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Employment Intensity of Non-Agricultural Growth: the case of
Burundi
RESEARCH PROPOSAL
Presented to
Partnership for Economic Policy (PEP)
By
Nicodème NIMENYA
&
Espérance KAMARIZA, Roselyne MUNEZERO, Youssouf KONE
BURUNDI
April 15, 2013
1
SECTION A
1. Abstract
After a long decade of conflict and economic slowdown from 1993 to 2003, Burundi
is progressively experiencing a new economic dynamism with a Gross Domestic
Product (GDP) growth rate of 4.2% in 2011 against 3.6% in 2006. While agriculture was
still the dominant sector of the economy until 2006 where its contribution was 43.64%,
its share in the GDP is since declining at the benefit of the services that have
significantly increased from 37.86% in 2006 to 46.25% in 2011 while the share of
industry remains almost constant around 18.5%.
Despite these recent figures, both researchers and policy-makers always consider
the predominance of Burundian agricultural sector in terms of employment, food
security, foreign earnings, and finally GDP formation. Less attention is paid to nonfarm sector and its possible impact on employment and poverty alleviation has not
yet been highlighted. This research project aims to bridge this gap. In addition to the
impact of non-farm sector on employment and income generation, this research
intends to assess the economic impact of regional trade liberalization on non-farm
activities in Burundi using macro-policies simulations.
The role of non-farm activities on employment as well as the impact of changes in
tariffs following the establishment of the new East African Community (EAC)
Common External Tariff (CET) and tax harmonization in 2010 will be investigated using
a Computable General Equilibrium (CGE) model. A significant contribution of the
research will also be to update the 2006 Social Accounting Matrix (SAM).
Given that employment promotion and regional integration are at the forefront of
the national strategy for growth and poverty reduction for which the Government of
Burundi is actively looking for funds, policy implications and recommendations drawn
from this research will be of particular interest for policy-makers and development
practitioners. Furthermore, trainings courses and the use of CGE models will obviously
be helpful in terms of capacity development of Burundian research community.
Given that this research project is a result of a large consultation between
researchers and key strategic national institutions, a better cooperation between
researchers and policy-makers is also expected.
2. Main research questions and contributions
2.1. Key research questions and policy relevance
Background on Growth and Employment in Burundi
Employment, growth and poverty alleviation are at the forefront of the second
generation of current strategic document for growth and poverty reduction (CSLP II)
for the period 2012-2015 initiated by the Government of Burundi.
The agricultural sector is predominant in terms of rural employment (90% of total
population and 97% of poor people live in rural areas), food supply (the agriculture
contributes to about 95% in meeting food needs), contribution to the Gross Domestic
2
Product (GDP) formation (the value added of this sector represents more than 35% of
GDP), and more than 95% of foreign exports earnings in 2011. Given that the mining
sector is mainly informal or at an infant stage, the primary sector is reduced to
agriculture.
Despite the importance of agriculture in the Burundian economy, this sector is not
likely to stimulate an overall economic growth. The economic theory suggests that
an agricultural surplus is a prerequisite to industry and, lately, service generation
(Baran, 1957; De Janvry, 1975). The growth rate in agriculture is about 2.8% in 2012
and has probably minor effect on per capita GDP and poverty alleviation given that
total population is growing at approximately similar rate (2.4% in 2010). Soil
deterioration, insufficient financial resources and poor investment in agricultural
research, poor rural infrastructures combined with limited access to agricultural
inputs, and unfavorable environmental and climatic conditions hampered the
agricultural sector in the last 10 years.
The secondary sector, accounting for about 18.56% of GDP in 2011 mainly serves the
domestic market and the tertiary sector (services), representing around 46 % of GDP
in 2011, has displayed burgeoning growth since 2000, particularly in the mobile
telephony segment.
A recent study (UNDP, 2010) on the potential of growth and effect on household
income in Burundi showed that key contributing sectors to GDP growth and poverty
alleviation are agriculture, food industries, hotels, real estate and trade. They respond
strongly to an increase in demand from the rest of the economy, and in turn have a
ripple effect on other sectors.
It is often recognized that rural economies are not purely agricultural and that farm
households across the developing world earn an increasing share of their income
from non-farm activities (Smirt et al., 2010)1. Haggblade et al. (2002) find that rural
non-agricultural activities account for about 25% of rural employment and 35-40% of
rural income across the developing world. More frequently, agricultural and nonagricultural activities are linked together through drivers of non-farm activities, i.e.
“pull” and “push” factors will be investigated where “pull” factors mean attractive
opportunities or incentives while “push” factors are more distress’s responses (Davis,
2001).
Recent findings show that non-farm activities have high potential impact in terms of
economic development and poverty alleviation (Simrit et al., 2010). Due to its faster
development and higher growth rate compared to agriculture, rural non-agricultural
employment is then considered as one of “the robust policies to tackle the longstanding issue of poverty and income inequality in rural areas of many developing
countries” (Rajasekhar and Biradar, 1998; Biradar, 2008). Despite its important
contribution to economic development, growth in non-agricultural activities in
Burundi didn’t receive much attention from policy makers, development
practitioners and researchers.
Following Simrit et al. (2010), rural non-farm income exceeds farm labor income by a factor
20 to 1 Africa. In addition, while there is seasonal farm unemployment, non-farm activities are
less affected by seasonality.
1
3
Research Questions
In order to fully investigate the employment effect of non-agricultural growth in the
context of Burundian economy, the research intends to address the following main
research questions:
1. What is the poverty impact of growth in non-agricultural activities?
During the last years, the non-agricultural sectors experienced positive growth and
their contribution to economic growth increased significantly to the detriment of the
agricultural sector. The average annual growth rate of the service sector was about
more than 3% in 2009 while the manufacturing sector growth rate increased from
2.3% in 2008 to 6.3% in 2009. This research will assess the poverty implication of the
growth in the manufacturing and service sectors using a computable general
equilibrium analysis. More details on how this research question will be tackled are
provided on section 4 devoted to methodology.
2. How the regional trade liberalization (elimination of internal tariffs and duties) at
the EAC level is affecting employment in non-farm activities?
Trade liberalization and integration into the regional and global economy are major
pillars of the national strategic framework for growth and Poverty Reduction (CSLP II)
in Burundi and the country has a relatively open trade policy regime. According to
data collected in 2008, trade openness is around 40% and the country is part to
several regional trade integration initiatives like the Common Market for Eastern and
Southern Africa (COMESA) and the East African Community (EAC). The last
commitment in this direction is the beginning of negotiation for a tripartite
agreement SADC-COMESA-EAC aimed at creating a free trade area (FTA) among
the three regional economic communities (RECs).
It is within the EAC that Burundi has made its major progress in terms of regional trade
integration. Indeed, the country has signed the treaty of accession to the EAC on
June 18, 2007, which resulted in the implementation of the Protocol on Customs
Union (in force in the region since 1 January 2005). The Common External Tariff (CET)
currently used by EAC Partner States is aligned with that of COMESA: 0% for raw
materials and equipment, 10% on intermediate goods and 25% on finished products.
The CET rates are relatively higher than the former (national) tariff and the applied
rate is above the bound rate for certain products.
In July 2010, the common market protocol came into force. Currently, Burundi is
trying to implement the various measures under the Protocol. Burundi is also
negotiating with the European Union (EU) the Economic Partnership Agreement
(EPA) since 2007. An interim EPA was initialed on 23 November 2007 in Kampala. This
agreement provides the conditions for market opening between the parties: Burundi
is committed to liberalize 82.6% of imports from the EU by 2033, while the EU maintains
a free access Law and quotas for imports from the Burundi.
Customs duties are the main instrument of Burundi’s trade policy. Membership of EAC
requires Burundi to adjust its tariffs on imports from EAC countries to bring it into line
with the Customs Union principle of applying a Common Internal Tariff. The
programme for gradual elimination of internal tariffs within the EAC, adopted in 2005,
was completed in January 2010. EAC members had adopted an asymmetrical tariff
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reduction approach with a transitional period of five years, in order to account for
the differences in the size and structure of their economies. Burundi and Rwanda
started implementing the provisions of the Customs Union from July 2009. Tariffs on
trade between Kenya and Burundi had already been eliminated under the
Common Market for Eastern and Southern Africa (COMESA). There are no longer any
internal tariffs on intra-EAC trade.
The measure that will have the greatest impact and implication for Burundi is the
adoption of the new CET. However, it is not yet clear on how these changes related
to the regional integration process will affect the non agricultural sector in term of
labor market regulation, wages and employment.
The research intends to simulate a complete elimination of internal tariff on raw
material and capital goods and a 20% decrease respectively on intermediate and
final goods. A gradual elimination of tariff with the EU in the context of the EPA will
also be simulated.
2.2.
Description of the specific policy issues/needs that the research aims to
address; how the potential outcomes/findings may be used in policy making?
This research is expected to be implemented within 12 to 14 months. The first
semester will be used to make a literature review, a data collection (data on trade
and employment), updating the SAM of 2006, and PEP schools attendance. CGE
modeling as well as additional PEP training sessions will be organised during the
second semester. The team will simultaneously work on research communications
and valorisation.
The proposed research is a useful contribution to the current national strategic
framework for economic growth and poverty reduction initiated by the Government
of Burundi for the period 2012-2017. This framework is, along with the “Burundi Vision
2025”, the main tools of macroeconomic planning aiming at achieving the
Millennium Development Goals (MDG).
Obviously, this strategic framework is a result of several consultations from
policymakers, and key stakeholders such as the private sector, the civil society,
bilateral and multilateral donors. Hence any project stemming from this framework
keeps a consultation status. All the technical Ministries (Agriculture and Livestock,
Environment and Land Management, Mines and Energy, Finance and Planning,
Trade and Industry, Justice and Regional Integration) are involved in this national
planned setting. Furthermore, the team has extended its consultations to most of
these institutions. Information on these consultations and perceptions from persons of
contact is detailed in section 4 devoted to research communication strategy.
Methodology
In investigating the central question on employment intensity of non-agricultural
growth, we intend to adopt a methodological approach made of several successive
stages. In the lines below, we briefly describe what we are going to do, stage by
stage.
5
First stage: An overview of non-agricultural activities
Before detailing our responses to our two research questions, we will start by a
literature review of the heterogeneity of non-agricultural activities. This will enable a
full description of the most predominant of them in both time and spatial dimensions.
To do so, we should refer to existing databases. More details are provided in section
3 (data requirements & sources). Simrit et al. (2010) find that non-farm activities
emerge from exogenous chocks such as rainfall. Reardon (1998) finds that Rural NonFarm Activities (RNF) activities affect the performance of agriculture by providing
farmers with cash to invest in productivity-enhancing inputs. Alternatively, RNF sector
grows rapidly where output is available for processing and distribution.
Second stage (first and second research questions): (i) impact of non-agricultural
growth on poverty alleviation ;(ii) effects of regional trade liberalization on non-farm
employment.
These two research questions are to be undertaken with the use of macro-policies
simulations and Computable General Equilibrium modeling analysis. Indeed the
macro context involving devaluation or overvaluation of national currency, trade
liberalization (reduction of trade and non-trade barriers, fiscal deficits, cuts in
subsidies, etc., see trade liberalization scenarios described above) are more likely to
affect the development of RNF sector. For more details, see trade liberalizations
scenarios described above in section 2.1. In particular, the CGE model will be based
on the PEP1-T single country model. The PEP 1-T model is a recursive dynamic general
equilibrium model designated for the study of a national economy, which
distinguishes several categories of factors (labor and capital) and takes into account
all possible transfers between agents and large set of tax instruments.
All these above mentioned methodologies are largely used by the research
community. However in the particular context of Burundi, these methods have not
been used before. Hence the results stemming from these methods are more likely to
be innovative.
3. Data requirements and sources
Employment, growth and poverty alleviation are at the forefront of the national
strategy for poverty reduction (CSLP II). Hence, one of the programs in place to
assess the impact of CSLP is the national strategy for statistical development (SNDS)
that is a matrix of main indicators for monitoring activities undertaken within CSLP,
among others, rural non-agricultural employment.
Other sources of data are those relating to households surveys (Unified Questionnaire
on welfare based indicators 2006 “Questionnaire unifié des indicateurs de base du
bien-être de 2006”, nutritional survey (UNICEF 2007), general census of population
and housing (RGPH 2008), Monitoring of vulnerability assessment (WFP 2008), Health
and Demography Survey (EDS 2010), National Agricultural Survey (ENA 2012).
Data required to deal with the two research questions are mainly the Social
Accounting Matrix. An updated Social Accounting Matrix (SAM) is required to draw
the possible effects of macro-simulations using the CGE Model. The data used to
build the social accounting matrix (SAM) of Burundi are those of the year 2006 and
are essentially national accounts including the Input-Output table and elements of
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the Integrated Economic Accounts Table (TCEI). Data from the Balance of Payments
have also been exploited. The 2006 Social Accounting Matrix of Burundi includes a
total of seventy (70) accounts grouped into five (5) categories: Activity branches,
Commodities, Factors of production, Agents, and Accumulation.
While the team members have the necessary background and skills to build a new
SAM (some of them participated in a training course on Building and updating a
SAM last year with AGRODEP) and that the necessary data are available to do so,
we will concentrate in updating the existing SAM of 2006. The major updates will be
on the labor market structure and disaggregation of the trade module, which are
currently missing in the existing SAM. Because we will assess the employment effects
of the regional trade integration within the East African Community region, the main
trade data we will bring are the trade flows (imports and exports) between Burundi
and the other EAC Partner States. In doing so, trade flows in Burundi will be
disaggregating between the EAC members states (Kenya, Uganda, Rwanda and
Tanzania) and the rest of the world.
The data used to build up the social accounting matrix (SAM) of Burundi in 2006 are
essentially national accounts including the Input-Output table and elements of the
Integrated Economic Accounts Table (TCEI). Data from the Balance of Payments
have also been exploited. The 2006 Social Accounting Matrix of Burundi includes a
total of seventy (70) accounts grouped into five (5) categories: Activity branches,
Commodities, Factors of production, Agents, and Accumulation. An analysis of propoor growth in Burundi based on macroeconomic policies simulation and using the
SAM of 2006 was made by the UNDP in 2010. For more details on the description of
this SAM, see Appendix I.
Human resources who have benefited from special training sessions on this topic are
available for this project (See list of Team members).
4. Policy influence plan (or research communication strategy)
The first way in our policy influence plan was made of audiences from several
policymakers. The policymakers are generally interested by policy implications
underlined by the research activities. Both primary and secondary audiences exhibit
interest to our research project. However, most of the contacted persons are eager
to know the main results displayed by our research but have fewer comments on the
proposal itself. The Director of Research and Innovation at University of Burundi was
interested by our proposal and particularly the bridge we intend to gap in fostering
collaboration between policymakers and researchers. This director connected us to
other researchers who are working on the implementation of the CSLP. This is the
case of researchers from the Faculty of Economic Sciences who is dealing with
economic growth issues and the Permanent Secretary at the second VicePresidency who is coordinating the CSLP implementation.
On the other hand, results depicted from this research project are to be
communicated using various settings. We first plan to use existing inter-sectoral
groups in Burundi where generally results from research are communicated and
discussed with policy-makers, and technical and financial partners. Each technical
Ministry has its own sectoral groups. Given that this research involves several
ministries, the results will be discussed within more than sectoral groups. Second,
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once preliminary results are available, we intend to organize national policy
conferences, talk to the media as well as make policy briefs. We understand that this
communication scheme does not go beyond the one-way model of results’
dissemination. In the same time, it is easier to attract the media attention in
discussing results rather than methodological issues.
Third, we will use academic channels for communicating results from scientific
research. The Association of Professors of University of Burundi encourages this
framework. In our communication strategy, we intend to extend the dissemination of
our results to the scientific community of the country, especially young researchers
from public and private universities interested in economic development issues.
Conferences (to communicate results) and workshops (training sessions on
replication of our results) at the benefit of Students following master degree in
agriculture and rural development will be organized.
Finally, once the main results are available, the more interesting way to extend the
results from our research activities is made of international seminars and conferences
as well as submissions of our papers to international reviews.
The table below identifies major institutions and specific individuals who have already
been contacted for effective policy influence of the research.
Institution
Ministry of finance and economic
development planning
1st Vice Presidency
2nd vice presidency, SP REFES
Ministry in charge of Regional Integration
Ministry of trade, industry and tourism
Ministry of Agriculture and Livestock
University of Burundi
Institut National de la Statistique et des
Etudes Economiques du Burundi
Contact
M. Béatrice Samandari, Budget
Director
Mr Leonard Ntakarutimana,
Economic Advisor
Mr Léon Nimbona, Permanent
Secretary
Mr Hilaire NTAKIYICA, Coordinator of
the Economic and Social division
Mr Jérémie BANIGWANINZIGO
Director General of Trade
Ir. Odette Kayitesi, Minister of
Agriculture & Livestock
Dr. Steve De Cliff, Research Director
King Freedom Ph.D., Dean of the
Faculty of Agronomy
M. Jeanine Niyukuri, Director of
statistics & Economic studies
department
Target
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5. List of team members
Name
Age
Sex (M,F)
Nicodème
NIMENYA
41
M
Youssouf KONE
32
M
Espérance
KAMARIZA
37
F
Roselyne
MUNEZERO
35
F
Training and experience
He holds a Ph.D. in Agricultural
Economics and is a Professor at University
of Burundi. He is an analyst of
international agricultural trade, regional
integration and food security issues. He
has an experience in econometric
analysis and has recently attended a
training
course
on
GAMS-Based
Computable
General
Equilibrium
Modeling as well as a GAMS-advanced
CGE training course.
Holds a Master degree in Economics,
and is currently working as Trade Adviser
with the Commonwealth Secretariat Hub
and Spokes Programme in Burundi,
undertakes
analysis
and
provides
recommendations for trade policies
formulation,
negotiations
and
implementations. He has an experience
in
macroeconomic
analysis
and
attended various training courses on
GAMS-Based
Computable
General
Equilibrium (CGE) Modeling, Building and
Updating a Social Accounting Matrix,
Introduction
to
Applied
General
Equilibrium Analysis (GTAP Model). Kone
attended an advanced training course
on GAMS based CGE modeling in
December 2012.
Holds a diploma of an agronomist. She is
actually Director of statistic and
agricultural information Department at
the Ministry of Agriculture and Livestock.
She has benefited from several trainings
related to local planning and capacity
building, Environment and impact
evaluation, water harvesting, private
and public irrigation, integrated food
security and monitoring.
She holds B.A. degree in Agronomy
delivered by the Université du Burundi
and M.A. in agricultural economics
delivered by Université catholique de
Louvain in Belgium. She actually works at
the Ministry of Agriculture and Livestock
as an advisor.
9
6. Expected capacity building
The team members and their respective institutions are expected to gain from this
research project in terms of capacity building on the use of CGE Modelling and
comprehension of the links between non agricultural growth, employment and
poverty in fragile states like Burundi. Through PEP schools and the use of econometric
and CGE models, all the team members will get more skills in economic quantitative
analysis. Furthermore, some of them (those who are evolving in academic areas) will
upgrade through publications, others who are in the technical ministries will benefit
from this framework by increasing their ability of advisors in drawing responses and
recommendation to national priority needs.
All the tasks will be jointly undertaken by all the team members.
Name
Nicodème NIMENYA
Youssouf KONE
Espérance KAMARIZA
Roselyne MUNEZERO
Task
Literature review, updating the SAM, Construction of the
CGE model based on the PEP 1-T model, Policy simulation
and Interpretation, Drafting of the interim and final reports
Literature review, updating the SAM, Construction of the
CGE model based on the PEP 1-T model, Policy simulation
and Interpretation, Drafting of the interim and final reports
Literature review, updating the SAM, Construction of the
CGE model based on the PEP 1-T model, Policy simulation
and Interpretation, Drafting of the interim and final reports
Literature review, updating the SAM, Construction of the
CGE model based on the PEP 1-T model, Policy simulation
and Interpretation, Drafting of the interim and final reports
7. List of past, current or pending projects in related areas involving team members
Name of funding institution, title of project, list of team members involved
Name of funding
institution
GTAP
Title of project
Economic and Social
Impact of the EPA in
Cote d’Ivoire
Team members involved
Youssouf Kone
8. Describe any ethical, social, gender or environmental issues or risks that should
be noted in relation to your proposed research project.
To our knowledge there are no ethical, social, gender or environmental issues or
risks linked to this research project.
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Appendix 1 – Full description of Burundi 2006 SAM
Activity branches
Twenty-eight (28) activities were selected for the SAM and their respective value
added contribution to the GDP are described in the table 1 below.
Tableau 1-Activity branches in the SAM
Code
Branches
Production
value added
(Billion BIF)
Value
added/
production
Value added
(Billion BIF)
Share in
GDP
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Food crops
Coffee
Tea
Other export crops
Forestry
Livestock
Fishing
Extractive industries
Agro-food industries
ROALIMENTAIRES
Other
manufacturing
industries industries
Electricity,
Gaze and water
manufacturières
Construction
Commerce, repairing
Services
de réparation
Land
Transport
Water Transport
Air Transport
Other transport services
annexes
au transport
Postal
Services
télécommunications
Banks
and insuranceset
internet
Assurances
Restaurant
activities
restauration
eSet
Real
estate and
d'hébergement
management
immobilière
Computer
services
informatiques
annexes
Other
tradableetservices
Public Administration
Education
Health and social
actionsociale
Collective
& individual
acttivitiesactivities
Domestic human resources
521.0
139.3
14.7
3.1
12.7
45.2
20.4
11.3
346.4
85.1
13.5
75.4
159.8
67.5
2.7
1.0
3.4
23.5
55.0
122.0
163.5
0.7
6.8
118.1
48.5
9.7
3.5
9.5
81.3%
40.0%
47.4%
39.1%
88.0%
85.7%
23.9%
55.1%
25.6%
42.1%
56.1%
53.4%
54.9%
29.6%
48.6%
35.8%
76.2%
34.2%
63.2%
24.8%
99.0%
70.5%
82.2%
53.3%
95.3%
36.2%
47.7%
100.0%
423.6
55.7
7.0
1.2
11.1
38.8
4.9
6.2
88.8
35.8
7.6
40.3
87.7
20.0
1.3
0.3
2.6
8.0
34.7
30.3
161.9
0.5
5.6
63.0
46.3
3.5
1.6
9.5
35.4%
4.7%
0.6%
0.1%
0.9%
3.2%
0.4%
0.5%
7.4%
3.0%
0.6%
3.4%
7.3%
1.7%
0.1%
0.0%
0.2%
0.7%
2.9%
2.5%
13.5%
0.0%
0.5%
5.3%
3.9%
0.3%
0.1%
0.8%
Three (3) non-tradable branches are from the government: education, health and
social action.
The sectors with the highest weight in the Burundian economy are agriculture (521
Billions), the food industry (346 Billions), real estate (163.5 Billions), coffee (139 Billions),
hotels (122 Billions) and public administration (118 Billions).
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Factors of production
There are three types of factors, the remuneration of labor (191,264) and capital
inputs (984,042). The labor account is disaggregated between agricultural work
(14,457) and non-agricultural work (176807).
Agents
The matrix contains accounts of the three main categories of agents namely
households, firms and the Government. An account is also predicted to take into
account relations with the rest of the world.
Households receive factor payments (191,264 and 926,617 respectively for labor and
capital) they hold. They also receive interest and dividends from companies and
financial institutions (2294) and government transfers (258,335) corresponding to
benefits granted to households, grants to students etc ... and the rest of the world (32
475) received from private transfers and compensation of employees from outside.
These data are obtained from the balance of payments in 2006 and the table of
integrated economic accounts of the national accounts.
Households pay transfers (social security contributions and payroll taxes) to
government (28,194). They consume products (997815), pay transfers to the rest of
the world (212) and save part of income (47,864) which is paid into the accumulation
account.
Firms receive a share of the Gross Operation Surplus (GOS) as part of the capital
account (57,425). They also receive transfers from the rest of the world (5863)
essentially corresponding to interest and dividends. Transfers of interest and dividends
between firms are also tracked in the SAM (84,277). Firms also receive government
transfers (62,385) corresponding to production-related subsidies and other transfers
(50,160). With these resources, they pay dividends and interest to households (64,844)
and the rest of the world (16,402). Finally, they save a part of their resources (44,427).
The government receives taxes linked to production (22,275), current taxes on
income and capital and non-financial companies (62,550), taxes on household
income (28,194) and indirect duties and taxes on imports (109,308). It also receives
transfers from the rest of the world (229,207).
The rest of the world
The rest of the world account describes transactions with foreign countries. Imports
(494 436) and exports (118,245) of goods and services are included. These data
came from national accounts and balance of payments and take into account
both formal exchanges and informal transactions; and are adjusted when there is
sometimes a lack of supply or demand for a given good. As other capital inflows,
there are factor payments from the rest of the world and transfers from abroad (5863
for firms, 32,475 for households and 229,207 for the Government). Other outflows
represent factors payment by foreign countries and other transfers to other countries
(16,402 by firms, 212 by households, and 1118 by the Government). The deficit of the
balance of payments corresponds to net debt needed to finance the excess of
investment over domestic savings (126,378).
11
Value added contribution
The different sectors in the SAM generate more or less value, which affects their
weight in GDP. Thus, food industries or hotel services have a ratio of Value Added
Production of only 25%, while food crops, livestock or real estate have ratio of over
80%. Thus, in terms of GDP, the most important sectors are food crops, coffee and
livestock (35.4%, 4.7% and 3.2%), real estate (13.5%) the food industry and other
manufacturing (7.4% and 3%), public administration and education (5.3% and 3.9%),
and finally trade, financial services and hotel services (7.3%, 2.9% and 2.5%).
Spending of economic agents
The different expenditures of the economic agents are presented in the table 2
below, and it shows that farm households have no direct economic relationship to
the Government; they pay taxes only through indirect taxation, due to the informal
nature of agricultural activities. Savings is more important as a proportion of income
in non-agricultural households. With regard to firms, they spend more than 20% of
their income on capital, in investment, savings, and nearly 8% of their spending is
directed toward imports. Finally, nearly 45% of external resources are paid to the
government, against 6% for households and 1% for firms.
Income sources of economic agents
The SAM provides also information on the sources of income of agents which are
summarized in Table 2. Thus, household income, which represents 752 billion of
Burundian Francs or 63% of GDP, is mainly income from their capital (land and tool
for farm households, other capital assets for non-farm households). It seems that nonfarm households derive more income from labor, but this may be due to problems of
quantification of labor income in rural areas. Finally, farm households derive a larger
share of their income from government through transfers and subsidies they receive.
For other economic agents, the weakness of the private sector compared to the
public is striking. In addition, the dependence of public expenditure to external
support holds, since the government derives nearly half of its revenues from the rest
of the world, which also explains the importance of relations with the rest of the
world, more than 40 % of GDP.
12
Tableau 2. Income sources and expenditures for different economic agents
Goods
and
Services
Labor
Capital
-
%
-
%
1.9
27.5
-
%
69.9
59.9
27.4
3.1
%
0.4
40.1
13.4
100.0
-
-
-
-
100.0
-
96.5
Activities
%
Farm households
Non-farm households
Enterprises
Government
Gouvernement:
Production taxe
Government: Rights and
indirect Taxes
Rest of the World
Enterprise Househo
Government
s
lds
%
Capital
account
Rest of
the
World
Total
Mrds BIF
754.2
642.4
210.0
466.0
%
6.1
%
24.8
11.1
29.7
28.2
-
%
3.3
1.2
2.8
49.2
-
-
-
-
-
22.3
-
-
-
-
-
-
109.3
-
-
3.2
0.0
0.2
-
-
512.2
Capital
account
Rest of
the
World
Total
Répartition des dépenses des agents économiques
Activities
Goods
and
Services
Labor
Capital
Enterpris
es’
%
%
%
%
%
%
Farm households
Non-farm households
Enterprises
98.47
89.93
-
-
40.14
1.09
4.39
29.79
1.53
5.65
21.16
0.03
7.81
Mrds
Fbu
754.19
642.37
209.95
Government
Gouvernement: Production
taxe
Government: Rights and
indirect Taxes
Rest of the World
33.07
-
-
13.39
55.44
-
- 2.14
0.24
465.95
-
-
-
-
-
100.00
-
-
22.28
-
-
-
-
-
100.00
-
-
109.31
23.09
-
-
1.14
6.34
44.75
24.68
Househol Governme
ds
nt
%
512.17
13
Appendix II Structure of MFN duties
Chart III.1
Simple average of applied MFN rates, 2009 vs. 2011
(Per cent)
Agriculture
Products of animal origin
Dairy products
Fruit, vegetables, plants
Coffee, tea
Cereals and other preparations
Oilseeds, fats and oils
Sugars and confectionery
Beverages and tabacco
Cotton
2009 simple average rate (%)
Other agricultural products
2011 simple average rate (%)
Non-agricultural products
Fish and fishery products
Metals and minerals
Chemicals
Wood, paper, etc.
Textiles
Clothing
Leather, footwear, etc.
Non-electrical machinery
Electrical machinery
Transport equipment
Other manufactures
Petroleum
0
Source:
10
20
30
40
50
60
WTO Secretariat calculations, based on data provided by the EAC Secretariat and the
Burundian Government.
14