations. This can then be incorporated
r Report results
into inward investment promotion strategies and marketing efforts;
• Use SWOT analysis to identify each country’s comparative strengths, weak-
nesses, opportunities and threats as a destination for inward investment in the
selected industries;
• Identify each country’s comparative advantages and make recommendations for
improving the investment climate and attractiveness of each country for inward
investment promotion, which can assist an IPI in developing sector-specific key
selling messages to attract inward investment;
• Develop expertise within the IPIs through their involvement in the execution of
the work program and through targeted capacity building so that lessons learned
are institutionalized.
Methodology
MIGA’s EBP methodology aims to capture a snapshot of an industry in one
location at a static point in time from the unique perspective of the investor. Part
of this snapshot reflects objective, quantitative operating costs; another portion is
based on investors’ perceptions of qualitative operating conditions. Perceptions of
operating conditions, while subjective, are formed by the actual experiences of the
investor and can significantly influence the investment location decision.
Phases and Sequence
The Africa EBP was conducted in three main phases over the course of several
months beginning in November 2004 and ending in March 2005 (see Figure). In
SNAPSHOT AFRICA - KENYA
collecting information regarding operating conditions and investment motivation,
the Africa study relied mostly on first-hand information obtained through company
interviews. This was due to the difficulty of finding reliable and comparable data
through desktop research sources. The research team conducted a total of 297
company interviews with foreign and local investors in the six industries. Among
the surveyed companies, 37 percent were locally owned, 29 percent were joint
ventures between local and foreign firms, and 34 percent were foreign owned. The
primary data collected from company interviews using a standard questionnaire
was supplemented with secondary data obtained from provincial, national and
international sources.
Composition of interviewed firms
Sectors covered
Number of
Ownership structure of interviewed firms
firms
100 % local
Joint venture
100 % foreign
Textile
42*
20
10
12
Apparel
57**
21
26
10
Horticulture
47r
24
10
13
Food and beverage
52rr
19
13
20
processing
Shared services (Call
51
16
13
22
centers)
Tourism (Hotels)
48
11
13
24
TOTAl
297***
111
85
101
* 13 firms also produce apparel
** 13 firms also produce textiles
*** 278 individual interviews
r 6 firms also produce processed food
rr 6 firms are also horticulture producers
The Enterprise Benchmarking Model is predicated on a set of assumptions about
investment decisions, which are tested through empirical data gathered from
interviews and publicly available cost and quality condition rankings. The model
assumes several things about investment behavior, garnered through hundreds of
interviews with companies with international investments. These assumptions can
be broken down into two major categories: Assumption 1 - lower costs increase
the attractiveness of a potential investment location, when all else is equal.
Assumption 2 - Higher quality increases the attractiveness of an investment site.
SNAPSHOT AFRICA - KENYA
Model Measurements
The benchmarking model measures cost and quality conditions experienced by
investors utilizing desktop research and a detailed survey of investors already
operating in 11 African countries. The factors underlying these measurements are
listed in Figure below:
Site selection factors processed by the Enterprise Benchmarking
model
Site selection
Cost
Quality
consideration
factors
factors
Labor
labor
Potential to recruit local staff
Flexibility of labor environment
Infrastructure
Electricity
Power supply
Water
Water supply
Telecommunications and
Telecommunications and Internet
broadband
Internet
Availability and reliability of shipping
transportation
Natural gas
Freight shipment
Real estate
Real estate
Availability of land, office space,
buildings and sites
Construction
Office space
Living con-
None
Schools, safety, healthcare, etc,
ditions
Access to
None
Size of local market
markets
Proximity to raw materials, components
and equipment
Access to international tourists
General
None
Political, financial, and economic stability
business
environment
Weighting of Data
Investors do not place equal value on all cost and quality factors. A textile mill,
for example, might place premium value on locating near a source of raw cotton,
while a call center might value access to inexpensive and reliable telecommuni-
cations above all else. Based on the experiences of hundreds of foreign investors,
weightings were thus assigned to each factor that investors consider when making
location decisions. The benchmarking model processes the data in proportion to
the importance each site selection factor plays in a typical investment decision for
each industry.
SNAPSHOT AFRICA - KENYA
Kenya
General country info: Kenya
The most industrialized country in East
Africa and one of the top performing
countries in sub-Saharan Africa, Kenya
2004 Data
provides an impressive array of reasons
to invest in its industries. The country
Population
33.5 million
is reported by foreign investors to have
labor force
15.1 million
a well-developed port system with cold
language
English, Kiswahili
storage facilities and computerized port
procedures, and a motivated work force.
Area
580,370 km²
It is also a member of the East African
Arable land
4,650,000 ha (2003)
Community (EAC) of 93 million people,
GDP
USD 16.1 billion
where trade is envisaged to flow freely across Uganda, Tanzania and Kenya by
GDP growth
4.3 percent
2013. Add to this Kenya’s membership in the Common Market for Eastern and
GDP per capita* USD 427
Southern Africa (COMESA), with nearly 385 million people, and it is easy to see
GDP per capita
USD 1047
why a number of international companies have chosen the country as a regional
at PPP*
business hub. Kenya’s exports have increased substantially in recent years. In 2003
Industry value
USD 2.5 billion
top exports included horticulture (26.7 percent) and tea (24 percent), followed by
added
apparel, coffee, iron and steel, soda ash, fish and plastics.
Manufacturing
USD 1.6 billion
value added
Despite having one of the most diversified economies in the region, Kenya’s FDI
FDI inflows
USD 46.1 million
flows have been consistently lower than those of its neighbors in recent years.
2003 did see a sharp rise in FDI inflows, totaling USD 82 million, a considerable
FDI (percent of
0.29 percent
GDP)
upturn from 2002 where FDI inflows totaled just USD 28 million. Inflows settled
at USD 46 million in 2004 (see Figure) and are forecast to end at USD 54 million
Market access
EAC 93 m
COMESA 385 m
in 2005. The main sources of FDI are India, China, the UK and Germany. The
1985-90
1991
1992
1993
1994
1995
EBP Total
84
77
92
267
519
COTONOU
853
456 m
Government has implemented reforms in the legal framework for FDI in order to
EBP av.
9
9
10
30
AGOA 58
299 95
m
encourage investment. Some of these incentives include abolishing export and
sSA av.
28
45
33
46
72
95
IOR-ARC 2 b
Sub-Saharan Africa Total
1257
2076
1498
2099
3304
4361
import licensing, except for a few items listed in the Imports, Exports and Essential
Ghana
8
20
23
125
233
107
* Constant 2000 USD
Kenya
37
19
6
2
4
32
Supplies Act (Chapter 502); rationalizing and reducing import tariffs; revoking all
Lesotho
10
7
Source: W 3
orld
15
Bank, UNCT 19
AD
275
export duties and current account restrictions; freeing Kenya shilling’s exchange
Madagascar
9
14
21
15
6
10
Mali
1
1
-22
4
17
111
rate; allowing residents and non-residents to open foreign currency accounts
Mozambique
4
FDI inflows
23
for
25
Kenya,
32
35
45
with domestic banks; and removing restrictions on borrowing by foreign as well
Senegal
12
-8
21
-1
67
32
Tanzania
3
sub-Saharan
0
Africa
12
average,
20
EBP
50
120
as domestic companies. Restrictions on investment include recent changes stip-
Uganda
0
country
1
average
3
55
88
121
ulated in the 2004 Investment Promotion Act requiring a minimum investment
Data are in millions
of USD 500,000. The act also introduced requirements that the investment must
Page: Series: Foreign direct investment, net inflows in reporting economy (D
create employment for Kenyans, generate Government revenues and bring new
EBP av.
sSA av.
Ghana
EBP av.
sSA av.
Kenya
technology into the country.
350
350
300
300
250
BENCHMARKING SUMMARY: Human resources and international transportation
250
200
200
infrastructure are two key aspects of Kenya’s attractive investment environment.
150
150
The country boasts the highest literacy rate resulting in a high level of qualified
USD (million)
100
USD (million)
100
upper level staff and skilled labor. This large supply of labor also contributes to fairly
50
50
0
0
low wage levels. Flexible employment regulations make workforce management
1
9
1
1
1
1
1
1
1
1
1
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
8
9
9
9
9
9
9
9
9
9
0
0
0
0
0
9
9
9
9
9
9
9
9
9
9
0
0
0
0
0
5
9
9
9
9
9
9
9
9
9
0
0
0
0
0
8
9
9
9
9
9
9
9
9
9
0
0
0
0
0
-
1
2
3
4
5
6
7
8
9
0
1
2
3
4
9
5
-
1
2
3
4
5
6
7
8
9
0
1
2
3
4
comparatively easy for companies in Kenya. Kenyan firms also benefit from access
0
9
0
to well developed sea shipping and airfreight services. Investors reported some
of the lowest prices in office rentals, and utility costs are at a competitive level
compared to other surveyed countries. In part this is due to the relatively low cost
Source: World Bank 2004
of water, which was the third lowest at USD 0.42 per cubic meter. Kenya’s EPZs also
strengthen the operating environment for zone-based industries, as these areas
have comparatively good electrical, water, and telecommunications connections.
SNAPSHOT AFRICA - KENYA
Sector Snapshots
Each sector included in this chapter (textile, apparel, food and beverage processing,
Tariffs
horticulture, shared services and tourism) begins with a global sector brief, followed
Though tariff levels are an important
by country specific sector briefs and a SWOT analysis. In order to study the via-
factor for sectors such as textile, apparel,
horticulture and food and beverage
bility of the sectors studied in this report, each sector’s market trends and future
processing, most sub-Saharan African
prospects within the global context was analyzed. The country-specific sector briefs
countries have tariff-free access to a
highlight information and factors relevant to the sector in that country.
number of major markets within a wide
range of export products. It is, for this
The SWOT analysis at the end of every sector brief provides a general overview
reason, that tariffs are not a general worry
for investors in Africa. Among the more
of strengths, weaknesses, opportunities and threats that investors in the country
popular trade agreements are the African
experience while investing in the relevant sector. The strengths and weaknesses
Growth Opportunity Act (USA), the Cotonou
for each sector present whether the country is among the three countries that per-
Agreement (EU), the Everything But Arms
formed worst in the six most important surveyed site selection factors as reported
(EBA) amendment to the EU’s Generalized
by investors presently operating in Africa. Three of the six factors pertain to quality
System of Preferences (EU), the Common
Market for Eastern and Southern Africa
factors and three to operating cost factors (see Table). It is worth noting that not
(COMESA), the East African Community
all countries were benchmarked in all sectors. lesotho is benchmarked in only the
(EAC), the Economic Community of West
textile and apparel sector, while Mozambique and Uganda were not benchmarked
African States (ECOWAS) and the Southern
for the textile sector and the tourism (hotels) sector respectively.
African Development Community (SADC).
Top six site selection factors according to surveyed investors
Textile
Apparel
Horticulture
Food and Beverage
Shared Services
Tourism
Quality factors (In order of importance)
1
Access to markets
Access to markets
Access to markets
Access to markets
Access to markets
Access to markets
and supplies
and supplies
and supplies
and supplies
and supplies
and supplies
2
General business
General business
General business
General business
General business
General business
environment
environment
environment
environment
nvironment
environment
3
local potential to
local potential to
Availability of real
local potential to
local potential
local potential to
recruit staff
recruit staff
estate/Arable land
recruit staff
to recruit staff/
recruit staff/ Real
Infrastructure
estate
Cost factors (In order of importance)
1
Wage levels
Wage levels
Wage levels
Wages levels
Wages levels
Cost of real estate
2
Cost of real estate
Cost of real estate
Cost of real estate
Cost of real estate
Telecommu-
Wage levels
nications
3
Cost of water and
Cost of water and
Cost of transport
Cost of construction
Cost of real estate
Cost of construction
power
power
SNAPSHOT AFRICA - KENYA
SNAPSHOT AFRICA - KENYA
Textile Sector
Between 2000 and 2004, the value of world exports of textile products grew at
Textile Sector Survey Profiles
an average annual rate of 4.4 percent. With exports from emerging economies
growing at a slightly higher rate, their share of world exports increased by 1.5 per-
Companies
42 *
centage points to 46.7 percent in 2004. Currently, the major players in the global
interviewed
textile market are China, the US, the EU, India, Pakistan, Japan, Republic of Korea
Average Investment Characteristics
and Turkey. low cotton prices provide cheap inputs to textile operations worldwide.
According to the EIU, estimated global consumption of cotton in 2004/05, at
Ownership
47% local owned
24% joint ventures
23.4m tons, is slightly higher than expected and represents an increase of almost
29% completely
10 percent over the last year. Overall, world cotton consumption in 2005/06 is
foreign owned
forecast to reach 24.35m tons, an increase of 4 percent.
Investment size
USD 15.8 million
Factory floor space 23,559 m²
The elimination at the end of 2004 of quantitative import restrictions under the
World Trade Organization (WTO) Agreement on Textiles and Clothing (ATC) has
Number of
591
employees
greatly affected the textile industry (see Table). A recent study predicts the following
trends as a result of the elimination of quotas on textiles: an increase in the share
Sales
USD 13.2 million
of world exports for textiles emanating from emerging economies; a considerable
Company exports
Cotton yarn
gain in the export shares of countries with low labor costs, such as China, India
organic cotton
cotton fabric
and Pakistan; heightened competition among suppliers in low-cost countries; and
printed fabrics
increased specialization of products among source countries.
polyester fabrics
blankets
The textile industry is usually characterized as capital intensive and highly
bed sheets
automated, with a reliance on unskilled labor. Although labor costs in Africa are
*13 firms also produced apparel
generally competitive with those in China or India, the main factor decreasing the
competitiveness of Africa in the global textile trade is high utility costs, particularly
for electricity and water, coupled with supply unreliability. A number of successful
textile producing countries, such as China and India, rely on strong backward
linkages for production inputs, and textile industries in Africa have yet to create
such linkages to the local economy.
A number of countries benefit from AGOA’s third-country fabric sourcing allowance,
which permits African countries, exporting under the AGOA agreement, to source
raw material inputs from non-AGOA countries. This arrangement is slated to expire
in 2007, which will increase the need for AGOA countries to source inputs from
local suppliers. African textile exports under AGOA totaled USD 1.4 billion in 2005,
which represents a 12 percent decline from the previous year, due to increased
global competition, brought about by the elimination of the multi-fiber agreement
(MFA). Africa has had little success thus far in attracting FDI into the textile sector.
According to loco Monitor, an online FDI tool, Africa receives just 2 percent of
global FDI, while Asia Pacific and Europe together account for almost 80 percent.
The largest share of FDI in Africa in the textile sector is from the EU, followed by
North America and Asia Pacific, while Africa and the Middle East account for many
small-scale projects.
Sub-Saharan Africa does possess a number of advantages that increase its attrac-
tiveness as an investment location, particularly its low labor costs and abundance
of unskilled labor. Investors in Africa can also benefit from preferential access to a
number of global markets, including AGOA, and large and still developing regional
trade zones. A number of sub-Saharan African governments are putting increased
emphasis on developing EPZs that provide improved access to global markets and
infrastructure. Successful EPZ investments are evident in African countries such
as Mauritius and lesotho.
SNAPSHOT AFRICA - KENYA
Textile Brief
Snapshot Africa Report
• The textile industry developed rapidly after independence in 1963 to become one
Motivation Graphs: Pg. 14 – 17
of the main industries in the country. A massive inflow of used products and
Breakdown of cost motivations
cheaper Asian imports nearly wiped out the textile and apparel industries during
Figure 4: Breakdown of cost motivations reported by
Figure 5: Breakdown of quality motivations reported by
reported by textile firms
the 1990s.
textile firms
textile firms
11%
16%
• Due to AGO1A
1%, Kenya has seen a revival in its textile industry with investment
20%
rising from USD 16 million in 1999, to USD 162 million in 2004. Currently, there
exist ar1o
1% und 35 textile mills in the country. Main exports include yarn, fabrics
20%
11%
and other textiles, totaling 1,854 tons in 2003.
• Textile14 p
% roduction has an opportunity to strengthen the cotton-textile-apparel
2%
value chain, of which at the moment only the apparel part is competitive.
5%
33%
5%
30%
• The majority
11 of
%
textile firms located in the EPZ export their products to the US
Real estate
market and are
Generforeign
al businessowned,
environme primarily
nt
by Indians, Sri lankan and Bangladeshis.
Water & power
Kenya is the
A second
ccess to malargest
rkets and s exporter
upplies
of textiles under AGOA, after lesotho.
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
• Principal domestic
Infrastructu exports
re
are primarily to the EAC and COMESA, with Uganda
Telecommunications
and Tanzania
Livi primary
ng environm destination
ent
countries. Kenyan textile firms export products
Tariffs
equally by roadway and sea shipping.
Tax
• Textile firms have shifted most of their employment rolls from permanent to
Snapshot Africa Report
casual labor in response to volatile market conditions for global exports.
Figure 6: Breakdown of cost motivations reported by
Figure 7: Breakdown of quality motivations reported by
apparel firms
apparel firms
Motivation Graphs: Pg. 14 – 17
8%
Breakdown of quality motivations
10%
Figure 4: Breakdown of cost motivations reported by
Figure 5: Breakdown of qual1i9t%
y motivations reported by
24%
reported by textile firms
10%
textile firms
textile firms
The elimination of the Multi-fiber Agreement
23%
11%
11%
7%
16%
20%
The MFA was set up in 1974 to protect the European and American textile and apparel industries from
11%
low-cost pr
17od
% ucts from Asian countries. In time, the MFA developed into a complex system of quotas
and restrictions on various products. In order to cope with these restrictions, exporting countries became
11%
3%
20%
adept at shifting production to less restricted product categories and countries when they reached their
4%
quotas on specific products. Since quota
29% allocations were usually based on historic export performance,
4%
32%
there was a further
1 incentive
0%
to increase exports to unrestricted markets, even when it was not profitable,
14%
2%
in order to increase subsequent years’ quota allotments. As a result, the quota system provided many
Real estate
developing countries
Gene with
ral bu access
siness ento
vir markets
onment
they otherwise would not have accessed. These countries
5%
Water & power
33%
are being adversely
Ac affected
cess to m by
ark the
ets phase-out.
and supplies In addition, in order to avoid quotas a number of countries
5%
Wage levels
30%
11%
moved up into higher
Real evalue-added
state
production, sourcing out low-cost production to less quota-restricted
Transport
countries. This en
L c
o o
c u
al ra
pogted
nt it
a h
l t e
o frr
e a
c ct
rui u
t r
s itn
afgf of the global value chain and developed textile and apparel
Construction
Real estate
General business environment
firms in developiIn
nf g
ra c
stou
rucn
t t
u ri
re es. During the Uruguay Round of WTO negotiations, the ATC called for
Telecommunications
Water & power
Access to markets and supplies
the phase-out of qu
Livi ota
ng s o
envi n
ro te
nm xtil
ent es and apparel over a 10-year period, beginning in January 1995, and
Tariffs
Wage levels
Real estate
ending in January 2005. There is general agreement that the elimination of textile and apparel quotas will
Tax
Transport
Local potential to recruit staff
immediately benefit a small handful of developing countries - those that possess a strong and diversified
Construction
mix of textile and apparel products, engage in full-package production, produce high-quality, high value-
Infrastructure
Telecommunications
added products, and possess diverse markets outside the US and the EU. These countries include China,
Living environment
Tariffs
India and Pakistan.
Tax
(Source: UNCTAD 2005)
Figure 6: Breakdown of cost motivations reported by
Figure 7: Breakdown of quality motivations reported by
apparel firms
apparel firms
8%
10%
19%
24%
10%
23%
7%
17%
3%
4%
4%
29%
32%
0
SNAPSHOT AFRICA -
10%
KENYA
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
Comparative SWOT Analysis for Textile
Kenya vs. Snapshot Africa
Labor market availability in the textile
Strengths
Weaknesses
sector*
Good current export performance
Weak rating on corruption perception
low country risk rating
Unfavorable labor relations
Labor market availability in the textile sector*
Kenya
Snapshot av.
5
Business start-up procedures minimal
Difficulty of sourcing local raw material inputs
low employment rigidity
Difficulty of sourcing local component inputs
4
Good availability of managers
High site lease costs for industrial land
3
Good availability of professionals
2
Good availability of technical workers
1
Good availability of skilled workers
0
Good availability of unskilled workers
M anagers Professionals Technical
Skilled
Unskilled
workers
workers
workers
low wage rates for managers
*(5 = High availability, 1= low availability)
low wage rates for technical workers
Labor market availability in the textile sector*
low water costs
Annual water costs for running a textile mill, in USD (thousands)
Kenya
Snapshot av.
*(5 5
= High availability, 1= low availability)
350
30
4 0
Opportunities
Threats
250
3
Textile production has the opportunity to
The largest threat to Kenyan textile are Asian
200
strengthen the cotton-textile-apparel value
competitors. Companies in China and India
15
2 0
change, of which at the moment only the apparel have lower input and transportation costs, so
100
part is competitive. A recent study reveals an
they are able to supply apparel firms worldwide
1
50
annual local demand at 3.8 percent, with local
with inexpensive fabric. Environmental concerns
0 0
production accounting for only 45 percent of the
also pose a threat to the industry. Firms in this
M K
a e
n n
a y
g a
ers P L
r o
of w
e e
s stion Snaps
als Te h
c o
h t
nic H
al ighest
Sk Les
illed otho
UnskTunis
illed ia
local market. The availability of EPZs and MUBs
sector use many chemicals for the processing
annual
av
Annual water costs w.orker
for s annualworkers
running wo
a rkers
cost of
cost of
provide investors a better infrastructure from
and dying of fabric. The absence of proper
water*
water*
*(5 = High
textile availability,
mill, in 1= low availability)
USD (thousands)
which to operate. A number of foreign textile
waste facilities could pose a danger to the areas
*Among Snapshot Africa countries
firms already operate within these zones and
surrounding textile sites.
Annual water costs for running a textile mill, in USD (thousands)
export their products to global markets. A variety
350
of products are currently produced including
300
yarn and knitted and woven fabrics.
250
200
150
100
50
0
Kenya
Lowest Snapshot Highest
Lesotho
Tunisia
annual
av.
annual
cost of
cost of
water*
water*
*Among Snapshot Africa countries
* Among Snapshot Africa countries
SNAPSHOT AFRICA - KENYA
SNAPSHOT AFRICA - KENYA
Apparel Sector
During the last two decades, trade in apparel has grown significantly and
Apparel Sector Survey Profiles
developing countries have made a considerable contribution to this growth. In this
period, apparel exports from developing countries increased sevenfold. According
Companies
57*
to UNCTAD, developing countries accounted for 76 percent of total world clothing
interviewed
exports in 2003, compared with a 1985 figure of only 8 percent. Total global apparel
Average Investment Characteristics
trade was USD 462 billion in 2003 and has grown at a compounded annual rate of
Ownership
37 % local owned
6.6 percent since 1990. Market leaders in apparel exports include China, EU, Turkey,
45 % joint
Mexico, India, the US and Indonesia. The expiration of the MFA in December 2004
ventures
has greatly affected global trade and investment in the apparel sector.
18 % completely
foreign owned
The clothing industry is labor-intensive and offers entry-level jobs for unskilled labor
Investment size
USD 4.1 million
in developed as well as developing countries. The majority of clothing is produced
Factory floor space
15,224 m²
from textiles and fabrics across a very wide range of products, materials, styles and
Number of
708
usage. There are many stages in the production of apparel such as pattern making,
employees
cutting and sewing, trimming, garment dyeing, ticketing, folding and packaging.
Sales
USD 5.9 million
The variations are unlimited and as fashions change and materials develop, new
Company exports
Casual wear, jeans,
garments are being developed all the time as well as being re-invented. Moreover,
sports wear, ethnic
it is a sector where relatively modern technology can be adopted even in poor
wear, uniforms,
countries at low investment costs. This feature of the industry has made it
shirts and
attractive as the first step towards industrialization for many poor countries such
bottoms, shoes,
underwear, socks,
as Bangladesh, Sri lanka, Viet Nam and Mauritius. Some of these countries have
jackets, sweaters
experienced a very high output growth rate in the sector.
* 13 firms also produced textile
With the disappearance of the global quota system, which is expected to further
consolidate production in a few super competitive countries, increased com-
petition for FDI is expected. Elimination of quotas has benefited China, though
increased fear of dumping of cheap Chinese apparel products has raised caution in
markets such as the EU and the US. From this perspective, Africa could still benefit
from a number of preferential trade agreements such as AGOA and the EU’s lomé
Accord. As pointed out by a Value Chain Study conducted by UNIDO, sub-Saharan
Africa currently lags behind other developing regions mainly due to poor trans-
portation and communications infrastructure. These factors are very important
to the functioning of apparel firms. Apparel exporters require ready access to
inputs and global markets, streamlined customs procedures and reliable transport
infrastructure. A number of countries are making an effort to both improve their
communications infrastructure and to develop EPZs, and firms have benefited
by establishing in these zones in countries such as Mauritius and Madagascar.
Apparel production in sub-Saharan African countries also suffers from a weak
cotton-textile-apparel value chain.
SNAPSHOT AFRICA - KENYA
Snapshot Africa Report
Motivation Graphs: Pg. 14 – 17
Figure 4: Breakdown of cost motivations reported by
Figure 5: Breakdown of quality motivations reported by
textile firms
textile firms
11%
16%
11%
20%
11%
20%
11%
14%
2%
5%
33%
5%
30%
11%
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
Apparel Brief
Snapshot Africa Report
• Before the decline of the textile industry in the early 1990s over 110 large scale
Fig Breakdown
ure 6: Breakof
d cost
own motivations
of cost motivations reported a
b p
y parel Fm
igaunru
e fa
7 c: tu
Br reer
a s
k dw
o ewre
n r
o ef gqis
u taelirteyd ,
mw
o ittih
v aatino i
n n
s srta
e lple
o d
rt eca
d pbayc ity to meet 85
Motivation Graphs: Pg. 14 – 17
reported by apparel firms
apparel firms
percent of
ap the
pare total
l firmnational
s
demand of 141.3 million square meters.
Figure 4: Breakdown of cost motivations reported by
Figure 5: Breakdo8w
% n of quality motivations repo •
rt eA
d c c
b o
y rding to the Gov10er
% nment, there are now just 55 apparel manufacturing
textile firms
textile firms
19%
firms, with 29 functioning under the Manufacturing
24%
Under Bond (MUB) scheme
10%
and 26 firms under the EPZ regime.
11%
16%
23%
11%
20%
7%
• A number of products are being produced within the EPZ including men’s cotton
11%
shirts, denim jeans, polyester nightwear, women’s knit tops, chino pants, knit
17%
20%
11%
bottoms, fleece jackets, children’s clothes, lingerie and sportswear.
3%
4%
• Government figures report that only 37 percent
29%
of apparel is imported, showing
14%
4%
32%
10%
2%
that there are opportunities for production to serve the local and regional
5%
Real estate
markets.
33%
General business environment
5%
30%
Water & power
11%
Access to markets and supplies
Wage levels
• Apparel manufactured
Re in
al esKenya
tate
is primarily exported to the US, but companies
Real estate
Transport
also serve the region
L a
o lc aC
l O
potM
en E
ti S
al A
to m
rec ar
rui k
t e
st t,
af fand export smaller quantities to the
General business environment
Water & power
Construction
Access to markets and supplies
UK.
Infrastructure
Telecommunications
Wage levels
Real estate
Living environment
Tariffs
Transport
Local potential to recruit staff
Tax
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
Breakdown of quality motivations
Figure 6: Breakdown of cost motivations reported by
Figureported
re 7: Breby
ak apparel
down o firms
f quality motivations reported by
apparel firms
apparel firms
8%
10%
19%
24%
10%
23%
7%
17%
3%
4%
4%
29%
32%
10%
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
SNAPSHOT AFRICA - KENYA
Comparative SWOT Analysis for Apparel
Kenya vs. Snapshot Africa
Labor market availability in the
Strengths
Weaknesses
apparel sector*
Good current export performance
Difficulty of sourcing local component inputs
Labor market availability in the apparel sector*
Increase in trade competitiveness
Weak rating on corruption perception
Kenya
Snapshot av.
5
low country risk rating
Unfavorable labor relations
Business start-up procedures are minimal
Poor availability of unskilled workers
4
low employment rigidity
High site lease costs for industrial land
3
Good availability of managers
2
Good availability of professionals
Good availability of technical workers
1
Good availability of skilled workers
Labor market availability in the apparel sector*
0
Kenya
Snapshot av.
low water costs
M anagers Professionals Technical
Skilled
Unskilled
5
workers
workers
workers
*(5 = High
4 availability, 1= low availability)
Opportunities
Threats
*(5 = High availability, 1= low availability)
The apparel sector has experienced significant
The largest threat to apparel operations in Kenya
International air freight rates (Regular ra
3
te for general cargo under 45kg (USD/kg)
growth due to improved market access
are created by dependence on foreign fabric.
Singapore Changi (SIN)
2
through AGOA. Exports to the USA increased
Supplies from Asia will no longer be eligible to
70
Tokyo Narita (NRT)
from USD 44 million in 2000 to USD 226
be used in AGOA exports starting in September
60
Los Angeles (LAX)
1
million in 2004. However, apparel operations
of 2007, creating high demand for textile exports
New York (JFK)
in Kenya are currently operating at less than
from AGOA countries, so Kenyan firms may find
50
0
Amsterdam Schiphol (AM S)
50 percent capacity, so there is much room
it difficult to obtain inputs.
40
M anagers Professionals Technical
Skilled
Unskilled
International air freight rates (Regular
for growth. Kenya has the potential for value
workers
workers
workers
30
chain advantages in producing customizable
rate for general cargo under 45kg
*(5 = High availability, 1= low availability)
smaller-scale orders of apparel for rush delivery
20
(USD/kg)
with unused productive machinery. Airfreight
10
rates from Kenya to the USA or Europe are
International air freight rates (Regular rate for general cargo under 45kg (USD/kg)
0
the second lowest among profiled countries,
South Sin K
gaepnoyrae Cha Sn
ngia (ps
SI h
No)t
Senegal
Tanzania
behind only South Africa, so shipping goods
Africa
av.
70
Tokyo Narita (NRT)
quickly to customers would be possible. There
60
Los Angeles (LAX)
are opportunities for the production of t-shirts
New York (JFK)
for export. Government figures report that 37
50
Amsterdam Schiphol (AM S)
percent of apparel are imported, illustrating
40
opportunities for production to serve the local
30
and regional markets.
20
10
0
South
Kenya
Snapshot
Senegal
Tanzania
Africa
av.
SNAPSHOT AFRICA - KENYA
SNAPSHOT AFRICA - KENYA
Horticulture Sector
The horticulture sector is defined as the production and marketing of highly per-
Horticulture Sector Survey Profiles
ishable products destined for fresh consumption, with relatively high-value per
unit. Average annual worldwide production and trade in horticultural goods (fresh
Companies
47*
fruits, leguminous vegetables, cut flowers, nuts, and spices) have grown steadily.
interviewed
From 1993-2002, world trade in fruits and vegetables increased by 37 percent to an
Average Investment Characteristics
estimated USD 75 billion. While production has risen steadily in most regions of
Ownership
51 % local owned
the world, an increasing share of this production growth has occurred in developing
21 % joint ventures
countries. Today, according to FAOSTAT, Asia is the leading exporter of fresh fruit
28 % completely
and vegetables (USD 607 million), followed by latin America (USD 408 million).
foreign owned
Sub-Saharan Africa’s export value is USD 89.6 million, behind the US (USD 205
Investment size
USD 4.9 million
million) and the EU (USD 96 million).
Size of site
195 ha
Number of
462
Among developing regions, Africa has shown relatively higher growth not only in
employees
the export growth of fruits and vegetables, but also in terms of the share of fruits
Sales
USD 18.7 million
and vegetables in the region’s total agricultural exports. In many African countries,
horticulture exports have become a bright spot with vegetable and fruit exports now
Company
Roses
exports
beans
ranking first in total sub-Saharan Africa agricultural exports. More than 60 percent
vanilla
of this volume comes from the Southern African Customs Union (SACU), with
gum arabic
Kenya’s in particular, a successful example. A number of other countries across
mangoes
Africa have moved aggressively in recent years in efforts to duplicate Kenya’s
tomatoes
success story and several have achieved some notable success in diversifying their
cashews
live plants
production and accessing export markets.
pineapples
citrus fruit
In export markets, supermarkets are increasingly playing an important role in the
banana
horticulture industry, particularly in the retail of fruits and vegetables. This trend,
baby corn
combined with the increased concern for food safety issues, is the force shaping
peppers
the new supply chain structure in the horticulture sector. There is heavier reliance
*13 firms also produced processed food
on fewer but trusted suppliers whose relationship is based on stringent and
detailed contracts. In some cases, this relationship may also involve technical and
other assistance. However, there has not yet been a trend for these supermarkets
and hypermarkets to become direct investors. In fact, the majority of horticulture
commodities in Africa today are produced by smallholders, who, in turn, depend
on medium-to large-scale agri-businesses to organize their produce for exports.
While the amount of FDI in the horticulture sector is not substantial compared
to other sectors, such as light manufacturing, it is a factor. In fact, FDI is behind
almost all the successful horticulture development stories in Africa, and continues
to play an important role. Opportunities are sought by entrepreneurs, particularly
in the final-market country, who see climate and other production advantages in
Africa. In the horticulture sector there appear to be export opportunities in the
growth in demand for high quality pre-packed vegetables. An advantage for Africa
is that these industries require a combination of labor-intensive activities such as
pre-packaging work, and lower labor costs. Africa’s position with regard to fresh
cut flowers, starting material for cut flowers (seeds, young plants, cuttings, etc.)
and pot plants, is currently strong. In particular, starting material presents good
opportunities because of its relatively high levels of labor intensity, which now
makes it impossible to produce it in Europe.
For potential investors, in addition to the climatic requirements, good logistics in
order to comply with just-in-time-and-shape delivery required by buyers is critical.
Equally important is the availability of inputs such as pesticides, fertilizers, and
packaging materials. Market access questions will be determined by the ability to
comply with trade standards rather than tariff levels.
SNAPSHOT AFRICA - KENYA
Horticulture Brief
• Europe is the main importer of Kenya’s fresh horticultural products with countries
like the UK, Germany, France, Switzerland, Belgium, the Netherlands and Italy
Breakdown of cost motivations
leading the way. Other importers include Saudi Arabia and South Africa.
Figure 8: Breakdown of cost motivations reported
Figure 9: Breakdown of quality motivations
reported by horticulture firms
by horticulture firms
reported by horticulture firms
• Flowers accounted for 53 percent of horticulture export volume in 2004, followed
7%
by vegetables (35 percent)
8%
and fruits (12 percent). Total export volume in 2004
20%
18%
totaled 166,100 tons valued at USD 600 million.
16%
16%
• Foreign investment stems from major global competing flower producers such
6%
as the Netherlands, Israel and the UK.
3%
8%
• More than 1o
3 t
% her East African countries, Kenyan horticulture producers tend to
directly sell to brand name supermarket
31 chains.
%
26%
14%
• Kenyan horticulture 1firms
4%
employ about 1,500 workers, of which 70 percent are
permanent employees and 30 percent are casual labor.
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
• Within Kenya, horticulture firms look for sites with access to roads that lead to
Real estate
Transport
airports and sea ports.
Local potential to recruit staff
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
Figure 10: Breakdown of cost motivations reported Figure 11: Breakdown of quality motivations
by fBreakdown
ood and b of
ev quality
erage p motivations
rocessing firms
reported by food and beverage processing firms
Figure 8: Breakdown of cost motivations reported
Figure 9: Breakdown of quality motivations
reported by horticulture firms
by horticulture firms
reported by horti 1c0%
ulture firms
8%
16%
18%
7%
8%
13%
20%
18%
7%
18%
16%
16%
10%
6%
3%
3%
8%
23%
13%
8%
12%
31%
43%
11%
26%
14%
14Re
% al estate
General business environment
Water & power
Access to markets and supplies
Real estate
Wa
General ge
bus lieve
nes ls
s environment
Real estate
Water & power
Acce T
s ra
s t n
o s p
m oart
rkets and supplies
Wage levels
Local potential to recruit staff
Real C
es otn
at setruction
Transport
Local T
peole
t c
e o
nt m
ialm
t u
o nric
e ati
ru ot n
s s
Infrastructure
taff
Construction
Infras T
t a
ru ri
c ftfs
ure
Living environment
Telecommunications
LivingT
a
e x
nvironment
Tariffs
Tax
Figure 10: Breakdown of cost motivations reported Figure 11: Breakdown of quality motivations
by food and beverage processing firms
reported by food and beverage processing firms
10%
SNAPSHOT AFRICA -
8%
KENYA
16%
18%
13%
7%
18%
10%
3%
23%
8%
12%
43%
11%
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Telecommunications
Infrastructure
Tariffs
Living environment
Tax
Comparative SWOT Analysis for Horticulture
Kenya vs. Snapshot Africa
International sea freight rates to
Strengths
Weaknesses
Rotterdam in USD (thousands) per
Good current export performance
Difficulty of sourcing local raw material inputs
40 foot container
Increased trade competitiveness
Difficulty of sourcing local component inputs
Abundance of arable land
Difficulty of sourcing local equipment/ chemical
International sea freight rates to Rotterdam in USD (thousands) Per 40 foot container
inputs
Standard
Refrigerated
7
Good country credit rating
Poor rating on corruption perception
6
low country risk rating
Unfavorable labor relations
5
Business start-up procedures are minimal
High wage rates for professionals
4
low employment rigidity
High wage rates for technical workers
3
2
low shortage of water supply
High costs for purchasing farm land
1
low air transport costs for shipments to
Amsterdam
0
Kenya
Snapshot av. M adagascar M ozambique
Tanzania
low container costs for sea transport to
International sea freight rates to Rotterdam in USD (thousands) Per 40 foot container
Rotterdam
Standard
Refrigerated
Availability of arable land (thousands square kilometers)
7
66
Opportunities
Threats
55
4
Kenya enjoys tropical and temperate
International competition is a major threat to
4
climate conditions, where a variety of fruits,
the horticulture sector of Kenya. These countries
3
3
vegetables and flowers can be planted year
include Cote d’Ivoire, Morocco, Zimbabwe,
2
round. Horticultural products produced
South Africa and Cameroon. Expansion into
21
in Kenya include snow peas, sugar snaps,
the USA market is hampered by a lack of direct
1
baby vegetables, beans, tomatoes, potatoes,
flights from Kenya to the USA.
A 0
vailability of arable land (thousands
Kenya
Snapshot av. M adagascar M ozambique
Tanzania
avocadoes, mangoes and pineapples. Since
0
square kilometers)
the sector is so well developed, value added
Kenya
Lowest
Highest
M ozambique
Tanzania
availability*
availability*
products can also be developed such as
Availability of arable land (thousands square kilometers)
high quality packaging material. Kenya’s
*Among
6
Snapshot Africa countries
horticulture sector is one of the major producers
and exporters of horticulture in the world.
5
Opportunities in Kenya’s horticulture sector exist
4
in expanding operations to include exports to
non-traditional markets currently underserved
3
or not served by Kenya. These include countries
2
in East Asia such as: Japan, China, Taiwan, and
Australia. Operating costs, though modest,
1
include high land prices for industrial and farm
0
land. According to UNCTAD, Kenya has no more
Kenya
Lowest
Highest
M ozambique
Tanzania
than 1 percent of the EU-15 market share for
availability*
availability*
edible vegetables and 0.1 percent in edible fruits.
*Among Snapshot Africa countries
* Among Snapshot Africa countries
SNAPSHOT AFRICA - KENYA
0
SNAPSHOT AFRICA - KENYA
Food and Beverage Processing Sector
The food and beverage processing sector refers to the manufacturing, processing
Food and Beverage Processing
and preservation of meat, fish, fruit, vegetables, oils and fats; manufacture of dairy
Sector Survey Profile
products; manufacture of grain mill products, starches and starch products and
prepared animals feeds; manufacture of other food products (e.g. bread, sugar,
Companies
52*
chocolate, pasta, coffee, nuts and spices); and the manufacture of bottled and
interviewed
canned soft drinks, fruit juices, beer, wines, etc.
Average Investment Characteristics
Ownership
37 % local owned
Global market growth for processed food and beverages has been strong in recent
25 % joint ventures
years, with sales totaling an estimated USD 3.2 trillion, or about three-fourths of
38 % completely
total world food sales. Africa is no exception. Agro-processing is one of the most
foreign owned
significant manufacturing activities in Africa. In fact, agribusiness activity, of which
Investment size
USD 38.1 million
food processing represents a large share, accounts for approximately one-fifth (or
Factory floor
35,795 m²
USD 70 billion) of the region’s GDP and just under half of the region’s value-added
space
in manufacturing and services.
Number of
518
employees
Despite strong production and sales growth of processed foods and beverage
Sales
USD 52.9 million
in recent years, growth in trade has been slow, at about 6 percent of sales. The
Company
Dried fruits and
presence of tariff escalation and growing use of trade remedy measures (such
exports
vegetables
as antidumping and countervailing duties and safeguard measures) are partly to
bottle beverages and
blame. Such mechanisms favor trade in raw commodities at the expense of pro-
fruit juices
cessed products, reflecting countries’ efforts to encourage domestic processing.
palm oil
As a result, firms looking for access to foreign markets often opt to make foreign
peanut oil
sugars
direct investment. Market saturation at home and the search for higher profit
jellies and jams
margins in new underserved markets is pushing food manufacturers to seek
powdered milks
overseas markets. These companies are looking to capitalize on increased local
biscuits
demand for higher value foods, a trend driven by rising incomes and increased
cookies
urbanization. At the same time, consumer-driven changes are increasingly pushing
candy
canned fruits and
food suppliers to meet consumer demand and preferences at a local level. This
vegetables
requires food suppliers to be capable of tailoring their products to the unique char-
*13 firms also produced horticulture
acteristics of consumer demands in each market that they serve, for which FDI
offers a better tool than exports.
The largest food companies such as Nestlé, Kraft, Unilever, Coca-Cola and Pepsi
already have a strong presence across the developing world. In Africa alone, the
Coca-Cola Co. has more than 100 bottling and canning plants; Nestlé has 27
factories supplying African consumers with a wide range of products including
powdered milk, soluble coffees, bottled water, breakfast cereals, chilled dairy and
ice cream and infant nutrition. Unilever is currently operating in 13 countries with
more than USD 2 billion sales annually. In recent years, South African firms in
particular have expanded into the region with new retail food formats, fast food
outlets, and pan-African processed food brands. Given the importance of the size
of the local or regional market, formulating regional trade blocs is one way to
enhance attractiveness to investors. According to the UN’s Food and Agriculture
Organization (FAO), the East African milk market alone is due to double by 2030
to 475 million metric tons. Fisheries is a constantly expanding sub-sector, espe-
cially in East Africa, as the region is endowed with some of the largest freshwater
lakes and abundant fishery resources, including the Nile perch, the most widely
processed fish for export in the region. From 1995-2001, exports of fish and fish
products from the EAC nearly tripled in value. In West Africa, Ghana successfully
tapped into the endowment of fish supply and attracted FDI: Starkist’s investment
in canned tuna manufacturing tripled Ghana’s export capacity of processed tuna.
SNAPSHOT AFRICA - KENYA
Figure 8: Breakdown of cost motivations reported
Figure 9: Breakdown of quality motivations
by horticulture firms
reported by horticulture firms
7%
8%
20%
18%
16%
16%
6%
3%
8%
13%
31%
26%
14%
14%
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
Food and Beverage Processing Brief
• Food and beverage processing in Kenya usually centers on the processing of
milk, canned meats, vegetables and fruits, and sugar.
Breakdown of cost motivations
reported by food and beverage
• Kenyan food processing companies serve local, regional, and international
Figu processing
re 10: Breafirms
kdown of cost motivations reporte markets,
d Figur including
e 11: Brea disaster
kdown orelief
f quaagencies.
lity motivations
Figure 8: Breakdown of cost motivations reported
by
Fi f
g o
u o
r d
e a
9:n d
Br b
e e
a v
k e
d roag
w e
n p
ofr o
q cueaslistin
y g
m fi
o rtim
v s
ations
reported by food and beverage processing firms
by horticulture firms
reported by horticulture firms
• The average Kenyan food and beverage processing operation employs 615
10%
8%
16%
people and is located on two hectares
18% of land.
10%
7%
16%
8%
18%
13%
20%
• Food and beverage operations in Kenya generally import all of their capital
7%
18%
16%
16%
equipment, but are able to source about 60 percent of operational inputs
18%
7%
locally.
6%
10%
3%
3%
• Within Kenya, food and beverage processing companies look for industrial sites
8% 3%
13%
23%
with easy road access to ports and prefer to locate near industrial towns that
8%
12%
31%
have a large labor supply.
23%
43%
12%
11%
26%
14%
Re
1 a
4 l
%estate
• Kenya is the largest exporter of fruits and vegetables in East Africa. There exists
11%
General business environment
Water & power
potential to add value to those products by canning, freezing, and packaging
Re Real estate
al estate
Access to markets and supplies
General business environment
Wage levels
them according to retail customer specifications.
Wa Water & power
ter & power
Real estate
Access to markets and supplies
Wa Wage levels
Transport
ge levels
Real estate
Local potential to recruit staff
TraTransport
Construction
nsport
• Processing activities that have recently contributed to the sector’s growth are
Local potential to recruit staff
Infrastructure
Co Construction
Telecommunications
nstruction
Infrastructure
improvements in the milk processing environment, fish processing, oil pro-
Tel Telecommunications
Tariffs
Living environment
ecommunications
Living environment
duction, sweets and biscuits and animal feed. Opportunities also exist in the
Ta Tariffs
Tax
riffs
processing of sugar where current growth rates and refining capacity do not
Ta Tax
x
meet local demands.
• Kenya is also uniquely positioned for exports in this sector in that it has the
Breakdown of quality motivations
HACCP -approved food processing factories required for accessing the US and
reported by food and beverage
EU markets.
processing firms
Figure 10: Breakdown of cost motivations reported Figure 11: Breakdown of quality motivations
by food and beverage processing firms
reported by food and beverage processing firms
10%
8%
16%
18%
13%
7%
18%
10%
3%
23%
8%
12%
43%
11%
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Telecommunications
Infrastructure
Tariffs
Living environment
Tax
SNAPSHOT AFRICA - KENYA
Comparative SWOT Analysis for Food and Beverage Processing
Kenya vs. Snapshot Africa
Labor market availability in the food
Strengths
Weaknesses
and beverage processing sector*
Good current export performance
Weak rating on corruption perception
Ease of sourcing local raw material inputs
Unfavorable labor relations
Labor market availability in the food and beverage processing sector*
Good country credit rating
Kenya
Snapshot av.
5
low country risk rating
4
Minimal business start-up procedures
low employment rigidity
3
Good availability of managers
2
Good availability of professionals
1
Good availability of technical workers
Labor market availability in the food and beverage processing sector*
Kenya
Snapshot av.
Good availability of skilled workers
05
M anagers Professionals Technical
Skilled
Unskilled
Good availability of unskilled workers
workers
workers
workers
4
low number of yearly blackouts
*(5 = High availability, 1= low availability)
3
low number of yearly brownouts
*(5 = High availability, 1= low availability)
low shortage of water supply
Total
2 annual cost to employer per function in USD (millions)
M anagement
Professional
Technical
low wage rates for managers
1
Skilled
Unskilled
3.0
low wage rates for technical workers
0
2.5
M anagers Professionals Technical
Skilled
Unskilled
workers
workers
workers
2.0
Opportunities
Threats
*(5 = High availability, 1= low availability)
Total annual cost to employer per
Kenya is the largest exporter of fruits and
What threatens investment is competition.
1.5
function in USD (millions)
vegetables in East Africa. There exists great
Within its own market, Kenya has the ability to
1.0
potential to add value to those products by
fill local demand for processed products, though
Total annual cost to employer per function in USD (millions)
M anagement
Professional
Technical
canning, freezing, and packaging them according cheaper imports could discourage investment.
0.5
Skilled
Unskilled
to retail customer specifications. Indeed,
Droughts and fires could affect the availability of
3.0
firms in both the horticulture and processing
local inputs.
0.0
2.5
Kenya Lowest labor
Snapshot av. Highest
TanzaniaM ozambique
sectors have begun to vertically integrate these
costs*
labor costs*
operations in order to increase profits and
*Among
2.0
Snapshot Africa countries
expand exports. Processing activities that have
recently contributed to the sector’s growth
1.5
are improvements in the milk processing
1.0
environment, fish processing, oil production,
sweets and biscuits and animal feed. Currently,
0.5
Kenya produces more milk than it can consume.
0.0
This provides investment opportunities to
Kenya Lowest labor
Snapshot av. Highest
TanzaniaM ozambique
produce powdered milk, cheese, butter, or
costs*
labor costs*
long life (UTH) milk to serve the local and
*Among Snapshot Africa countries
global market. Opportunities also exist in the
processing of sugar where current growth and
* Among Snapshot Africa countries
refining does not meet local demands. Kenya
is also uniquely positioned for exports in this
sector in that it has the HACCP-approved food
processing factories required for accessing the
USA and EU markets. Transportation costs to
Europe are also very low for Kenyan exports.
SNAPSHOT AFRICA - KENYA
SNAPSHOT AFRICA - KENYA
Shared Services (Call Centers) Sector
Call center operation is a segment within the outsourcing trend. Outsourcing
Shared Services Sector Survey
occurs when one company delegates responsibility for performing a function or
Profile
series of tasks to another company. Outsourcing services span a wide range – from
call center functions (outbound tele-marketing campaigns, data-cleaning, surveys,
Companies
51
help desks, inbound services) to business process functions such as fulfilling
interviewed
financial, insurance, healthcare, human resource, tax compliance functions, data
Average Investment Characteristics
conversion, and IT services. In sub-Saharan Africa, where the sector is still nascent,
Ownership
31 % local owned
outsourcing is almost exclusively in call center operation, with the exception of
25 % joint ventures
South Africa. Offshore outsourcing now represents a USD 100 billion market that
44 % completely
is growing at more than 30 percent per annum. The majority of current demand
foreign owned
for offshore outsourcing services comes from developed countries: the United
Investment size
USD 1.8 million
States and Canada (15.9 percent) and Western Europe (44.8 percent). The primary
Building floor
1,093 m²
countries exporting services to satisfy this demand include Ireland, India, and
space
Canada. In sub-Saharan Africa, South Africa and Mauritius are the only countries
Number of
135
that have begun to emerge on the radar screen of investors, but their estimated
employees
market size is still miniscule compared to competitors around the world.
Sales
USD 12,7 million
Behind the rapid growth in offshore outsourcing are the improved quality and lower
costs of telecommunications and Internet infrastructure. The development of the
industry has led to an increased general knowledge and experience in offshore out-
sourcing. This means there is now less risk associated with including offshore out-
sourcing in the evaluation and implementation process of a company’s business
plan. As a consequence, there is international competitive pressure to include
offshore outsourcing as a component of overall business strategy to reduce cost
and/or to increase productivity.
The factors making a foreign country an attractive base for offshore outsourcing
services, according to an index developed by A.T. Kearney, are the following:
financial structure, people skills and availability, and business environment. The
market growth of offshore outsourcing does not necessarily lead to higher levels
of FDI in the industry, as the relationship between offshore outsourcing service
providers and their clients is generally contractual. Nevertheless, there is plenty of
opportunity for FDI growth.
Trends in offshore outsourcing indicate a promising future. As with any maturing
market, offshore outsourcing moves up the value chain, reflecting increased levels
of provider competence and confidence among their customers. Customers will
multi-source from more than one provider (and country), depending upon type
of services required, costs and risks. Due to increased competition and risk man-
agement, providers extend their services offerings (e.g., call-center services extend
to back-office services) and offer new value-added services. Mature offshore markets
then outsource to new, lower cost countries or locations within the same country.
Higher value outsourcing services (IT and financial) migrate to those countries
with greater protection of intellectual property and privacy. Increased demand and
competition for offshore outsourcing services is likely to lead to rising labor costs,
resulting in decreased service levels and the tendency to move offshore to lower
cost countries.
SNAPSHOT AFRICA - KENYA
Shared Services (Call Centers) Brief
• The Kenyan shared service sector is still in its early stages, but it is more
Breakdown of cost motivations
developed and widespread than in most sub-Saharan countries and already has
reported by shared services (call
third-party service providers.
centers) firms
Figure 12: Breakdown of cost motivations reported by
Figure 13: Breakdown of quality motivations reported
• Capital equipment such as computers, routers, smart cards, and modems are
shared services (cal centers) firms
by shared services (cal centers) firms
imported from Europe. Some software is authored and produced locally, but
8%
most is imported.
1%
16%
11%
22%
• Within Kenya, shared service operations look for office buildings with existing
18%
6%
reliable infrastructure
17%
connections and security provisions.
• Kenyan skilled workers and managers are often hired away by new companies
5%
emerging in this sector locally or in other sub-Saharan countries.
3%
25%
• While most countr
19ie
% s have barely emerging in-house service departments,
Kenyan firms’ clients include banks, government, hospitals, insurance com-
43%
panies, travel agencies, mobile
6 %telecommunications companies and individual
Real estate
consumers in Africa, Europe,
General
and
busines North
s enviro America.
nment
Water & power
Access to markets and supplies
Wage levels
• Opportunities in this sector
Real esta lie
te primarily with local entrepreneurs. Starting with
Transport
Local potential to recruit staff
Construction
small local and overseas clients, Kenyans are best poised to demonstrate the
Infrastructure
Telecommunications
capabilities of the sector. Kenya could also envisage becoming a call center base
Living environment
Tariffs
for South African firms since Kenya’s operating environment is drastically less
Tax
expensive than that of South Africa’s.
Breakdown of quality motivations
Figu reported
re 14: Brby
ea shared
kdown services
of cost (call
motivations reported by
Figure 15: Breakdown of quality motivations reported
Figure 12: Breakdown of cost motivations reported by
T
Foiu
g rure 13: Breakdown of quality motivations reported
centers)
ism (Ho firms
tels) firms
by Tourism (Hotels) firms
shared services (cal centers) firms
by shared services (cal centers) firms
1% 6%
11%
8%
3%
1%
16%
11%
22%
7%
32%
16%
18%
6%
41%
17%
15%
1%
5%
3%
25%
14%
19 29%
%
21%
3%
43%
Real esta
6 te
%
General business environment
Real estate
Water
General & p
busi owe
nes r
s environment
Access to markets and supplies
Water & power
Ac W
c a
esgse t le
o ve
m ls
arkets and supplies
Real estate
Wage levels
Re T
alra
e n
s s
t p
atoert
Local potential to recruit staff
Transport
Construction
Local potential to recruit staff
Infrastructure
Construction
Telecommunications
Infrastructure
Living environment
Telecommunications
Tariffs
Living environment
Tariffs
Tax
Tax
SNAPSHOT AFRICA - KENYA
Figure 14: Breakdown of cost motivations reported by
Figure 15: Breakdown of quality motivations reported
Tourism (Hotels) firms
by Tourism (Hotels) firms
1% 6%
11%
3%
7%
32%
16%
41%
15%
1%
14%
29%
21%
3%
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
Comparative SWOT Analysis for Shared Services (Call Centers)
Kenya vs. Snapshot Africa
Total annual cost to employer per
Strengths
Weaknesses
function in USD (millions)
Good country credit rating
Difficulty of sourcing local equipment inputs
low country risk rating
Poor rating on corruption perception
Total annual cost to employer per function in USD (millions)
Minimal business start-up procedures
Unfavorable labor relations
M anagement
Professional
Technical
Skilled
Unskilled
low employment rigidity
Poor availability of unskilled workers
1.3
1.2
1.1
Ease of finding workers with a good command of Expensive high-bandwidth Internet usage
1.0
the official language
charges
0.9
0.8
Good availability of managers
0.7
0.6
0.5
Good availability of technical workers
0.4
Total annual cost to employer per function in USD (millions)
0.3
Good availability of skilled workers
0.2
M anagement
Professional
Technical
0.1 Skilled
Unskilled
low wage rates for managers
1.3 0.0
1.2
Kenya
Snapshot
Uganda
Ghana
Tanzania
av.
low wage rates for professionals
1.1
1.0 *Among Snapshot Africa countries
low wage rates for technical workers
0.9
0.8
low wage rates for skilled workers
0.7
*Among Snapshot Africa countries
0.6
low wage rates for unskilled workers
0.5
0.4 Annual Office rental costs for a 1,000 square meter suburban office space (in USD/thousands)
low rental costs for suburban offices
0.3
200
0.2
180
0.1
160
0.0
140
Opportunities
Threats
Kenya
Snapshot
Uganda
Ghana
Tanzania
120
av.
100
A well-trained work force with competitive wages Threats stem from competing countries with
*Among 80
Snapshot Africa countries
endows Kenya with some of the best potentials
a better IT infrastructure and a well-trained
Annual office rental costs for a 1,000
60
for investment in this sector. Opportunities in
English-speaking work force. Increasing electrical
40
square meter suburban office space
this sector lie primarily with local entrepreneurs.
blackouts could also be detrimental to the
20
(in USD/thousands)
Starting with small local and overseas clients,
development of the sector.
0
Kenya
Second
Snapshot
Highest
Tanzania
Kenyans are best poised to demonstrate the
lowest
av.
rental
Annual Office rental costs for a 1,000 square meter suburban office space (in USD/thousands)
rental
costs
capabilities of the sector. Kenya could also
costs
200
envisage becoming a call center base for
180
South African firms since Kenya’s operating
160
environment is drastically less expensive. Other
140
markets would include European countries and
120
the USA. In addition, there have been recent
100
commitments by the government to overhaul
80
Kenya’s IT sector in the coming years
60
40
20
0
Kenya
Second
Snapshot
Highest
Tanzania
lowest
av.
rental
rental
costs
costs
SNAPSHOT AFRICA - KENYA
SNAPSHOT AFRICA - KENYA
Tourism (Hotels) Sector
After a drop in tourism caused by the events of September 11, 2001, and other
Tourism Sector Survey Profile
natural disasters, global tourism has seen a rebound since 2004. According to the
UN World Tourism Organization (UNWTO), the number of international tourist
Companies
48
arrivals in 2005 is estimated at 808 million, up from 766 million in 2004. The
Interviewed
UNWTO is expecting tourism arrivals to double by 2010 and reach 1.56 billion by
Average Investment Characteristics
2020. Globally, tourism accounts for roughly 35 percent of exports of services and
Ownership
23 % local owned
over 8 percent of exports of goods, and is the world’s largest employer.
27 % joint ventures
50 % completely
According to the UNWTO, sub-Saharan Africa saw the strongest growth in tourism
foreign owned
in 2005 estimated at 13 percent, with particularly remarkable results for Kenya
Investment size
USD 14.6 million
(26 percent between January and October compared with the same period of the
Hotel floor
17,789 m²
previous year), and Mozambique (37 percent Jan.-Sept.). South Africa (11 percent
space
Jan.-Aug.) as well as Seychelles (7 percent) and Mauritius (6 percent), all improved
Number of
215
on their 2004 results. Tourism is often a leading generator of foreign exchange in
employees
African countries. Total tourist expenditure in Africa was estimated at about USD
Sales
USD 5.3 million
33 million in 2004, and is anticipated to increase to USD 47 million by 2010 and to
USD 77 million by 2020.
Sub-Saharan Africa is heavily endowed with exceptional attractions for the local and
international tourism markets. These include natural resources, biodiversity and a
number of historical heritage sites. The greatest numbers of tourist arrivals to sub-
Saharan African countries were visitors from other countries within the region.
Nonetheless, arrivals from Europe, Asia and North America are also growing.
Europeans tend to visit single countries, while North American travelers usually
visit several countries as part of a circuit tour. While North Americans number
fewer than Europeans, their expenditure tends to be higher. Asians form a smaller
part of African tourism, but are growing in importance.
African countries offer unique opportunities for investment in safari, beach,
adventure, cultural and ecotourism holidays as well as opportunities for business
travel. At the early stages of investment, anchor or magnet projects create the
base for future investment. Some cities have become hubs for tourism investment
with a full complement of hotels catering to local and foreign tourists. These
investments are typically made by foreign investors, but often with local partners
who are skilled at negotiating with government. These anchor – or greenfield -
investments require financial engineering suited to the hotel sector. Ownership
and operations are often separated, with one company owning the building and
an operating company managing or leasing the property. Ownership companies
are suited to local and foreign investment with substantial equity (20-50 percent
of investment) and long-term loans consistent with real estate financing. In this
context, investors look for the additional comfort that guarantees can offer on the
equity and associated long-term lending.
Most international chains, on the other hand, are management companies pro-
viding skilled management services. A limited number will also take equity positions
as a demonstration of goodwill and a few are exploring long-term investment as a
new strategy. Anchor projects of course also attract the smaller investments char-
acteristic of tourism investment – small guest houses, new restaurants and vastly
improved travel agency and tour operator services. Financing of tourism SMEs
conforms to schemes for SMEs in general and typically does not lend itself as well
to guarantees – although technical support is often a feature of such operations
and some countries are experimenting with credit and guarantee schemes.
SNAPSHOT AFRICA - KENYA
Figure 12: Breakdown of cost motivations reported by
Figure 13: Breakdown of quality motivations reported
shared services (cal centers) firms
by shared services (cal centers) firms
8%
1%
16%
11%
22%
18%
6%
17%
5%
3%
25%
19%
43%
6%
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
Tourism (Hotels) Brief
Breakdown of cost motivations
• Kenya received 1,146,100 international visitors in 2003 of which vacation seekers
Figure 12: Breakdown of cost motivations reported by
F
F iiggureported
urre
e 1143:: BBrby
re
ea tourism
ak
k ddoowwnn (hotels)
o
o ff cqousatl ifirms
m
ty o tmivoatitivoantiso rnesp roerpteoartcd ecbdoy u ntedFi fgour e6 01 5p: eBrceeankt,d b
o u
w s
n i n
o e
f sqs
u v
alistit
y o
r
ms
ot1i6
v ap
ti eorc
n e
s nrte, pa
o n
rtde t
d r ansit visitors
shared services (cal centers) firms
T
b oy usrihsam
re (dH soetrevlisc) efsi r(mcasl centers) firms
19 percen
bt.y M
Toousrti sar
mr i(ve
H oftro
el m
s) fG
ir er
m m
s any followed by the UK, Italy, the US and
France.
8%
1%
16%
11 1
% % 6%
11%
3%
22%
• Foreign ownership of hotels accounts for around 18 percent, of which 14.5
7%
18%
6%
percent is non-African. The hotel occupancy ra
32% te in 2002/2003 was on average
1 1
7 6%
%
50.1 percent (75.8 percent in high season and 27.6 percent in low season).
41%
15%
1%
• Within Kenya, tourism operations prefer to locate in areas near primary natural
5%
tourist attractions despite less developed infrastructure.
3%
25%
19%
• Kenyan hotels source more than 90 percent of food and beverage inputs locally,
14%
43%
29%
21%
6%
3%
but import all capital equipment. Hotel furnishings are obtained primarily from
Real estate
General business environment
Europe, but some hotels buy local products to foster supportive relations with
Real estate
Water & power
Access to markets and supplies
local residents.
General business environment
Water & power
Access to markets and supplies
Wage levels
Re W
al a
e g
stea lteevels
Real estate
Transport
LocTara
l pnostpeonrt
tial to recruit staff
• A recent investment Guide for UNCTAD highlights a number of tourism opportu-
Local potential to recruit staff
Construction
Inf C
rasotn
rusctru
u c
retion
nities in the sub sectors of conferences, sports, retirement, ecotourism, cultural
Telecommunications
Infrastructure
Livi T
n e
g le
e c
n o
vi m
ro m
n u
m neic
ntations
and cruise tourism both
Tariffs
Livi on
ng e the
nviro coast
nment and around lake Victoria.
Tariffs
Tax
Tax
• The government is looking to diversify tourism by targeting Asian countries
and new direct flights to Hong Kong via Bangkok seek to encourage this trend.
Recent upgrades to the airports aim to increase arrival capacity from 2.5 million
to 5.5 million passengers per year.
Breakdown of quality motivations
Figure 14: Breakdown of cost motivations reported by
Figu reported
re 15: Brby
ea tourism
kdown (hotels)
of qualitfirms
y motivations reported
Tourism (Hotels) firms
by Tourism (Hotels) firms
1% 6%
11%
3%
7%
32%
16%
41%
15%
1%
14%
29%
21%
3%
Real estate
General business environment
Water & power
Access to markets and supplies
Wage levels
Real estate
Transport
Local potential to recruit staff
Construction
Infrastructure
Telecommunications
Living environment
Tariffs
Tax
0
SNAPSHOT AFRICA - KENYA
Comparative SWOT Analysis for Tourism (Hotels)
Kenya vs. Snapshot Africa
Number of direct weekly flights to
Strengths
Weaknesses
EBP countries from Europe and Asia
Good country credit rating
Weak rating on corruption perception
low country risk rating
Unfavorable labor relations
Number of direct weekly flights to EBP countries from Europe and Asia
Business start-up procedures are minimal
lack of direct flights to US
50
45
low rigidity of employment
Expensive sales price for hotel land
40
Number of direct weekly flights to Europe
Good quantity of direct flights to Europe
High hotel construction costs
35
Number of direct weekly flights to Asia
30
Good quantity of direct flights to Asia
25
20
High annual passenger arrival rate
15
Good availability of managers
10
5
Good availability of technical workers
0
Good availability of skilled workers
Kenya
Senegal Tanzania Madagascar Uganda Mozambique
Good availability of unskilled workers
Labor market
Number of availability
direct weekly in the tourism
flights to EBP (hotels) sector*
countries from Europe and Asia
Ease of finding workers with a good command of
Kenya
Average
505
the official language
45
4
low wage rates for managers
40
Number of direct weekly flights to Europe
35
Number of direct weekly flights to Asia
low wage rates for technical workers
3
30
low wage rates for skilled workers
252
20
low wage rates for unskilled workers
15 1
10
50
Labor market availability in the
Opportunities
Threats
0
M anagers Professionals Technical
Skilled
Unskilled
tourism (hotels) sector*
Kenya
Senegal Tanz w
a o
ni rk
a e
Mrs
adaga w
s o
c r
a k
r ers
Ugandawo
Mrk
o ezrasmbique
Kenya already has one of the strongest tourist
Threats to tourism in Kenya arise from other
*(5 = High availability, 1= low availability)
sectors in sub-Saharan Africa; and tourism
sub-Saharan countries that offer similar tourist
Labor market availability in the tourism (hotels) sector*
grew by 31 percent in 2004/2005. Further
attractions, but in a much safer environment.
Kenya
Average
opportunities for growth will involve diversifying
The biggest source of new competition is
5
the type of experience that tourists can enjoy in
Tanzania. local security issues and travel
Kenya. Eco-tourism will likely target the same
advisories could also threaten the tourism
4
natural resources as those already served by high industry.
3
volume tourism, but in more remote corners.
Business tourism is also an area that provides
2
opportunities for growth. The Government is
looking to diversity tourism by targeting Far
1
Eastern countries and new direct flights to Hong
Kong via Bangkok seek to encourage this trend.
0
Business opportunities exist in catering to this
M anagers Professionals Technical
Skilled
Unskilled
workers
workers
workers
tourism market. A recent investment Guide
for UNCTAD highlights a number of additional
*(5 = High availability, 1= low availability)
opportunities, such as: conference tourism,
sports tourism, retirement tourism, ecotourism,
*(5 = High availability, 1= low availability)
cultural tourism and cruise tourism, both on the
coast and around lake Victoria; and possible
investment exist in serving these new circuits.
Recent airport upgrades will seek to increase
arrival capacity from 2.5 million to 5.5 million
passengers per year.
SNAPSHOT AFRICA - KENYA
SNAPSHOT AFRICA - KENYA
Appendices
I. Acronyms and Abbreviations
II. Data Definitions and Sources
III. Tables and Findings
IV. The Kenya Investment Authority (KIA)
SNAPSHOT AFRICA - KENYA
Appendix I. Acronyms and Abbreviations
AGOA
American Growth and Opportunity
IPI
Investment Promotion Intermediary
Act
IPZ
Industrial Processing Zones
API-Mali
Agence de Promotion des
ISP
Internet Service Provider
Investissement Mali
IT
Information Technology
APIX
Agence de Promotion des
JV
joint-venture
Investissements et des Grands
KIA
Kenya Investment Authority
Travaux
kVA
Kilovolt-ampere
ATC
Agreement on Textiles and Clothing
kWh
Kilo-Watts hour
av.
Average
lNDC
lesotho National Development
CFA
West African Franc
Corporation
CIS
Community of Independent States
MFA
Multi-Fiber Arrangement
CITES
Convention on International Trade in
MIGA
Multilateral Investment Guarantee
Endangered Species of Wild Fauna
Agency
and Flora
MNC
multi-national corporation
COMESA Common Market for Eastern and
MUB
Manufacturing Under Bond
Southern Africa
NDC
National Development Council
CPI
Centro de Promoção de
OECD
Organization for Economic Co-
Investimentos Mozambique
operation and Development
CTI
Computer Telephony Integration
PABX
Private Automatic Branch Exchange
DTIS
Diagnostic Trade Integration Study
PAD
Port autonome de Dakar
EAC
East African Community
PATI
Priority Areas for Tourism Investment
EASSy
Eastern Africa Submarine Cable
PPP
Purchasing Power Parity
System
SACU
Southern African Customs Union
EBA
Everything But Arms
SADC
Southern African Development
EBP
Enterprise Benchmarking Program
Community
ECOWAS Economic Community of West
SEZ
Special Economic Zones
African States
SME
small and medium-sized enterprises
EIU
Economist Intelligence Unit
SWOT
Strength, Weakness, Opportunities
EPZ
Export Processing Zone
and Threats
EU
European Union
TFCA
Trans-frontiers Conservation Areas
EUREPGAP Global Partnership for Safe and
TIC
Tanzania Investment Center
Sustainable Agriculture
UAE
United Arab Emirates
FAO
Food and Agriculture Organization
UEMOA
Union Economique et Monétaire
FAOSTAT Food and Agriculture Organization
Ouest Africaine
Statistical Database
UIA
Uganda Investment Authority
FDI
Foreign Direct Investment
UK
United Kingdom
FEE
Free Export Enterprise
UNCTAD
United Nations Conference on Trade
GDP
gross domestic product
and Development
GIPC
Ghana Investment Promotion Center
UNIDO
United Nations Industrial
GUIDE
Guichet Unique des Investissements
Development Organization
et de Développement des Entreprises
UNWTO
United Nations World Tourism
Ha
Hectare
Organization
HACCP
Hazard Analysis and Critical Control
USA
United States of America
Points
USAID
United States Agency for International
ICT
Information and Communications
Development
Technology
USD
United States Dollar
IFC
International Finance Center
UHT
Ultra High Temperature
IFZ
Industrial Free Zone
VAT
value added tax
IPA
Investment Promotion Agency
VoIP
Voice-over Internet Protocol
IPC
Investment Promotion Center
WTO
World Trade Organization
SNAPSHOT AFRICA - KENYA
Appendix II: Data Definitions
and Sources
4. Customs Clearance
This appendix provides detail on quantitative and quali-
Source: Company interviews
tative data collected for this study, both through desktop
Interviewed company managers were asked how long it normally
research and fieldwork, and the sources used.
takes for imported inputs to clear customs based on the expe-
rience of their firms.
Intellectual Property Rights Protection
General Business Environment
(Refer to Table 1)
Source: Global Competitiveness Report 2004 – 2005,
World Economic Forum
Data are based on a survey of intellectual property rights by the
Economic, Financial, and Political Stability
World Economic Forum.
1. Country Credit Rating
Source: Institutional Investors
This Index is based on a biannual survey of leading commercial
banks, and captures risk perceptions of the main commercial
Corporate Taxation
lenders. The Index is widely referenced in International Finance
Corporation/World Bank Group publications.
(Refer to Table 2)
2. Country Risk Rating
Corporate Tax Rate
Source: Euromoney
Source: Price Waterhouse Coopers Tax Guide and/or
The data are taken from Euromoney’s semiannual rating of the
local tax authorities
political and economic performances of 185 sovereign countries.
• Ghana - Ghana Internal Revenue Service
To obtain the overall country risk score, Euromoney assigns a
• Kenya - Kenya Revenue Authority, Price Waterhouse Coopers Tax
weighting to nine categories: political risk (25 percent), economic
Guide and/or local tax authorities
performance (25 percent), debt indicators (10 percent), debt in
• lesotho - lesotho National Development Corporation (lNDC)
default or rescheduled (10 percent), credit ratings (10 percent),
• Madagascar - Price Waterhouse Coopers Tax Guide and/or local
access to bank finance (5 percent), access to short-term finance
tax authorities
(5 percent), access to capital markets (5 percent) and forfeiting
• Mali - Maître Cheickne Touré ACGE Tax Adviser
(5 percent).
• Mozambique - 3rd supplement to BR No. 30 (2002), www.forum-
turafrica.org
• Senegal - Price Waterhouse Coopers Tax Guide and/or local tax
Doing Business and Bureaucracy
authorities
1. Number of Procedures Required to Start a Business
• Tanzania - Price Waterhouse Cooper Tax Datacard
• Uganda - Uganda Revenue Authority
Source: Doing Business in 2005, World Bank
Data on the highest corporate tax rate in each country were col-
The Doing Business survey examines the start-up of com-
lected and entered in the Enterprise Benchmarking Model
mercial or industrial firms. It counts all procedures required to
incorporate and register a firm. A ‘procedure’ is defined as any
interaction of the company founder with external parties such as
Sales Tax Rate
government agencies, lawyers, auditors and notaries.
Source: Price Waterhouse Coopers Tax Guide and/or
local tax authorities
• Ghana - Ghana VAT Service
2. Number of Days Normally Required to Start a
• Kenya - Kenya Revenue Authority
Business
• lesotho - lesotho National Development Corporation (lNDC)
Source: Doing Business in 2005, World Bank
• Madagascar - Price Waterhouse Coopers Tax Guide and/or local
The Doing Business survey examines the start-up of commercial
tax authorities
or industrial firms. It counts the number of days required to incor-
• Mali - Maître Cheickne Touré ACGE Tax Adviser
porate and register a newly formed company. Time is recorded in
• Mozambique - law No. 3 (1998), BR No. 1, www.forumturafrica.
calendar days.
org
• Senegal - Price Waterhouse Coopers Tax Guide and/or local tax
authorities
3. Corruption Perception Index
• Tanzania - Price Waterhouse Cooper Tax Datacard
Source: Transparency International
• Uganda - Uganda Revenue Authority
This Index measures countries in terms of the degree to which
Data on sales tax or VAT were entered in the benchmarking model.
corruption is perceived to exist among public officials and poli-
ticians. The Index is the composite of corruption indices from
independent sources. Countries are given an index score between
0 and 10, with a score of 10 indicating no perceived corruption
and a score of 0 indicating extreme perceived corruption.
SNAPSHOT AFRICA - KENYA
Property Tax Rate
Size of Domestic Market
Source: Price Waterhouse Coopers Tax Guide and/
Source: Gross domestic product, World Development
or local tax authorities
Indicators, World Bank
• Ghana - Director of Research, Ghana Internal Revenue Service
This datum takes each country’s gross domestic product as
• Kenya - Nairobi City Council
a proxy for the size of the domestic market. Many firms, par-
• lesotho - lesotho Revenue Authority
ticularly in the apparel and food processing sectors specifically
• Madagascar - Price Waterhouse Coopers Tax Guide and/or local
chose their locations in order to serve the local markets in Mali
tax authorities
and other sub-Saharan African countries.
• Mali - Maître Cheickne Touré ACGE Tax Adviser
• Mozambique - Decree No. 50 (2000), Rro 51 (2000), taxchina.
org
Access to International Tourists
• Senegal - Price Waterhouse Coopers Tax Guide and/or local tax
authorities.
1. Number of Weekly Direct Flights from Country
• Tanzania - Implementing Tax Reform in Tanzania, by Roy Kelly
Source: Airlines that serve each country
and Zanab Musunu
• Ghana - Ghana Civil Aviation Authority
• Uganda - Uganda Revenue Authority
• Kenya - KQ Air, Air India, and Ethiopian Airlines
Data on property tax rates were entered in the model. In some
• lesotho - International passenger flights to overseas markets are
countries, property is taxed as a corporate profit based on
not available
the value of the property rental income. In those cases, the
• Madagascar - Air Madagascar
rental income of a property was assumed to be 10 percent of
• Mali - Regie Administrative de l’Activité, assistance (RAGAAE),
the property value and the property tax rate was entered as 10
Monsieur Maïga, Chef d’escale Airport Service, Bamako
percent of the corporate tax rate.
• Mozambique - Mozambique Civil Aviation Authority
• Senegal - Air Senegal, Air France, British Airways, lufthansa
• Tanzania - British Airways, KlM, Swiss International, Emirates
Air, Oman Air, and Kenya Airways
Access to Markets
• Uganda - Civil Aviation Authority
(Refer to Tables 3-7)
Data were collected on the number of weekly direct flights from
each country to the United States, Europe, and Asia. ‘Direct flight’
is defined as a flight given a single flight number that originates
Export Competitiveness
in the studied country and terminates or discharges passengers
1. Current Export Performance
in the US, the EU or Asia. Direct flights are not necessarily non-
stop, as long as passengers remain on the same aircraft.
Source: ITC Trade Performance Current Index,
International Trade Center
The ITC Trade Performance Current Index measures the trade
2. Passenger Arrivals
performance of a sector in a variety of countries. The index
covers 184 countries and 14 sectors. It provides a static view of
Source: World Tourism Organization93
a country’s recent export performance, ranked between 1 and
Data on the number of annual arrivals of tourists were collected
184. If a country did not show up in the index, it means that the
as an indication of the size of the current market for hotels and
country was not a big performer in trade in a particular industry.
other tourist services in each country.
In those cases, a value of 185 was entered in the Enterprise
Benchmarking Model. The ITC Index for textiles, processed
foods, and fresh fruits were utilized in the model.
Real Estate Quality
(Refer to Table 8)
2. Change in Export Performance
Source: ITC Trade Performance Change Index,
Availability of Land
International Trade Center
Source: Company interviews
The ITC Trade Performance Change Index captures recent trends
Firms were asked to recall the number of industrial, agricultural,
of the change of a country’s export performance. The index ranks
hotel, or office sites within the country they considered during
184 countries in 14 sectors. If a country does not have a change
their initial investment decision. The greater the number of
ranking for a sector, it means that the country is not likely a large
sites, the higher the quality score calculated by the Enterprise
performer in trade in that particular industry. In those cases, a
Benchmarking Model.
value of 185 was entered in the Enterprise Benchmarking Model.
The ITC Index for textiles, processed foods, and fresh fruits were
utilized in the model.
Availability of Agricultural Land
Source: Availability of Arable Areas, Food and
3. Average Tariff for Imported Inputs
Agriculture Production Yearbook, United Nations
Source: Consolidated Trade Database, World Trade
Food and Agriculture Organization
Organization
This study utilized the FAO’s Annual survey of agricultural land.
Data on the average import tariffs for textiles and electric
The availability of arable land is gathered and noted in thousands
machinery were gathered and entered into the Enterprise
of hectares for each surveyed country.
Benchmarking Model. These data serve as indications as to the
openness of a country to imports as well as the cost of importing
Vacancy Rate for Industrial Land and Buildings
needed capital inputs and intermediate goods for production.
Source: Real estate agencies, free zones, and industrial
estates
• Ghana - Ghana Investment Promotion Center
• Kenya - CB Richard Ellis
SNAPSHOT AFRICA - KENYA
• lesotho - lesotho National Development Corporation (lNDC)
2. lease Price of Industrial land
• Madagascar - Financière d’Investessement Aro (FIARO)
Source: Real estate agencies, investment promotion
Industries
• Mali - Average of values provided by Agence des zones indus-
agencies, and free zones and industrial estates.
trials; Agence de cessions immobilières; and IFA Baco Agence
• Ghana - land Developers Company ltd.
immobilières
• Kenya - CB Richard Ellis
• Mozambique - Average of values provided by JHI Real Estate,
• lesotho - lesotho National Development Corporation (lNDC)
Imovisa, and Jat
• Madagascar - Financière d’Investessement Aro (FIARO)
• Senegal – Source not available
Industries
• Tanzania - Survey of vacancy rates in industrially zoned areas,
• Mali - Average of the prices quoted by the following: AZI Sa
industrial estates, and free zones near Dar es Salaam
Agence de zones industrials du Mali; ACI Agence de cessions
• Uganda - Bageine & Company and Knight Frank
immobilières; Architect/expertise AUE; Architect Coulibaly
The vacancy rates or percentage of available industrial land and
Concept AU; and IFA Baco agence immobilières
buildings, within 20 kilometers of the capital city was gathered
• Mozambique - JHI Real Estate
and entered into the Enterprise Benchmarking Model.
• Senegal - Pyramid Group
• Tanzania - Ministry of land and Human Settlement
• Uganda - Uganda Investment Authority (UIA)
The cost of a yearly lease for industrially zoned land or
Vacancy Rate for Office Space
industrial estate was researched and entered into the Enterprise
Source: Real estate agencies and office building man-
Benchmarking Model.
agement companies
• Ghana - Ghana Investment Promotion Center
3. Additional Industrial Site Occupancy Charges
• Kenya - CB Richard Ellis
• lesotho - lesotho National Development Corporation (lNDC)
Source: Real estate agencies, investment promotion
• Madagascar - Financière d’Investessement Aro (FIARO)
agencies, and free zones and industrial estates.
Industries
• Ghana - The Consultant PSI Properties
• Mali - Average of values provided by Agence des zones indus-
• Kenya - CB Richard Ellis
trials; Agence de cessions immobilières; and IFA Baco Agence
• lesotho - lesotho National Development Corporation (lNDC)
immobilières
• Madagascar - Financière d’Investessement Aro (FIARO)
• Mozambique - Average of values provided by JHI Real Estate,
Industries
Imovisa, and Jat
• Mali - Average of the prices quoted by the following: AZI Sa
• Senegal – Source not available
Agence de zones industrials du Mali; ACI Agence de cessions
• Tanzania - Average vacancy rates reported by Waterfront,
immobilières; Architect/expertise AUE; Architect Coulibaly
Millennium Tower, PPF Towers, and JM Mall
Concept AU; and IFA Baco agence immobilières
• Uganda - Bageine & Company and Knight Frank
• Mozambique - Mozambique Investment Promotion Center
The vacancy rates, or percentage of available office space in
• Senegal - Pyramid Group
the center of the capital city, was gathered and entered into the
• Tanzania - Ministry of land and Human Settlement
Enterprise Benchmarking Model.
• Uganda - Uganda Investment Authority (UIA)
In cases where industrial estates or free zones charge additional
maintenance fees or security charges, those data were entered
Real Estate Costs
into the model as additional costs per square meter.
(Refer to Tables 9-10)
4. Purchase Price of Tourist Hotel land
Cost of Land
Source: Real estate agencies and investment pro-
motion agencies
1. Purchase Price of Industrial land
• Ghana - land Bank Management Officer, Ghana Investment
Promotion Center
Source: Real estate agencies, investment promotion
• Kenya - The Property Gallery
agencies, and free zones and industrial estates
• lesotho - lesotho National Development Corporation (lNDC)
• Ghana - Ghana Investment Promotion Center
• Madagascar - Financière d’Investessement Aro (FIARO)
• Kenya - The Property Gallery
Industries
• lesotho - lesotho National Development Corporation (lNDC)
• Mali - Average of the prices quoted by the following: AZI Sa
• Madagascar - Financière d’Investessement Aro (FIARO)
Agence de zones industrials du Mali; ACI Agence de cessions
Industries
immobilières; Architect/expertise AUE; Architect Coulibaly
• Mali - Average of the prices quoted by the following: AZI Sa
Concept AU; and IFA Baco agence immobilières
Agence de zones industrials du Mali; ACI Agence de cessions
• Mozambique - Average of the prices quoted by Abrantina and JHI
immobilières; Architect/expertise AUE; Architect Coulibaly
Real Estate
Concept AU; IFA Baco agence immobilières
• Senegal - Pyramid Group
• Mozambique - Mozambique Investment Promotion Center
• Tanzania - MyBeach real estate agency and the Ministry of Natural
• Senegal - Pyramid Group
Resources and Tourism
• Tanzania - Ministry of land and Human Settlement
• Uganda - Uganda Investment Authority (UIA)
• Uganda – Uganda Investment Authority (UIA)
The purchase price of land in locations suitable for tourist devel-
The cost of purchasing industrially zoned land or industrial estates
opment - beaches, game parks, and city center - was researched
was researched and entered in the Enterprise Benchmarking
and entered into the Enterprise Benchmarking model as the cost
Model as the cost per square meter. These data were verified in
per square meter. Where laws do not allow purchase of land,
company interviews, when respondents were asked how much
long-term leases were also considered as “purchases”.
they paid for their sites. Where laws did not allow purchase of
land, long-term leases were also considered as “purchases” for
the purpose of this datum.
SNAPSHOT AFRICA - KENYA
Cost of Office Space
Construction Costs
1. lease Price of Class A Office Space
1. Cost of Warehouse Construction
Source: Real estate agencies and office building man-
Source: Local engineering and construction com-
agement companies
panies
• Ghana - Ghana Investment Promotion Center
• Ghana - Business Development Manager, Taysec- A
• Kenya - The Property Gallery
TaylorWoodrow Company
• lesotho - lesotho National Development Corporation (lNDC)
• Kenya - The Property Gallery
• Madagascar - Financière d’Investessement Aro (FIARO)
• lesotho - lesotho National Development Corporation (lNDC)
Industries
• Madagascar - Tectra SARl
• Mali - Average of prices provided by SICG Habitat, Blal; Agence
• Mali - Average of prices provided by SICG Habitat; Architect
de cessions immobilières; Architect Sidibe; and IFA Baco agence
Sidibe AUE; Architect Coulibaly Concept; and IFA Baco agence
immobilières
immobilières
• Mozambique - JHI Real Estate
• Mozambique - Average of the prices quoted by Abrantina and JHI
• Senegal - Pyramid Group
Real Estate
• Tanzania - Average of prices provided by 50 Mirambo, PPF Tower,
• Senegal - Pyramid Group
and JM Mall
• Tanzania - Caspian Construction Company
• Uganda – Uganda Investment Authority (UIA)
• Uganda - Uganda Investment Authority (UIA)
Class A office space is defined as offices in or near the center
The price of construction of a concrete block warehouse was
of the capital city. These costs were entered in the model as the
entered into the Enterprise Benchmarking Model as the cost per
price per square meter for a one-year lease.
square meter of construction. Warehouse construction cost was
also used as a proxy for the construction of a simple factory shell,
since there is little actual difference in cost. This study did not
2. lease Price of Class B Office Space
investigate the cost of outfitting a factory with machinery.
Source: Real estate agencies and office building man-
agement companies
• Ghana - A&C Development Company
2. Cost of Hotel Construction
• Kenya - The Property Gallery
• lesotho - lesotho National Development Corporation (lNDC)
Source: Local engineering and construction com-
• Madagascar - Financière d’Investessement Aro (FIARO)
panies
Industries
• Ghana - Property Manager, Ghana Investment Promotion Center
• Mali - Average of prices provided by SICG Habitat, Blal; Agence
• Kenya - The Property Gallery
de cessions immobilières; Architect Sidibe; and IFA Baco agence
• lesotho - lesotho National Development Corporation (lNDC)
immobilières
• Madagascar - Tectra SARl
• Mozambique - JHI Real Estate
• Mali - Average of prices provided by SICG Habitat; Architect
• Senegal - Pyramid Group
Sidibe AUE; Architect Coulibaly Concept; and IFA Baco agence
• Tanzania - Average of prices provided Millennium Tower and
immobilières
Water Front
• Mozambique - Average of the prices quoted by Abrantina and JHI
• Uganda – Uganda Investment Authority (UIA)
Real Estate
Class B office space is defined as office buildings within 20 kilo-
• Senegal - Pyramid Group
meters outside the city center. These costs were entered in the
• Tanzania - Caspian Construction Company
model as the price per square meter for a one-year lease.
• Uganda - Uganda Investment Authority (UIA)
The construction price of a five-star quality hotel was entered
into the Enterprise Benchmarking Model as the cost per square
3. Additional Office Space Occupancy Charges
meter of construction. This study did not investigate the cost of
Source: Real estate agencies and office building man-
outfitting a hotel with furnishings and equipment.
agement companies
• Ghana - Average of prices provided by A&C Development
Utility Costs
Company and Ghana Investment Promotion Center
• Kenya - The Property Gallery
(Refer to Table 11)
• lesotho - lesotho National Development Corporation (lNDC)
• Madagascar - Financière d’Investessement Aro (FIARO)
Cost of Telecommunications
Industries
• Mali - Average of prices provided by SICG Habitat, Blal; Agence
Source: Telecommunication companies
de cessions immobilières; Architect Sidibe; and IFA Baco agence
• Ghana - Ghana Telecom
immobilières
• Kenya - Telkom Kenya
• Mozambique - JHI Real Estate
• lesotho - lesotho National Development Corporation (lNDC)
• Senegal - Pyramid Group
“Investing in lesotho”
• Tanzania - Average of prices provided by 50 Mirambo, PPF Tower,
• Madagascar – Telma
JM Mall Millennium Tower, and Water Front
• Mali - Société des telecommunications du Mali (Sotelma)
• Uganda – Uganda Investment Authority (UIA)
• Mozamibique - Mozambique Telecommunications
In cases where office buildings charge additional maintenance,
• Senegal - Société National de Télécommunications de Senegal
parking or security fees, those data were entered into the model
(SONATEl)
as additional costs per square meter.
• Tanzania-Tanzania Telecommunications Co., ltd
• Uganda-Uganda Telecom ltd and MTN Uganda ltd
Data were gathered on the per minute cost of landline telephone
calls from the capital city of each country to the following
locations:
1. Domestic call within the same country
2. Call to a neighboring country
3. Call to the United States
SNAPSHOT AFRICA - KENYA
Cost of High-Speed Internet
3. Cost of Power Generator Operation
1. Monthly High-Bandwidth Internet Charge
Source: Company interviews
Interviewees were asked whether or not their firms used their
Source: Internet service providers
own power generators, how many hours the generators operated
• Ghana - Ghana Telecom
each month, and the cost of generator operation per hour. These
• Kenya - JamboNet
data were used to calculate the overall cost of electricity for the
• lesotho - Telecom lesotho
average firm in each sector.
• Madagascar - Simicro and Blueline
• Mali - IKATEl
Cost of Water
• Mozambique - TV Cabo
• Sénégal - Société National de Télécommunications de Senegal
Source: Water utilities in each country
(SONATEl)
• Ghana - Ghana Water Company
• Tanzania - Benson Online
• Kenya - Nairobi Water Company
• Uganda - Uganda Telecom ltd
• lesotho - Average rate from local utility companies
Data were gathered on the monthly charges for a 256-kbps
• Madagascar - Jirama
Internet connection.
• Mali - Energie du Mali
• Mozambique - Mozambique Investment Promotion Center
• Senegal - Senegalaise des Eaux (SDE)
2. Internet Usage Charges
• Tanzania- City Water
Source: Internet service providers
• Uganda - National Water and Sewerage Company
• Ghana - Ghana Telecom
Data were collected on the charges per cubic meter for water
• Kenya - JamboNet
used for industrial and agricultural uses.
• lesotho - Telecom lesotho lesotho - Telecom lesotho
• Madagascar - Simicro and Blueline
Cost of Gas
• Mali - IKATEl
1. Cost of Natural Gas (Methane)
• Mozambique - TV Cabo
• Senegal - Société National de Télécommunications de Senegal
Source: Natural gas utilities, where available
(SONATEl)
Madagascar – No information available
• Tanzania - Secretarial Services at Business Centers in Dar es
Tanzania - average of prices reported by Tanzania Breweries ltd,
Salaam
Kioo Glass,
• Uganda - Uganda Telecom ltd
TANESCO, and Twiga Cement
Data were gathered on the per minute usage charges for high-
The cost of methane gas was collected, measured in cubic
speed (256-kpbs) Internet, if any.
meters.
2. Cost of liquefied Petroleum Gas (Propane or
Cost of Power
Butane)
1. Electricity Capacity Demand Charges
Source: LPG providers
Source: Electricity utilities in each country
• Ghana- Tema Oil Refinery
• Ghana - Electricity Company of Ghana
• Kenya - BOC Gases ltd
• Kenya - Kenya Power and lighting Co.
• lesotho - lesotho National Development Corporation (lNDC)
• lesotho - lesotho National Development Corporation (lNDC)
• Madagascar - Galana Distribution SA.
• Madagascar - Jirama
• Mali - lPG providers
• Mali - Energie du Mali
• Mozambique - Average of prices provided by Globgas, Mocacor,
• Mozambique - Electricidade de Mocambique (ECM)
and Petrogas
• Senegal - Société Senegalaise d’Électricité (SENElEC)
• Senegal - Société Africaine de Raffinage
• Tanzania - Tanzania Electric Supply Company, ltd (TANESCO)
• Tanzania - lPG providers
• Uganda - Uganda Electricity Distribution Company, ltd (UEDCl)
• Uganda - Shell, Caltex, Kobil
Data were collected on charges levied by power companies for
The cost of propane or butane gas was collected, measured in
the maximum capacity of electricity demanded for low to medium
kilograms.
voltage power, measured in kilowatts (KW) or in kilovolt amperes
(KVA).
Transportation Costs
2. Electricity Usage Charges
(Refer to Tables 12-13)
Source: Electricity utilities in each country
• Ghana - Electricity Company of Ghana
1. Cost of Air Freight
• Kenya - Kenya Power and lighting Co.
• lesotho - lesotho National Development Corporation (lNDC)
Source: Freight forwarders, airfreight companies, and
• Madagascar - Jirama
airlines
• Mali - Energie du Mali
• Ghana - McDan Shipping Co. ltd. and Aviance ltd
• Mozambique - Electricidade de Mocambique (ECM)
• Kenya - SDV Transami
• Senegal - Société Senegalaise d’Électricité (SENElEC)
• lesotho - Rates from South Africa were used, plus a 30 percent
• Tanzania - Tanzania Electric Supply Company, ltd (TANESCO)
increase to account for overland transportation
• Uganda - Uganda Electricity Distribution Company, ltd (UEDCl)
• Madagascar - Air France, Air Mauritius, and Air Madagascar
Data were collected on the charges per kilowatt-hour (kWh) for
• Mali - Air France Freight Service
industrial electricity usage during peak operating periods.
• Mozambique - Manica Freight Services
• Senegal - South African Airways Air Cargo Service
• Tanzania - Malai Freight ltd, KlM Airlines, British Airways
• Uganda - Emirates Airlines Sky Cargo, British Airways
The cost of shipping a parcel of 45 kilograms or less by air was
calculated from the capital city of each country to the following
destinations:
SNAPSHOT AFRICA - KENYA
Kennedy International Airport, New York City, USA (East Coast)
Score = 5: There are very many qualified candidates. It is an
los Angeles International Airport, los Angeles, USA (West
employer’s market.
Coast)
Score = 4: There is a large enough pool of qualified workers, and
Schipol International Airport, Amsterdam, Holland
the company usually has no difficulty in hiring employees.
Changi International Airport, Singapore
Score = 3: The company needs to search hard, but eventually
New Tokyo International Airport, Narita, Japan
finds the right personnel.
Costs do not include the price of insurance, handling, or other
Score = 2: At least 50 percent of the time, the company can find
charges.
the right personnel after a lengthy search.
Score = 1: It is impossible to find the right personnel.
2. Cost of Sea Freight
Flexibility of Labor Environment
Source: Freight forwarders and sea freight com-
panies
1. Rigidity of Employment
• Ghana - McDan Shipping Co. ltd.
Source: Rigidity of Employment Index, Doing Business
• Kenya - SDV Transami and Maersk Sealines, ltd.
• lesotho - Rates quoted by Safmarine are for shipment from
in 2005, World Bank
South Africa including overland transportation
Data on the rigidity of employment was sourced directly from
• Madagascar - Scandinavian Eastern Africa line (SEAl),
the World Bank’s Doing Business in 2005 publication. The index
Mediterranean Shipping Company (MSC), Compagnie Maritime
measures how difficult it is to hire a new worker, how rigid the
d’Affrètement-Compagnie Générale Maritime (CMA-CGM), and
restrictions are on expanding or contracting the number of
SCAC
working hours, and how difficult and costly it is to dismiss a
• Mali - Maersk lines and Groupe Ami GCM GMM
redundant worker. Specifically, the index is the average of three
• Mozambique - Manica Freight Services
employment indices that evaluate the following:
• Senegal - Maersk Senegal SDV
1. Difficulty in Hiring: Allowance of term contracts for temporary
• Tanzania - Maersk Sealines, ltd.
tasks
• Uganda - SDV Transami, Maersk Sealines
Regulated minimum length of term contracts
The costs of shipping a regular 40-foot container, a refrigerated
Ratio of mandated minimum wage to average value-added per
40-foot container, and bulk items per kilogram were calculated
worker
from the capital city of each country - including overland trans-
2. Rigidity of Hours: Restrictions on night work
portation to the nearest seaport - to the following locations:
Allowance of weekend work
Port of New York City, USA (East Coast)
legal workweek of 5 ½ days or more
Port of long Beach, USA (West Coast)
Allowance for workday to extend to 12 hours or more
Port of Rotterdam, Holland
Annual paid vacation of 21 days or less
Port of Singapore
3. Difficulty in Firing: Ability to fire workers on grounds of
Port of Yokohama, Japan
redundancy
Need to notify union for firing one worker
Costs do not include insurance, handling charges, or other fees.
Need to notify union for group dismissals
Need for union approval for firing one redundant worker
Need for union approval for dismissing a group of workers
Labor Market Quality
legal mandate for training or replacement of worker prior to dis-
(Refer to Tables 14-19)
missal
Application of priority rules for dismissals
Application of priority rules for reemployment
Potential to Recruit Local Staff
1. Availability of Qualified Personnel
Scores are indexed on a scale of 0 to 100. The higher the value of
the index score, the more rigid are labor regulations.
Source: Company interviews
Companies rated their satisfaction in recruiting local staff for
five categories of job positions - management, professional,
technical, skilled, and unskilled workers. Satisfaction ratings were
2. Average Weekly Working Hours
given on a scale of 1 to 5 according to the following criteria:
Source: Company interviews
Firms were asked to indicate the average weekly working hours
Score = 5: There are many qualified candidates. It is an employer’s
per employee. This often differed from the legally mandated
market.
workweek length, and varied by industry. The longer the workweek,
Score = 4: There is a large enough pool of qualified workers, and
the more attractive the working environment was considered for
the company usually has no difficulty in hiring employees.
investors.
Score = 3: The company needs to search hard, but eventually
finds the right personnel.
3. Social Climate
Score = 2: At least 50 percent of the time, the company can find
the right personnel after a lengthy search.
Source: Cooperation in Labor-Employer Relations,
Score = 1: It is impossible to find the right personnel.
Global Competitiveness Report 2004 - 2005, World
Economic Forum
The World Economic Forum conducts an annual Executive
2. Mastery of Required language Skills
Opinion Survey of firms throughout the world. Entrepreneurs
Source: Company interviews
and business executives were asked to rate the labor-employer
Companies listed the languages they require employees to speak
relations in their countries on a scale of 1 (“Generally confronta-
in the workplace. They rated the ease with which they actually
tional”) to 7 (“Generally cooperative”).
found workers with satisfactory command of those languages.
Satisfaction ratings were given on a scale of 1 to 5 according to
the following criteria:
0
SNAPSHOT AFRICA - KENYA
4. Degree of Unionization
2. loss of Air Shipments
Source: Company interviews
Source: Company interviews
Interviewed firms indicated the percentage of workers in their
Investors were asked to indicate the percentage of airfreight
companies that belonged to labor unions. The Enterprise
shipments that become lost or never reach their destination. If
Benchmarking Model is programmed under the assumption that
airfreight transportation was not available, a response of ‘0’ was
investors prefer low degrees of unionization to high union mem-
entered.
bership.
5. labor Turnover
Freight Shipment by Train
Source: Company interviews
1. Punctuality of Rail Shipments
Companies were asked to indicate the annual average turnover
Source: Company interviews
among employees. ‘Annual turnover’ refers to the number of
Investors were asked the percentage of time that rail freight
employees who resigned voluntarily in the past year, divided by
shipments reach their destinations on schedule. If rail freight
the total number of employees. lower rates of turnover are con-
transportation was not available, a response of ‘0’ was entered.
sidered more preferable to investors than high turnover rates.
2. loss of Rail Shipments
Source: Company interviews
Access to Inputs and Outputs
Investors were asked to indicate the percentage of rail freight
shipments that become lost or never reached their destination. If
(Refer to Tables 20-25)
rail freight transportation was not available, a response of ‘0’ was
entered.
Availability of Raw Materials
Source: Company interviews
Freight Shipment by Sea
Company managers were asked the percentage of raw materials
1. Punctuality of Sea Shipments
they imported for use in their production. ‘Raw material’ refers
to any input that has not yet undergone significant processing,
Source: Company interviews
such as raw cotton, timber, sugar, milk, steel ingot, etc. It is
Investors were asked the percentage of time that sea freight
assumed that locations in which raw materials can be sourced
shipments reach their destinations on schedule. If sea freight
locally are more attractive than those where raw materials must
transportation was not available, a response of ‘0’ was entered.
be imported.
2. loss of Sea Shipments
Presence of Suppliers or Clusters Network
Source : Company interviews
1. Availability of Components
Investors were asked to indicate the percentage of sea freight
shipments that become lost or never reach their destination. If
Source: Company interviews
sea freight transportation was not available, a response of ‘0’ was
Company managers were asked the percentage of components
entered.
they imported for production. ‘Component’ refers to any input
that has undergone significant processing or transformation,
such as yarn, fabric, precision molded plastic, engines, etc.) It
Freight Shipment by Road
is assumed that locations in which components can be sourced
1. Punctuality of Road Shipments
locally are more attractive to investors than those where com-
ponents must be imported.
Source: Company interviews
Investors were asked the percentage of time that road freight
shipments reach their destinations on schedule. If road freight
2. Availability of Capital Equipment or Chemicals
transportation was not available, a response of ‘0’ was entered.
Source: Company interviews
Company managers were asked to indicate the percentage of
2. loss of Road Shipments
equipment and chemicals required for production that they
import. ‘Equipment’ or ‘chemicals’ refer to all capital inputs like
Source: Company interviews
machinery, computers, telephones, fertilizers, hotel furnishings,
Investors were asked to indicate the percentage of road freight
etc.) It is assumed that locations in which capital equipment can
shipments that become lost or never reach their destination. If
be sourced locally are more attractive to investors than those
road freight transportation was not available, a response of ‘0’
where equipment must be imported.
was entered.
Telecommunications
Infrastructure Quality
1. Quality of Telephone Service
(Refer to Tables 26-31)
Source: Company interviews
Companies were asked to rate the quality of landline telecom-
Freight Shipment by Air
munications on a scale of 1 to 5 corresponding to the following:
1. Punctuality of Air Shipments
Score = 5: Connections are always clear. Calls are never dropped.
Source: Company interviews
lines are never down
Investors were asked the percentage of time that airfreight
Score = 4: Connection is usually clear. Calls are almost never
shipments reach their destinations on schedule. If airfreight
dropped. lines are almost never down.
transportation was not available, a response of ‘0’ was entered.
Score = 3: Connection is sometimes not clear. Some calls are
dropped. lines are sometimes down.
Score = 2: Connection is sometimes not clear. There is a problem
SNAPSHOT AFRICA - KENYA
with dropped calls. The line is often down.
Interviewed companies rated the quality of the public waste
Score = 1: Connection is never clear. Calls are always dropped.
treatment system on a scale of 1 to 5, as follows:
lines are often down, or no landline is available, and mobile tele-
phones are necessary for communication.
Score = 5: Public waste treatment facility provides first stage
(solid particle removal), second stage (aeration, organic matter
killed), and third stage (removal of heavy metals and chemicals)
2. length of Time to Install landline Telephone Service
biological and chemical treatment to the highest international
Source: Company interviews
standards. Tap water is chlorinated and potable.
Interviewed companies indicated the length of time it normally
Score = 4: Public waste treatment facility provides first, second
takes to install a new telephone landline.
stage, and third stage biological and chemical wastewater
treatment, but tap water is not potable.
Score = 3: Public waste treatment facility provides first and
IT Infrastructure
second stage treatment only. Wastewater smells.
Score = 2: Public waste treatment facility provides first stage
1. Quality of Internet Service
treatment only. Wastewater remains harmful to the envi-
Source: Company interviews
ronment.
Companies were asked to rate the quality of high bandwidth
Score = 1: Public wastewater treatment is not available. Raw
Internet (speed greater than 256 kbps) on a scale of 1 to 5, cor-
sewage freely enters the environment, or company has its own
responding to the following:
treatment facility.
Score = 5: Internet is always operational. Internet service is never
Quality of Living Conditions
down or disconnected.
Score = 4: Internet service is usually operational. Service is
(Refer to Tables 32-37)
almost never down or disconnected.
Score = 3: Internet service is sometimes not operational.
Cost of Living
Sometimes the service is dropped or not operational.
Score = 2: Internet service is sometimes not operational. There is
Source: Company interviews
a problem with frequent disconnections of service.
Companies were asked to rate the cost of living in the investment
Score = 1: High-speed Internet connections are not available.
location on a scale of 1 to 5. Responses differed depending on
whether the interviewee was local or foreign.
2. length of Time to Install Internet Service
Score = 5: Much less expensive than where company head-
quarters is, or very inexpensive.
Source: Company interviews
Score = 4: Slightly less expensive than where company head-
Interviewed firms indicated the length of tome it normally takes
quarters is or fairly inexpensive.
to install Internet service in their locations.
Score = 3: About the same as where the company headquarters is
or mediocre, but not ideal.
Score = 2: Slightly more expensive than where company head-
Power Supply
quarters is or fairly expensive.
1. Number of Blackouts
Score = 1: Much more expensive than where company head-
quarters is, or very expensive.
Source: Company interviews
Companies were asked the number of hours per month that
they experienced a total loss of power without the use of back-
up generators. Firms that were totally reliant on generator power
Level of Safety
were considered to be under permanent blackout conditions, and
Source: Company interviews
a value of 300 hours per month was entered in the Enterprise
Companies were asked to rate the level of personal and company
Benchmarking Model.
safety in the investment location on a scale of 1 to 5. Responses
differed depending on whether the interviewee was local or
foreign.
2. Number of Brownouts
Source: Company interviews
Score = 5: Much safer than where company headquarters is, or
Companies were asked to indicate the number of hours per
very safe.
month they experience reductions in voltage lower than the
Score = 4: Slightly safer than where company headquarters is, or
minimum voltage specified for the system, or upward spikes in
fairly safe.
the power supply.
Score = 3: About the same as where the company headquarters
is, or mediocre, but not ideal.
Score = 2: Slightly less safe than where company headquarters is,
Water Supply
or fairly unsafe.
Score = 1: Much less safe than where company headquarters is,
Source: Company interviews
or very unsafe.
Interviewed firms were asked to indicate the number of days per
year they experience a shortage of water supply from the publicly
supplied water provider. Companies that did not have access to
Schools
municipal water supplies and were reliant on their own wells or
1. Number of International Schools
private water delivery were considered to experience a permanent
Source: Ministries of Education, investment pro-
shortage of water. A value of 365 was entered in these cases,
except for horticulture firms, which are typically in rural areas
motion agencies, and school district offices
without expectation for municipal water supplies.
• Ghana - Ghana Education Service
• Kenya - Kenya Private Schools Association
• lesotho - Department for International Development
Waste Treatment
• Madagascar - Ministry of Education
Source: Company interviews
• Mali - Ministry of Education
SNAPSHOT AFRICA - KENYA
• Mozambique - Ministries of Education, investment promotion
Responses differed depending on whether the interviewee was
agencies, and school district offices
local or foreign.
• Senegal - Ministries of Education, investment promotion
agencies, and school district offices
Score = 5: Much better than where company headquarters is, or
• Tanzania - Ministry of Education and Culture
excellent, many activities.
• Uganda - Monitor Business Directory
Score = 4: Slightly better than where company headquarters is, or
Data on the number of international schools in the capital city of
good, some activities.
each country were collected.
Score = 3: About the same as where the company headquarters
is, or mediocre, but not ideal.
Score = 2: Slightly worse than where company headquarters is,
2. Quality of International Schools
or fairly bad, not many activities.
Source: Company interviews
Score = 1: Much worse than where company headquarters is, or
Companies were asked to rate the quality of international schools
very bad, hardly any activities.
in the investment location on a scale of 1 to 5 according to the
following criteria. Responses differed depending on whether the
interviewee was local or foreign. .
Operating costs
Score = 5: Much better than schools where company head-
(Refer to Tables 38-43)
quarters is, or excellent.
Score = 4: Slightly better than schools than where company
Labor Cost
headquarters is or good.
Score = 3: About the same as where the company headquarters
Source: Company interviews
is, or mediocre, but not ideal.
labor cost data were collected during the course of 25 company
Score = 2: Slightly worse than schools where company head-
interviews and aggregated by industry sector for analysis by the
quarters is, or fairly bad.
Enterprise Benchmarking Model. Company officials were asked
Score = 1: Much worse than schools where company head-
to indicate the average annual fully burdened gross salaries of
quarters is, or very bad.
workers - including expatriate - they typically hired in the fol-
lowing five job categories.
Management: Mid- to upper-level managers
3. Quality of local Schools
Professionals: Chief financial officer, lawyer, consultant
Source: Company interviews
Technical Workers: Engineer, programmer, systems analyst,
Companies were asked to rate the quality of local schools in the
agronomist, accountants
investment location on a scale of 1 to 5 according to the fol-
Skilled Workers: Data entry clerks, customer service represen-
lowing criteria. Responses differed depending on whether the
tatives, assembly line workers with special skills
interviewee was local or foreign.
Unskilled Workers: Drivers, janitors, chambermaids, entry-level
assembly line workers, farmhands
Score = 5: Much better than schools where company head-
Gross salaries include wages and benefits such as mandatory
quarters is, or excellent.
pension or social security contributions, healthcare, transpor-
Score = 4: Slightly better than schools than where company head-
tation, lodging, and any other benefits paid by the employer.
quarters is, or good.
Companies were instructed to provide average salary information
Score = 3: About the same as where the company headquarters
for the types of workers that typically fill the above positions.
is, or mediocre, but not ideal.
The higher the labor costs, the lower the level of desirability to
Score = 2: Slightly worse than schools where company head-
potential investors.
quarters is, or fairly bad.
Score = 1: Much worse than schools where company head-
quarters is, or very bad.
Healthcare
Source: Company interviews
Companies were asked to rate the quality of healthcare in the
investment location on a scale of 1 to 5 according to the fol-
lowing criteria. Responses differed depending on whether the
interviewee was local or foreign.
Score = 5: Much better than healthcare where company head-
quarters is or excellent.
Score = 4: Slightly better than healthcare than where company
headquarters is, or good.
Score = 3: About the same as where the company headquarters
is, or mediocre, but not ideal.
Score = 2: Slightly worse than healthcare where company head-
quarters is, or fairly bad.
Score = 1: Much worse than healthcare where company head-
quarters is, or, very bad.
Quality of Recreational Activities
Source: Company interviews
Companies were asked to rate the quality of recreational activities
in the investment location, such as access to restaurants, family
activities, golf and other sports, nature-related, and other
activities on a scale of 1 to 5 according to the following criteria.
SNAPSHOT AFRICA - KENYA
Appendix III: Tables and Findings
The tables below present the study’s findings by factor and country, including
both quantitative and qualitative data collected through desktop research and
fieldwork. The fieldwork consisted of interviews with companies operating in the
nine subject countries, and South Africa and Mauritius, added in order to serve as
African benchmarking countries. In addition, the tables below include comparator
countries, Tunisia, France, Ireland and Nigeria, shown at the right side of each
table, that provide comparative investment costs and quality factors from global
competitor countries. Each table notes the scales of measurement applied. For
more information on the individual data points, please refer to Appendix II for data
definitions and sources.
Table 1: General business environment
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
Institutional
29.3
26.5
32.0
18.7
23.7
25.8
33.1
26.3
21.2
59.3
57.8
55.1
92.7
90.5
21.1
Investors Country
Credit Rating 1
Euromoney Country
40.5
38.0
37.7
31.6
31.2
35.7
39.2
37.2
35.9
59.8
57.1
56.8
91.4
94.0
33.3
Risk Poll 2
Number of
12.0
12.0
9.0
13.0
13.0
14.0
9.0
13.0
17.0
9.0
6.0
9.0
7.0
4.0
10.0
procedures required
to start a business
Number of days
85.0
47.0
92.0
44.0
42.0
153.0
57.0
35.0
36.0
38.0
46.0
14.0
8.0
24.0
44.0
required to start a
business
Corruption
3.6
2.1
n/a
3.1
3.2
2.8
3.0
2.8
2.6
4.6
4.1
5.0
7.1
7.5
1.4
Perception Index 3
Intellectual Property
3.3
2.7
n/a
2.8
2.4
2.2
3.7
3.0
2.7
4.7
3.7
4.7
5.8
4.7
2.6
Protection 4
Rigidity of
34.0
24.0
27.0
49.0
66.0
64.0
64.0
65.0
7.0
52.0
37.0
54.0
66.0
29.0
44.0
Employment Index
labor Relations
4.3
3.6
n/a
4.0
4.4
4.0
3.7
4.6
4.1
3.8
4.2
4.6
3.5
5.0
3.5
Index
1 Index based on a bi-annual survey of leading commercial banks; 100 is the best rating in a range of 1–100.
2 Rating of the political and economic performances of 185 sovereign countries; 100 is the best rating in a range of 1–100.
3 Index that measures countries in terms of perceived corruption among public officials; 10 is the best rating in a range of 0–10.
4 Based on survey that asks executives to rate aspects of business in their own countries; 7 mean “most protected” in range of 1–7.
SNAPSHOT AFRICA - KENYA
Table 2: Tax rates
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
Corporate income
30.0
30.0
35.0
35.0
35.0
32.0
33.0
30.0
30.0
35.0
25.0
35.0
34.3
25.0
35.0
tax (percent)
Sales / VAT tax
12.5
16.0
14.0
20.0
18.0
17.0
18.0
20.0
17.0
14.0
15.0
18.0
19.6
21.0
5.0
(percent)
Property tax
0.1
0.6
2.8
3.5
15.0
1.0
3.9
0.2
10.0
3.0
2.5
3.0
3.0
2.0
10.0
(percent)
Table 3: Access to markets/ tariff rates for textiles
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
ITC Trade
185
95
185
90
185
185
88
99
97
39
60
68
4
42
185
Performance
Current Index 1
ITC Trade
185
92
185
6
185
185
28
108
87
25
1
7
73
4
185
Performance
Change Index 1
Average tariff on
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
24.0
24.0
0.0
imports to the US 2
Average tariff on
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.0
0.0
0.0
0.0
0.0
n/a
imports to the EU
1 The ITC index is based on a ranking of country-level trade competitiveness by sector; 1 is the best ranking in a range of 184. The score of 185 was given to those
countries where no ranking was available.
2 Average import tariffs expressed as a percentage to be added to the value of the imported product; 0.0 means no tariff, due to exemptions.
SNAPSHOT AFRICA - KENYA
Table 4: Access to markets/ tariff rates for apparel
EBP countries
Comparator countries
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
Mauritius
T
unisia
F
rance
Ireland
Nigeria
ITC Trade
185
91
185
68
108
185
185
111
185
31
8
12
185
185
Performance
Current Index 1
ITC Trade
185
14
185
25
29
185
185
107
185
97
34
75
185
185
Performance
Change Index 1
Average tariff on
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
12.2
12.2
0.0
imports to the US 2
Average tariff on
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
n/a
imports to the EU
1 The ITC index is based on a ranking of country-level trade competitiveness by sector; 1 is the best ranking in a range of 184. The score of 185 was given to
those countries where no ranking was available.
2 Average import tariffs expressed as a percentage to be added to the value of the imported product; 0.0 means no tariff, due to exemptions.
Table 5: Access to markets/ tariff rates for horticulture
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
ITC Trade
46
36
185
76
107
96
119
51
53
8
98
99
5
17
185
Performance
Current Index 1
ITC Trade
68
20
185
46
101
34
21
107
87
64
120
102
125
160
185
Performance
Change Index 1
Average tariff on
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
20.0
20.0
n/a
imports to the US 2
Average tariff on
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
n/a
imports to the EU
1 The ITC index is based on a ranking of country-level trade competitiveness by sector; 1 is the best ranking in a range of 184. The score of 185 was given to those
countries where no ranking was available.
2 Average import tariffs expressed as a percentage to be added to the value of the imported product; 0.0 means no tariff, due to exemptions.
SNAPSHOT AFRICA - KENYA
Table 6: Access to markets/ tariff rates for food and beverage processing
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
ITC Trade
121
73
185
112
185
118
93
130
113
21
59
111
1
9
185
Performance
Current Index 1
ITC Trade
138
26
185
123
185
19
1
143
34
91
102
111
104
72
185
Performance
Change Index 1
Average tariff on
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.5
3.5
n/a
imports to US 2
Average tariff on
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.5
0.0
5.2
0.0
0.0
n/a
imports to the EU
1 The ITC index is based on a ranking of country-level trade competitiveness by sector; 1 is the best ranking in a range of 184. The score of 185 was given to those
countries where no ranking was available.
2 Average import tariffs expressed as a percentage to be added to the value of the imported product; 0.0 means no tariff, due to exemptions.
Table 7: Number of direct weekly flights to EBP countries and annual passenger arrivals
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
Number of direct
0
0
0
0
0
0
7
0
0
10
0
308
67
0
2
weekly flights to US
Number of direct
33
50
0
11
11
3
22
13
7
92
29
0
0
20
27
weekly flights to
Europe
Number of direct
7
18
0
2
0
0
0
11
0
23
19
147
0
7
7
weekly flights to
Asia
Annual passenger
483
927
186
170
96
246
427
552
254
6640
702
75048
6369
887
1088
arrivals (thousands)
SNAPSHOT AFRICA - KENYA
Table 8: Quality of real estate
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
Availability of
4181
4600
330
2950
4660
4200
2460
4000
5100
14753
100
2771
18449
1121
30200
arable land (square
kilometers)
Vacancy rate for
62.50
40.00
32.50
70.00
26.00
95.00
27.21
20.00
5.00
8.00
9.00
n/a
n/a
n/a
n/a
industrial buildings
(percent)
Vacancy rate for
42.50
50.00
10.00
90.00
33.00
37.00
27.96
4.00
20.00
25.10
30.00
n/a
n/a
n/a
n/a
offices (percent)
Surveyed companies
50.00
46.67
25.00
48.57
68.00
65.28
58.06
60.71
54.55
58.33
36.84
n/a
n/a
n/a
n/a
purchasing real
estate (percent)
Table 9: Real estate costs
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
Sale price of
12.35
186.0
8.15
15.00
22.10
7.50
43.00
12.58
11.00
58.00
18.00
n/a
10.70
n/a
12.68
industrial land
(USD/ m2)
(realtors)
Sale price of hotel
45
60
33
45
62.40
80
43
12.97
15
300
32
71
544
458
42
land (USD/ m2)
(realtors)
Surveyed companies
50.0
53.3
75.0
51.4
32.0
34.7
41.9
39.3
45.5
41.7
63.2
n/a
n/a
n/a
n/a
leasing real estate
(percent)
lease price of
0.247
47.48
2.05
9
2.21
65.31
11.88
11.12
52.8
72.3
61.64
3.48
25.45
33.92
1.90
industrial site
(USD/ m2 / year)
(realtor)
Class A office rental
213.2
121.6
11.24
72.46
243.5
184
130.6
178.4
252
146.6
180.8
n/a
589.5
496.2
n/a
occupancy cost
(USD/ m2/ year)
Class B office rental
134.4
70.76
8.428
41.4
84.77
124.7
78.38
174
150
127
92.05
n/a
166.6
328.5
n/a
occupancy cost
(USD/ m2/ year)
SNAPSHOT AFRICA - KENYA
Table 10: Construction costs (USD/ m²)
EBP countries
Comparator countries
Africa
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
T
unisia
F
rance
Ireland
Nigeria
Warehouse
400
330
350
190
289
300
217
550
185
450
130
183
793
935
132
Office Building
1400
1200
570
320
720
550
326
1000
550
700
710
415
2387
2451
151
Hotel
1600
1370
733
220
900
550
543
600
404
800
1610
567
2999
3483
188
Table 11: Utility costs (in USD)
Telecom Costs (USD/ minute)
Internet costs
Electricity costs
Water costs
(USD/m³)
local calls
International
International call High bandwidth Usage charge for Demand charge
Water for
call to adjacent
to the USA
Internet (USD/
industrial use
for industrial use
industrial use
country
mo.)
(USD/kWh)
(USD/kVA)
EBP country
Ghana
0.02
0.28
0.39
252
0.05
12.29
0.77
Kenya
0.04
0.16
0.88
1690
0.06
3.68
0.42
lesotho
0.33
0.36
1.08
814
0.04
7.07
0.49
Madagascar
0.08
0.75
0.90
840
0.08
12.02
0.26
Mali
0.03
0.59
0.89
1089
0.12
2.91
0.56
Mozambique
0.06
0.42
0.77
594
0.05
5.25
0.88
Senegal
0.23
1.07
1.07
57
0.14
13.10
1.56
Tanzania
0.07
0.47
1.11
1900
0.06
6.01
0.67
Uganda
0.07
0.38
0.76
3548
0.10
2.33
0.76
South Africa
0.06
0.26
0.54
42
0.08
0.88
1.38
Mauritius
0.03
0.19
0.19
188
0.06
3.25
0.38
Comparator country
Tunisia
0.01
0.48
0.52
18
0.07
1.48
0.68
France
0.02
0.17
0.17
34
0.07
n/a
1.99
Ireland
0.05
0.15
0.19
43
0.12
8.70
1.63
Nigeria
0.16
0.43
1.45
236
0.28
n/a
0.91
SNAPSHOT AFRICA - KENYA
Table 12: International sea freight rates (USD Per 40 foot container)
To Rotterdam
To New York
To long Beach
To Yokohama
To Singapore
Container Type
Standard
Refrigerated
Standard
Refrigerated
Standard
Refrigerated
Standard
Refrigerated
Standard
Refrigerated
From EBP Country
Ghana
1953
4948
3500
4500
2900
4200
3500
4500
3500
2600
Kenya
2000
5475
4900
5675
5400
7075
2200
6275
1400
6075
lesotho
2606
3750
3540
4405
3850
5500
1700
3600
1500
3000
Madagascar
3111
2940
4552
7975
5600
4775
2852
5800
1700
4800
Mali
4392
5218
6926
7754
8525
9377
4703
7168
4393
7061
Mozambique
3500
6500
6800
8400
7000
8800
3500
4500
3500
4500
Senegal
2193
4239
4500
5902
6477
9362
2431
6706
2106
6206
Tanzania
3123
4842
4621
5146
5071
6546
2131
5456
1731
5256
Uganda
3800
9500
3800
10691
4100
10691
3200
10691
3000
10491
South Africa
1450
2900
3500
7000
3700
7000
1250
2500
1100
2000
Mauritius
1948
5948
5445
None
5755
None
2484
5084
1684
5284
From Comparator country
Tunisia
1118
2118
4286
6786
4350
6900
n/a
n/a
n/a
n/a
France
1097
1097
2891
2891
n/a
n/a
n/a
n/a
n/a
n/a
Ireland
1161
1161
5050
5050
5815
5815
n/a
n/a
n/a
n/a
Nigeria
2161
3824
4756
7256
5456
7956
n/a
n/a
n/a
n/a
Table 13: International air freight rates (Regular rate for general cargo under 45kg (USD/kg)
To Amsterdam Schiphol
To New York (JFK)
To los Angeles (lAX)
To Tokyo Narita (NRT)
To Singapore Changi
(AMS)
SIN
From EBP country
Ghana
4.05
8.20
8.20
16.26
14.84
Kenya
2.50
3.80
4.00
4.90
4.00
lesotho
4.47
4.56
4.56
4.4
4.4
Madagascar
2.46
3.6
3.96
4.14
2.15
Mali
5.38
9.68
11.50
15.96
16.18
Mozambique
2.90
4.65
5.00
4.30
4.00
Senegal
5.28
3.81
4.63
17.57
18.27
Tanzania
4.09
5.39
4.43
8.10
41.65
Uganda
6.04
10.64
12.37
7.95
3.40
South Africa
3.44
3.51
3.51
3.39
3.39
Mauritius
2.70
10.10
13.07
4.70
2.66
From comparator country
Tunisia
4.5
7.5
n/a
n/a
n/a
France
2.39
1.55
1.9
n/a
n/a
Ireland
2.2
2.2
3.83
14
12.77
Nigeria
1.95
3.85
n/a
n/a
n/a
0
SNAPSHOT AFRICA - KENYA
Table 14: Labor market: Textile*
Africa
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Availability of managers
3.0
3.3
1.3
2.1
1.3
2.8
2.8
2.5
2.7
2.6
2.3
2.4
Availability of professionals
3.5
4.0
2.7
3.0
2.0
3.3
3.0
2.3
2.7
3.2
2.5
2.9
Availability of technical workers
3.3
4.5
1.7
3.0
1.7
3.0
3.3
2.5
2.0
2.0
2.3
2.6
Availability of skilled workers
3.5
4.8
1.7
3.4
1.7
2.8
3.3
3.0
3.5
2.8
1.5
2.9
Availability of unskilled workers
4.3
5.0
4.9
4.6
4.3
5.0
5.0
4.3
4.6
4.6
3.0
4.5
Ease of finding workers with command of
3.8
5.0
3.1
3.5
2.0
4.0
4.3
4.5
4.8
4.2
4.8
4.0
language
Number of weekly work hours per
40.0
45.8
45.0
50.0
40.7
45.7
44.0
45.3
43.4
45.6
48.9
44.9
employee
Percentage of unionized workers
94.4
81.3
29.0
36.2
66.7
61.0
93.8
12.5
0.0
69.2
45.0
53.5
Average annual turn-over rate
14.3
4.5
4.8
6.2
0.1
3.2
0.0
5.0
22.0
3.4
10.6
6.7
* All scores calculating the availability of labor are rated from 1 – 5, with 5 symbolizing a better availability of labor and the score of 1 as worse.
Table 15: Labor market: Apparel*
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
Mauritius
A
Availability of managers
3.2
3.1
1.7
2.1
3.0
2.8
2.7
1.3
2.9
2.8
2.6
Availability of professionals
4.6
3.9
2.3
2.3
3.5
3.3
3.7
2.5
2.3
2.9
3.1
Availability of technical workers
3.4
3.7
2.3
2.3
3.0
3.0
3.0
2.0
2.3
3.0
2.8
Availability of skilled workers
3.8
3.7
2.3
3.4
2.5
2.8
2.7
2.8
2.9
2.3
2.9
Availability of unskilled workers
4.8
4.1
4.8
4.4
4.5
5.0
4.6
5.0
4.6
3.1
4.5
Ease of finding workers with command of
4.6
4.6
3.2
3.5
3.0
4.0
3.6
5.0
4.6
4.4
4.0
language
Number of weekly work hours per
41.0
45.4
45.0
52.7
40.0
45.7
40.0
45.0
48.3
49.3
45.2
employee
Percentage of unionized workers
64.0
80.7
17.9
58.7
50.0
61.0
53.6
0.0
0.0
19.3
40.5
Average annual turn-over rate
1.0
4.4
7.6
10.2
11.0
3.2
0.4
6.7
20.1
8.5
7.3
* All scores calculating the availability of labor are rated from 1 – 5, with 5 symbolizing a better availability of labor and the score of 1 as worse.
SNAPSHOT AFRICA - KENYA
Table 16: Labor market: Horticulture*
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Availability of managers
4.4
2.4
2.0
4.2
3.3
3.4
1.6
2.2
2.5
2.9
Availability of professionals
4.2
2.8
3.0
4.0
3.0
4.0
2.0
3.4
3.8
3.4
Availability of technical workers
4.0
3.4
2.9
3.6
2.7
3.6
2.0
1.8
2.8
3.0
Availability of skilled workers
4.6
3.8
3.0
2.6
3.3
2.8
4.0
3.2
2.8
3.3
Availability of unskilled workers
4.8
4.8
4.3
4.2
4.5
4.4
4.8
4.7
4.3
4.5
Ease of finding workers with command of
4.0
4.6
3.2
4.0
3.5
4.0
4.2
4.3
3.5
3.9
language
Number of weekly work hours per
44.8
45.4
44.0
50.5
36.3
37.3
46.2
49.2
45.1
44.3
employee
Percentage of unionized workers
49.6
24.2
1.7
0.0
47.5
0.0
74.0
0.2
45.3
26.9
Average annual turn-over rate
26.9
7.0
12.8
7.4
4.8
1.8
8.2
14.3
19.4
11.4
* All scores calculating the availability of labor are rated from 1 – 5, with 5 symbolizing a better availability of labor and the score of 1 as worse.
Table 17: Labor market: Food and Beverage Processing*
Africa
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Availability of managers
3.2
4.3
3.0
3.0
2.0
2.7
3.4
1.7
2.4
2.6
2.8
Availability of professionals
3.4
4.3
2.0
3.4
3.8
2.0
3.8
1.4
2.4
2.8
2.9
Availability of technical workers
3.4
4.3
1.0
3.3
3.4
3.0
3.6
2.6
3.2
4.0
3.2
Availability of skilled workers
4.0
4.5
4.0
3.4
2.8
2.7
3.0
3.8
3.0
3.8
3.5
Availability of unskilled workers
4.0
5.0
5.0
4.7
4.8
4.7
4.2
4.7
4.5
5.0
4.7
Ease of finding workers with command of
4.4
5.0
4.0
2.4
3.1
3.3
4.4
4.1
4.3
4.2
3.9
language
Number of weekly work hours per
40.0
51.9
40.0
42.9
44.0
44.6
42.0
47.8
50.3
40.7
44.4
employee
Percentage of unionized workers
85.0
0.0
53.0
2.5
78.0
66.3
37.0
43.8
10.0
51.2
42.7
Average annual turn-over rate
3.4
0.7
10.0
7.3
4.8
0.3
1.1
10.4
24.9
6.5
6.9
* All scores calculating the availability of labor are rated from 1 – 5, with 5 symbolizing a better availability of labor and the score of 1 as worse.
SNAPSHOT AFRICA - KENYA
Table 18: Labor market: Shared Services (Call Centers)*
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Availability of managers
4.6
3.2
2.0
2.4
2.3
3.6
3.0
2.5
2.6
3.0
2.9
Availability of professionals
4.6
3.8
3.2
3.0
3.0
4.0
3.0
4.0
3.4
3.4
3.5
Availability of technical workers
4.8
4.4
2.5
2.8
3.7
4.0
3.0
4.0
3.0
3.2
3.5
Availability of skilled workers
4.4
4.4
3.5
3.3
4.0
4.5
3.3
3.5
3.6
3.6
3.8
Availability of unskilled workers
5.0
4.4
4.4
4.0
4.7
4.4
4.0
4.9
4.8
3.8
4.4
Ease of finding workers with command of
4.4
5.0
3.0
3.6
3.7
4.0
3.0
4.5
4.2
3.6
3.9
language
Number of weekly work hours per
40.0
49.0
41.9
39.4
40.5
39.4
44.7
44.4
39.0
42.3
42.1
employee
Percentage of unionized workers
69.8
0.0
2.0
12.0
19.0
19.0
1.7
0.0
16.0
0.0
13.9
Average annual turn-over rate
1.7
17.6
13.7
6.1
3.6
5.1
20.3
17.9
11.7
22.5
12.0
* All scores calculating the availability of labor are rated from 1 – 5, with 5 symbolizing a better availability of labor and the score of 1 as worse.
Table 19: Labor market: Tourism (Hotels)*
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
South
Mauritius
A
Availability of managers
3.0
2.7
2.0
3.5
2.2
2.5
2.2
3.4
2.8
2.7
Availability of professionals
4.2
3.3
3.4
4.0
2.6
3.0
1.7
3.4
3.4
3.2
Availability of technical workers
3.8
3.7
2.4
2.0
2.6
3.0
2.7
3.6
2.6
2.9
Availability of skilled workers
4.2
3.7
2.8
2.0
2.4
3.4
3.8
4.0
2.4
3.2
Availability of unskilled workers
4.2
4.5
3.8
4.0
3.8
5.0
4.7
4.4
3.8
4.2
Ease of finding workers with command of
3.8
4.3
2.8
4.0
2.6
3.8
3.5
4.2
3.0
3.6
language
Number of weekly work hours per
40.0
47.5
44.6
45.3
42.4
46.5
50.2
42.0
46.4
45.0
employee
Percentage of unionized workers
96.0
83.3
21.0
81.7
56.2
54.0
21.3
17.8
5.0
48.5
Average annual turn-over rate
1.7
5.6
8.4
6.3
2.7
1.6
17.1
7.3
15.8
7.4
* All scores calculating the availability of labor are rated from 1 – 5, with 5 symbolizing a better availability of labor and the score of 1 as worse.
SNAPSHOT AFRICA - KENYA
Table 20: Access to inputs and outputs: Textile
Africa
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Percentage of raw materials needed for
75.0
77.5
98.8
78.0
16.7
99.0
12.5
65.6
36.0
70.8
56.7
62.4
production imported
Percentage of components needed for
1.5
100.0
89.6
97.0
70.0
99.6
47.0
90.6
62.6
55.6
95.0
73.5
production imported
Percentage of equipment/ chemicals
96.3
100.0
94.2
95.4
69.0
98.8
75.0
100.0
100.0
62.6
62.5
86.7
needed for production imported
Number of days to clear customs
13.5
12.8
11.5
4.8
3.0
8.0
4.3
12.0
3.3
5.5
13.4
8.4
Table 21: Access to inputs and outputs: Apparel
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
Mauritius
A
Percentage of raw materials needed for
52.5
86.0
97.5
80.8
90.0
99.0
52.9
67.5
55.8
48.3
73.0
production imported
Percentage of components needed for
68.8
99.3
79.2
97.1
85.0
99.6
70.0
95.0
70.4
77.1
84.2
production imported
Percentage of equipment/ chemicals
84.0
100.0
88.3
96.0
60.0
98.8
100.0
100.0
100.0
76.0
90.3
needed for production imported
Number of days to clear customs
7.6
13.0
8.1
5.8
0.8
8.0
5.7
5.1
6.2
3.2
6.3
Table 22: Access to inputs and outputs: Horticulture
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Percentage of raw materials needed for
21.4
76.0
21.4
42.0
31.7
64.0
80.0
21.7
0.0
39.8
production imported
Percentage of components needed for
42.0
96.0
33.3
100.0
35.0
47.0
96.0
26.0
0.0
52.8
production imported
Percentage of equipment/ chemicals
45.0
98.0
32.5
73.0
86.7
64.0
98.8
81.7
15.0
66.1
needed for production imported
Number of days to clear customs
19.0
13.3
8.2
5.6
3.4
3.3
9.4
5.5
12.0
8.8
SNAPSHOT AFRICA - KENYA
Table 23: Access to inputs and outputs: Food and Beverage Processing
Africa
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Percentage of raw materials needed for
61.0
37.5
100.0
31.2
52.7
60.0
67.0
43.8
40.0
4.0
49.7
production imported
Percentage of components needed for
34.4
43.5
100.0
1.2
49.2
90.0
34.0
30.0
31.5
5.8
42.0
production imported
Percentage of equipment/ chemicals
74.4
97.5
100.0
60.0
86.0
90.0
97.0
97.8
70.8
41.0
81.4
needed for production imported
Number of days to clear customs
6.6
10.0
2.0
7.8
3.6
3.3
4.0
58.8
4.5
9.7
5.7
Table 24: Access to inputs and outputs: Shared Services (Call Centers)
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Percentage of raw materials needed for
80.0
66.7
0.0
n/a
n/a
n/a
n/a
0.0
0.0
29.3
production imported
Percentage of components needed for
10.0
n/a
100.0
65.0
n/a
59.0
n/a
0.0
0.0
39.0
production imported
Percentage of equipment/ chemicals
95.0
100.0
45.0
83.2
100.0
81.6
100.0
99.3
2.0
78.5
needed for production imported
Number of days to clear customs
12.7
14.0
n/a
5.0
7.0
8.4
21.0
7.8
n/a
10.8
Table 25: Access to inputs and outputs: Tourism (Hotels)
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
South
Mauritius
A
Percentage of raw materials needed for
n/a
6.7
n/a
20.8
80.0
0.0
n/a
0.0
50.0
26.3
production imported
Percentage of components needed for
n/a
53.3
78.0
68.1
55.0
22.0
n/a
0.0
n/a
46.1
production imported
Percentage of equipment/ chemicals
100.0
47.5
78.0
92.5
70.0
46.0
88.0
0.0
n/a
65.3
needed for production imported
Number of days to clear customs
15.5
18.0
n/a
14.6
9.0
6.7
52.3
n/a
n/a
19.3
SNAPSHOT AFRICA - KENYA
Table 26: Infrastructure: Textile
Africa
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Quality of landline communications*
3.3
2.0
2.7
2.8
2.3
3.8
4.5
3.3
4.3
4.2
4.5
3.4
Number of days to install a phone
11.0
39.5
63.3
67.4
46.0
3.5
6.8
13.8
6.7
19.6
7.0
25.9
Quality of Internet*
3.3
3.0
1.0
1.4
2.0
3.7
2.3
2.5
3.0
4.0
4.3
2.8
Number of days to install a broadband line
7.0
8.8
n/a
2.5
7.5
1.0
6.7
5.0
9.4
68.2
3.7
12.0
Number of hours of blackouts experienced
9.0
19.5
1.2
4.9
2.0
25.7
3.3
79.0
31.5
1.2
1.8
16.3
per month
Number of hours of brownouts
12.0
52.8
0.4
0.9
0.0
8.5
2.9
96.3
28.3
0.2
11.9
19.5
experienced per month
Average number of hours of generator
9.0
16.0
0.0
7.6
2.0
5.0
2.9
16.0
22.0
0.8
2.2
7.6
usage per month
Number of days per year of water supply
93.0
7.5
30.5
9.8
0.7
296.0
0.8
48.7
0.0
9.6
4.5
45.5
shortage
Quality of the public waste treatment
3.3
4.0
2.4
1.0
1.3
1.0
1.0
2.0
1.6
3.4
4.0
2.3
system*
Number of alternative sites considered
1.3
1.0
2.1
4.3
2.7
1.5
1.0
1.0
5.6
1.0
1.7
2.1
during investment process
* All scores calculating these infrastructure qualities are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
Table 27: Infrastructure: Apparel
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
Mauritius
A
Quality of landline communications*
3.4
3.3
2.3
3.4
4.0
3.8
4.4
3.8
4.0
4.1
3.7
Number of days to install a phone
19.5
26.4
105.5
86.8
12.0
3.5
5.0
4.0
7.3
9.3
27.9
Quality of Internet*
3.0
3.3
1.0
1.4
1.0
3.7
3.0
3.0
2.0
4.3
2.6
Number of days to install a broadband line
10.5
6.4
n/a
3.5
1.0
1.0
7.4
3.5
8.3
26.5
7.6
Number of hours of blackouts experienced
7.0
19.6
1.8
24.5
2.0
25.7
7.5
12.0
32.0
1.1
13.3
per month
Number of hours of brownouts
5.4
31.4
0.2
24.2
0.0
8.5
1.5
8.0
28.3
6.6
11.4
experienced per month
Average number of hours of generator
7.8
16.8
0.1
60.0
2.0
5.0
3.0
16.0
32.3
0.1
14.3
usage per month
Number of days per year of water supply
3.8
17.1
61.1
57.9
0.0
296.0
5.7
172.0
0.3
2.4
61.6
shortage
Quality of the public waste treatment
4.3
4.1
1.8
1.0
1.5
1.0
1.0
2.0
1.6
3.9
2.2
system*
Number of alternative sites considered
1.0
1.3
1.2
4.4
1.0
1.5
1.2
1.6
4.0
1.6
1.9
during investment process
* All scores calculating these infrastructure qualities are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
SNAPSHOT AFRICA - KENYA
Table 28: Infrastructure: Horticulture
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Quality of landline communications*
2.6
2.2
3.3
2.6
3.8
3.8
2.2
3.3
3.4
3.0
Number of days to install a phone
9.6
94.7
52.5
118.0
1.7
10.0
21.0
8.3
174.4
54.5
Quality of Internet*
3.6
3.2
2.6
1.0
3.8
2.4
3.6
3.5
3.8
3.0
Number of days to install a broadband line
4.6
117.6
n/a
4.8
1.7
5.8
4.3
25.8
15.8
22.5
Number of hours of blackouts experienced
76.8
5.8
95.0
52.0
52.6
58.4
45.6
179.5
9.2
63.9
per month
Number of hours of brownouts
106.0
102.0
101.7
1.1
80.5
7.5
120.4
6.6
2.5
58.7
experienced per month
Average number of hours of generator
76.8
93.0
45.0
48.0
124.8
58.0
54.8
330.0
9.2
93.3
usage per month
Number of days per year of water supply
1.0
0.0
0.4
3.6
4.6
63.0
0.0
0.3
0.0
8.1
shortage
Quality of the public waste treatment
3.2
3.2
1.0
1.0
1.0
1.0
1.0
4.7
4.0
2.2
system*
Number of alternative sites considered
2.0
1.0
4.2
4.0
1.8
4.2
1.8
7.3
1.3
3.1
during investment process
* All scores calculating these infrastructure qualities are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
Table 29: Infrastructure: Food and Beverage Processing
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Quality of landline communications*
3.4
2.8
3.4
3.4
3.8
4.4
4.0
4.0
3.6
3.6
Number of days to install a phone
5.6
14.5
41.9
38.0
4.0
10.6
10.4
7.0
19.3
16.8
Quality of Internet*
3.3
3.3
1.4
3.0
3.8
2.0
3.1
2.8
4.0
3.0
Number of days to install a broadband line
4.0
5.8
5.0
2.4
3.0
7.0
4.3
5.3
15.5
5.8
Number of hours of blackouts experienced
56.8
14.0
36.0
27.8
40.0
36.8
54.6
166.3
1.2
48.2
per month
Number of hours of brownouts
54.8
13.0
67.4
6.6
n/a
10.0
42.3
137.8
0.4
41.5
experienced per month
Average number of hours of generator
62.6
25.0
50.0
28.8
n/a
25.0
133.3
26.5
1.2
44.1
usage per month
Number of days per year of water supply
4.4
0.0
0.7
10.0
365.0
38.5
236.9
5.0
0.0
73.4
shortage
Quality of the public waste treatment
4.4
3.8
1.0
1.0
1.5
1.0
1.6
1.4
4.0
2.2
system*
Number of alternative sites considered
1.3
1.0
1.4
1.6
2.0
2.8
1.1
1.7
1.5
1.6
during investment process
* All scores calculating these infrastructure qualities are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
SNAPSHOT AFRICA - KENYA
Table 30: Infrastructure: Shared Services (Call Centers)
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Quality of landline communications*
3.6
3.6
3.3
2.8
4.0
4.4
3.5
4.6
4.0
3.4
3.7
Number of days to install a phone
26.5
11.8
44.8
49.4
2.8
3.4
24.0
5.0
39.3
10.8
21.8
Quality of Internet*
3.8
3.4
2.8
2.4
3.7
3.2
3.0
3.9
4.4
4.0
3.5
Number of days to install a broadband line
10.5
8.3
15.8
5.4
1.0
5.2
13.0
6.7
4.5
3.5
7.4
Number of hours of blackouts experienced
16.8
10.3
54.8
16.2
4.5
16.4
38.0
66.9
0.4
0.4
22.5
per month
Number of hours of brownouts
47.6
4.7
11.0
1.5
2.0
67.8
92.7
8.3
0.0
1.4
23.7
experienced per month
Average number of hours of generator
42.4
n/a
96.7
16.3
n/a
14.4
15.3
74.6
0.4
0.5
32.6
usage per month
Number of days per year of water supply
2.0
0.6
0.0
0.0
0.5
0.5
14.0
0.6
0.0
0.0
1.8
shortage
Quality of the public waste treatment
1.0
5.0
1.0
1.0
1.0
1.0
2.7
3.3
4.4
4.0
2.4
system*
Number of alternative sites considered
2.0
1.4
8.2
3.0
2.0
2.2
2.0
3.3
2.7
3.0
3.0
during investment process
* All scores calculating these infrastructure qualities are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
Table 31: Infrastructure: Tourism (Hotels)
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
South
Mauritius
A
Quality of landline communications*
3.0
2.6
3.4
2.7
3.8
3.6
3.5
4.0
3.8
3.4
Number of days to install a phone
184.8
57.0
43.8
35.3
1.7
76.6
32.3
14.3
26.4
52.5
Quality of Internet*
4.0
3.2
1.0
3.2
3.8
3.2
4.0
4.0
4.3
3.4
Number of days to install a broadband line
8.7
5.8
22.0
3.4
1.7
3.2
28.0
25.1
95.6
21.5
Number of hours of blackouts experienced
13.4
123.7
36.3
9.0
52.6
36.0
278.5
10.5
6.5
62.9
per month
Number of hours of brownouts
16.6
0.7
85.5
1.0
80.5
1.8
450.0
0.0
10.0
71.8
experienced per month
Average number of hours of generator
13.4
209.0
45.0
8.4
124.8
34.0
274.5
3.9
6.5
79.9
usage per month
Number of days per year of water supply
10.0
18.0
0.7
7.2
4.6
73.6
301.7
0.2
1.9
46.4
shortage
Quality of the public waste treatment
4.8
3.5
1.0
1.0
1.0
1.0
1.2
4.2
2.0
2.2
system*
Number of alternative sites considered
1.0
1.0
3.3
11.0
1.8
1.4
1.7
2.0
1.0
2.7
during investment process
* All scores calculating these infrastructure qualities are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
SNAPSHOT AFRICA - KENYA
Table 32 Living conditions: Textile*
Africa
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Cost of living
3.5
2.5
2.3
2.8
2.0
3.4
1.5
4.0
3.0
3.4
3.0
2.9
level of safety
3.8
1.0
1.4
3.2
4.3
3.6
3.5
2.5
3.0
2.8
3.0
2.9
Quality of international schools
3.5
4.5
3.6
3.5
2.0
2.3
4.0
4.0
1.8
3.4
n/a
3.3
Quality of local schools
3.3
4.0
2.0
3.0
1.0
2.8
3.0
2.0
2.0
3.8
3.0
2.7
Health care
3.0
2.0
2.1
1.6
1.0
2.4
3.0
2.0
1.8
3.0
3.0
2.3
Quality of recreational services
3.0
4.0
2.1
2.6
1.3
2.2
2.0
2.0
2.2
4.0
4.0
2.7
* All scores calculating the quality of living conditions are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
Table 33: Living conditions: Apparel*
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
Mauritius
A
Cost of living
4.2
1.7
1.7
3.0
2.0
3.4
2.0
1.7
2.9
3.4
2.6
level of safety
4.4
2.0
1.8
3.4
3.5
3.6
4.0
2.3
3.6
4.0
3.3
Quality of international schools
4.2
4.1
3.2
3.4
1.5
2.3
4.3
2.7
2.4
3.8
3.2
Quality of local schools
4.2
3.3
2.0
3.0
1.5
2.8
3.0
2.0
2.5
4.3
2.8
Health care
4.2
2.7
2.2
2.1
3.0
2.4
3.3
1.3
2.1
3.6
2.7
Quality of recreational services
4.2
3.6
1.2
2.7
1.5
2.2
3.0
2.0
2.1
2.6
2.5
* All scores calculating the quality of living conditions are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
Table 34: Living conditions: Horticulture*
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Cost of living
4.4
2.6
2.6
2.9
2.7
3.0
3.0
3.2
3.6
3.1
level of safety
4.2
1.4
3.3
4.2
1.3
4.0
2.0
3.2
2.2
2.9
Quality of international schools
3.4
4.0
3.9
4.0
n/a
3.8
3.4
3.7
3.6
3.7
Quality of local schools
3.2
2.2
n/a
2.0
1.7
3.8
1.6
1.8
3.0
2.4
Health care
3.8
2.2
2.4
2.0
1.7
3.4
2.0
2.0
2.8
2.5
Quality of recreational services
3.6
4.0
2.9
2.6
2.3
4.0
2.6
3.5
4.2
3.3
* All scores calculating the quality of living conditions are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
SNAPSHOT AFRICA - KENYA
Table 35: Living conditions: Food and Beverage Processing*
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Cost of living
4.0
2.5
3.1
3.0
2.0
2.0
1.4
2.6
4.2
2.8
level of safety
3.8
2.0
3.6
4.4
2.3
3.8
3.9
3.8
2.2
3.3
Quality of international schools
3.6
4.5
4.3
3.2
3.5
3.8
3.3
3.0
3.8
3.7
Quality of local schools
4.0
3.3
2.0
1.7
2.5
3.6
2.2
3.0
2.8
2.8
Health care
3.6
2.0
2.3
2.1
1.7
3.4
1.9
1.8
3.0
2.4
Quality of recreational services
3.0
2.8
3.6
2.8
2.3
4.0
2.0
2.6
4.2
3.0
* All scores calculating the quality of living conditions are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
Table 36: Living conditions: Shared Services (Call Centers) *
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Cost of living
3.8
2.4
3.2
2.2
2.5
2.0
3.0
4.0
4.6
3.3
3.1
level of safety
4.6
2.4
2.8
4.2
1.8
4.0
2.5
3.4
2.6
3.5
3.2
Quality of international schools
4.0
4.2
4.0
2.9
2.7
4.0
3.0
3.1
4.2
3.7
3.6
Quality of local schools
3.6
3.5
1.7
1.5
2.0
3.1
3.0
2.1
4.2
2.0
2.7
Health care
4.0
2.5
2.0
1.3
1.8
2.6
3.5
1.9
4.2
2.0
2.6
Quality of recreational services
2.6
3.8
3.3
1.6
2.5
3.0
3.0
2.0
4.4
2.8
2.9
* All scores calculating the quality of living conditions are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
Table 37: Living conditions: Tourism (Hotels)*
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
South
Mauritius
A
Cost of living
4.0
2.3
2.2
2.0
3.0
3.0
3.0
4.0
3.0
2.9
level of safety
4.4
2.3
3.2
3.5
2.4
3.8
3.5
1.6
3.2
3.1
Quality of international schools
4.0
4.3
4.5
3.5
2.3
4.3
2.0
3.8
3.8
3.6
Quality of local schools
4.0
3.5
n/a
1.8
1.8
1.7
1.4
3.3
3.0
2.6
Health care
3.4
1.8
2.0
1.7
1.4
3.0
1.3
4.0
3.2
2.4
Quality of recreational services
2.2
3.8
1.8
1.7
1.8
3.0
1.3
4.0
3.4
2.6
* All scores calculating the quality of living conditions are rated from 1 – 5, with 5 symbolizing a better performance and the score of 1 as worse.
0
SNAPSHOT AFRICA - KENYA
Table 38: Operating costs: Textile
Africa
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Annual gross salary (in USD)
• Managers
23,190
13,183
14,413
25,511
18,511
7,854
12,569
7,580
18,581
64,463
20,420
20,571
• Professionals
20,581
12,051
27,704
5,245
4,553
15,071
10,293
11,603
13,822
45,181
17,637
16,704
• Technical workers
8,575
6,670
14,051
2,845
3,096
3,712
9,897
10,089
11,221
39,394
16,027
11,416
• Skilled workers
3,505
2,398
5,203
1,135
2,316
2,145
4,150
1,190
2,970
12,510
2,962
3,680
• Unskilled workers
1,417
1,065
3,090
618
1,029
998
2,082
704
1,615
5,315
3,339
1,934
Average wage burden as
88
83
95
81
77
67
83
81
70
79
75
80
percentage of gross salary
Interest rate (percent)
20
16
11
18
10
7
11
12
15
10
10
13
Table 39: Operating costs: Apparel
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
Mauritius
A
Annual gross salary (in USD)
• Managers
4,519
15,771
22,557
23,801
14,252
7,854
9,878
9,321
17,637
22,945
14,853
• Professionals
6,554
11,127
27,704
5,670
5,048
15,071
12,074
10,834
11,821
15,822
12,173
• Technical workers
8,053
6,603
23,086
5,151
3,266
3,712
8,981
8,533
8,346
16,137
9,187
• Skilled workers
1,011
1,420
6,645
1,318
2,286
2,145
2,925
1,377
2,253
2,871
2,425
• Unskilled workers
570
1,048
4,772
610
1,158
998
1,746
855
1,067
2,989
1,581
Average wage burden as
88.0
79.4
95.0
71.3
75.5
66.8
78.5
87.5
77.4
81.7
80
percentage of gross salary
Interest rate (percent)
16.0
12.7
12.8
17.0
n/a
7.1
11.7
10.2
16.0
10.5
13
Table 40: Operating costs: Horticulture
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Annual gross salary (in USD)
• Managers
5,246
20,172
8,263
9,026
14,095
36,413
24,781
22,577
50,814
21,265
• Professionals
6,135
16,049
1,813
4,216
12,089
19,398
22,645
11,754
36,547
14,516
• Technical workers
2,785
10,572
2,506
4,038
4,842
9,947
5,007
4,215
19,924
7,093
• Skilled workers
1,637
1,846
732
1,455
3,442
2,629
1,379
2,162
14,169
3,272
• Unskilled workers
774
1,037
480
750
1,069
1,223
1,511
1,428
3,721
1,333
Average wage burden as
88.0
79.0
47.0
56.0
83.8
80.8
87.2
81.1
79.4
75.8
percentage of gross salary
Interest rate (percent)
22.0
6.6
19.3
12.8
5.1
9.8
8.9
9.1
8.1
11.3
SNAPSHOT AFRICA - KENYA
Table 41: Operating costs: Food and Beverage Processing
Africa
verage
Ghana
Kenya
l
esotho
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
A
Annual gross salary (in USD)
• Managers
11,017
16,652
29,316
15,910
35,002
35,774
24,933
25,894
28,608
88,715
31,182
• Professionals
8,948
13,908
32,573
3,386
13,755
14,982
15,416
22,712
8,551
103,825
23,806
• Technical workers
5,676
6,222
19,544
2,454
8,301
11,094
11,473
13,561
4,447
55,531
13,830
• Skilled workers
3,551
3,534
9,772
1,111
3,500
7,433
6,277
4,998
3,209
24,098
6,748
• Unskilled workers
2,265
1,693
4,886
506
2,289
1,495
3,473
2,141
1,433
11,870
3,205
Average wage burden as
82
75
n/a
79
72
70
79
83
79
75
77
percentage of gross salary
Interest rate (percent)
20
8
11
19
10
n/a
10
12
11
11
13
Table 42: Operating costs: Shared Services (Call Centers)
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
Uganda
South
Mauritius
A
Annual gross salary (in USD)
-
• Managers
23,265
14,846
10,284
28,674
25,713
30,080
20,814
33,045
65,472
17,123
28,021
• Professionals
25,502
11,171
3,226
20,068
12,871
20,100
24,660
14,247
101,792
14,498
25,960
• Technical workers
10,738
8,421
2,642
11,863
7,838
13,534
n/a
9,480
51,010
11,416
14,441
• Skilled workers
5,369
3,921
1,104
7,942
3,199
8,445
4,045
4,701
29,121
4,281
7,538
• Unskilled workers
3,803
1,444
698
2,496
1,685
4,902
n/a
2,648
12,899
2,414
3,822
Average wage burden as
78
86
65
75
89
70
75
81
82
83
77.8
percentage of gross salary
Interest rate (percent)
9
16
n/a
7
n/a
7
7
18
10
n/a
10.7
Table 43: Operating costs: Tourism (Hotels)
Africa
verage
Ghana
Kenya
Madagascar
Mali
Mozambique
Senegal
T
anzania
South
Mauritius
A
Annual gross salary (in USD)
• Managers
4,295
19,156
21,272
30,438
29,396
27,645
30,379
38,111
42,164
26,984
• Professionals
6,085
10,950
7,828
10,933
13,092
16,396
27,223
43,974
30,685
18,574
• Technical workers
2,021
5,196
1,916
6,325
6,214
12,239
17,941
21,889
7,301
9,005
• Skilled workers
1,678
2,465
1,009
2,888
2,588
4,794
4,644
12,508
4,575
4,128
• Unskilled workers
1,275
1,274
706
1,545
1,932
2,287
2,654
6,078
2,452
2,245
Average wage burden as
88.0
85.0
61.6
78.7
61.1
71.6
74.3
70.3
78.0
74
percentage of gross salary
Interest rate (percent)
n/a
13.8
15.9
12.3
6.6
8.5
6.1
10.5
12.0
11
SNAPSHOT AFRICA - KENYA
Appendix IV: The Kenya Investment Authority (KIA)
The Kenya Investment Authority (KIA) was established
The Kenya Investment Authority (KIA)
by the Investment Promotion Act, 2004, as a more
8th Floor, National Bank of Kenya Building
powerful successor organization to the Investment
Harambee Avenue
Promotion Centre established in 1986, with the ability to
P.O. Box 55704, 00200 City Square
grant investment certificates and play a more active role
Nairobi, Kenya
in promoting and facilitating investments. The Primary
Tel: +254.20.22.1401-4
role of the KIA is to assist investors in obtaining permits,
Fax: +254.20.24.3862
licenses, incentives and exemptions, promote both
info@investmentkenya.com
foreign and domestic investment opportunities, advise
www.investmentkenya.com
the Government of Kenya on improving the investment
climate, and facilitate and manager investment sites,
estates and land. The organization is run by a board of
directors, composed of individuals from both the public
and private sector, has a staff of 69, and the Managing
Director, Ms. Susan Kikwai is responsible for man-
agement.
(Source: UNCTAD, KIA)
SNAPSHOT AFRICA - KENYA
www.miga.org
SNAPSHOT AFRICA - KENYA
