Mozambique Agriculture
Support Policy Review
June, 2024
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Mozambique
Agriculture Support
Policy Review
Realigning Agriculture Support Policies and Programs
Assessment of Government Support to Agriculture
(2019-2022)
Table of Contents
Executive Summary 3
Introduction 9
Technical Considerations 11
I. Country Context. 12
II. Agricultural Sector Context 20
III. Overview of the Level of Agricultural Public Expenditure 26
IV. Assessment of the Support to Agriculture in Mozambique (2019-2022) 31
4.1 The OECD Methodology - Rationale and Coverage 31
4.2 Technical Concepts for the Calculation of Indicators 32
4.3 Beneficiaries and Funding Sources of Support to Agriculture. 35
4.4 Total Support Estimate for Agriculture (TSE) 36
4.5 Producer Support Estimate (PSE) 38
4.5.1 Level of support 38
4.5.2 Analysis of Producer Support by Product 41
4.6 General Services Support Estimate (GSSE) 47
4.7 Consumer Support Estimate (CSE) 49
4.8 Consumer Support Estimate (CSE) by Product 51
V. Agricultural Support and Structural Challenges - Four key dimensions. 52
VI. Conclusions 58
VII. Main Policy Recommendations 60
Bibliography 63
ANNEX 1. Consumer Price Index – Mozambique (Base Year 2016=100) 66
ANNEX 2. General overview of jobs registered by activity. 68
ANNEX 3. General Import of Goods (US$ Million). 69
ANNEX 4. Imports of Goods by Country of Origin (US$ Million). 71
ANNEX 5. General Export of Goods (US$ Million). 73
ANNEX 6. Exports of main products by activity, 2023 (US$ Million) 74
ANNEX 7. Export of Goods by Destination Country (US$ Million). 75
ANNEX 8. Credit Portfolio Balance by Sectors of Economic Activity 77
ANNEX 9. Gross Domestic Product (US$ million, 2014 constant prices) 78
ANNEX 10. Gross Domestic Product (US$ million, current prices) 79
ANNEX 11. Estimates of Support to agriculture (million meticais) 80
ANNEX 12. Estimates of Total Support to Agriculture and its components (US$ million) 81
ANNEX 13. Main Characteristics of Agricultural Selected Products for the Analysis. 82
ANNEX 14. Estimates of Producer Support by Components (Millions Meticais) 84
ANNEX 15. Mozambique, Tariff Profile (WTO) 89
ANNEX 16. Average Yields for Selected Products and Countries 2000-2020 90
ANNEX 17. Program and Projects Executed by the Government Considered for PSE 91
Estimation
ANNEX 18. Mozambique Poverty Assessment (June 2023) and Mozambique Country 95
Climate and Development Report (CCDR, 2023)
List of Acronyms
AAGR Average Annual Growth Rate
AfCFTA Africa Continental Free Trade Area
Ag GDP Agriculture Gross Domestic Product
AgPERs Agriculture Public Expenditure Reviews
AU African Union
CAADP Comprehensive Africa Agriculture Development Program
CAP Common Agriculture Policy
CGE Government of Mozambique’s Central Account
CIF Cost, insurance and Freight
CO2 Carbon Dioxide
COVID-19 Coronavirus disease
CPI Consumer Price Index
CSA Climate Smart Agriculture
CSE Consumer Support Estimate
EU European Union
FAO Food and Agriculture Organization
FOB Free on Board
FTA Free Trade Area
GDP Gross Domestic Product
GHG Greenhouse Gases
GSSE General Services Support Estimate
Ha Hectare
IFC International Finance Corporation
IFPRI International Food Policy and Research Institute
IMF International Monetary Fund
INE National Institute of Statistics of Mozambique
LCU Local Currency Unit
MADER Ministry of Agriculture and Rural Development
MAFAP Market-oriented Smallholder Agriculture Project
MEF Ministry of Economy and Finance
MFN Most Favored Nation
MOPHPR Ministry of Public Infrastructure, Housing and Hydric Resources
MPS Market Price Support
MSME Micro, small, and medium enterprise
MZN Metical-Mozambique’s official currency unit
Mts Meticais
MT Metric Tons
NGO Non-Governmental Organization
1
NSmartAg Nutrition Smart Agriculture
OECD Organization for Economic Cooperation and Development
PEDSA 2 Second Agrarian Sector Development Strategy
PNISA 2 National Agriculture Investment Plan
PSE Producer Support Estimate
SCT Single Commodity Transfer
SREP Sustainable Rural Economy Program
SSA Sub-Saharan Africa
TSE Total Support Estimate
WB World Bank
WBG World Bank Group
WFP World Food Programme
WTO World Trade Organization
2
Executive
Summary
Introduction
Various efforts have been made to comprehensively assess agricultural policies
in countries worldwide using diverse methodologies, including some generated
by several international organizations. Since first applied in the 1980s, the OECD’s
methodology has been regarded as a practical policy monitoring and evaluation tool.
It has been frequently used as a reference to establish a dialogue at the national
and international levels since it allows comparisons among countries and their
economies, measuring the impact of policies on the gross income of both consumers
and producers.1 The OECD methodology focuses on estimating the value of monetary
transfers made by taxpayers and consumers, specifically to agricultural producers, as
a direct result of the implementation of agricultural policies.
This study aims to apply the OECD methodology to measure monetary transfers to
the agricultural sector and the producers between 2019 and 2022. These transfers
are measured by four primary indicators: (i) Total Support Estimate (TSE), which is
the leading indicator measuring the impact of all policies on the entire agricultural
sector; (ii) Producer Support Estimate (PSE), quantifying the transfers to specific
groups of agricultural producers; (iii) General Services Support Estimate (GSSE),
measuring the transfers resulting from the implementation of public investment
policies in public goods or services; and (iv) Consumer Support Estimate (CSE),
measuring the impact on domestic consumers. The results aim to provide insights
into the effectiveness, efficiency, and impact of current initiatives and identify areas for
improvement in the Government of Mozambique’s agriculture policies and programs.
The report presents conclusions and offers policy recommendations based on these
results.
Country and Sectoral Context.
Mozambique is a low-income country in Southeastern Africa with a population of
about 34.5 million. Its Gross Domestic Product (GDP) is estimated at approximately
US$23.9 billion for 2023 (current prices), with a GDP per capita of US$687.38, which
ranks among the lowest globally. Although the country’s economic growth rate has
decelerated over the second half of the last decade, there has been a rebound in the
last three years, reaching an annual growth rate of about 5 percent between 2022 and
2023.
The agricultural sector currently represents almost a quarter of the total GDP.
3
Mozambique remains predominantly rural, with about two-thirds of its estimated 34.5
million people residing and working in rural areas (2024). Agriculture is an important
source of job creation, increasing its relative participation in total job creation from
21.4 percent in 2018 to 29.5 percent in 2022.
Mozambique’s National Trade Balance has historically been in deficit. For 2022
2023, accumulated exports reached US$25,982 million, while imports amounted
to US$36,401 million, resulting in an accumulated deficit of US$10,419 million.
Mozambique is a net importer of agricultural goods, depending heavily on imports to
satisfy domestic demand, and imports of agricultural products have registered higher
growth than exports, resulting in a sizable trade deficit.
Agricultural production in Mozambique has increased in recent years (2018-
2022) at an average annual growth of 1.5 percent. Expanding the agricultural
sector has important effects in terms of poverty reduction, income generation, and
employment generation. However, it faces hurdles such as low productivity and limited
competitiveness, inadequate access to advanced technologies, inadequate rural
infrastructure, low value added, and market uncertainties. The country is ranked as
the third most vulnerable to climate change in Africa due to a combination of natural
hazards, including flooding, droughts, and cyclones with the corresponding effects on
the agricultural sector.
Agricultural Public Expenditure
Over 2019-2022, Mozambique’s public agricultural investments in nominal terms
increased slightly. The country has been lagging in addressing the goal agreed in the
Malabo declaration, which consisted of allocating 10 percent of the national budget
to the agricultural sector. Annual expenditures for the agricultural sector have been
around an average of 6 percent of agricultural GDP (2019-2022). The country has
also one of the lowest levels of expenditures in agriculture research.
Agriculture Support Estimates in Mozambique (2019-2022)
Total Support Estimate for Agriculture (TSE). TSE comprises the sum of
transfers to agricultural producers, both targeted individually (PSE) and collectively
(GSSE), as well as direct budgetary transfers to consumers. In absolute terms, the
TSE in Mozambique amounted to about US$ 567 million for 2019 2022, equivalent
to an average of 3.5 percent of the national GDP, reaching a peak of 4.9 percent in
2022. Compared with other countries, these monetary transfers to the sector are
relatively small in absolute terms but high in relative terms as a percentage of GDP
and comparatively higher than in most other countries with similar analysis. Most
of the monetary transfers to the sector were funded by consumers. For every dollar
transferred to the sector, an average of about 84 cents was covered by consumers
(paying domestic prices above international reference prices) and the remaining 16
cents by taxpayers (through the finance of public programs). This pattern contrasts
with OECD countries, where taxpayers generate the most significant proportion of the
transfers.
An analysis of the composition of the TSE shows that direct support to producers
(PSE) makes up most of the total support to the sector (an average of 89.7 percent
of the TSE). On the other hand, support aimed at the sector as a whole, with
4
characteristics of public goods (GSSE), represents, on average, 10.3% of the total.
Direct support is less relevant in OECD countries, where a more significant share of
consumer subsidies exists and is funded by taxpayers.
Producer Support Estimate (PSE). For 2019-2022, the PSE average stood at
around 6.8 percent (reaching about 9.1 percent in 2022). This indicates that about
6.8% of gross producer income came from transfers derived from agricultural
policies. Within the PSE, market price support represented, on average, 99.1
percent of all direct support, while production and input supports are extremely small.
Compared with other international experiences, Mozambique stands out with its high
concentration of price support within the composition of the PSE. Countries with
relatively higher levels of agricultural development generally show significantly lower
MPS levels.
Analysis of Producer Support by Product. The methodology applied for this
analysis allows for identifying and quantifying the level of support transferred to
a specific type or group of products, which is referred to as Single Commodity
Transfers. The agriculture products selected for this analysis were rice, cassava,
maize, tomatoes, and sweet potatoes, chosen due to their strategic importance in
production, consumption, and/or national trade. Throughout 2019 2022. rice exhibited
the highest average PSE (47.0 percent), meaning that transfers to rice producers
accounted for an average of 47 percent of their gross income (and the rest was due
to their market operations). The rest of the products had lower levels of support:
Cassava, 8.8 percent; Tomato, 2.1 percent; Corn, 0.8 percent; and Sweat Potato, 0.2
percent. Mozambique’s PSE level for rice is comparable to that of other countries like
Korea and Japan. However, in Mozambique, it is mainly through prices, which implies
important impacts and distributional effects for rice consumers and mainly low-income
consumers, who spend a higher proportion of their income in food.
General Services Support Estimate (GSSE). Government policies also support the
agricultural sector by funding activities that produce public goods and services such
as agricultural research and development, technology transfer, extension services,
capacity building, inspection, information, and sector promotion. These expenses
are typically funded by taxpayers or other sources but not directly by consumers.
Public goods and services generate positive externalities for the entire sector.
In Mozambique, the GSSE has increased its relative importance within the Total
Support Estimate (TSE), from 5.0 percent in 2019 to 15.9 percent in 2022, with an
annual average for the period estimated at around 10.3 percent of the TSE. However,
Mozambique’s GSSE level as a proportion of the TSE continues to be below the
OECD average and even below other economies in the region, such as South Africa.
Consumer Support Estimate (CSE). The Consumer Support Estimate (CSE)
measures consumers’ cost (or benefit) from the national government’s implementation
of sector support policies. A negative CSE indicates a negative cost to the consumer,
equivalent to an implicit tax on the consumption of agricultural products, generated
due to having a domestic price above an international reference price. This can be
done through the imposition of administered prices or other types of price support
mechanisms. For Mozambique, the average consumer support CSE was negative
across the entire analyzed period by 7.1 percent. In the case of other countries,
even though the CSE is also negative, additional resources are provided by other
consumer support programs financed by taxpayers which more than compensate for
the negative CSE. Analyzing the CSE by product, the estimates for Mozambique are
5
-11. 6 percent for rice, -10 percent for Cassava, -4 percent for tomato, -0.4 percent for
Corn, and ineligible for sweet potato.
Conclusions
Based on the assessment of the agriculture support estimates, the main findings to be
considered for future agriculture policy decisions forward are the following:
(a) Total agricultural support (TSE) in Mozambique from 2019 to 2022 was
approximately an average of 3.5 percent of the national GDP. Although this is
relatively low in absolute terms, it is a relatively high rate as a percentage of the
national GDP. This level fluctuated from 1.9 to 4.9 percent of the GDP from 2020 to
2022, reflecting the significant influence of international price movements and the
differential generated with domestic prices.
(b) Considering the source of support, consumers were responsible for financing
about 84 percent of these transfers by paying prices higher than the average prices
in international reference markets (implying an implicit tax on consumers). The
remaining 16 percent was financed by taxpayers through the support of national
government programs and projects.
(c) Out of the total TSE, direct support to producers was an average of 89.1
percent (almost entirely through market price support, MPS). This entails implications
of efficiency because MPS tends to be a highly distorting mechanism and prevents
production decisions from being carried out by market signals. It also has equity
implications because it is primarily large producers who benefit from higher prices.
(d) When analyzing the support targeted at specific products, it is noted that
cassava and rice accounted for almost 60.7 percent of the average support granted
to specific products during the period analyzed.(e) When analyzing the support
targeted at specific products, it is noted that cassava and rice accounted for almost
60.7 percent of the average support granted to specific products during that period.
(e) Although an increasing absolute level of public investment in public goods
for the sector was observed (mainly for infrastructure and knowledge), this type of
support accounted for 5 percent of the total estimated transfers during the analyzed
period 2019 2022, equivalent to only 0.07 percent of GDP.
Recommendations
Gradually phase out market price support. This type of support tends to benefit
only a specific product or group of products, with a high degree of market distortion, to
the extent that it generates artificial incentives to produce regardless of the profitability
and comparative advantages that other products may have, hence generating an
inefficient allocation of resources at a high social cost.
There is a need to shift the paradigm of how agricultural support is
approached from market price support to public goods and services.
Market price support has failed to achieve structural changes in the sector. It is
recommended that it be replaced with an increase in public investment in public
6
goods and services to create enabling conditions for private sector investments
in well-functioning agriculture markets. In accordance with international evidence,
investments in agriculture public goods and services should aim a minimum 2.5
percent of the agricultural GDP in the next 5 years, i.e., about double the current
level. In the context of Mozambique, key public goods and services for the agriculture
sector constitute rural physical and digital connectivity, agriculture research and
development, technology transfer, education and capacity building, disease control
and inspection, and public services to support market access.
Shift from implicit taxation to positive support to food consumers. As the
negative CSE estimates demonstrate, Mozambican food consumers are funding a
significant proportion of the support to the agriculture sector. A shift away from this
approach will reduce the implicit food tax consequently increasing the welfare of the
poorest.
Policy shifts must be a gradual process. The impact on public finances must
be considered carefully when looking at policy shifts. A sudden and immediate
dismantling of price support could generate disruptive risks and political tensions,
potentially aggravating the issues. Reductions in trade barriers should be
accompanied by other fiscal measures to offset an eventual impact on public finances.
Design support schemes for small producers, promoting and supporting
organizational improvements and removing constraints along key value
chains. Promoting associativity through different mechanisms such as producer
organizations, cooperatives, productive alliances, contract farming, etc., is a strategy
that can be beneficial for the efficiency of the sector. International evidence suggests
that organization and scale can facilitate solutions to agriculture market failures.
Agriculture risk management, and financial instruments more broadly, should
an integral part of farmer’s coping mechanisms to shocks. Their inclusion would
generate social benefits far exceeding the related costs. The design, assessment,
and eventual trial of a program that partially subsidizes the insurance premium of
index-based insurance is important considering the sector’s high exposure to climate
risks that Mozambique faces and the cost-benefit ratio of transferring these risks
to international markets. The possibility of generating liquid guarantee programs
granted to non banking financial entities, such as credit cooperatives or associations,
is an alternative that can allow the financial inclusion of the most vulnerable segment.
Policy reforms should be followed by creating instruments for monitoring and
evaluating results. This would allow for continuous monitoring of public policies and,
thus, improvement based on the results and lessons learned. Policy evaluation and
evidence-based policy formulation must continue to be areas of investment and part
of the working culture in agricultural sector institutions.
7
8
Introduction
1. Various efforts have been made to carry out comprehensive assessments
of agricultural policies in countries around the world using diverse methodologies.
Some of these include efforts by international organizations such as the Food and
Agriculture Organization of the United Nations (FAO), the World Trade Organization
(WTO), the International Food Policy Research Institute (IFPRI), and the Organisation
for Economic Co-operation and Development (OECD).
2. The OECD’s methodology (designed in the 1970s and first applied in the
1980s) has been adapted and established as an effective policy monitoring and
evaluation tool. It has been frequently used as a reference to establish a dialogue
at the national and international levels. Due to its standard methodology, it allows
comparisons among countries and their economies, measuring the impact of policies
on the gross income of both consumers and producers1.
3. It is important to highlight that the OECD methodology estimates the value
of monetary transfers made by taxpayers and consumers to agricultural producers,
including transfers generated from implementing agricultural policies. Consequently, it
enables the observation of the significance of the effects of these transfers in the total
producers’ gross income.
4. The methodology considers four basic indicators to determine the types and
the value of the transfers made by taxpayers and consumers to agricultural sector
producers:
a) Total Support Estimate (TSE): Quantifies, in monetary terms, the full impact of all
policies for the entire agricultural sector (comprising PSE, CSE, and GSSE).
b) Producer Support Estimate (PSE): Quantifies the total transfers to agricultural
producers resulting from implementing agricultural policies targeted at a specific
product or group of products.
c) General Services Support Estimate (GSSE): Quantifies the total transfers to the
agricultural sector resulting from the implementation of public investment policies in
public goods or services (or having characteristics of public goods/ services).
d) Consumer Support Estimate (CSE): Quantifies the impact of agricultural policies
on domestic consumers of a particular product.
1
See methodology manual at: http://www.oecd.org/agriculture/topics/agricultural-policy-monitoring-
and-evaluation/documents/producer-support-estimates-manual.pdf.
9
5. The primary goal of this analysis is to quantify the impact of agricultural
policies implemented by the Government of Mozambique between 2019 and 2022
on agricultural producers, the entire sector, and consumers based on the transfers
these policies generate. The result of this analysis reflects transfers derived from the
implementation of agricultural policies of the Government of Mozambique, as well as
the transfers resulting from the implementation of all national policies. The analysis
estimates the amount of these transfers, their importance in the gross income of the
producer, and the Gross Domestic Product (GDP), thereby facilitating the assessment
of their impact and enabling comparisons over time and with other economies2.
6. This assessment aims to provide insights into the effectiveness, efficiency,
and impact of current initiatives and identify areas for improvement or adjustment,
thus assisting the Government in evaluating and refining its agriculture policies and
programs. By thoroughly reviewing these policies and programs, the Government can
make informed decisions to support farmers better, enhance agricultural productivity,
ensure food security, promote sustainability and stimulate rural development.
Ultimately, the goal is to optimize the effectiveness of government interventions in the
agricultural sector to achieve broader economic, social, and environmental national
objectives.
7. The analysis covers the period from 2019 to 2022, which is considered relevant
because various events occurred during this period that significantly impacted the
sector, such as the global COVID-19 pandemic and a crisis in food prices due to
Russia’s invasion of Ukraine and the resulting ongoing conflict. Based on the results
obtained, the final section of this report presents conclusions and offers some policy
recommendations.
8. Throughout this document, the Public Expenditure Review (PER) carried
out in 2022 is mentioned several times. This PER has been used as a reference
for estimating support for Mozambique. In such a report, it is possible to see the
budgetary disbursements made by the Mozambican government in favor of the
agricultural sector, which is basically financed by taxpayers. The estimation of support
with the OECD methodology considers this information but also considers other
support that is not part of the public budget that comes from the implementation of
measures that affect the level of market prices, such as, for example, the imposition
of tariffs on the import of certain products. This type of support, which is not part of
the public budget, represents a transfer to the sector and is normally financed by
consumers.
2
Annually, the OECD estimates the transfers resulting from the implementation of national government policies,
considering Mozambique as a non-member country. The results are published on the OECD website.
10
Technical
Considerations
9. The Producer Support Estimates (PSE) and all the support estimation
indicators were assessed in strict adherence to the methodology established by the
Organisation for Economic Co-operation and Development (OECD), which enables
international comparisons of relevant countries.
10. Efforts were made to predominantly consider information from national
official sources, such as the National Institute of Statistics (INE), the Central Bank of
Mozambique (CBM), the Ministry of Agriculture and Rural Development (MADER),
as well as from international sources like the Food and Agriculture Organization of
the United Nations (FAO), the OECD, and the World Bank Group (WBG). Information
regarding budgetary expenditures is derived from the General Account of the
Republic of Mozambique from 2019 to 2022.
11. The products to be analyzed were selected considering their relative
importance in the value of national production, including criteria for imported and
exported products.
12. The period analyzed, from 2019 to 2022, is marked by a global food price crisis
that began in 2020 (due to the pandemic) and intensified in 2022 (due to Russia’s
invasion of Ukraine). Therefore, the results might be influenced by these international
price movements.
13. It is important to note that the results presented in this Report represent
a national average. It is recommended that the Ministry of Agriculture and Rural
Development (MADER) and the National Institute of Statistics (INE) be strengthened
institutionally to enable them to provide more reliable information on average producer
and consumer prices.
11
1. Country
Context
14. Mozambique, a low-income country in Southeastern Africa, faces
significant challenges with a population of 34.5 million people3. Its Gross
Domestic Product (GDP) is estimated at approximately US$23.9 billion for 2023
(current prices), with a GDP per capita of US$687.38, which ranks among the lowest
globally (about US$ 18,407 million for 2022)4. Poverty remains a pressing issue,
with the national poverty rate increasing from 48.4 percent to 62.8 percent between
2014/15 and 2019/20, resulting in the number of poor people rising from 13.1 to
18.9 million. Despite this, economic growth has gained momentum, driven by robust
services production and liquid natural gas production. After a modest recovery in
2021, growth accelerated to 4.2 percent in 2022 and is projected to reach 6.7 percent
in 20245. This growth is primarily attributed to the expansion of liquid natural gas
production in Cabo Delgado Province, which is expected to contribute significantly to
the country’s economic development.
15. Although the country’s economic growth rate has decelerated over
the second half of the last decade, there has been a rebound in the last three
years. According to the data from the National Institute of Statistics (INE), in 2023,
the GDP amounted to 747,552 million meticais at 2014 constant prices (around
US$ 11,699 million), which represented an Average Annual Growth Rate (AAGR)
of 5.0 percent compared to the previous year. This was the most significant growth
observed since 2015 when the AAGR reached 6.7 percent. Throughout the entire
period analyzed, the GDP AAGR of GDP was 3.8 percent (see Figure 1; further
details are provided in Annexes 9 and 10).
Figure 1. Annual GDP Growth (2014-2023)
3
World Population Prospects: The 2022 Revision. (Medium-fertility variant). Updated on July 16, 2023, with the latest July 2023-July 2024 estimates from the United
Nations, Department of Economic and Social Affairs, Population Division. Accessed at: https://www.worldometers.info/world-population/mozambique-population/.
4
International Momentary Fund; World Economic Outlook (2023). Accessed at https://www.imf.org/external/datamapper/profile/MOZ
5
World Bank (2022). “The World Bank in Mozambique”. Accessed at: https://www.worldbank.org/en/country/mozambique/overview.
12
16. Agricultural GDP has maintained relatively high growth rates compared
to the other sectors. During the period 2014-2023, the average annual growth of the
agricultural sector was 3.8 percent, but also showed a variability greater than that of
the total economy. During 2020, when low economic growth was recorded due to the
COVID-19 pandemic, the agricultural sector demonstrated resilience by consolidating
itself as an essential activity and a significant engine for development and
employment. The high variability of the sector’s growth rate can often be attributed
to factors such as price variability and climatic conditions, which reflect a condition of
vulnerability and affect production performance.
17. The agricultural sector currently represents almost a quarter of the total
GDP, a share that has grown slightly in recent years. In 2023, the agricultural sector
contributed 24.3 percent to the total GDP, only marginally higher than in 2014 (see
Figure 2).
Figure 2. Composition of the Gross Domestic Product of Mozambique: 2014 vs 2023
Source: Based on data from the National Institute of Statistics of Mozambique.
18. Mozambique remains predominantly rural, with about two-thirds of its
estimated 34.5 million people residing and working in rural areas as of 2024.
While there was a 4.3 percent increase in the urban population in 2022, reaching
12.6 million, most of Mozambique’s population still lives in rural areas (about 20.39
million people). Despite rural-urban migration, more than half of the population is
projected to continue to reside in rural areas until 2040. This trend is propelled by
rapid population growth, particularly among rural households in the northern and
central regions, where rural women have an average of 2.1 more children than urban
women. This rapid growth, coupled with a persistently young age structure, results in
an estimated average of 450,000 youths being added annually to the rural workforce.
Consequently, Mozambique is expected to remain predominantly rural for the current
generation, highlighting the importance of prioritizing rural income growth initiatives6.
19. Registered employment in Mozambique has decreased in the last
few years, while the primary sector has gained prominence as a source of
employment. According to the INE, 361,632 jobs were recorded in 2022, which
represents a decrease of 24.5 percent compared to the 478,904 jobs registered in
2019. This decline was even more pronounced during the 2020 global crisis when
job registrations fell by 47 percent compared to 2019. Meanwhile, the primary
sector proves to be a driver in job creation as it shows growth, increasing its relative
participation in total job creation from 21.4 percent in 2018 to 35.2 percent in 2020
6
Mozambique rural population 1960-2024. Accessed at: https://www.macrotrends.net/global-metrics/countries/MOZ/mozambique/rural-population
13
and 29.5 percent in 2022 (see Figure 3). See also Annex 2 for more detailed
employment information.
Figure 3. Registered employment by the main sources of employment 2018-2022 (absolute and percent)
Source: Based on data from the National Institute of Statistics (INE), Mozambique, 2022.
20. The rise in the general Consumer Price Index (CPI) over recent years in
Mozambique has been particularly driven by increased fuel and food prices.
According to the data from the National Institute of Statistics (INE), the average
General CPI for 2023 stood at 160 (2016=100), representing an increase of 37.1
percent compared to the average of 122.8 for 2019. Meanwhile, the subcomponent
for electricity, gas, and other fuels registered an average of 216.1 in 2023, with an
increase of 49.7 percent compared to the average of 157.9 for 2019. Similarly, food
and beverages recorded an average index of 178.2 in 2023, an increase of 58.9
percent compared to the average of 119.3 for 2019 (See Figure 4).
Figure 4. Consumer Price Index (CPI) 2019-2022 (2016=100)
Source: Based on data from the National Institute of Statistics (INE) 2023.
21. Although prices showed a significant increase between 2019 and the
first half of 2022, driven mainly by increases in food and fuel prices, during the
second half of 2022 and in 2023, this increase slowed down. General inflation
peaked in August 2022 with an annual increase rate of 13 percent. In 2023, the
annual general inflation was 5.3 percent. Meanwhile, food prices exhibited an average
annual inflation of 12.9 percent in 2022, decreasing to 10.2 percent during 2023. In
14
contrast, the average annual inflation of fuel prices increased between 2022 and
2023, from 7.4 to 10.5 percent (see Figure 5). Annex 1 contains further information on
CPI and its main components7.
Figure 5. Annual inflation 2019-2023 (percentage)
Source: Based on data from the National Institute of Statistics (INE), 2023.
International Trade
22. The value of total exported goods maintained solid growth after
contracting during the 2020 global COVID-triggered crisis. The Free-On-
Board (FOB) value of exports for 2022 was US$8,280 million, representing a sizable
cumulative increase of 73.0 percent since 20198, which was the last year before the
negative effects of the COVID-19 pandemic. This growth was mainly driven by the
extractive industry, whose growth between 2019 and 2022 was 123.8 percent. Within
this industry, natural gas and mineral carbon stand out with growth of 134.6 and 132.7
percent, respectively. However, the products with the greatest growth were peanuts,
with 397 percent, and legumes and vegetables, with a growth of 172.4 percent
during the same period (see Annex 5 and 6). After the lowest point in 2020, exports
increased for the last two years at a cumulative rate of 122.6 percent over the exports
in 2020. Over half of Mozambique’s exported value is concentrated in a few countries,
where the primary trading partners are India, South Africa, the United Kingdom, and
China. These countries’ relative importance has increased from 46.0 percent in 2019
to 51.7 percent in 2022 (see Figure 6 and Annexes 6 and 7).
Figure 6. Exports of goods by main destinations 2014-2022 (US$ million)
Source: Based on data from the Central Bank of Mozambique.
7
MOZ/mozambique/rural-population National Institute of Statistics (INE), 2023.
8
Central Bank of Mozambique, 2023.
15
23. The main economic activities for the country’s exports are the extractive
and manufacturing industries. The group of extractive industries has increased
its relative importance within the total value of exports, rising from accounting for
38.7 percent in 2019 to 56.7 percent in 2023. Meanwhile, the relative importance of
agricultural products decreased during the same period. For 2023, the extraction and
manufacturing industries combined represented 73.2 percent of the value of exports.
Meanwhile, the value of agricultural exports grew at an AAGR of 0.9 percent between
2014 and 2023, with a decrease in its relative weight from 11.9 to 6.1 percent. (See
Figures 7 and 8) and the total agricultural exports accounted for 6.1 percent of the
total value. It is worth noting that agri-food products (including tobacco, beverages,
sugar, preparation for cereals, food preparations for animal fodder, etc.) represent 4.2
percent of the total manufacturing industry, equivalent to 0.7% of total exports. These
two figures constitute agro-industrial exports equivalent to 6.8% of total exports (see
Figures 7 and 8 and Annex 6).
Figure 7. Composition of exports by sector 2014-2023 (percentage)
Source: Based on data from the Central Bank of Mozambique.
Figure 8. Exports by economic activity 2023 (100% = US$ 8,276 million)
Source: Based on data from the Central Bank of Mozambique.
24. The agriculture exports show a high concentration on a few products.
Only two products, tobacco and vegetables, together amount to more than 60 percent
16
of agriculture exports, which may become vulnerable to the volatility of international
prices, and the annual growth rate showed in last years is relatively low. Peanuts and
cashews represent 13.7 percent and 11.4 percent of the total agricultural export value,
respectively (see Figure 9). Peanuts and cashews have shown significant growth
dynamics between 2014 and 2023, with average annual growth rates of 27.2 percent
and 21.6 percent, respectively (see also Annex 5).
25. The imports of goods increased significantly over the last five years,
showing a peak in 2022 due to the rising demand for capital goods (machinery
and tractors). In 2022, the value of total imports reached a record of US$13,337.3
million, slowing down to around US$ 9,179.6 million in 2023. However, 2023 imports
were 31.2 percent higher than in 2019. The share of capital goods (machinery and
tractors) has been increasing, with an average share of 22.8 percent of the total
imports for the period from 2019-2023. Meanwhile, consumer goods accounted for an
average of 23.1 percent for the same period 2019 2023, with automobiles, medicines,
and rice being the main consumer goods demanded in this sector (see Figure 9). On
the other hand, wheat and rice are the agricultural products with the highest import
volumes, accounting for 96.1 percent of the total agricultural import value in 2023.
According to trade figures from the Central Bank, these products have experienced
average annual growth rates of 5.7 percent and 6.7 percent, respectively, over the
period from 2014 to 2023. In contrast, some imported products (such as sugar) are
being phased out.
Figure 9. Composition of the Value of Agricultural Exports/ Imports in 2022
Figure 10. Import of main goods (USD million)
Source: Based on data from the Central Bank of Mozambique. 17
Trade Balances
26. Mozambique’s National Trade Balance has historically been in deficit.
From 2020 to 2023, accumulated exports reached US$25,982 million (with an AAGR
of 30.5 percent). In contrast, imports amounted to US$36,401 million (even with a
lower AAGR of 15.7 percent), resulting in an accumulated deficit of US$10,419 million
for this four-year period. These figures indicate that exports are growing faster than
the period from 2014 to 2019, during which the AAGR for exports was 4.1 percent.
27. Agricultural Trade Balance. Mozambique is a net importer of agricultural
goods, depending heavily on imports to satisfy domestic demand. Between
2014 and 2023, imports of agricultural products registered higher growth than exports,
with average annual rates of 5.3 percent and 0.9 percent, respectively. In addition,
the net agriculture trade balance shows an important degree of volatility, which
complicates its long-term positive sustainability (See Figure 11).
Figure 11. Mozambique’s Agricultural Trade Balance (FOB), 2014-2023 (millions of dollars)
Source: Based on data from the Central Bank of Mozambique.
Household Expenditures.
28. Households in Mozambique spend an average of about 39 percent
of their income on food, which increases as income decreases. In 2022, the
average household spent 38.8 percent of its income on food. For the lowest-income
households in the country, this average was 47.8 percent (see Table 1).9
Table 1. Structure of monthly household expenditures in 2022 (percentage)
Source: INE
9
National Institute of Statistics (INE), 2023.
18
29. On average, cereals constitute almost 41 percent of the total
expenditures in food. Table 2 shows that food expenditures were particularly
focused on cereals and vegetable products during 2022; these two groups of food
products accounted for 65 percent of total expenditures in food. On the other hand,
fruit, meat, and fish represent a relatively low percentage of the total expenditures.
Households with lower income levels spend about 10.5 percent of their income
on corn flour-based foods, just under half of the 23.3 percent of higher-income
households. Lower-income households spend more on products such as wheat
bread, mackerel, and chicken (see Table 3).10
Table 2. Structure of monthly spending on food products by population quintiles, according to food groups in
2022 (percentage). (National Institute of Statistics, 2023)
Source: INE
Table 3. Spending on some basic products over total food spending in 2022 (percentage) INE, 2023.
Source: INE
10
National Institute of Statistics (INE), 2023.
19
2. Agricultural
Sector Context
30. Most rural households in Mozambique remain net food consumers,
still depending on agriculture production for extra cash income, thus
vulnerable to price increases that may constrain consumption and potentially
heighten poverty risks. However, agriculture remains one of the cornerstones of
Mozambique’s economy, contributing 24.3 percent of its GDP. The agricultural sector
holds vast growth potential due to the country’s resources, diverse agroecological
zones and strategic geographical position, particularly due to its proximity to
neighboring landlocked countries and various export departure points. Smallholder
farmers play a crucial role in this sector, accounting for most of the agricultural
production. Approximately 4.3 million small- and medium holder farmers contribute
to 99 percent of the country’s agricultural output, while about 873 large commercial
farmers contribute the remaining 1 percent. However, agriculture is practiced on
5.5 million ha (about 15 percent of the arable land), primarily in flood- and drought-
prone areas. Challenges such as limited access to credit and markets, low utilization
of improved inputs, and reliance on rain-fed agriculture make the sector susceptible
to shocks. Maize and cassava are the main food staples, cultivated by about 84
and 43 percent of Mozambican smallholders, respectively, covering over a third of
cultivated land. Other important staples include wheat and rice. Despite 45 percent of
the country being suitable for agriculture, less than 15 percent is currently cultivated,
indicating untapped potential for agricultural expansion and development. The main
products in terms of their contributions to the agricultural sector value added are:
cassava, accounting for 16 percent; bovine milk, accounting for 13 percent; maize,
8 percent; tomatoes, 7 percent; beans, 7 percent; chicken, 7 percent; and pork, 6
percent.
31. Agricultural production in Mozambique has increased in recent years.
During 2018-2022, production increased at an average annual growth of 1.5 percent,
while more recently, between 2020 and 2021, Mozambique’s agricultural production
value experienced a 4 percent increase rate, attributed to favorable weather
conditions and increased government support11. In 2021, the sector’s production value
reached US$ 7,948 million, and it is estimated that in 2022, the production value
reached about US$ 7,971 million. Mozambique is established as one of the leading
cassava producers, where its production represents approximately 2 percent of the
global volume, a figure that positions the country as the tenth-largest producer of
cassava. Although cassava experiences diverse favorable agroclimatic conditions, it
is an example of a product with high unrealized potential. Mostly, traditional and non-
mechanized production systems and poor transportation infrastructure reflect low
productivity levels and have limited the performance of cassava production systems.12
20
32. There are several factors contributing to this relatively low level of growth,
including insufficient agricultural support services such as extension, research, and
financial services, limited utilization of improved inputs, heavy dependence on rainfall
for predominantly rain-fed agriculture, unsustainable land use practices like slash and
burn agriculture, and constrained access to input and output markets, especially in
the northern and central regions. Additionally, challenges such as lacking formal land
property rights, inadequate rural infrastructure, storage and irrigation facilities (with
only about 3 percent of cultivated land under irrigation), and fragmented institutional
arrangements at both central and sub-national levels further impede progress.
Addressing these obstacles is imperative to enhance agricultural productivity and
foster sustainable development in Mozambique’s agricultural sector.
33. Expanding the agricultural sector holds immense poverty reduction,
income generation, and employment potential. However, it faces hurdles such as
low productivity due to reliance on traditional farming methods, inadequate access to
advanced technologies, and market uncertainty. Despite simulations indicating that
agricultural growth could significantly alleviate poverty and inequality compared to
other sectors, persistent challenges like limited access to finance, quality assurance,
competitiveness, value addition, seasonal production, and climate vulnerabilities
hamper its full potential.13 Nevertheless, agriculture remains pivotal for food security,
with many smallholders prioritizing subsistence over profit. Transitioning from
agricultural to industrial employment would be risky without improved agricultural
productivity.
34. Mozambique has abundant natural resources, including vast arable
land, mineral deposits, freshwater sources, and offshore natural gas reserves.
Despite this wealth, the country has struggled to utilize these resources effectively
for sustained poverty reduction. The extensive natural capital encompasses 36 million
hectares of arable land, 32 million hectares of natural forests, and a lengthy coastline
rich in biodiversity, hosting diverse marine and terrestrial species, including many
endemic ones. However, Mozambique faces significant challenges in sustaining its
renewable resources, notably high deforestation rates, averaging 267,000 hectares
annually14. This rampant deforestation contributes to climate change by emitting
substantial amounts of CO2, accounting for a significant portion of the country’s
greenhouse gas emissions. The main drivers of deforestation is the expansion
of shifting agriculture, worsening land degradation, water scarcity, and increased
vulnerability to climate change impacts. Addressing these challenges is crucial for
promoting sustainable development and preserving Mozambique’s natural heritage for
future generations.
35 Notwithstanding the agricultural comparative advantages and resource
endowments, the average productivity levels (measured by yields) are among the
lowest in the region (see Annex 16), showing marginal increases in the last 20 years
for products such as rice, maize and cassava. This indicates that strengthening
the adoption of technology, improving rural infrastructure (including expansion of
irrigation), reducing constraints along major value chains, and enhancing market
access, financial services, and risk management could go a long way in increasing
sustainable agricultural production and competitiveness, as well as climate change
resiliency.
11
International trade administration report (2022). Accessed at: https://www.trade.gov/country-commercial-guides/mozambique-agricultural-sectors
12
See: “The Cassava Value Chain in Mozambique”. Jobs Working Paper 31. World Bank
13
Africa Olojoba & Karin Kaechele (2021). Accessed at: https://blogs.worldbank.org/nasikiliza/results-
based-climate-finance-boosts-sustainable-forest-conservation-mozambique
21
36. The country is ranked as the third most vulnerable to climate change
in Africa due to a combination of natural hazards, including flooding,
droughts, and cyclones15. With its extensive coastline of more than 2,700 km,
numerous international river basins, and heavy reliance on agriculture, Mozambique
is particularly susceptible to such environmental shocks, especially given its high
poverty rates and inadequate infrastructure. Most of the population resides in low-
lying coastal areas, where they face chronic poverty and rely heavily on subsistence
agriculture (undertaken by about 70 percent of the rural population). The increasing
intensity and frequency of storms, droughts, and floods are expected to exacerbate
food insecurity and agricultural income, further threatening livelihoods. Rising
temperatures and changing rainfall patterns are likely to decrease crop yields, while
increased flooding necessitates further land clearing, exacerbating deforestation
and land degradation. According to the Global Risk Data Platform (UNEP/GRID-
Europe), drought is the adverse climatic event to which Mozambique has the highest
physical exposure. In some districts of the country, the expected average annual
population exposed to this event is larger than 300,000 inhabitants, with higher
exposure in Manica, Sofala, Nampula and Zambezia, all of them important agricultural
regions. Moreover, warming oceans pose significant risks to coastal ecosystems and
fisheries, impacting tourism and livelihoods dependent on marine resources. Overall,
Mozambique faces significant challenges in adapting to and mitigating the impacts of
climate change, particularly in the face of existing socio-economic vulnerabilities and
environmental degradation.
37. Consistent with the situation across sub-Saharan Africa, women in
Mozambique play a vital role in agriculture, constituting over 70 percent of the
agricultural labor force. Despite their significant contributions, the productivity of
female farmers tends to be lower than that of male farmers. This productivity gap is
influenced by various factors, such as unequal access to quality seeds and inputs,
limited mobility due to cultural norms and knowledge gaps, and time constraints.
Female-headed households exhibit lower productivity than male-headed households,
with more pronounced differences observed in the central-north regions. While
female-headed households tend to cultivate relatively smaller plots, a significant
productivity gap persists, suggesting underlying structural issues related to technical
efficiency and discrimination. Addressing gender-specific obstacles in the agriculture
and fisheries sectors is essential for empowering women to reach their economic
potential and reducing poverty and food insecurity overall. By promoting gender
equity, Mozambique can further harness the full potential of its agricultural sector and
contribute to sustainable development.
38. Leaving behind the challenges posed by the COVID-19 crisis,
Mozambique’s economic recovery is anticipated to gain momentum, with
projections suggesting an average growth rate of 5.7 percent between 2022
and 2024.16 Despite its potential to alleviate poverty and inequality significantly,
agricultural productivity in Mozambique lags behind regional standards,
particularly evident in low cereal yields per hectare. The recent main policy
recommendations have focused on realigning agricultural support strategies to
enhance competitiveness, climate resilience, and food security. Suggestions have
included redirecting agricultural support towards public goods and services like
rural infrastructure and research, fostering a shift towards market-driven agricultural
policies, reducing implicit taxation on food to alleviate the burden on the poorest
households, recommending mechanization and promoting smart subsidies to
enhance productivity, resilience, and nutritional outcomes while integrating climate-
Climate watch historical GHG emissions (2023). Accesses at: https://data.worldbank.org/indicator/
15
EN.ATM.CO2E.PC?end=2020&locations=MZ&start=1990&view=chart
Montana MQC & Hasegawa H (2018). The current situation and perspectives regarding agriculture mechanization in Republic of Mozambique.
16
Agricultural mechanization in Asia, Africa and Latin America 49: 34.EN.ATM.CO2E.PC?end=2020&locations=MZ&start=1990&view=chart 22
smart technologies. These measures aimed to optimize agricultural support programs,
fostering sustainable growth and development in Mozambique’s agricultural sector. 17
39. Expanding extension services ensures that technological advancements
reach most small-scale farmers. While the number of extension workers has
increased significantly from 501 technicians in 1999 to 1,775 technicians in 2022, this
number still falls short of meeting demand. Official statistics indicate that the coverage
rate of public extension services reached only about 4 percent of total households
engaged in agriculture in 2015. Furthermore, challenging working conditions have led
some technicians to seek other job opportunities, further hindering the availability of
extension services. Despite this growth, many farmers still lack access to agrarian
extension services.18
40. Most recent data available shows that the number of full-time equivalent
(FTE) agricultural researchers per 100,000 smallholder farmers (and per one
million population) has increased from 3.1 (11.4) in 2013 to 3.7 (13.9) in 2017.
Agricultural researchers with Ph.D. degrees saw the highest percentage increase,
at 35 percent, followed by those with B.Sc. degrees at 32 percent, and finally, those
with M.Sc. degrees at 18 percent, between 2013 and 2017. Despite these differential
percentage increases, the proportions of FTE agricultural researchers accounted for
by researchers with each degree (Ph.D., M.Sc., and B.Sc.) remained consistent over
the period from 2013 to 2017. On average, researchers with Ph.D. degrees accounted
for 8 percent, researchers with M.Sc. for 43 percent, and researchers with B.Sc. for
49 percent of the total.
41. It is evident that mechanization adoption rates are nearly non-existent in
northern Mozambique19. Some large-scale farmers offer land preparation services
to smaller neighboring farmers, typically after tending to their own fields. Since larger
farms often prioritize their own land, preparation on other farms where plowing is
done with hired tractors may be delayed. This delay can impact planting timing and
potentially reduce yields. Additionally, limited entry space in subsistence farmers may
limit the use of tractors and increase the use of 2-wheel tractors and handheld farm
tools. Additionally, there is a reduced number of imported tractors, which is strictly
limited to public institutions, indicating low purchase power by subsistence farmers.
Montana MQC & Hasegawa H (2018). The current situation and perspectives regarding agriculture mechanization in Republic of Mozambique.
16 18
Agricultural mechanization in Asia, Africa and Latin America 49: 34. EN.ATM.CO2E.PC?end=2020&locations=MZ&start=1990&view=chart
17
Marassiro MJ, Oliveira MLR, Come S. (2020). Three decades of agricultural extension in Mozambique:
Between advances and setbacks. Journal of Agricultural Studies 8 (2): 418.
23
BOX 1: CHARACTERISTICS AND PERFORMANCE OF SMALL-SCALE PRODUCTION
IN MOZAMBIQUESTRATEGY 2020–2030
The small-scale producers’ segment of the sector has an important presence and relevant
characteristics in the national supply. This segment of producers presents structural difficulties that
limit their access to markets under profitable conditions. This is of special importance given that the
sector employs 30% of the employed population and generates 24% of GDP. According to information
from the 2020 Agricultural Census, carried out by MADER, these are some of the most significant
characteristics of small producers.
(a) High participation in the number of total units. Out of the 4.2 million rural economic units, small-
scale producers represent 92% of the total, while large-scale producers only represent 0.02%
(b) Low participation in extension services. Only 6.9% of small units receive visits for extension
services.
(c) Poor use of improved technologies. Only 9.1% of small units use irrigation technology, and only
7.8% use chemical fertilizers. Less than 10% of the units use certified seed for basic cereals such as
corn or rice.
(d) Low level of organization. Only 3.5% of the small units belong to a productive association (e.g.,
cooperative, etc.)
(e) Poor access to credit and financing. Only 0.6% of the small units have received any agricultural
credit.
(f) Low market share. In the case of rice, only 12 percent of small-scale producers sold their products
in the market, 20 percent in the case of maize, and only 12 percent in the case of cassava.
(g) Average productivity lower than the national average. In 2022, the average maize yield by
smallholders was 0.8 tons/ha, which is 37% lower than the national average. In the case of rice, the
yield was 32% lower than the national average.
Source: Inquérito Integrado Agrário, 2020. Ministério da Agricultura e Desenvolvimento Rural (MADER).
Commercial Financing Services.
42. Commercial financing continues to lose relative importance compared to
the GDP. In 2023, the total balance of the outstanding credit portfolio amounted
to about 245,677 million meticais (US$3,844 million), with an AAGR of 2.3
percent recorded for the four-year period 2019 to 2023. Nevertheless, the credit
portfolio decreased when compared with GDP levels, moving from 22.5 percent of the
total national GDP in 2019 to 20.5 percent in 2022, a reduction of 2 percentage points
over three years (See Figure 12).
43. Meanwhile, the agricultural, forestry, and fisheries sectors have lost
prominence in the credit portfolio. According to data from the Bank of Mozambique
for 2023, the sector’s total balance stood at 5,097 million meticais (about US$80
million), representing 2.1 percent of the total year-end balance. This was lower than
the 3.7 percent the sector’s portfolio represented at the end of 2019 (see Figure 13).
24
Figure 12. Year-end balance and its participation in the GDP (EFPI): 2014-2023(US$ million and percentage)
Source: Central Bank of Mozambique and INE
Figure 13. Share of the agricultural, forestry, and fisheries sector in the total credit portfolio balance 2014-2023
Source: Central Bank of Mozambique and INE
25
3.Overview of the
Level of Agricultural
Public Expenditure
44. Over the 2019-2022 period, Mozambique’s public investments in the
agriculture sectors lightly increased in nominal terms. Although in 2022
agriculture budgetary expenditures almost doubled the equivalent expenditure from
the previous year (Figure 14), the country has been lagging in addressing the goal
agreed in the Malabo declaration, which consisted in allocating 10 percent of the
national budget to the agricultural sector. The most recent 4th CAADP biennial report
review covering the period 2015 to 2023 positions Mozambique as “out of track” in
addressing this and the other six goals of the Malabo declaration until 2025 (AU,
202420). That scenario is similar to the other 11 countries from Southern Africa that
have been analyzed.
Figure 14: Mozambique’s agriculture budgetary expenditures and its share of national expenditures (2014-2022)
Source: Based on data collected from the Government General Account (CGE, 2014-2022) (MEF, 2019-2022)
45. In addition, based on data from the Government General Account (CGE) and
the National Institute of Statistics (INE)21, annual expenditures for the agricultural
sector have been around 6 percent of agricultural GDP on average (2019-2022).
19
AU. (2024). 4th CAADP Biennial Review Report 2015-2023. African Union.
20
INE. (2024). Estatísticas Económicas. From Instituto Nacional de Estatística: https://www.ine.gov.mz/web/guest/d/pib_optica_producao_2022.
26
In 2022, the relation of the expenditures for agriculture to the agricultural GDP
increased with respect to 2021, from around 5 percent to about 8 percent. However,
the pattern of GDP and agriculture GDP during 2014-2022 does not indicate that an
increased agriculture expenditure has been leading to efficiency gains (see Figure 15),
even though these effects may be perceived only in the longer term due to several
continuous investment cycles.
Figure 15: National and Agricultural GDP and Agriculture Expenditures as a percentage of Agricultural GDP
(LCU and percentage).
Source: Based on data collected from CGE (MEF, 2019-2022) and INE (2024)
46. PEDSA II and its Investment Plan. The new Plano Estratégico para o
Desenvolvimento do Sector Agrário (PEDSA 2030 or PEDSA II) has been formally
approved in 2023 and, as a continuation of the previous PEDSA, its mission is “to
accelerate the Mozambican economic grow through the agrarian sector’s accelerated
and sustainable transformation to enhance income generation, food security and
nutrition and additional job opportunities creation” (MADER, 2023 p.1422). PEDSA II’s
investment plan (PNISA II) identifies a financial gap of nearly 524,000 million MZN
(equivalent to USD 8,451 million) for its full implementation. This is equivalent to about
50 percent of the country’s average GDP or nearly twice the average agriculture GDP
over the period 2019-2022.
47. Agriculture Production and Productivity as the Second Last Investment
Priority in PEDSA II. PEDSA II is designed around four strategic pillars to be
implemented within two periods (2022-2026 and 2027-2030). Within the new
Agricultural Investment Plan (PNISA II), budget allocation for the strategic pillar
focused on improving production, productivity and agricultural competitiveness (Pillar
1) corresponds to nearly 19 percent of the total. Pillars 3 (related to marketing issues)
and 2 (dealing with sustainable management of natural resources) comprise the
largest shares of budget allocation, at 46 and 28 percent, respectively. Nevertheless,
investments in agricultural research, extension and irrigation are budgeted at about
two-thirds of the budget allocated to Pillar 1.
MADER. (2023). PEDSA 2030. Plano Estratégico para o Desenvolvimento do Sector Agrário. Ministry of Agriculture and Rural Development.
21
27
48. Levels and Trends of Agrarian Sector Expenditures. The institutional
arrangement of the agrarian sector in Mozambique, which deals with the key functions
or programs contributing to the agricultural development, is fragmented in five
different ministries: (i) the Ministry of Agriculture and Rural Development (MADER)
as the leading body responsible for (amongst others) agricultural policies formulation
and implementation, including as well the provision of agricultural services; (ii)
the Ministry of Land an Environment (MTA), which deals with the sustainable use
of natural resources including land for agriculture; (iii) the Ministry of Public Works,
Housing and Water Resources (MOPHRH), whose core business include as well
the construction and/or rehabilitation of rural infrastructure that play a central role to
agricultural competitiveness; (iv) the Ministry for Sea, Interior Waters and Fisheries
(MIMAIP), that oversees the other arm of the agrarian23 sector arm related to (on and
off-shore) fishery development, and; (v) the Ministry of Industry and Trade (MIC), who
deals as well with trade and policy formulation and implementation within the domain
of the agriculture sector. As highlighted in the World Bank’s 2021 report24, public
expenditure trends over the period 2013-2017 indicate that “Agricultural budgetary
allocations are erratic and decreasing among all ministries (except [ex-]MITADER
[now MTA]) […] and misaligned with the relative importance of the sector’s share
of GDP” (WB, 2021, pp. 13-14). Nevertheless, available data from the most recent
period (2020-2022) suggest an overall increase in budget execution over the five most
relevant ministries in the agricultural sector. This general pattern is highlighted for
investments (Figure 16) or functioning expenditures25 (Figure 16) in budget executions.
Across the five ministries, the highest investment budget execution has been from
the MOPHRH, whilst MADER reveals the largest budgetary execution for operational
functioning expenditures. MADER also displays the largest relative share of the
functioning budget executed on goods and services expenditures.
Figure 16: Public investment expenditures in the agricultural sector, by ministry (million LCU).
Source: Data from CGE (MEF, 2019-2022)
22
PEDSA defines the agrarian sector as comprised of agriculture, livestock, forestry, and fishery activities. We adopt
the term agriculture sector interchangeably with the broader definition of the agrarian sector.
WB. (2021). Mozambique Agriculture Support Policy Review. Realigning Agriculture Support Policies and Programs. World Bank
23
As disaggregated in Figure 17, functioning expenditures include expenditures on personnel (salaries),
24
government bodies functioning (current transfers), capital, goods and services, and others. 28
Figure 17: Public expenditures allocated for operational functioning by ministries in the agricultural sector (million
LCU).
Source: Data from CGE (MEF, 2019-2022)
49. Funding of Agricultural Expenditures. Budget endowment for public
investments has been significantly higher for MOPHRH and MADER compared to
MTA, MIMAIP and MIC. For MIC, nearly 80 percent of the total investment funding
over the period 2019-2022 has been from internal sources, and for MTA it has been
around 58 percent. On the other hand, for MADER internal funding covered about 25
percent of total funding (see Table 4). For the remaining ministries, internal funds have
also represented less than half of total funding (20 and 32 percent for MIMAIP and
MOPHRH, respectively). Nevertheless, external funding remains in the main form of
donations across the five ministries, either in cash or in-kind (see Figure 18).
Table 4: Investment budget allocations by source of funding across the key Ministries 2019-2022 (million LCU).
Source: Data from CGE (MEF, 2019-2022)
29
Figure 18: External funding for agriculture investment by source of funding 2019-2022 (103 Million LCU).
Source: Data from CGE (MEF, 2019-2022)
50. Expenditure on Agricultural Research Remains Low. General spending
in agriculture has remained relatively low and about half of the Malabo declaration
target of 10 percent, and key investment areas have not been effectively targeted in
Mozambique. The World Bank’s (2019) report highlights low levels of investments in
strategic areas of the agrarian sector, such as agricultural research, extension and
irrigation. The most recent Union Africa report on agriculture research investment
echoes that and positions Mozambique in the second lower group in terms of
agriculture research spending. The country is also ranked amongst the worst
performers in terms of agriculture research system (AU, 202226). According to the
same report, the country’s share of agriculture research expenditures was nearly
around 0.5% of national GDP in 2016. Although access to the most recent and
updated data would be essential for a more accurate assessment, given the several
internal and external macroeconomic constraints the country has faced in the last
decade, the pattern of agriculture research spending and performance is unlikely to
improve.
25
AU. (2022). Boosting Investment in Agriculture Research in Africa: Building a Case for Increased Investment in Agricultural Research in Africa. African Union
30
4. Assessment of the
Support to Agriculture
in Mozambique
(2019-2022)
4.1 The OECD Methodology - Rationale and Coverage
51. This section provides an estimate of the level of monetary transfers to
agriculture in Mozambique resulting from implementing agricultural policies
during the period 2019-2022. The methodology used for estimating support to
agriculture was created and used by the Organisation for Economic Co-operation
and Development (OECD). Each year since 1987, the OECD has measured monetary
transfers associated with agricultural policies in many countries using its standard
methodology. The methodology developed by OECD for estimating agriculture
support was developed to monitor and evaluate agricultural support policies and
programs using a common and easy-to-use approach for policy dialogue among
countries and to provide economic data to assess the effectiveness and efficiency of
national policies. The main indicators to be used were mandated by OECD Ministers
in 1987 and have since been calculated for the OECD as well as an increasing
number of non-OECD countries and are widely referred to in the public domain.
52. The objectives of agricultural policies in OECD countries have evolved
over time, from overcoming food shortages or surpluses in the post-war period to
securing food safety, environmental quality, and preservation of rural livelihoods.
Policy instruments have also changed, reflecting changes in domestic political and
economic settings and, progressively, developments in international economics.
Given this diversity, the OECD has developed a methodology, called PSE in the
literature, to compute support indicators measuring transfers to the agricultural sector
and enabling comparability over time and across countries. PSE indicators provide
insights into the burden that agricultural support policies place on consumers (market
price support) and taxpayers (budgetary transfers). This is the most widely and
systematically used methodology to monitor support to the agricultural sector currently
available internationally, and its results (published annually) provide important
contributions to the international policy dialogue on agriculture and trade27.
53. There are at least three clear benefits when adopting this methodology for
reviewing agriculture policies at a global level:
• Monitoring and evaluation of agricultural policy developments: This includes
policy reforms achieved by countries over time through specific reform efforts (e.g.,
the U.S. Farm Bills and EU Common Agriculture Policy (CAP) reforms), as well as
progress towards achieving international commitments agreed (EU, CAADP)28.
As it is neither affected by inflation nor the size of the sector, it allows comparisons in the level of support to be made both over time and between countries.
26
OECD’s Producer Support Estimate and Related Indicators of Agricultural Support: Concepts, Calculations, Interpretation and Use (The PSE Manual).
27
This commitment stated that “agricultural trade should be more fully integrated within the open and multilateral trading system,”, and it called for OECD
28
countries to pursue “a gradual reduction in protection and a liberalization of trade, in which a balance should be maintained as between countries and
commodities.” Ministers also requested the OECD to develop a method to measure the level of protection in order to monitor and evaluate progress.
31
• Establishment of a common base for policy dialogue: By using a consistent
and comparative method to evaluate the nature and incidence of agricultural
policies, countries have a common base to engage in trade negotiations and
common agriculture policy discussions (WTO, WB, IMF, and FAO). They are also
useful for farming and non-government organizations and research institutions
in discussing the differentiated impact of agriculture policies. Mexico, Colombia,
Central America and the Andean countries used these estimates to develop their
transition into the FTAs with the U.S. and the EU.
• Undertaking research on policy impacts: The data serves as an input into
modeling to assess the effectiveness and efficiency of policies in delivering the
outcomes for which they were designed and to understand their effects on
production, trade, income, and the environment. While the indicators cannot by
themselves quantify these impacts, the economic information upon which they are
based is an important building block for further analysis.
54. While there are strong advantages, there are also some limitations to
using the OECD methodology to review Mozambique’s agriculture support
policies. The advantages are that: (i) it provides a systematic and integrated view of
agriculture support policies and programs (not limited to the more traditional public
expenditure reviews and rates of protection); (ii) given the large number of countries
using this same methodology, an immediate benchmarking is possible across a
large set of comparators29; and (iii) the methodology is simple and can be integrated
into the agriculture public policy analysis conducted by the Government and other
stakeholders.
55. At the same time, the methodology also has some disadvantages and
limitations, mainly: (i) Only a few African countries have carried out agriculture support
estimates with it, meaning Mozambique cannot benchmark its results across a large
number of African countries (e.g., South Africa and Angola are early adopters), and
(ii) since the estimates are based on the monetary value of budget and price support,
other non-monetary supports, like the quality of policies, are not captured. As an
example, the methodology can identify how much policy support is invested in land
administration efforts but is unable to qualify the impact (quality) of those policies.
56. This report produces indicators covering a range of agricultural support
and is expected to inform any eventual trade negotiations and policy reforms
to enhance sector competitiveness and economic diversification. In particular,
the support indicators are expected to be relevant to AfCTA trade negotiations
on agriculture and food products. These estimates would enable Mozambique to
benchmark against trading partners and comparator countries like South Africa in
relation to the level and composition of agriculture support. Given the current fiscal
constraint and the need to diversify its economy, there is a window of opportunity for
the Government of Mozambique to gradually broaden the trade of agricultural inputs
and products while shifting public spending towards more targeted interventions.
4.2 Technical Concepts for the Calculation of Indicators
29
At present, the OECD methodology for agriculture support estimates covers 109 countries. This includes OECD countries, non-OECD EU Member
States (subject to data availability), and several developing countries where monitoring is done by the OECD, IADB, and FAO’s MAFAP unit. The 54
countries monitored by the OECD are Argentina, Australia, Brazil, Canada, Chile, China, Colombia, Costa Rica, the European Union (Austria, Belgium,
the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands,
Poland, Portugal, Spain, Slovakia, Slovenia, Sweden, the United Kingdom), India, Indonesia, Iceland, Israel, Japan, Kazakhstan, Korea, Mexico,
New Zealand, Norway, the Philippines, the Russian Federation, South Africa, Switzerland, Turkey, Ukraine, the United States and Viet Nam.
32
57. Agricultural support is defined in this report as gross monetary
transfers to agriculture from consumers and taxpayers arising from public
policies that support the agricultural sector measured at a farm level.
This definition covers budgetary and non-budgetary expenditures such as credit
concessions and direct subsidies (electricity, fuel, water, farm inputs). It also includes
implicit price support from border trade (tariffs, taxes) and domestic market measures
(e.g., minimum product support prices). Overall, the methodology enables the
computation of total transfers to producers (PSE), consumers (CSE), and general
services (GSSE), respectively, with a clear identification of transfer sources (domestic
taxpayers and consumers)30. The OECD methodology also allows the calculation
of disaggregated PSE for each product considered. The different levels of support
are reflected in the Producer Single Commodity Transfers (SCT), a measure of
commodity-specific agricultural policies.
58. This methodology identifies three major indicators: (a) the Total Support
Estimate (TSE); (b) the Producer Support Estimate (PSE); (c) the Consumer Support
Estimate (CSE); and (d) the General Services Support Estimate (GSSE) (see Box 2).
It is important to highlight that the estimations have considered the transfers resulting
from implementing national and provincial government policies (Ministry of Agriculture
and Rural Development, Ministry of Land and Environment, National Institute of
Statistics, and municipalities, among others). This approach allows for quantifying
these transfers and estimating their impact on the producer/consumer or the provincial
and national sectors.
The PSE is an indicator that measures the annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured
30
at the farm-gate level, arising from policy measures that support agriculture, regardless of their nature, objectives or impacts on farm production or income.
The GSSE is a proxy for public support to agricultural public goods such as research and extension, agricultural education and some research and extension,
agricultural education and some infrastructure investments closely linked to agriculture. It is defined as the annual monetary value of gross transfers arising from
policy measures that create the public goods and the enabling conditions for the primary agricultural sector through development of private or public services, 33
and through institutions and infrastructures regardless of their objectives and impacts on farm production and income, or consumption of farm products.
BOX 2: OECD INDICATORS OF SUPPORT TO AGRICULTURE
1. Producer support indicators. Throughout this document, it will be emphasized that the estimation of the
various supports comes from the implementation of agricultural policy measures by the National Government
and their impact on the producer (individually or collectively), the consumer, and the entire agricultural sector.
(a) Producer Support Estimate (PSE). It is the absolute monetary value of gross transfers to agricultural
producers, measured at the farm level, resulting from implementing the government’s agricultural policy
measures supporting agriculture. The identified sources of these transfers are consumers (through the
payment of higher prices) or taxpayers (through the budgetary funding of various government public
programs). These transfers are estimated irrespective of their nature, objectives, or impacts on agricultural
production or incomes.
(b) Percentage of PSE (%PSE). The %PSE represents monetary gross transfers to producers as a
percentage of gross agricultural revenues at the farm level (including transfers). It is the OECD’s key indicator
for measuring support to agricultural producers, as it provides insights into the burden that agricultural
support policies place on consumers (i.e., market price support) and taxpayers (budgetary transfers).
(c) Producer Single Commodity Transfers (Producer SCT). The annual monetary value of gross transfers
from consumers and taxpayers to agricultural producers (at the farm level), resulting from policy measures
by the Government that are directly related to the production of a single product. This indicator will also be
referred to as “PSE by product” in this study.
(d) Producer Single Commodity Transfers as a percentage of Gross Income (Producer %SCT). The SCT
as a percentage of the gross agricultural revenues for the specific product. This indicator will also be called
“PSE percent by product” in this study.
2. Consumer support indicators
(a) Consumer Support Estimate (CSE). The annual monetary value of gross transfers to (from) consumers
of agricultural products, measured at the farm level, arises from the implementation of government policy
measures supporting agriculture, irrespective of their nature, objectives, or impacts on agricultural product
consumption. If negative, the CSE measures the burden on consumers (implicit tax).
(b) CSE as a percentage (%CSE). CSE as a percentage of net consumption expenditure (measured at
the farm gate) net of transfers from taxpayers to consumers. The %CSE measures the subsidy or implicit
tax placed on consumers by agricultural price policies (depending on whether it is positive or negative).
3.General services support indicators for agriculture
(a) General Services Support Estimate (GSSE). Represents the annual monetary value of gross
transfers from taxpayers to general services provided collectively to agricultural producers (inter alia, rural
infrastructure, research and development, training, inspection, marketing, and promotion), arising from
the implementation of government policy measures that support agriculture, regardless of their nature,
objectives, and impacts on agricultural production, income, or consumption. The GSSE does not include
any transfers to individual producers.
(b) GSSE as a percentage (%GSSE). GSSE as a percentage of the Total Support Estimate (TSE).
4. Total Agriculture support indicators
(a) Total Support Estimate (TSE). The annual monetary value of all gross transfers from taxpayers
and consumers arising from implementing government policy measures supporting agriculture, net of
associated budgetary revenues, regardless of their objectives and impacts on agricultural production
and income or the consumption of agricultural products.
(b) TSE as a percentage (%TSE): TSE as a percentage of the agricultural GDP.
34
59. Beyond the formal definitions outlined in Box 2, It is useful to have a clear and
practical concept of these indicators:
• PSE: refers to the monetary transfers individual producers receive due to national
policies. This amount is analyzed as part of the producer’s gross income,
representing the percentage of his gross income a producer receives due to the
policies, while the rest is derived from his own productive activities in the market.
• GSSE: refers to transfers received by the sector as a whole (and not individual
producers) and basically includes the transfers received from investments in public
goods such as research, infrastructure, health, etc. This indicator, in addition to
being presented in absolute values, is usually also presented as a percentage of
GDP, providing some relative context with the size of the entire economy.
• CSE: refers to transfers to/from consumers. Some policies that seek to benefit
producers are carried out at the expense of consumers and these benefits to the
producers also represent an “implicit tax” on the consumer. A negative %CSE
implies that the value of the food basket for an average consumer becomes more
expensive (implicit tax), as a result of support received by the producers.
4.3 Beneficiaries and Funding Sources of Support to Agriculture.
60. This methodology enables the identification of transfer beneficiaries and the
identification (and quantification) of the funding sources for these transfers. This
enables the evaluation of the policies that generate such transfers in relation to the
major reforms established in previous years, with outcomes assessed considering
the externalities to all economic agents involved in the sector’s development.
Typically, the sources of these transfers are consumers (who may transfer resources
to producers by paying prices above market levels) and taxpayers (who fund the
execution of public programs and projects). The methodology applied in this study
is consistent with the one used in OECD reports, which periodically monitors and
evaluates agricultural policies in OECD and other countries.
61. Figure 19 illustrates the relationship between recipients (beneficiaries) and
funding sources for transfers generated by agricultural policies. There are three
fundamental types of recipients: individual producers, the entire agricultural sector,
and consumers. When a state policy measure benefits a specific product or group
of products, such measures are classified within the PSE category, and their funding
source can be consumers (through higher prices) or taxpayers (through tax payments
that finance support programs).
62. Meanwhile, when a government policy is implemented and the beneficiary
is the entire sector, it is classified as GSSE, and these measures are financed
by taxpayers. Finally, agricultural policy measures that make the consumption of
agricultural products cheaper (or more expensive) or easier (or more difficult) are
classified within the CSE. The financing for these measures can come from taxpayers
(via public programs that subsidize the consumption of products) or directly from
consumers (through government intervention measures that influence market prices).
35
Figure 19. Scheme of Transfers Associated with the Implementation of Agricultural Policies.
4.4 Total Support Estimate for Agriculture (TSE)
63. The Total Support Estimate for Agriculture (TSE) is the main “Aggregate”
indicator that includes the sum of transfers to agricultural producers, both targeted
individually (PSE) and collectively (GSSE), as well as direct budgetary transfers
to consumers, all resulting from government agricultural policies. This indicator can
be expressed in absolute terms or as a percentage of GDP (%TSE). In the latter
case, %TSE indicates the cost that support for the agricultural sector represents
for the economy and is commonly used to make meaningful comparisons between
economies or over time. In absolute terms, the TSE in Mozambique for the period
2019-2022 amounted to 37,094 million meticais (MMT) (about US$ 567 million),
equivalent to an average of 3.5 percent of the national GDP during the period
analyzed and reaching a peak of 4.9 percent in 2022. (See Figure 20)31
Figure 20. Total Support Estimate (TSE) and its share of GDP 2019-2022 (MMT, USMM and percentage)
31
The increase towards 2021 and 2022 was attributed to various causes: 1) the market price support programs significantly increased
from 2020 to 2021, rising from 41,937.6 MT Million to 127,122.7 MT Million; 2) State public investment in general services and,
particularly, the expenditure related to the development and maintenance of infrastructure nearly tripled during that period.
36
64. Compared with other countries, the monetary transfers to the sector
associated with agricultural policies are relatively small in absolute terms
but high in relative terms as a percentage of GDP. Figure 21 shows that, on
average for 2019 to 2022, the Total Support Estimate as a proportion of total GDP is
comparatively higher in Mozambique than in other countries.
Figure 21. Total Support Estimate, relative to GDP (Percentage TSE) Average 2019-2022
65. Most of the monetary transfers to the sector were funded by consumers.
For every dollar transferred to the sector, an average of about 84 cents were
funded by agricultural consumers (through the payment of domestic prices above
international reference prices) and the remaining 16 cents by taxpayers (through the
finance of public programs). This pattern is in stark contrast to OECD countries, where
taxpayers are the ones generating the most transfers compared to consumers (See
Figure 22). The promotion of various agricultural reforms in developed countries over
the past thirty years has sought to reduce the impact on consumers in supporting the
sector. To the extent that consumers are the main source of financing for transfers
to the sector, this can have important distributional repercussions. As will be seen
below, these repercussions can imply outcomes that negatively impact lower-income
households32.
Figure 22. Total Support Estimate by Source of Financing (average 2019-2022)
32
“The Distributional Impact of Agricultural Sector Reforms in Africa: A Review of Past Experience”. IMF
37
66. An analysis of the composition of the TSE shows that direct support to
producers (PSE) makes up most of the total support to the sector (an average
of 89.7 percent of the TSE). On the other hand, support aimed at the sector as a
whole, with characteristics of public goods (GSSE), represents, on average, 10.3%
of the total (see Figure 23). In OECD countries, direct support is less relevant, but
a greater share of taxpayer-funded consumer subsidies exists. This implies that the
mechanism of support for the sector in the country has basically been through direct
support for individual products or groups of products. In contrast, collective support for
the sector (public goods) has represented a smaller proportion within this structure.
The structural challenges of the sector can hardly be overcome through a scheme of
individual support. The evidence shows that the average productivity of key products
has remained stagnant in recent years and the high dependence on imports of
strategic products continues to be evident.
Figure 23. TSE by component of Support (2019-2022)
4.5 Producer Support Estimate (PSE)
4.5.1 Level of support
67. The Producer Support Estimate, in absolute terms (PSE) or as a percentage
of farm revenues (%PSE), is one of the most relevant indicators used to gauge the
impact on the farmer of transfers associated with implementing government policies.
As explained, these transfers come either from consumers or taxpayers. This
indicator can be expressed in absolute terms or as a proportion of the producer’s
gross agricultural income (PSE%). Under this criterion, the indicator allows for
reasonable comparisons between products, countries, or over time, and the
organization itself considers it the “most appropriate indicator for comparing changes
in the level of support to the farmer.”
68. Figure 24 displays Mozambique’s total %PSE estimate from 2019 to 2022. In
the first year, the %PSE indicates that 9.0 percent of the gross income of agricultural
producers was generated by government support policies through transfers. Despite
some mid-year declines, in 2022, it increased to a similar level as in 2019. For that
period, the %PSE average stood at around 6.8 percent. On average, 6.8% of gross
producer income in the period analyzed came from transfers derived from agricultural
policies, and the rest, 93.2%, from producers´ market activity. Nonetheless, as seen
below, this high level of support maintains high differences when analyzed by product.
38
Figure 24. Producer Support Estimate as percentage of Total Income (%PSE) 2019-2022
69. The %PSE indicator is lower than international comparisons. The level
of this indicator in Mozambique, as a proportion of income for the analyzed period
(6.8 percent), is comparatively low33. This means that the impact of transfers on the
producer’s income is relatively low compared with other countries (See Figure 25).
However, it is important to go further in analysis and see how this level of support is
composed.
Figure 25. %PSE Average for Selected Countries (2019-2022)
70. Table 5 shows the PSE composition according to each support
category’s importance. The market price support represented 99.1% of all direct
support on average for the period analyzed. Production and input support are much
less important. It is observed that other types of support granted without conditioning
to production (“decoupled”) have no relevance in the menu of support in the country.
These types of support, considered as “decoupled”, are considered to have a lower
impact on trade, production or consumption, i.e., with a relatively lower level of
distortion, compared to support via price, production or inputs, which are considered
highly distorting, ineffective in transferring income to producers and, above all,
inequitable. The design of this type of support does not condition the production of
certain products and, instead, focuses on other variables that do not affect production
decisions, such as the producer’s income level. By contrast, price support is much
less important in the OECD countries. Other types of support (taxpayer-funded) not
conditional on producing certain products (decoupled) are more important within the
As mentioned, comparison with other economies is reasonable and valid to the extent that the %PSE estimations reflect the importance of transfers generated by
33
policies (whether provincial or national) in the gross income of the producer. This enables a reasonable comparison with the same impact across other economies.
39
PES scheme. The OECD support is usually considered more effective in transferring
income to all producers, less inequitable, and less distorting.
Table 5. PSE Composition by Category of Support in Mozambique (Average 2019-2022)
71. Figure 26 includes the relative composition of the PSE according to the support
categories from 2019-2022. In this graph, the PSE amounts do not include the
Market Price Support (MPS) and only the categories of support granted from public
budgetary resources. In the case of Mozambique, production budgetary support
accounted for 52% of the PSE (excluding the MPS), almost 40% corresponded to
input subsidies, and the rest (8%) to miscellaneous support.
Figure 26. Porcentual Composition of Producer Support Estimate (without MPS) Average 2019-2022
72. From the list of countries for which there is available data, Mozambique stands
out for the high concentration of price support within the composition of the PSE (see
40
Figure 27). Countries with relatively higher levels of agricultural development generally
show a low MPS level within their PSE scheme.
Figure 27. Composition of Producer Support Estimate: 2019-2022 Average
Source: Based on OECD data
4.5.2 Analysis of Producer Support by Product
73. The methodology applied for this analysis allows for identifying and
quantifying the level of support transferred to a specific type or group of products
(“%PSE by product”). Formally, the analysis of support by product is referred to
as “Single Commodity Transfers.” For this discussion, it will be called “Producer
Support Estimate to the Product (name of the product).” It includes transfers made
for a particular product, such as rice or cassava. The PSE by product can also be
expressed in absolute terms and as a percentage of the producer gross income
generated by the product under analysis. In the latter case, for example, a support
of 33 percent indicates that the average value of the transfers derived from the
implementation of agricultural policies specific to that commodity is equivalent to
one-third of the gross agricultural income of the producers of that particular product.
For this analysis, the selected products were rice, cassava, maize, tomatoes, and
sweet potatoes, which were chosen due to their strategic importance in production,
consumption, and national trade.
74. There is no defined criterion for selecting products subject to this type of
support analysis. As a general rule, the criteria for selecting products must consider
aspects such as the relative weight of each product in the value of domestic
production and, in any case, comply with a number representing about 70% of the
total production value. The decision to choose one product or another may be related
to aspects such as the strategic importance of each product in the sector and the
national economy during the analysis period. In this way, the selection criteria must
consider the importance of the selected product in consumption, trade, employment,
planted area, etc. On some occasions, the selection is related to the proximity of
international trade negotiations, where certain products could have export potential
beyond their importance today in the abovementioned variables. The evolution
of markets over time can also give greater importance to certain products than in
41
previous years. In general, this decision is normally aligned with the interests and
objectives of each study.
75. For the purposes of the present analysis, the five products mentioned above
were included, considering that they were representative of national production,
planted area, consumption, employment, and trade. For future exercises, it would be
advisable to expand the analysis of other products such as pork, beans, etc.
76. Figure 28 displays Mozambique’s PSE as a percentage (%PSE) for the five
products included in this support analysis, as an average for the 2019-2022 period.
Throughout this period, rice exhibited the highest %PSE (47.0 percent), while the
other products had significantly lower levels of support. During the analyzed period,
transfers to rice producers accounted for an average of 47 percent of their gross
income; the rest of their income was due to their market operations. On the other
hand, for sweet potato producers, the transfers represented only 0.2 percent of their
gross income. These disparities between the two products are partly explained by
the fact that the domestic prices received by the producers are significantly higher
than the international reference prices. This difference is very important, especially
in rice and cassava, and it is largely explained by the distortions caused by price
support policies (basically import tariffs and restrictions), which prevent domestic
prices from aligning with international prices. This highlights the highly uneven impact
of agricultural policies across different products. Annex 14 includes details on PSE
calculation for each product.
Figure 28. %PSE by Product in Mozambique.(Average 2019-2022)
77. Table 6 includes the tracking of this indicator for each year analyzed. Rice,
cassava, and tomatoes show significant increases towards 2021, whereas all
products, except cassava, experience a decrease in the %PSE level in 2022. This
increase in 2021 resulted from the significant resource boost from various state
programs that year, aimed at financing agricultural projects and categorized under
“Commodity-based supports” in the Producer Support Estimate. Between 2020 and
2021, there was a significant increase in transfers (particularly for cassava). This was
because the recorded domestic prices rose significantly, reaching levels well above
those in the international reference markets, influencing the support level. Although
the international price of cassava increased significantly in those years (52%), the
domestic price increased by more than 145%. Several variables can explain this
increase, one of them coming from the reduction in domestic supply generated by the
continuation of restrictions on imports derived from tariffs and import difficulties in a
context of constant demand and a period of supply difficulties that continued after the
pandemic. Products with a lower level of support generally see lower international and
domestic price differentials.
42
Table 6. %PSE by Product in Mozambique 2019-2022
78. Mozambique’s support level for rice is comparable with other countries
like Korea and Japan. One characteristic is that support for rice in Mozambique is
mainly through prices, which implies important impacts and distributional effects
for rice consumers and mainly low-income consumers, who pay higher prices to be
transferred to producers (see Figure 29). In general, this high level of rice subsidy has
not resulted in a significant effect on the overcoming of existing structural challenges,
and there is no evidence of increases in yields and productivity, or in access to formal
credit, the reduction of dependence on imports or the entry of small producers into the
product marketing circuits. In the case of maize, Mozambique is below the average
%PSE of 4.9 percent of OECD countries for said period (see Figure 30).
Figure 29. Producer Single Commodity Transfers, relative to commodity specific gross farm recipts (Percentage
SCT): Rice, 2019-2022 Average
Figure 30. Producer Single Commodity Transfers, relative to commodity specific gross farm recipts (Percentage
SCT): Maize. 2019-2022 Average
43
Source: Own elaboration with OECD data
79. Concentration of Support. During the period under review, the direct annual
support to products (PSE) was, on average, about US$ 504 million. Of that total, only
two products (cassava and rice) concentrated 60.7 percent of the total, the rest of
which was distributed among other agricultural products. Table 7 shows the extent to
which the products under consideration account for the total support granted directly
in Mozambique.
Table 7. PSE concentration support by product
80. Direct support to products in Mozambique is through prices. The following
Table 8 shows the support structure of each product analyzed during the analysis
period. Here it can be seen that for the products analyzed, the support mechanism
is basically via prices. Perhaps in the case of maize, other support mechanisms
prevail to a greater extent, such as support for production or inputs. This aspect is
highly relevant because, to the extent that a product of high importance in domestic
consumption is supported via price, it has relevant distributional implications,
especially in the most vulnerable households that allocate a higher level of
expenditure on food and certain products. The case of sweet potatoes differs because
price support is non-existent. Cassava, on the other hand, was mainly supported
through price but to some extent marginally through support for inputs and production.
Table 8. Participation by type of support in PSE by product
44
BOX 3: PRICE VOLATILITY AND IMPACTS ON PSE RESULTS FOR RICE, MAIZE AND
OTHER COMMODITIES.
During the period analyzed, the producer support for maize, rice, and cassava showed significant variability. To explain
this behavior, it is crucial to consider that changes in the PES do not necessarily correspond to changes in policy
measures. This is true in Market Price Support, based on the gap between producer and border prices, as measured
against current market conditions. When border reference prices change due to variations in world market prices or
exchange rates, domestic producer prices may not follow (because internal measures are in place that prevent them
from doing so). Hence, the Market Price Support element in the PSE will change. Nevertheless, such variations in the
PSE are an appropriate reflection of the nature of market price support policies. It indicates that these policies (e.g.,
the border regime in place) insulate domestic markets from changing world market conditions and provide an amount
of support that varies over time according to movements in the world market prices.
The high volatility of international prices experienced in recent years, particularly in the period under analysis, has
influenced the PSE results of various products, including those analyzed. The figure below shows the behavior of the
FAO Food Price Index over the years, which denotes high volatility during the last years and a considerable increase
from 2020.
The tables below in this Bow show a comparison of the PSE% for maize and rice during the period 2019-2022 between
selected countries. In this table you can see the following:
Maize.
An overall reduction in PSE% is observed, mostly explained by the increased price level since 2020. Some countries
moved from large positive levels of support to large negative levels (e.g., Russia and India). The volatility of the support
level during this period was significant in those countries and in others, such as Brazil and Turkey, which went from
minimum levels in 2019 to levels three times higher than their average. Hence, the standard deviation of the period
is higher than the average.
In the case of Angola, between 2019 and 2022, there was a reduction in the PSE%, consistent with the trend observed
at the general level and which responds to the increase in international prices observed at the global level. There is also
slightly above-average volatility measured by standard deviation. The main explanation for this is that the domestic
price differential with the international reference price was only positive in 2020 and 2021, when the domestic price
was above the reference but subsequently converged with the international price, and consequently, the differential
was zero, in turn, the PSE% was close to zero.
Rice.
Support levels are generally higher than those observed in maize and other products. The general average observed
indicates a reduction in the level of generalized support due to the upward trend in international prices (although a
significant number of countries also increased the level of support).
45
In the case of Angola, as in the general trend, a high level of support was observed in 2019 and a reduction towards
2022, resulting from the increase in international prices observed at the global level. There is significant volatility,
although the standard deviation of the support levels is lower than its average. The main explanation for this in Angola
is that the price differential has been positive since domestic prices have always been higher than international
reference prices. However, since international prices showed a significant increase towards 2021 and 2022, and
domestic prices did not fall in the same proportion, this differential was considerably reduced, and with it, the support
measured with the PSE%.
Note. It has not been possible to compare Cassava with other countries; however, it also showed significant volatility.
This is because the price differential has been characterized by volatile behavior in this period. Domestic prices have
maintained a different trend from the reference markets, generating significant price differentials in some years and
minimums in others.
46
4.6 General Services Support Estimate (GSSE)
81. In addition to the transfers directly received by individual producers,
government policies also provide support to the agricultural sector through the funding
of activities that offer general benefits (public goods), such as agricultural research
and development, transfer of technologies, training, inspection, information, and
promotion of the sector, inter alia. Generating these types of public services produces
positive externalities for the entire sector. The methodology estimates this type of
transfer to the sector through the General Services Support Estimate (GSSE), which
considers the amount of public (government) investment in these activities. The GSSE
is funded by taxpayers, and its financing by the state government is crucial because,
due to their nature as public goods, the level provided by the market is less than the
socially optimal level.
82. During the period 2019-2022, the GSSE for Mozambique averaged 4,060.6
MZN Million annually (about US$ 62.2 million). On average, approximately 52.1
percent of the total GSSE disbursements were allocated to financing the development
and maintenance of infrastructure (such as water catchment infrastructure, rural
infrastructure, rural sanitation, and rural electrification); 44.1 percent to Research and
Development (including training, research, knowledge and technology transfer, and
resources for agricultural institutes); with 2.8 percent directed towards Inspection and
Control (covering sanitary defense, input regulation, and sanitary monitoring), and 1.0
percent towards marketing and promotion (See Table 9). Mozambique is one of the
countries where infrastructure development and maintenance components, as well as
agricultural development and knowledge, have greater weight within the GSSE. These
two components explain 96.2% of Mozambique’s GSSE (see Figure 31).
Table 9. Composition of GSSE (Average 2019-2022)
Figure 31. Composition of General Services Support Estimate (Average 2019-2022)
47
83. It is worth mentioning that the GSSE has increased its relative importance
within the Total Support Estimate (TSE), moving from representing 5.0 percent in
2019 to 15.9 percent in 2022. For this period, the annual average is estimated at
around 10.3 percent (see Figure 32).
Figure 32. General Services Support Estimate (GSSE) and its share in the Total Support Estimate (TSE) 2019-
2022
84. Compared with the investment in public goods carried out by other economies,
Mozambique’s GSSE level as a proportion of the TSE continues to be below the
OECD average and even below other economies in the region, such as South Africa
(see Figure 33).
Figure 33. General Services Support Estimate, relative to TSE (Percentage GSSE) 2019-2022 Average
85. Evidence indicates that the level of GSSE frequently has a positive correlation
with the countries’ development levels. Additionally, this type of support is classified
within the WTO’s green box, meaning it is exempt from compensatory measures by
trading partners. Investment in GSSE is frequently linked to long-term agricultural
growth and competitiveness. Figure 34 displays the GSSE as a percentage of
Mozambique’s and the OECD’s GDP from 2019 to 2022. The data indicate that the
Mozambican government’s public investment in general services, when measured as
a proportion of its GDP, has been increasing during 2019-2022, showing an average
for the period of 0.4 percent and reaching about 0.8 percent in 2022. This indicator is
higher than that of OECD countries, which averaged 0.07 percent of GDP during the
same period (See Figure 35).
48
Figure 34. General Services Support Estimate (GSSE) as a percentage of GDP (2019-2022)
Figure 35. General Services Support Estimate, relative to GDP (2019-2022)
4.7 Consumer Support Estimate (CSE)
86. The Consumer Support Estimate (CSE) measures the cost (or benefit) to
consumers resulting from the national government’s implementation of sector support
policies. A negative CSE indicates a negative cost to the consumer, equivalent
to an implicit tax on the consumption of agricultural products. To the extent that an
agricultural policy raises the domestic price of products above international reference
prices (through the imposition of administered prices, or other types of price support
mechanisms), the consumer is the one who bears that cost, which is transferred as
a benefit for the producers. Conversely, a policy leading to a domestic price lower
than the international reference price (e.g., a price ceiling) creates an “implicit subsidy”
for the consumer, funded by the producer. The methodology also considers, in
addition to these supports, those arising from consumer subsidy programs financed
by taxpayers and can “attenuate” or reduce the negative impact on the consumer’s
balance. In any case, both sources of financing are considered in the calculations to
determine the net support to the consumer.
87. The main agricultural policy In Mozambique that had a negative impact on
consumers during the period under review was the existence of tariffs on imports
that seek to protect the producer from international competition but, at the same time,
prevent an increase in domestic supply, increasing the price that at the end of the
49
day is paid for by the consumer. On the other hand, it was possible to identify in the
analysis other programs carried out by the provincial governments, using budgetary
resources to subsidize the consumption of some foods. The methodological analysis
considers both elements; however, even considering the subsidy programs, it has not
been possible to compensate for the implicit tax derived from the trade restrictions,
and consequently, the balance continues to be negative. 34
88. Like the PSE, the CSE can be expressed in relative terms as a percentage of
consumption expenditure (%CSE). For Mozambique, the average consumer support
%CSE was negative across the entire analyzed period (- 7.1 percent), representing an
implicit consumer tax. During this period, food consumption subsidies and nutritional
support programs were also implemented by Provincial Governments; however, these
programs did not make the indicator substantially positive when taken into account
for the calculation. The average estimated result shows that due to the nearly non-
existent implementation of state-funded subsidy programs, consumers experienced
an increase in the cost of the food basket by 7.1 percent. In practice, this means that
the producer support policies (financed by consumers) acted as an “implicit tax” on
food consumption, amounting to 7.1 percent of the consumers’ expenditures on
consumption items (see Figure 36).
Figure 36. Consumer Support Estimate (CSE) as a proportion of the value of the consumer basket (%CSE).
2019-2022 Average
89. This implicit tax is higher than the average of OECD countries, recorded at
3.9% for the period analyzed (see Figure 37). In the case of the USA, even though the
CSE is negative, very important resources are provided by other consumer support
programs (financed by taxpayers), which more than compensate for the negative CSE
amount, turning the final result into positive ranges.
Figure 37. (%CSE). 2019-2022 Average
The programs identified for the food subsidy were “Promocao de seguranca alimentaria e nutricional” and “Avalacao de seguranca alimentaria e nutricional”.
34
50
Source: Own elaboration with OECD data
4.8 Consumer Support Estimate (CSE) by Product
90. The following analysis includes the calculation of the CSE (average CSE%
for the period 2019-2022) broken down by each of the products analyzed. These
averages CSE% are negative for four of the five products and zero for sweet potatoes
(See Figure 38).
91. The analysis of rice consumption reveals a significant implication of the support
policies. These policies, designed to bolster the sub-sector, effectively impose an
‘implicit tax’ on consumers. This tax, equivalent to 11.6% of the value of the product’s
consumption, is derived from transfers corresponding to market price support.35 To the
extent that government price support measures were in place (in this case, through
taxes on imports of this product), consumers had to pay higher prices in the domestic
market than those prevailing in the international markets of reference. Thus, this
implicit tax was passed on to them. Similar situations are observed in the rest of the
products analyzed.
Figure 38. Average CSE% for key products
51
5. Agricultural Support
and Structural
Challenges - Four key
dimensions.
92. The analysis of the support to the agricultural sector in Mozambique reveals
at least four structural challenges that have yet to be overcome. Addressing these
challenges is urgently necessary to promote sustained growth and sustainable
sectorial development, a task that requires the attention and action from all
stakeholders.
A. High Supply Fragmentation: Small Producers and Supply Constraints
93. The potential opportunities represented by market price support are not
captured by smallholders. One of the main objectives traditionally pursued by price
intervention policies has been to increase domestic prices relative to the border
price to protect domestic production from international competition and increase
producer farm incomes. In principle, higher food prices increase the funds available to
producers for investment purposes and generate incentives for production growth. In
that sense, higher food prices might be considered an opportunity. To materialize that
opportunity, diverse aspects, such as access to land, machinery, technologies, and
credit, are critical in determining who can benefit from higher prices.
94. However, key supply constraints have impeded the intended result. Small
producers have faced several supply constraints that prevent a positive response
from higher prices. There have been substantial difficulties in accessing key inputs,
such as fertilizers or certified seeds, that are not affordable to them, given their low
production scale and incomes. In addition, since most smaller farmers are basically
producing for self-consumption, increasing food prices there does not necessarily
mean higher benefits for them. On the other hand, the possibility of accessing credit
to finance the use of productive assets or the purchase of inputs is scarce or non-
existent for this segment; only 0.6% of this segment has received a loan. The limited
participation of small-scale producers in markets could also result from the high
transaction costs implied by transport and infrastructure constraints and safety levels
when transporting them. In products such as rice, maize, and cassava, which have
been favored by higher prices, the participation of small producers in the markets is
less than 20%.
95. The productivity (measured by yields) of agriculture in Mozambique has been
observed to be low and non-growing. For smallholder agriculture, those figures
show levels even 40% below average (see Annex 16). This presents a vicious circle,
52
as low yields make it difficult to generate sufficient income to finance investment in
technology and knowledge that, in turn, are necessary to increase returns.
96. Promoting associativism and organization is a crucial resource to facilitate
access to markets, inputs, and credit for small producers. Most informal chains where
smallholders are typically involved are characterized by spot market transactions,
small percentages of production sold off the farm, and weak information systems.
Among other elements, the link to larger value chains is highly influenced by the
organization of producers that allows economies of scale in the acquisition of inputs
and technical assistance to be able to achieve production volumes with the standards
required at the commercial level, as well as having better access to markets based
on larger volumes of sales by the organization and increased bargaining power.
Currently, only 3.5% of the small units belong to an association, and less than 7%
receive visits from extension workers.
97. Small producers are also highly exposed to risks arising from climatic
conditions. Changing climatic conditions are a factor that significantly affects the
determinants of smallholder income, including yields and harvests. Only 9% of small
units use irrigation technology, which could be a major element in decreasing their
exposure to climatic events. Current conditions and failures in the insurance market,
evidenced by high population dispersion and transaction costs, have made it difficult
to access risk management and transfer services such as agricultural insurance. In
the absence of those instruments, adverse shocks force small producers to divert
resources from other priorities like nutrition, children’s education and healthcare,
producing persistent damages to their food security. Without formal agricultural
insurance, low-scale farmers depend on informal insurance; consequently, farmers
tend to limit production size with lower investments, as precautionary savings are the
first protection against calamities.
B. Low productivity levels
98. Measures that distort markets, such as border protection, reduce
incentives to use production factors more productively. These distorting
measures can maintain resources in the sector that would otherwise be reallocated
to more productive uses; they can encourage more intensive production, sometimes
on marginal or fragile land; and they can encourage production practices that do not
always consider longer-term environmental sustainability.
99. The Mozambican agricultural sector has ample room for improvement.
Even though land with potential for agriculture represents 63.5% of the total land area,
total land under cultivation is only 15% of total arable land. However, the average
agricultural yields of products that have been protected by price support measures
are low compared to other economies and have remained relatively unchanged in the
last 20 years. The incentives for investment in terms of adequate and stable levels
of profitability have been lacking. Still, there are also significant constraints to the
adoption of improved technologies, such as a shortage of locally improved seeds,
planting materials, and other inputs, as well as a restricted supply of modern farm
equipment, all of which indicates that the sector has a lot of room for improvement.
Sustainability refers to preserving natural capital, i.e., environmental sustainability. This encompasses managing agriculture’s use of natural resources to
36
ensure their long-term viability and reducing the negative environmental impacts of agriculture production, which can damage natural assets. Sustainable
agriculture production systems also need to adapt to the projected impacts of climate change and mitigate greenhouse gas (GHG) emissions.
53
100. The framework of solutions should include measures that enable long-
term productivity gains and sustainability as two sides of the same coin.36
These include investments that promote innovation, infrastructure capacity, and
farmers’ access to input and output markets while ensuring the resilience of farmers
and the agri-food system. Knowledge infrastructure is a public good that can
enable innovation; it includes general-purpose technologies and specific knowledge
infrastructure, such as databases and institutions.
101. A growing public investment in infrastructure (physical and market
information) facilitates the flow of knowledge and the adoption of new
practices. Cunguara et al (2011), found that living near a tarred road is essential
for farmers to benefit from improved technologies. They are vital to delivering
and accessing important services. They are critical in linking farmers and related
businesses to markets, reducing food waste, boosting agriculture productivity, raising
profits, and encouraging investment in innovative techniques and products. In this
process, public investment in rural infrastructure, including irrigation systems and
resource management, is equally important as an instrument to promote productivity.
102. Public investment in education and research facilitates producers’
acceptance of technological innovation and, in turn, increases productivity
levels. Innovation systems require well-educated researchers, teachers, extension
officers, and producers to develop relevant innovations; it is generally easier for
farmers with higher education and skills to adopt some technological innovations.
Evidence in Mozambique shows that farms with access to agricultural advisory
services, those with access to rural credit and members of agricultural associations
are more likely to adopt new agricultural technologies.37
103. Continued public investment in extension services and technical
assistance is necessary to transfer the benefits generated by education and
knowledge. The potential benefits of innovations are only realized if effectively
implemented. Training, extension, and advisory services in primary agriculture can
facilitate the transfer and successful adoption of innovation. Given the very large
number of small farmers in Mozambique, extension services have a particularly
important role in facilitating farmers’ access to technology and knowledge and
contribute to facilitating farmers’ effective participation in innovation networks and
ability to formulate their specific demands. It is also important to support the diffusion
of innovation in small agri-food firms.
104. It is important to consider the private sector and non-governmental
organizations as a strategic ally in generating and transferring R&D. The public
sector remains the main source of funding for agriculture R&D, whether performed
in public or private organizations. Various funding mechanisms are used, from direct
spending on research projects, including Public-Private Partnerships (PPPs) and “pull
mechanisms” to various tax incentives. Business investment in R&D is normally driven
by market demand, but governments also provide different incentives. Some, like R&D
tax rebates, apply to the economy in general, while others are agriculture specific.
105. Complementarily, it is advisable to assess the efficiency of the tariff
protection profile as an effective mechanism to promote the flow of investment
and knowledge. According to the World Trade Organization (WTO), the country’s
tariff profile shows a higher average level of tariffs in agriculture (14%) than in the
nonagricultural sector (9.7%). More than 60% of MFN tariffs within the sector are
37
Uaiane, Rafael. “Determinants of agricultural technical efficiency and technology adoption in Mozambique”. Michigan State University
54
between 15 and 25%. Trade can facilitate the flow of goods, capital, technology,
knowledge, and people needed to innovate. Openness to trade and capital flows
is conducive to innovation. It provides a larger market for innovators, reinforces
competition, and increases access to new technologies, ideas, and processes,
including foreign direct investment in agriculture (FDI) and related technological
spillovers, and facilitates cross-country collaboration. Trade and investment openness
can influence innovation throughout the food supply chain, from input suppliers to
food service and retail firms. Input and output markets that operate effectively can
foster productivity growth. Trade and investment openness can also facilitate the
development of market mechanisms to foster more environmentally sustainable
production.
C. Financial services for the agricultural sector
106. Rural economic units’ insufficient access to financing is a critical
obstacle to encouraging investment in productive assets, machinery, and
equipment, which directly impacts productivity levels. Access to financing (or
its restriction) affects the availability of working capital to purchase inputs, acquire
management and production models, and adopt technologies and technical-
productive capacities, all of which may translate into greater productivity and
profitability of productive units.38
107. Mozambique has a low level of commercial financing to the primary
sector, representing only 2% of the total credit portfolio, with a decreasing
trend in recent years. Commercial and development banks finance value chains of
different crops (e.g., cotton, sugarcane, cashew, sesame, soya, beans, maize, etc.).
However, due to high operation costs and lack of infrastructure, loans are almost
exclusively targeted at larger-scale farmers, those who can at the least offer some
collaterals and sure market potential. Therefore, access to finance among smallholder
farmers is highly limited, with a very low uptake of financial products. According to
MADER’s Agricultural Census, only 0.6% of small farmers have received a credit, in
some cases in extremely high interest rates of up to 30-48% per annum (PWC, 2018).
108. The financial market has several failures that limit access to the sector
and, in particular, to small producers. In addition to high exposure to weather,
market access, pest and diseases risks, the sector has other failures related to lack
or asymmetries in information, lack of collateral and high transaction costs, which limit
the effective demand for agricultural credit and other financial services and, therefore,
discourage financial intermediaries from considering rural areas as priority. Lack of
access to insurance also limits the access to finance. Banks demand insurance for
giving loans and, without the insurance component, it is hard for farmers to receive
credit from the banks. In the absence of insurance, banks demand instead collaterals
before providing money, which is also a significant limitation for small producers.
109. There is an opportunity to establish measures that eliminate restrictions
on access to credit, contributing to breaking the cycle of low investment,
low productivity and low growth in the sector. Given the lack of banking supply,
especially for small producers, the possibility is to open to other formal financial
institutions, such as savings and credit cooperatives and associations, foundations
and corporations dedicated to granting low-value credit and other financial services.
They have greater local knowledge of customer needs and credit technologies than
traditional banking, which makes them more effective in addressing the obstacles
See IFC (2012) and Uaiene, Arndt, and Masters (2009), who empirically analyze the relationship between agricultural
38
credit and technology and show that producers with access to credit are more likely to adopt technology. In turn, Foster and
Rosenzweig (2010) show that the credit crunch plays a preponderant role in delaying technology adoption.
55
indicated. The presence of these entities allows access to credit to producers
generally excluded from the financial system, such as women, who usually do not
have access to credit services due to a lack of assets or collateral in their name.
110. Support provided to second-tier guarantee funds that strengthen
the financial capacity of private entities dedicated to the low-income rural
population may be another relevant mechanism to expand access to financing
sources. The target population of small producers is characterized by dependence
on multiple sources of income and having little collateral and financial information
available, as well as requiring constant technical support. The support must be
directed to entities that must meet at least the following requirements: use specialized
credit technologies for low amounts in the rural sector; maintain controls on the
prevention of money laundering; submit audited financial statements; have strong
corporate governance; and reflect reasonable financial indicators.
D. Climate change, resilience and risk management
111. Mozambique’s agricultural potential is hampered by its high exposure to
climate risks, while farmers often deal with drought, floods, uneven rain and
cyclones. The Global Climate Risk Index (produced by German Watch) analyses
to what extent countries have been affected by the impacts of weather-related loss
events, places Mozambique as the third most vulnerable climate change country in
Africa (see paragraph 35) and at the top of the Southeast African region, with at least
26 large climatic shocks affecting agriculture sector since 199039. Weather risks such
as drought, flood, and extreme winds can cause irreversible damage to households
and affect food security. The most direct consequence of adverse climatic events is
the destruction of production and a substantial loss of income.
112. While climatic risks are present and spread throughout the country,
mitigation capacity is very limited.40 Currently, no major product in the market
provides coverage for weather-related events. The Mozambican insurance sector is
miniscule, with the non-life insurance market representing only 0.69% of GDP, which
is much lower than the African average of 1.11%. Climatic calamities have affected
the agriculture sector 26 times since 1990. Given the high dependence on agriculture
and frequent exposure to adverse climatic shocks, agricultural insurance offers an
untapped opportunity to mitigate risk across the agriculture value chain.
113. Clearly, agricultural insurance can provide a much-needed safety net
to farmers, protecting them from climate change-induced shocks. However,
the take-up of agricultural micro-insurance has remained low, and increasing it has
remained a notably difficult policy to achieve. Despite being subject to potential
benefits from insurance, households may struggle to rationalize paying a premium,
given that there is only a pay-out in the case of a weather shock. Also, given the
competing uses of the limited funds that households have at the start of the growing
season, the opportunity cost of insurance is high. Hence, there might be a case for
subsidizing insurance premiums for small farmers, at least at the beginning. Another
factor is related to difficulty in understanding and using insurance policies properly.
One of the findings of a pilot program carried out by the World Bank in Mozambique
suggests that financial education is a must for the success of agricultural insurance,
with most farmers not being fully aware of how the insurance works. Education
services may be granted through extensionist services. 42
39
The Climate Change Performance Index 2023: Results | Germanwatch e.V.
40
Armand, A. et al. “Managing Agricultural Risk in Mozambique”. International Growth Center, 2019.
56
114. The introduction of an agricultural insurance product could potentially
have large benefits. For example, at the end of a poor growing season (driven by
adverse weather), while uninsured families might be forced to continue reducing
consumption or liquidating assets, insured families should be able to maintain a
comparatively higher level of consumption and assets. Asset and consumption
smoothing in anticipation of bad harvest due to adverse weather is a crucial factor in
the context of smallholder farmers.43 The second important effect of being insured
could be the change in investment strategies. Due to financial constraints and
uncertainty, households do not invest enough in changes that can boost productivity.
However, insurance has the potential to significantly increase a household’s ability to
invest in productivity improvements. Households would accumulate better investments
over time, leading to better income and improvements in human capital. Since some
of those investments may need banking finance, access to insurance facilitates
access to credit.
115. A public policy that favors the development of instruments for
management and transfer of risks faced by the sector is subsidies for
insurance premiums properly targeted to innovative solutions. A large share
of low-scale farmers cannot afford to pay a large share of their production as a
premium. Similarly, given the dispersion of producers and high climatic risk, insurance
premiums are expected to be high due to general low take-up. Any public policy to
solve this market failure must consider the involvement of the private sector to
design and execute innovative solutions, such as weather index-based insurance,
to reduce their operation costs and provide an affordable premium to small-holder
farmers as an initial solution.44 In some countries, such as Brazil, the design of these
subsidies contemplates the conditionality of activities by the producer in favor of the
environment.
A simulation carried out by PWC in Mozambique indicates that, in the presence of climatic calamities, the net income of
41
producers who have insurance can be between 15 and 100% higher than producers who do not have insurance.
42
See: World Bank Document
Karlan, D., Osei, R., Osei-Akoto, I. and Udry, C. 2014. Agricultural Decisions after Relaxing Credit and
43
Risk Constraints. The Quarterly Journal of Economics 129(2), pp. 597-652
44
Market insurance evaluation carried out by PWC IN 2019 claims that there are some companies looking into the possibility of implementing an index-
based insurance product after a pilot by the World Bank GroupRisk Constraints. The Quarterly Journal of Economics 129(2), pp. 597-652
57
6. Conclusions
116. Based on the assessment of the agriculture support estimates, the main
findings to be considered for future agriculture policy decisions forward are the
following:
a) The level of total agricultural support (Total Support Estimate-TSE) in
Mozambique for the period 2019 2022 was approximately an average of US$567.8
million per year, equivalent to 3.5 percent of the national GDP. Although it is relatively
low in absolute terms, the ratio results relatively high as a percentage of the national
GDP.
b) A significant characteristic of this support is its high level of volatility. The level
fluctuated from 1.9 to 4.9 percent of the GDP from 2020 to 2022. This reflects the
significant influence of international price movements and the differential between
these and domestic prices.
c) Considering the source of support, consumers were responsible for financing
about 84 percent of these transfers by paying prices higher than the average prices in
international reference markets. The remaining 16 percent was financed by taxpayers
through the support of national government programs and projects. This means that,
for every monetary unit (Metical) transferred to the agricultural sector derived from
agricultural policies, 84 cents were generated by consumers, who pay prices for
food higher than those prevailing in the reference international markets, implying an
“implicit tax” on consumers of these products, equivalent to 7 percent of the value of
the average basic basket of consumption items.
d) This “implicit tax” on consumers is also regressive. Of the total household
expenditure in Mozambique, on average 39 percent is allocated to food. However, this
percentage reaches up to 49 percent in the case of the poorest households, meaning
that transfers to the sector by consumers represent a disproportionate burden for
these poorest households .
e) This conclusion also entails implications of efficiency (to the extent that it tends
to be a highly distorting mechanism and prevents production decisions from being
carried out by market signals), equity (to the extent that it is primarily large producers
who benefit from higher prices, but not necessarily low scale or self-consumption
producers. Moreover, international evidence indicates that price support is not been
58
an adequate mechanism to address structural constraints such as scarce access to
credit, limited increase in productivity, achievement of economies of scale or greater
access to markets, or increased exports, or the construction of more efficient and
resilient food systems.
f) In general, most support to agriculture is through direct transfers to determined
products or groups of products (74%), while transfers to the sector as a whole (public
goods) represent only 14%. In the first case, these transfers had a relatively small
impact on producers’ gross income (6.8%) and burdened consumers, implying high
distortion and negative distributive effects.
g) When analyzing the support targeted at specific products, it is noted that
cassava and rice accounted for almost 60.7 percent of the average support granted
per product during that period. This high and concentrated support was mainly
provided through higher prices, which were mainly caused by trade measures (import
restrictions), which negatively impacted low-income consumers for whom these
products are essential in their basic diet.
h) An increasing absolute level of public investment in public goods for the sector
was observed and was aimed mainly at infrastructure and knowledge. These types of
support and transfers are considered highly efficient in promoting sustained long-term
productivity.
i) However, this type of support accounted for 5 percent of the total estimated
transfers during the analyzed period 2019 2022, and it was equivalent to only 0.07
percent of GDP, which could be considered relatively low compared to other
developed economies.
117. The conclusions of this study are consistent with and reinforce the
findings of other Bank thematic studies. For example, in the case of the Country
Climate and Development Report (CCDR, 2023), Priority area 3, has a stronger
relevance for agricultural development in direct relation with the scope of this report.
Promoting technology development to increase productivity and adopting climate-
smart agriculture (CSA) and human capital development would induce structural
transformation to reduce the impact on those most exposed to climate change,
reducing inequality and enhancing growth. Similarly, the Mozambique Poverty
Assessment of 2023 concludes that supporting the most vulnerable households
through adaptive targeted protection programs is essential to ensuring the poorest
and most vulnerable households are included. Win win solutions can also be
promoted by tailoring cash programs and expanding digital payments to the needs of
vulnerable groups (subsectors, types of farmers, or regions).
45
Source: National Statistic Institute of Mozambique; Inquérito Sobre Orçamento Familiar, 2022
59
7. Main Policy
Recommendations
118. Phase out production price support. As mentioned above, support via
market prices tends to benefit only a specific product or group of products, with a high
degree of market distortion, to the extent that it generates “artificial” incentives for the
production of these specific products, regardless of the profitability and comparative
advantages that other products may represent, generating a high social cost.
119. Support via prices has not contributed to overcoming structural challenges
such as the difficulty of generating economies of scale, access to inputs, improving
productivity, increasing access to formal financing for small and medium-sized
enterprises, vulnerability to climate shocks and market, or the difficulty in investing in
the sector in the presence of imperfect land markets. In addition, it has not contributed
to ensuring food security either, as the country is still highly dependent on imports
for some key consumer products. Yet, these products continue to have high levels
of domestic subsidy. The lack of a solution for these challenges is, among other
elements, evident by observing the historically low yields of strategic products (e.g.,
corn, rice) and significant gap compared with other countries.
120. Recommendation: There is a need to shift the paradigm on how
agricultural support is approached, from price support to public goods and
services. The results demonstrate that a strong emphasis on producers’ support is
failing to achieve structural changes towards allocative efficiency gains and imposing
high social costs. It is recommended that a shift in price support be initiated as
the main tool to support the agricultural sector in the country and replace it with
an increase in public investment in public goods that creates enabling conditions
for private sector investments in a more liberalized market structure. This level
of investment in public goods should theoretically be above a minimum level of 2.5
percent of the agricultural GDP in the next 5 years (about double the current level
of 1.4 percent). Key public goods for the agriculture sector in Mozambique constitute
rural infrastructure, technological research and development, transfer of technology,
education and capacity building, disease control and inspection, as well as public
services to support market access. That is also particularly relevant in the context
of the AfCFTA (African Continental Free Trade Area) agreement. Thus, to achieve
substantial gains from this agreement, Mozambique must seek to improve its
productive and allocative efficiencies.
121. However, it is important to stress that such policy shift must be gradual, and,
60
most importantly, the resulting impact on public finances must be considered very
carefully. Otherwise, a sudden and immediate dismantling of price support could
generate a disruptive risk and political tensions, aggravating the issues. The additional
public investment that is proposed could imply an increase in budgetary spending (or
at least a reorganization of current public spending). Without adequate medium and
long-term fiscal planning it could compromise the public finances in the absence of
additional or alternative sources of public revenues.
122. Reductions in trade barriers should be accompanied by other fiscal measures
to offset an eventual impact on public finances. Among these measures should be
considered the implementation of domestic taxes on food products with potential
negative impacts on health, e.g. products high in calories and fats. These types of
taxes are more efficient since it is applied to overall consumption and not only to
certain imported food products.
123. Recommendation: Design support schemes for small producers,
promoting and supporting organizational improvements and removing
constraints along key value chains. The country’s current productive structure
shows a large number of small producers, often isolated and without access to
economies of scale or markets. Promoting support to generate associations by
creating producer organizations and cooperatives is a strategy that can be very
important for the inclusion of the small-scale economy. Cooperatives and producer
associations can assist in this objective, as can productive alliances that facilitate the
solution of market failures by linking producer organizations to reliable buyers, thus
favoring the access of groups of small and medium-sized producers with minimal
levels of distortion, strengthening competitiveness and enhancing overall food
systems.46 The Productive Alliances is a proven framework to facilitate organized
farmers’ access to markets through integral actions to help carry out investments to
introduce technological changes to enhance production and competitiveness and
secure highly demanding markets. The World Bank can assist with designing these
alliances, considering successful experiences in the past in various regions of the
world.
124. Recommendation: Shift from implicit taxation to positive support to
food consumers. As the negative CSE estimates demonstrate, Mozambican food
consumers are funding a significant portion of the support to the agriculture sector.
A shift away from this approach will reduce the implicit tax on food consumers (“food
tax”), consequently increasing the welfare of the poorest. However, other public
policies and programs could be further enhanced to directly safeguard consumers
from food insecurity and nutrition challenges by targeting support through social
protection programs (food aid, school feeding, etc.) and countercyclical safety nets.
125. Recommendation: Public investment in general services is necessary
to resolve structural challenges in the sector, including the entry of low-scale
producers to marketing channels. The eventual increase in public investment in
general public goods and services in the sector should be carried out considering
agriculture’s opportunities and potential in the country. The focus of investments can
be the sustained increase in productivity levels. For this, greater public investment in
physical infrastructure (transportation, communications, irrigation) and non-physical
infrastructure (information, databases, institutional strengthening) play a significant
role that may facilitate the transfer of technology and knowledge. Consequently,
greater investment in education, extension services, and technical assistance also
46
See World Bank, “Linking Farmers to Markets through Productive Alliances”, 2016.
61
play an important role in the investment process in public goods and services. Actions
to generate and transmit knowledge should consider the importance of allowing and
promoting the joint participation of the private and social sectors in this objective.
126. Recommendation: Since many producers cannot access risk
management instruments, their inclusion would generate social benefits
far exceeding the related costs. The design, assessment, and eventual trial of a
program that partially subsidizes the insurance premium of index-based insurance
is important considering the high exposure of the sector to climate risks that
Mozambique faces and the cost-benefit ratio of transferring these risks to international
markets (instead of being internalized by the local small and vulnerable producers).
This process must also include the participation of the private sector in the design
and implementation. Government investment should consider technical assistance
programs that disseminate the importance and culture of insurance in the first stage,
and premium subsidies should be subsequently considered for innovative programs
aimed at producers who cannot access insurance.
127. Recommendation: It is of the utmost importance to create conditions
for small and medium producers to access formal financing to allow the
capitalization of their productive units. The possibility of generating liquid
guarantee programs granted to non banking financial entities, such as credit
cooperatives or associations, is an alternative that can allow the financial inclusion of
the most vulnerable segment. These supports may be conditional on these entities
having minimum operating requirements and standards previously established by the
relevant authority, and on achieving specific objectives such as inclusion of women
and youth, adoption of sustainable climate-smart practices and technologies, amongst
others.
128. Recommendation: Policy reforms should be accompanied by
instruments for monitoring and evaluating results. This would make it possible
to continuously monitor public policies and thus improve them based on the results
obtained and the lessons learned. In this process, effective coordination between
government institutions is key, for which adequate and sustained budgetary and
human resources is needed.
62
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Journal of Agricultural Economics, Vol. 104/2, pp. 502-529, https://doi.org/10.1111/ajae.12255.
Anderson, K. and E. Valenzuela (2021), “What impact are subsidies and trade barriers abroad
having on Australasian and Brazilian agriculture?”, Australian Journal of Agricultural and Resource
Economics, Vol. 65/2, https://doi.org/10.1111/1467-8489.12413.
Blandford, D. and K. Hassapoyannes (2018), “The role of agriculture in global GHG mitigation”, OECD
Food, Agriculture and Fisheries Papers, No. 112, OECD Publishing, Paris, https://doi.org/10.1787/
da017ae2-en.
DeBoe, G. et al. (2020), “Reforming Agricultural Policies Will Help to Improve Environmental
Performance”, EuroChoices, Vol. 19/1, pp. 30-35, https://doi.org/10.1111/1746-692X.12247.
FAO (2021), The share of agri-food systems in total greenhouse gas emissions: Global, regional and
country trends 1990–2019, Food and Agriculture Organization of the United Nations, Rome, Italy,
https://fenixservices.fao.org/faostat/static/documents/EM/cb7514en.pdf
Guerrero, S. et al. (2022), “The Impacts of Agricultural Trade and Support Policy Reform on Climate
Change Adaptation and Environmental Performance: A Model-Based Analysis”, OECD Food,
Agriculture and Fisheries Papers, No. 180, OECD Publishing, Paris, https://www.oecd-ilibrary.org/
agriculture-and-food/oecd-food-agriculture-and-fisheriesworking-papers_18156797.
Heisey, P. and K. Fuglie (2018), “Public agricultural R&D in high-income countries: Old and new roles
in a new funding environment”, Global Food Security, Vol. 17, pp. 92-102, https://doi.org/10.1016/j.
gfs.2018.03.008.
Henderson, B. and J. Lankoski (2020), “Assessing the Environmental Impacts of Agricultural Policies”,
Applied Economic Perspectives and Policy, pp. 1-16, https://doi.org/10.1002/aepp.13081.
Instituto Nacional de Estadística de Mozambique. Inquérito Sobre Orçamento Familiar, 2022
International Monetary Fund. “The Distributional Impacts of Agricultural Sector Reforms in Africa: A
Review of Past Experiences”.
USDA. How Transportation Costs Affect Fresh Fruit and Vegetable Prices. Richard
63
Volpe, Edward Roeger, and Ephraim Leibtag (2013).
OECD (2019), Enhancing Climate Change Mitigation through Agriculture, OECD Publishing, Paris,
https://doi.org/10.1787/e9a79226-en
OECD. Agricultural Market Information System: Home (amis-outlook.org)
OECD. Agricultural Policy Monitoring and Evaluation OECD iLibrary | Agricultural Policy Monitoring
and Evaluation 2020-2022 (oecd-ilibrary.org)
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OECD data Monitoring and evaluation: Reference Tables: Total Support Estimate (TSE) (oecd.org)
World Bank Group. “Linking Farmers to Markets through Productive Alliances”. 2016.
World Bank. “The Cassava Value Chain in Mozambique”. Jobs Working Paper, 31.
64
ANNEXES
65
ANNEX 1. Consumer Price Index – Mozambique (Base Year 2016=100)
Various goods and services
Housing, water, electricity,
Restaurants, hotels, cafes,
domestic equipment, and
Electricity, gas, and other
Alcoholic beverages and
Food products and non-
Leisure, recreation, and
Furniture, home decor,
Clothing and footwear
and similar (includes
alcoholic beverages
gas, and other fuels
routine household
Communications
maintenance
Education
Transport
catering)
tobacco
culture
Month
Health
Total
fuels
Year
2019 Jan 121.9 118.3 119.6 130.4 123.6 158.2 118.3 122.1 133.3 102.8 111.6 126.5 125.0 130.2
2019 Feb 122.5 119.5 120.1 131.1 123.6 158.7 118.8 122.9 132.7 102.9 112.5 127.6 125.6 131.1
2019 Mar 123.4 120.9 119.7 131.5 127.0 171.0 119.8 125.1 132.7 103.0 112.5 127.6 126.2 131.3
2019 Apr 123.3 120.2 119.9 132.3 127.8 173.8 119.6 125.4 132.9 103.0 112.6 127.6 126.2 131.4
2019 Mai 122.6 118.8 119.7 131.6 126.5 169.7 119.8 125.6 132.0 102.7 113.3 127.6 126.3 131.6
2019 Jun 122.0 117.3 121.2 131.6 126.1 168.4 119.7 125.7 132.0 102.7 113.6 127.6 126.5 131.5
2019 Jul 121.5 115.6 122.6 131.9 125.7 167.0 119.0 125.9 132.1 102.9 113.7 127.6 127.2 131.7
2019 Ago 121.9 116.5 123.3 131.9 125.8 167.1 119.1 125.9 132.0 103.1 113.9 127.6 127.7 132.0
2019 Set 122.2 117.3 123.3 132.3 125.7 166.8 119.4 126.0 131.4 103.2 113.7 127.6 128.2 132.2
2019 Out 123.0 119.3 123.8 131.9 125.6 166.3 119.3 129.1 131.8 103.1 113.3 127.6 128.6 132.2
2019 Nov 124.1 121.8 124.2 133.0 125.2 164.9 119.4 129.0 131.9 103.3 112.9 127.6 128.6 132.6
2019 Dez 125.6 126.0 124.5 133.3 125.2 165.2 119.1 129.2 131.6 103.3 112.9 127.6 128.8 132.2
2020 Jan 126.9 128.7 126.0 134.5 125.3 165.6 120.3 129.9 131.7 103.2 113.4 131.8 129.3 132.6
2020 Feb 127.2 129.3 126.3 134.4 125.5 166.0 120.7 129.9 131.9 103.2 113.9 131.8 129.6 132.5
2020 Mar 127.3 129.3 126.5 134.3 125.3 165.0 120.9 129.5 132.0 103.2 114.8 131.8 129.7 133.1
2020 Apr 127.3 128.5 126.6 135.1 125.3 164.8 121.9 129.6 133.1 103.1 114.8 131.8 129.9 133.4
2020 Mai 126.6 127.5 126.9 135.1 125.3 164.5 122.6 129.0 132.7 103.0 115.4 119.1 130.0 131.8
2020 Jun 125.8 125.6 127.1 135.2 125.8 164.3 122.2 129.1 131.7 103.1 115.5 119.1 129.9 131.6
2020 Jul 125.6 125.0 129.9 135.4 125.7 163.8 122.1 129.8 131.5 103.2 114.3 119.1 130.0 132.1
2020 Ago 126.2 126.3 130.8 135.9 125.8 163.7 122.2 129.8 131.6 103.3 113.9 119.1 130.4 132.4
2020 Set 126.8 127.4 130.9 136.5 125.7 163.1 122.7 130.0 131.8 103.4 112.5 119.1 131.0 132.3
2020 Out 127.7 129.1 130.6 137.1 126.0 163.0 123.1 130.0 132.2 103.3 113.0 119.1 132.1 133.0
2020 Nov 128.7 131.6 130.7 137.3 126.1 163.2 123.7 130.1 131.9 103.3 113.7 119.1 132.2 133.3
2020 Dez 130.9 136.7 131.1 137.5 126.3 163.1 124.5 130.1 131.6 103.3 114.9 119.1 134.4 134.2
2021 Jan 132.7 141.3 133.8 139.5 127.7 165.5 125.9 130.1 131.9 103.2 118.2 120.5 134.7 135.6
2021 Feb 134.8 145.4 133.9 139.9 131.9 181.3 126.2 130.3 131.9 103.2 118.4 120.5 135.2 136.6
2021 Mar 136.0 146.7 134.2 141.6 132.3 182.9 127.6 130.5 132.4 103.3 118.8 124.4 136.0 137.0
2021 Apr 135.6 144.9 136.4 141.9 132.0 183.6 127.8 130.4 132.9 103.3 118.7 124.5 136.2 137.8
2021 Mai 134.7 142.1 136.7 142.8 131.7 182.7 128.0 130.2 132.9 103.2 117.7 124.5 137.1 138.3
2021 Jun 134.0 139.9 138.1 143.4 131.1 181.0 128.1 130.8 133.0 103.2 117.2 124.5 137.6 138.9
Page | 49
66
Various goods and services
Housing, water, electricity,
Restaurants, hotels, cafes,
domestic equipment, and
Electricity, gas, and other
Alcoholic beverages and
Food products and non-
Leisure, recreation, and
Furniture, home decor,
Clothing and footwear
and similar (includes
alcoholic beverages
gas, and other fuels
routine household
Communications
maintenance
Education
Transport
catering)
tobacco
culture
Month
Health
Total
fuels
Year
2021 Jul 133.5 138.6 137.9 143.6 131.4 182.2 128.4 130.9 132.9 103.2 117.6 124.5 138.1 138.5
2021 Ago 134.0 139.4 138.1 143.5 131.7 182.8 128.7 130.9 133.2 103.2 118.3 124.5 138.6 139.1
2021 Set 135.1 142.0 138.4 143.9 132.1 182.7 128.9 131.3 133.4 103.1 119.6 124.5 140.0 139.3
2021 Out 136.4 144.4 138.4 144.5 133.2 185.1 129.5 134.6 135.1 103.5 119.9 124.5 140.6 140.7
2021 Nov 137.9 145.9 139.3 145.0 135.7 187.3 129.9 135.7 138.5 103.5 121.0 124.5 142.1 141.1
2021 Dez 140.2 151.0 139.9 145.7 136.6 190.5 131.0 135.9 138.5 103.6 121.7 124.5 144.0 141.6
2022 Jan 143.0 153.4 139.3 146.0 135.6 185.1 131.9 141.6 142.5 103.4 121.9 128.9 145.8 142.3
2022 Feb 143.8 155.2 138.3 146.2 136.1 184.7 132.4 141.2 142.9 103.4 122.0 129.2 146.2 142.6
2022 Mar 145.0 156.5 138.7 146.9 137.6 189.4 133.3 141.4 145.8 103.4 122.1 129.2 146.7 143.2
2022 Apr 147.0 158.6 139.6 146.8 137.8 190.1 134.5 141.4 151.5 103.4 122.7 129.2 147.5 143.6
2022 Mai 148.2 160.8 140.1 147.1 138.5 191.6 135.8 141.5 152.9 103.5 122.8 129.2 148.0 144.3
2022 Jun 149.3 161.8 139.9 147.0 140.2 195.4 136.2 142.0 156.5 103.5 122.9 129.2 149.1 145.0
2022 Jul 150.4 162.5 140.3 147.2 141.5 200.0 136.4 141.7 160.3 103.4 123.2 129.2 149.3 145.9
2022 Ago 151.3 163.5 140.1 147.1 141.6 200.3 136.3 141.5 163.4 103.5 123.4 129.2 149.6 146.3
2022 Set 152.3 165.2 140.4 147.3 142.3 202.9 136.3 142.2 165.3 103.5 123.6 129.2 149.6 146.5
2022 Out 152.6 165.6 140.9 147.4 142.4 203.6 136.2 142.4 165.5 103.6 122.5 129.2 150.0 147.1
2022 Nov 153.4 167.8 141.2 147.5 142.3 203.0 136.3 142.7 165.4 103.6 122.2 129.2 150.6 147.3
2022 Dez 155.5 172.7 141.8 147.8 142.9 202.5 136.4 142.6 165.3 103.6 122.3 129.2 152.1 147.1
2023 Jan 157.0 177.5 143.9 148.7 145.3 213.7 136.3 139.8 166.3 103.7 123.9 137.0 153.5 149.3
2023 Feb 158.6 181.2 144.5 149.4 144.9 212.5 136.8 140.2 166.5 103.9 123.8 141.0 153.5 150.0
2023 Mar 160.7 185.0 146.0 149.7 145.6 217.0 137.5 140.0 168.8 104.6 123.5 141.9 154.3 151.6
2023 Apr 161.1 185.6 146.5 150.2 146.4 216.3 137.6 141.2 169.1 104.6 121.4 141.9 154.5 151.7
2023 Mai 160.4 183.5 147.2 150.3 145.5 213.6 138.5 141.5 169.3 104.9 122.1 141.9 154.9 151.6
2023 Jun 159.5 172.7 142.9 148.3 154.5 216.2 142.9 133.5 172.5 106.2 125.1 147.5 164.6 171.0
2023 Jul 159.0 170.4 144.1 148.6 154.9 216.3 142.9 133.8 172.9 106.6 125.5 147.5 165.8 171.6
2023 Ago 158.8 169.5 144.3 148.9 154.3 215.7 143.1 134.0 172.7 106.7 124.9 147.5 166.9 171.7
2023 Set 159.3 170.1 145.2 149.4 154.3 215.9 143.4 134.4 173.1 106.8 125.0 147.5 167.9 172.3
2023 Out 159.8 170.9 146.7 149.8 154.4 216.5 143.9 134.5 173.2 106.8 124.8 147.5 168.5 172.3
2023 Nov 161.7 183.5 151.7 152.9 146.0 218.2 139.5 143.2 170.1 106.0 121.4 141.9 159.4 155.3
2023 Dez 163.8 188.5 152.1 153.0 146.8 221.7 139.9 144.0 170.1 106.0 121.0 141.9 160.8 155.6
Source: National Institute of Statistics (INE), Mozambique.
https://www.ine.gov.mz/web/guest/d/ipcmocambique_8-cidades_quadros_dezembro2023
Page | 49
67
ANNEX 2. General overview of jobs registered by activity.
Activities 2018 2019 2020 2022
Total 457,667 478,904 253,866 361,632
Agricultura, animal production, hunting, forestry, and fishing 97,714 57,309 89,424 106,760
Wholesale and retail trade 59,996 85,276 28,404 38,988
Administrative activities and support services 20,542 17,951 34,467 48,879
Hiring foreigners 23,291 26,535 24,359 23,765
Unspecified activities 36,772 86,153 0 0
Construction 36,013 31,319 14,569 19,831
Other service activities 37,126 28,858 9,858 16,748
Mines of RAS 18,589 20,441 12,896 13,585
Manufacturing industries 20,331 15,258 5,362 26,772
Human Health and social work activities 3,471 15,198 3,976 26,130
Transportation and storage 22,821 18,755 3,671 4,904
Activities of households as employers of domestic personnel and activities of
households for own use 20,217 18,997 1,249 789
Accommodation, catering and similar activities 9,098 9,170 3,305 5,380
Extractive industries 4,972 7,247 4,609 5,394
Public Administration and Defense, Compulsory Social Security 3,716 6,756 3,863 4,742
Education 5,835 5,338 4,257 3,369
Information and Communication Activities 9,030 4,949 1,999 2,854
Farms of RAS 5,728 3,911 1,208 2,201
Electricity, gas, steam, hot and cold water and cold air 4,141 4,829 1,207 1,477
Financial and insurance activities 3,356 4,184 1,048 1,086
Artistic, entertainment and recreational activities 1,668 1,007 440 4,791
Water collection, treatment and distribution, sanitation, waste management and
depollution 1,998 2,627 1,065 1,149
Advisory, scientific, technical and similar activities 1,400 2,018 1,738 909
Sport 4,768 917 0 0
Real estate activities 1,417 1,180 483 798
Repair of motor vehicles and motorcycles 2,442 1,235 0 0
Activities of international organizations and other extra-territorial institutions 338 682 409 331
Culture 877 568 0 0
Security 0 236 0 0
Source: National Institute of Statistics (INE), Mozambique.
Page | 49
68
ANNEX 3. General Import of Goods (US$ Million).
Description
2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Import of goods - fob 7951.7 7576.6 4732.9 5219.4 7027.0 6,999.0 5,921.9 7,961.9 13,337.3 9,179.6
1. Consumer goods 1757.5 1711.6 1109.0 1126.0 1571.9 1679.0 1552.9 2058.2 2092.1 2185.0
1.1 Rice 192.3 205.1 126.8 170.5 201.1 218.5 227.8 342.3 288.4 317.7
1.2 Wheat 145.2 129.6 98.1 120.4 176.8 180.3 194.1 216.0 242.2 261.1
1.3 Sugar 32.7 33.8 6.8 6.5 2.9 6.9 0.5 1.0 0.6 0.2
1.4 Cooking oil 93.2 72.5 64.8 55.4 111.9 175.1 176.3 320.1 315.6 266.1
1.5 Poultry meat and offal 24.6 19.0 11.2 8.2 12.1 17.0 23.3 38.2 38.2 39.9
1.6 Vegetables and Legumes 8.8 12.6 32.7 16.8 19.3 17.5 18.8 22.7 21.8 23.2
1.7 Fruit juices 21.5 19.6 13.9 13.8 19.0 17.4 11.9 16.1 16.6 18.1
1.8 Milk and dairy, eggs, natural honey 46.4 40.6 31.9 37.8 34.0 36.2 40.1 54.1 51.6 50.6
1.9 Beer and other alcoholic beverages 29.3 33.2 22.7 16.1 36.7 36.0 23.3 27.2 40.9 18.4
1.10 Shoe 28.1 26.8 18.7 20.6 33.4 25.1 21.2 27.4 27.4 32.4
1.11 Books, newspapers and others
from the printing industry 41.7 43.6 32.6 27.0 24.3 40.7 18.4 22.9 30.7 38.9
1.12 Paper and card 87.6 81.6 65.6 62.0 82.2 83.7 57.9 73.3 83.8 96.7
1.13 Automobiles 567.1 441.3 211.4 186.3 317.7 378.4 253.8 345.5 369.3 421.0
1.14 Car Accessories 65.0 51.6 34.5 32.8 40.7 43.4 33.4 41.5 46.4 52.4
1.15 New rubber tires 66.6 38.6 26.2 40.7 51.7 59.0 45.8 46.2 56.8 64.8
1.16 Processed Wood 10.5 18.9 12.0 13.3 97.5 25.3 20.4 32.3 20.0 19.1
1.17 Medicines and Reagents 176.2 314.1 210.2 227.1 223.6 229.5 306.2 334.7 321.4 354.2
1.18 Furniture and medical-surgical
equipment (including medical devices) 106.7 117.8 81.1 63.3 78.1 79.9 72.8 83.6 110.3 98.2
1.20 Soaps and cleaning products 13.8 11.4 7.9 7.6 8.7 9.1 6.9 13.0 10.0 12.0
2. Intermediate Goods 3056.8 2093.3 1684.3 1989.7 2639.1 2339.5 1794.9 2711.1 3674.5 3069.6
2.1 Fuels 1191.2 626.9 550.0 799.8 1148.0 964.4 541.8 946.9 1966.2 1417.1
2.1.1 Diesel 808.0 385.4 345.5 470.9 609.0 535.6 346.5 590.3 1389.8 942.0
2.1.2 Gasoline 270.5 153.3 141.4 226.7 423.3 167.8 135.5 233.3 379.5 347.8
2.1.3 Jet Fuel 78.2 51.3 36.6 47.3 45.3 46.3 18.0 30.3 75.5 70.1
2.1.4 LPG 19.4 18.0 10.2 15.2 19.1 19.7 15.9 36.2 39.7 32.5
2.1.5 Kerosene 15.1 18.9 16.3 39.6 51.4 194.9 26.1 56.8 81.7 24.7
2.2 Electric Power 245.2 223.5 175.9 244.6 219.9 156.0 187.1 253.9 203.5 190.9
2.3 Raw Aluminum 571.0 442.5 427.5 449.9 617.8 315.9 248.9 363.0 466.1 345.9
2.4 Construction Materials (Excl.
Cement) 772.8 653.7 403.4 378.6 517.4 586.8 607.8 865.3 651.7 758.7
2.5 Oil and Lubricants 93.2 0.0 0.0 0.1 0.1 0.2 0.1 0.0 0.0 0.0
2.6 Fertilizers 79.9 29.5 29.5 38.2 61.1 84.4 66.8 116.4 181.7 173.6
2.7 Cement 81.0 95.2 61.8 66.4 60.4 77.2 86.9 76.3 49.5 59.2
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69
Description
2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
2.8 Petroleum Tar and Bitumen 22.6 22.0 36.1 12.0 14.4 154.6 55.5 89.2 155.7 124.2
3. Capital Goods 1763.3 1594.8 1005.4 808.5 1129.5 1367.1 1083.8 1262.1 5523.6 1749.5
3.1 Machinery 1710.7 1555.4 970.0 768.0 1028.3 1309.5 1023.2 1184.4 5449.2 1632.0
3.2 Tractors e Semi-trailers 52.6 39.5 35.4 40.5 101.2 57.6 60.6 77.8 74.4 117.5
4. Miscellaneous Products 1374.1 2176.8 934.2 1295.2 1686.5 1613.5 1490.2 1930.4 2047.1 2175.5
Note:
Major Projects 1486.8 917.0 771.1 732.6 913.9 897.5 773.8 794.2 5447.6 1309.0
Excluding Major Projects 6464.9 6659.6 3961.8 4486.8 6113.1 6101.6 5148.1 7167.7 7889.7 7870.6
Source: Central Bank of Mozambique
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70
ANNEX 4. Imports of Goods by Country of Origin (US$ Million).
Description 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Imports of Goods - fob 7951.7 7576.6 4732.9 5219.4 7027.0 6999.0 5921.9 7961.9 13337.3 9179.6
1. Africa 3124.7 2633.9 1595.1 1711.1 2299.8 2241.3 2030.2 2441.4 2470.4 2442.2
1.1. SADC Member Countries 3109.3 2615.1 1575.6 1676.9 2253.5 2180.0 1995.9 2402.4 2432.2 2412.9
South Africa 2891.9 2380.2 1443.1 1513.5 1992.8 1944.8 1823.6 2097.4 2081.8 2128.6
Malawi 9.7 15.3 5.9 15.7 13.4 11.4 9.9 29.8 11.6 16.4
Zimbabwe 24.9 74.4 9.6 10.9 8.3 16.9 16.1 23.8 29.3 26.8
Angola 2.1 1.0 0.9 1.7 6.1 2.4 1.1 0.3 0.9 2.0
Tanzania 25.5 12.4 6.1 4.5 7.9 15.4 11.2 76.3 54.2 46.7
Swaziland 45.6 50.7 42.9 39.9 115.3 54.7 44.5 52.6 56.3 66.3
Namibia 55.8 48.1 32.6 48.9 49.3 67.8 35.3 48.3 43.5 48.8
Botswana 1.8 2.9 1.7 1.0 1.5 3.7 2.0 1.2 4.3 3.1
Zambia 24.9 7.8 7.7 7.1 8.5 15.5 15.9 22.4 25.8 32.9
Lesotho 0.1 0.0 0.1 0.2 0.2 0.7 0.2 3.6 0.2 0.2
Congo 0.6 0.6 0.5 0.2 0.2 0.4 0.6 0.5 0.3 0.4
Mauritius 26.2 21.0 24.0 30.9 47.4 36.9 34.8 36.4 123.4 40.3
Madagascar 0.3 0.5 0.1 2.6 2.7 9.3 0.7 9.9 0.5 0.5
DR Congo 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
1.2. Non-SADC Member Countries 15.4 18.8 19.5 34.2 46.2 61.3 34.2 39.0 38.2 29.2
Kenya 6.9 6.4 9.4 5.4 10.8 15.2 7.1 10.3 11.7 10.0
Others 8.5 12.4 10.1 28.9 35.4 46.1 27.1 28.7 26.5 19.2
2. Europe 1791.2 1776.9 1023.2 1233.3 1409.1 1058.8 929.2 1144.9 1117.0 1132.5
2.1. European Union Member
Countries 1694.2 1668.0 940.8 1164.9 1230.0 903.0 742.9 944.4 817.3 889.8
Germany 121.5 92.9 128.6 61.8 116.2 116.5 74.7 60.3 81.0 86.8
Austria 16.1 18.3 3.6 4.3 5.0 5.1 3.3 13.4 9.9 5.6
Belgium 30.8 47.5 39.2 28.9 36.1 53.5 34.4 45.4 50.9 51.0
Spain 53.3 52.5 30.6 26.2 70.3 46.2 34.5 32.4 63.4 149.2
Finland 22.0 10.9 86.0 2.2 1.3 3.9 1.7 3.5 6.0 4.1
France 67.3 268.9 57.8 231.4 25.3 38.8 36.4 184.7 78.4 62.4
Greece 4.1 0.8 0.8 0.5 1.3 2.7 0.5 0.7 0.5 0.3
Netherlands 605.3 564.0 114.5 446.3 475.4 135.5 51.8 48.8 60.7 59.2
Ireland 13.9 13.1 5.9 6.0 51.0 7.4 4.9 13.8 8.6 5.2
Italy 93.6 64.3 40.3 53.1 80.5 94.1 99.9 61.2 47.5 53.6
Luxembourg 1.4 0.2 0.6 0.1 0.2 0.6 1.0 13.1 0.2 0.2
Portugal 456.0 356.5 277.7 220.3 210.6 246.6 209.4 265.9 252.1 245.0
UK 118.4 95.6 101.6 33.6 66.8 90.2 116.9 127.4 47.5 50.6
Denmark 10.5 10.7 9.8 13.2 15.3 19.4 16.6 17.9 30.1 27.9
Sweden 67.1 27.6 11.8 8.1 15.4 13.6 9.9 5.3 6.1 5.4
Poland 5.1 15.2 4.6 24.2 14.3 9.4 22.0 29.6 14.0 35.9
Czech Republic 1.3 0.9 0.6 2.1 6.1 6.8 3.7 4.8 3.7 1.4
Hungary 0.4 0.4 0.6 0.5 0.4 0.9 0.6 0.7 2.7 1.6
Slovenia 0.4 0.2 0.4 0.1 0.1 0.1 0.2 0.2 0.9 0.6
Bulgaria 0.3 19.1 23.6 0.3 0.1 0.7 0.6 0.9 6.4 0.7
Malta 0.6 0.1 0.6 0.1 14.3 0.0 3.2 6.2 0.1 1.1
Estonia 0.1 0.0 0.0 0.0 2.7 0.2 0.5 0.2 0.3 0.7
Cyprus 1.7 1.9 0.9 1.5 1.8 1.6 1.5 1.4 3.3 0.4
Lithuania 1.7 3.8 0.4 0.1 19.2 7.3 13.0 6.0 29.7 28.3
Latvia 1.2 2.7 0.1 0.1 0.5 1.9 1.8 0.5 13.4 12.6
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Description 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
2.2. Countries Not Members of the
European Union 96.9 108.9 82.4 68.4 179.0 155.8 186.3 200.5 299.7 242.6
Norway 3.1 1.8 2.9 3.6 5.3 12.9 5.8 39.1 8.3 8.5
Switzerland 43.6 40.8 26.1 4.6 14.7 21.4 19.6 20.9 168.5 49.7
Türkiye 39.1 45.7 17.9 19.6 61.0 42.2 46.8 69.8 53.1 46.0
Others 11.1 20.6 35.5 40.6 98.0 79.3 114.1 70.8 69.8 138.5
3. America 367.0 289.7 266.8 256.4 328.5 374.7 279.9 405.1 399.9 330.5
3.1. North America 191.1 159.6 138.0 126.3 242.4 240.7 188.4 263.2 226.9 238.1
USA 158.3 124.3 110.0 101.5 200.0 188.7 140.1 209.6 199.0 163.6
Canada 31.6 33.4 18.6 22.4 30.9 42.6 41.5 45.8 15.7 68.7
Mexico 1.3 1.9 9.5 2.4 11.5 9.5 6.8 7.8 12.2 5.7
3.2. Other Countries in America 175.9 130.1 128.7 130.2 86.1 134.0 91.5 142.0 173.0 92.5
Argentina 27.0 32.9 27.0 36.7 34.3 64.8 52.7 79.8 103.9 53.1
Barbados 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Brazil 85.6 48.2 27.1 30.2 32.0 33.6 25.2 27.6 53.9 27.2
Cuba 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
Others 63.1 49.0 74.6 63.3 19.8 35.5 13.6 34.5 15.3 12.0
4. Australia 64.9 32.2 69.4 12.9 6.2 33.1 8.4 85.9 210.3 52.2
5. Middle East 491.2 674.9 390.8 549.7 545.6 654.6 442.4 773.5 1572.3 1189.1
United Arab Emirates 478.6 341.6 344.8 497.0 486.2 599.7 387.5 672.1 1332.6 946.4
Saudi Arabia 12.6 12.8 7.3 42.0 14.4 46.4 40.8 93.5 238.6 242.2
Others 0.0 320.4 38.7 10.8 45.0 8.4 14.2 8.0 1.1 0.6
6. Asia 2102.5 2038.5 1378.5 1445.3 2387.7 2631.5 2227.1 3100.4 7563.6 4030.5
Bangladesh 0.4 0.3 0.2 1.4 0.9 1.2 0.5 1.0 1.4 14.3
China 675.0 874.3 379.9 448.5 862.5 785.6 639.0 859.6 964.4 1411.5
Hong Kong 43.0 36.5 15.1 19.3 38.4 76.0 40.6 74.8 81.0 134.0
India 328.1 316.5 295.9 410.2 457.5 431.8 529.8 682.4 765.7 733.9
Indonesia 56.0 61.7 4.7 8.3 7.0 85.6 63.6 64.8 55.5 51.8
Japan 274.5 243.1 98.5 115.6 178.4 216.5 146.3 196.5 199.1 198.0
Malaysia 57.6 20.8 35.8 33.9 59.4 80.9 124.2 217.9 143.3 190.3
Pakistan 72.0 65.4 54.6 51.9 58.6 99.0 94.1 95.3 75.5 43.1
Singapore 109.9 149.8 306.6 92.6 256.7 473.2 329.9 541.0 617.6 560.8
Korea 43.7 34.6 32.5 17.3 22.5 23.8 21.0 40.9 4268.5 41.8
Taiwan 9.6 10.2 12.2 5.6 28.0 11.5 8.4 8.9 43.1 20.1
Thailand 140.6 125.1 81.3 120.0 143.7 112.6 69.1 95.4 94.6 122.9
Vietnam 124.7 77.0 60.2 73.8 34.6 66.2 65.5 64.7 57.2 124.6
Others 167.4 23.2 1.1 46.7 239.4 167.6 95.2 157.3 196.5 383.5
7. Others 10.3 130.6 9.1 10.6 50.2 5.1 4.7 10.7 3.9 2.6
Compilation: BM/DER
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ANNEX 5. General Export of Goods (US$ Million).
Description
2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Goods Exports - fob 3916.4 3413.3 3328.2 4754.8 6036.6 4786.7 3719.9 5704.5 8280.9 8276.4
1. Agricultural Products 465.1 387.7 315.3 315.0 288.1 430.8 339.8 400.2 562.3 503.3
1.1 Tobacco 256.1 257.5 206.0 211.6 210.9 230.7 177.7 144.2 150.6 154.2
1.2 Vegetables 41.7 19.4 22.0 14.1 12.5 82.2 57.6 151.4 223.9 149.5
1.3 Cotton 80.6 45.4 19.9 9.1 3.2 36.1 15.5 20.2 36.7 34.3
1.4 Peanuts 8.0 1.3 8.9 2.7 2.0 8.6 3.3 1.2 42.6 69.1
1.5 Cashew Nuts 9.8 10.2 15.8 31.4 14.8 30.3 44.7 30.1 51.7 57.3
1.6 Various fruits 68.8 53.8 42.8 46.2 44.6 42.9 40.8 53.2 56.9 38.8
Of which: Banana 49.4 45.1 23.4 32.8 38.8 33.1 33.7 41.2 41.4 32.3
2. Manufacturing Industry 1203.9 1125.0 990.3 1284.7 1863.4 1315.7 1189.7 1537.9 1954.2 1364.0
2.1 Aluminum Bars 1052.3 908.3 843.0 1101.0 1150.4 994.7 913.8 1258.7 1645.7 1100.5
2.2 Aluminum Cables 0.0 14.0 44.0 94.8 158.3 105.2 72.9 135.5 155.7 161.5
2.3 Sugar 81.3 137.3 46.1 53.1 177.0 84.6 68.2 39.9 57.1 24.1
2.4 Cashew Almond 9.9 9.8 13.4 11.2 1.9 57.0 28.9 21.7 23.8 20.4
2.5 Sunflower, safflower or cotton oil 26.8 17.2 12.4 13.7 13.3 15.8 14.9 22.2 28.9 12.9
2.6 Alcoholic drinks and vinegars 7.7 20.5 16.0 7.6 235.2 29.0 52.0 17.3 0.0 0.0
2.7 Wig and similar articles 25.9 17.9 15.4 3.3 127.4 29.6 39.0 42.5 43.0 44.6
3. Extractive Industry 1114.0 899.7 1286.0 2353.7 2299.1 1850.2 1146.1 2365.1 4141.5 4694.4
3.1 Rubies, sapphires and emeralds 81.8 89.7 100.6 96.9 125.8 121.9 12.0 158.1 185.9 228.1
3.2 Heavy Sands 191.3 161.4 189.9 210.1 286.1 271.7 253.5 470.0 561.9 514.6
3.3 Mineral Coal 501.0 375.3 719.2 1687.1 1655.3 1225.8 648.7 1465.6 2852.2 2225.6
3.4 Natural Gas 339.9 273.3 276.4 359.5 231.9 230.8 231.9 271.4 541.6 1726.1
5. Other Goods 300.6 198.0 108.0 126.8 163.9 187.8 99.6 124.8 275.5 133.9
5.1 Raw Wood 21.9 14.8 8.1 7.3 3.6 24.9 3.7 6.9 8.0 5.0
5.2 Lumber 124.4 64.6 17.2 41.9 18.9 17.3 12.9 15.0 15.2 11.2
5.3 Shrimp 42.5 22.6 29.5 23.6 49.8 42.9 35.8 41.0 34.8 41.1
5.4 Capital Goods 54.9 66.5 39.6 39.0 84.0 35.1 22.9 30.8 39.6 54.4
5.5 Re-exports and Bunkers 57.0 29.6 13.6 14.9 7.5 67.6 24.3 31.2 177.9 22.2
6. Electrical Energy 341.1 316.9 376.3 360.8 428.6 434.6 456.4 569.7 571.0 658.2
7. Product Miscellany 491.7 486.1 252.4 313.9 993.5 567.6 488.3 706.7 776.3 922.5
Grades:
Large Projects 2425.6 2035.1 2404.7 3718.6 3752.3 3157.6 2504.3 4035.4 6172.3 6225.0
Excluding Major Projects 1490.8 1378.2 923.6 1036.3 2284.2 1629.2 1215.6 1669.0 2108.5 2051.4
Compilation: BM
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ANNEX 6. Exports of main products by activity, 2023 (US$ Million)
Activity Product Value
Agricultural Tobacco 154.2
Agricultural Vegetables 149.5
Agricultural Cotton 34.3
Agricultural Peanut 69.1
Agricultural Cashews 57.3
Agricultural Various fruits 6.7
Agricultural Banana 32.3
Transforming Industry aluminum bars 1,100.5
Transforming Industry aluminum cables 161.5
Transforming Industry Sugar 24.1
Transforming Industry Cashew Almond 20.4
Transforming Industry Sunflower, safflower, or cottonseed oil 12.9
Transforming Industry Alcoholic beverages and vinegars 0.0
Transforming Industry Wig and similar items 44.6
Extractive Industry Rubies, sapphires and emeralds 228.1
Extractive Industry heavy sands 514.6
Extractive Industry Coal 2,225.6
Extractive Industry Natural gas 1,726.1
Others raw wood 5.0
Others Wood 11.2
Others Shrimp 41.1
Others Capital goods 54.4
Others Re-exports and Bunkers 22.2
Others Electric power 658.2
Others Miscellaneous products 922.5
Total 8,276.6
Source: Central Bank of Mozambique
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ANNEX 7. Export of Goods by Destination Country (US$ Million).
Description / Year 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Total Exports of Goods - fob 3,916.4 3,413.3 3,328.2 4,754.8 6,036.6 4,786.7 3,719.9 5,704.5 8,280.9 8,276.4
1. Africa 1,170.7 931.4 834.7 1,045.2 1,764.1 1,133.3 1,129.8 1,475.9 1,711.7 1,622.0
1.1. SADC Member Countries 1,137.7 923.2 818.7 1,023.3 1,715.0 1,110.5 1,095.9 1,411.3 1,647.4 1,574.1
South Africa 948.2 712.5 706.1 884.5 1,546.6 870.5 857.1 1,016.7 1,120.6 1,156.5
Malawi 29.6 14.0 16.9 20.5 29.1 58.4 46.7 45.2 47.4 48.3
Zimbabwe 96.5 89.8 45.2 56.5 36.6 76.9 114.9 216.9 210.8 173.1
Angola 2.8 4.7 2.4 3.0 2.9 4.6 5.9 1.0 3.0 3.6
Tanzania 31.2 13.0 8.2 10.8 24.1 11.9 6.4 4.2 5.7 1.4
Swaziland 3.2 1.1 6.4 1.7 30.2 17.6 10.6 24.8 64.9 20.0
Namibia 0.0 69.5 0.5 0.5 17.2 1.7 1.0 0.2 0.9 0.2
Botswana 2.4 0.3 4.9 11.5 3.1 20.4 4.9 6.9 40.4 51.1
Zambia 3.7 3.1 13.3 11.8 12.3 31.0 30.6 55.1 101.2 81.2
Lesotho 0.3 0.0 5.1 9.2 4.1 5.7 7.9 6.9 20.9 10.9
Congo 1.8 2.2 0.7 0.7 0.4 1.3 0.3 0.8 4.2 4.9
Mauritius 16.6 12.9 8.4 11.5 4.7 5.6 8.0 21.1 16.3 17.4
Madagascar 1.4 0.2 0.5 1.2 3.7 3.5 1.0 0.7 1.1 0.6
DR Congo 0.0 0.0 0.0 0.0 0.0 1.2 0.4 11.0 10.1 5.1
1.2. Non-SADC Member Countries 33.0 8.2 16.0 21.9 49.1 22.8 34.0 64.6 64.3 47.8
Kenya 9.2 3.2 7.7 15.0 22.9 9.2 7.6 22.0 27.7 1.4
Others 23.8 5.1 8.3 6.9 26.2 13.6 26.4 42.6 36.6 46.5
2. Europe 1,737.9 1,587.5 1,273.7 1,360.3 1,838.3 1,601.6 1,318.6 1,782.2 2,326.6 1,591.7
2.1. European Union Member Countries 1,613.0 1,445.7 1,207.0 1,282.6 1,723.3 1,528.4 1,276.9 1,674.6 2,099.8 1,310.6
Germany 22.6 23.8 10.9 8.8 23.0 18.5 15.7 24.3 16.4 20.3
Austria 0.1 0.0 0.0 0.0 0.0 0.1 0.1 1.2 7.7 0.0
Belgium 53.5 88.8 46.3 89.5 73.7 196.0 136.7 78.9 110.6 101.1
Spain 57.7 26.6 67.5 81.0 90.5 177.8 104.8 119.3 185.3 92.1
Finland 16.4 5.2 21.3 0.0 7.1 0.0 0.1 0.0 0.0 0.1
France 9.3 30.5 35.1 35.0 72.1 40.1 16.0 20.1 27.7 7.1
Greece 2.5 6.2 3.1 3.9 6.2 39.7 10.4 5.1 3.2 17.1
Netherlands 1,111.4 952.4 849.4 473.5 613.6 296.2 206.0 458.2 314.1 304.8
Ireland 0.3 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0
Italy 47.9 99.7 41.9 270.2 129.6 302.6 238.6 175.9 203.8 244.0
Luxembourg 2.3 46.6 4.0 0.0 0.0 0.1 1.7 9.0 32.4 22.3
Portugal 53.4 29.4 32.6 22.2 278.8 63.5 77.3 41.9 25.6 21.4
UK 209.9 84.2 59.2 210.8 312.7 220.2 364.7 586.0 985.4 399.8
Denmark 1.5 0.0 0.3 1.4 0.4 0.4 0.1 1.1 0.6 0.1
Sweden 0.1 0.1 0.1 3.6 0.4 3.1 3.7 2.0 1.9 1.3
Poland 13.2 22.1 26.9 31.4 85.0 127.1 77.3 116.7 134.9 48.4
Czech Republic 2.5 0.1 0.0 6.9 9.5 4.4 3.1 1.7 0.1 0.1
Hungary 0.3 0.6 0.5 1.4 0.3 1.0 0.8 2.0 0.1 0.3
Slovenia 0.0 3.1 1.5 23.8 19.6 21.5 19.8 29.9 49.6 19.4
Bulgaria 0.0 0.1 0.9 16.1 0.0 10.0 0.0 0.9 0.3 10.5
Malta 3.2 0.6 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0
Estonia 0.0 0.0 0.0 0.0 0.0 5.3 0.0 0.0 0.0 0.0
Cyprus 0.5 10.4 0.0 0.0 0.0 0.1 0.0 0.1 0.2 0.2
Lithuania 4.6 14.8 5.6 3.2 0.6 0.7 0.0 0.0 0.0 0.0
Latvia 0.0 0.3 0.0 0.0 0.0 0.1 0.1 0.3 0.0 0.1
2.2. Countries Not Members of the European
124.8 141.8 66.7 77.7 115.0 73.1 41.7 107.6 226.7 281.2
Union
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Description / Year 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Norway 2.4 3.1 2.5 1.2 0.0 1.6 0.6 0.2 0.1 0.3
Switzerland 87.9 27.8 17.0 21.1 28.3 21.6 24.9 38.6 142.2 98.6
Others 34.6 110.9 47.2 55.3 86.6 49.9 16.3 68.8 84.4 182.3
3. America 91.1 84.6 126.7 83.0 177.5 163.3 149.8 156.5 219.0 174.7
3.1. North America 70.9 66.3 109.3 75.8 104.2 99.6 89.9 154.2 160.8 127.0
USA 53.3 58.2 97.8 70.9 91.7 83.1 72.8 95.6 124.3 113.9
Canada 3.7 2.6 3.4 1.2 4.0 6.8 17.0 38.7 20.3 8.0
Mexico 13.9 5.5 8.0 3.7 8.6 9.7 0.1 19.9 16.2 5.1
3.2. Other Countries in America 20.2 18.3 17.3 7.1 73.3 63.6 59.9 2.3 58.2 47.8
Argentina 4.0 14.2 6.7 0.0 0.9 0.4 0.0 0.0 0.0 0.0
Brazil 8.3 1.4 3.0 0.9 34.8 60.1 33.2 1.3 3.1 1.2
Others 7.9 2.7 7.6 6.2 37.7 3.1 26.6 1.0 55.1 46.5
4. Australia 0.1 2.4 0.3 10.0 9.1 0.9 11.2 0.9 0.2 0.2
5. Middle East 68.9 55.0 35.7 63.1 58.1 88.7 66.2 78.6 186.2 272.4
Iran 0.3 0.2 1.8 0.4 0.0 0.0 0.0 0.0 0.0 0.0
Lebanon 1.0 0.7 2.9 5.3 1.9 4.8 0.9 0.3 0.4 0.3
Saudi Arabia 19.2 4.9 2.8 0.4 1.1 2.6 3.5 2.4 37.4 92.3
United Arab Emirates 46.2 34.3 19.7 55.4 55.1 81.2 61.8 75.9 148.4 179.5
Others 2.1 14.9 8.5 1.5 0.0 0.0 0.0 0.0 0.1 0.3
6. Asia 840.9 704.8 1,057.1 2,175.3 2,188.6 1,798.3 1,042.2 2,195.2 3,836.5 4,615.0
Bangladesh 14.2 4.4 1.1 0.3 0.1 19.8 4.1 0.5 4.9 42.6
China 204.2 131.7 142.7 252.6 249.0 326.8 261.2 490.8 428.5 1,175.4
Hong Kong 3.3 27.8 38.5 85.5 121.8 115.1 20.2 35.4 42.5 120.9
India 387.6 321.4 649.1 1,621.7 1,369.2 783.4 424.8 789.3 1,744.7 1,294.3
Indonesia 27.3 7.0 6.6 7.0 1.3 8.5 4.2 3.2 31.5 65.2
Japan 50.4 17.8 31.2 17.0 40.0 103.3 33.7 99.4 115.4 135.4
Malaysia 4.4 2.3 7.6 1.0 4.8 15.9 10.4 34.8 71.5 27.6
Pakistan 0.7 0.6 0.3 2.0 0.8 1.5 1.0 52.2 148.1 33.5
Singapore 74.7 141.9 140.7 141.4 230.0 170.1 109.6 388.0 320.1 390.3
Suriname 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Taiwan 22.6 0.6 11.7 0.0 0.2 1.2 0.3 0.2 1.1 0.5
Thailand 3.9 19.3 18.1 10.6 26.9 16.9 11.1 24.3 174.4 380.1
Vietnam 18.5 3.8 8.6 15.9 13.7 57.2 74.8 41.5 172.8 324.3
New Caledonia 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Others 29.2 26.0 0.8 20.2 130.8 178.7 87.0 235.8 581.0 625.0
7. Others 6.8 47.6 0.0 18.0 0.9 0.8 2.0 15.2 0.6 0.3
Compilation: BM/DER
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ANNEX 8. Credit Portfolio Balance by Sectors of Economic Activity
Silviculture Year-end
Unit Year Agriculture Livestock Fisheries Others
and Forestry Balance
MTT
2014 2434 151 571 776 181,963 185,896
MTT
2015 6333 335 136 1445 217,876 226,126
MTT
2016 8129 544 81 1814 255,505 266,073
MTT
2017 6094 524 71 1544 217,839 226,073
MTT
2018 5428 510 157 1515 206,251 213,861
MTT
2019 5769 864 163 1316 210,628 218,740
MTT
2020 5761 891 173 1533 231,388 239,745
MTT
2021 4838 816 44 1038 240,080 246,817
MTT
2022 4508 859 70 888 234,652 240,977
MTT
2023 3529 645 69 853 240,580 245,677
Source: Central Bank of Mozambique
Unit Year Agriculture Livestock Forestry Fishery Other Balance
MDD 2014 79.3 4.9 18.6 25.3 5,929.1 6,057.2
MDD 2015 165.4 8.8 3.6 37.8 5,691.6 5,907.1
MDD 2016 129.9 8.7 1.3 29.0 4,083.5 4,252.4
MDD 2017 95.8 8.2 1.1 24.3 3,424.6 3,554.0
MDD 2018 90.0 8.5 2.6 25.1 3,420.4 3,546.6
MDD 2019 92.2 13.8 2.6 21.0 3,367.4 3,497.0
MDD 2020 82.9 12.8 2.5 22.1 3,330.8 3,451.1
MDD 2021 73.9 12.5 0.7 15.9 3,667.0 3,769.9
MDD 2022 70.6 13.5 1.1 13.9 3,675.1 3,774.1
MDD 2023 55.2 10.1 1.1 13.4 3,765.5 3,845.3
Source: Central Bank of Mozambique
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ANNEX 9. Gross Domestic Product (US$ million, 2014 constant prices)
Activity 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Agriculture, Animal Production, Hunting,
4,178 4,332 4,463 4,652 4,836 5,000 5,063 5,244 5,430 5,715 5,922
Forestry and Fishing
Agriculture, Animal Production, Hunting
3,926 4,062 4,187 4,360 4,533 4,689 4,742 4,926 5,102 5,383 5,582
and Forestry
Agriculture 3,373 3,487 3,578 3,740 3,887 4,033 4,082 4,245 n/d n/d n/d
Animal Production 262 276 292 297 316 319 319 346 n/d n/d n/d
Forestry 290 299 316 323 330 337 341 335 n/d n/d n/d
Fishing, Aquaculture and Activities two
253 270 276 292 303 312 321 318 328 332 340
related services
Extractive industries 666 796 949 1,081 1,428 1,589 1,548 1,309 1,336 1,456 1,979
Manufacture 1,389 1,453 1,563 1,618 1,660 1,690 1,713 1,691 1,720 1,707 1,633
Gas and Water Electricity 533 546 595 623 602 582 573 599 597 621 634
Construction 297 341 373 383 371 369 377 375 378 382 369
Commercial, Automotive Vehicle Repair 1,766 1,936 2,107 2,075 2,025 2,057 2,078 2,028 2,071 2,127 2,144
Transport, Storage, Information and
1,727 1,963 1,992 2,018 2,111 2,211 2,300 2,267 2,292 2,497 2,631
Communications
Accommodation, Restaurants and Similar 349 362 381 383 381 396 402 313 298 330 357
Financial Activities 730 845 921 1,024 1,067 1,116 1,162 1,152 1,184 1,220 1,276
Real Estate Activities, Rent and Services
939 947 1,033 1,006 1,008 1,044 1,089 1,099 1,113 1,119 1,160
Provided to Companies
Public Administration, Defense and Social
914 1,057 1,229 1,325 1,353 1,376 1,433 1,294 1,313 1,340 1,401
Security
Education 1,077 1,161 1,226 1,250 1,269 1,279 1,291 1,275 1,308 1,352 1,386
Health and Social Action 249 263 278 301 315 319 333 357 387 396 402
Other Activities of Collective, Social and
139 144 150 155 161 166 171 175 181 187 191
People Services
Total Increased Values, base prices 14,953 16,147 17,262 17,896 18,585 19,196 19,534 19,179 19,609 20,449 21,485
Taxes on Products 1,899 1,952 2,054 2,158 2,220 2,325 2,485 2,576 2,659 2,746 2,873
VAT 1,294 1,308 1,373 1,491 1,521 1,610 1,759 1,813 n/d n/d n/d
Import Directives 230 265 291 273 279 319 336 317 n/d n/d n/d
Other Taxes on Products 375 379 390 395 420 397 390 446 n/d n/d n/d
Gross Domestic Product 16,852 18,099 19,315 20,054 20,804 21,521 22,019 21,755 22,268 23,195 24,358
Source: INE
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ANNEX 10. Gross Domestic Product (US$ million, current prices)
Activity 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Agriculture, Animal Production, Hunting, Forestry 4,198 4,528 3,990 2,874 3,457 3,837 3,842 3,826 4,348 4,920
and Fishing
Agriculture, Animal Production, Hunting and 3,933 4,246 3,742 2,713 3,274 3,642 3,639 3,616 4,127 4,660
Forestry
Agriculture 3,359 3,652 3,188 2,365 2,855 3,188 3,158 3,172 3,640 4,040
Animal Production 268 278 276 174 236 261 274 255 283 361
Forestry 306 317 277 174 183 194 207 189 203 259
Fishing, Aquaculture and Activities two related 265 282 248 160 183 195 204 211 221 260
services
Extractive industries 513 743 893 1,016 1,513 1,876 1,725 1,346 1,590 1,918
Manufacture 1,441 1,510 1,407 987 1,037 1,294 1,354 1,187 1,304 1,566
Production and Distribution of Electricity and Gas 493 495 449 272 354 408 390 368 388 427
Water Capture, Treatment and Distribution 35 35 35 23 24 30 36 34 43 50
Construction 365 429 368 202 203 198 201 161 223 234
Commercial, Automotive Vehicle Repair 1,830 1,947 1,817 1,287 1,339 1,428 1,572 1,495 1,482 1,604
Transport, storage 1,250 1,450 1,202 752 779 861 941 747 901 1,143
Accommodation, Restaurants and Similar 344 348 292 193 218 233 249 165 158 195
Information and Communication 582 614 586 350 385 494 483 455 489 521
Financial Activities 856 845 754 692 646 629 646 621 713 990
Real Estate Activities, Rent and Services Provided 1,000 989 830 486 495 543 520 448 492 507
to Companies
901 1,057 1,114 823 767 1,010 1,034 954 1,059 1,250
Public Administration, Defense and Social Security
Education 1,142 1,079 957 625 506 453 511 567 642 799
Health and Social Action 287 244 220 155 153 177 218 218 269 340
Other Activities of Collective, Social and People 146 142 121 78 86 91 101 94 105 117
Services
Total Increased Values, base prices 15,384 16,454 15,035 10,815 11,963 13,562 13,823 12,686 14,206 16,580
Taxes on Products 1,926 1,912 1,895 1,347 1,297 1,462 1,689 1,548 1,961 1,827
VAT 1,294 1,308 1,351 945 920 1,080 1,160 1,087 1,409 1,317
Import Directives 305 269 292 200 171 164 286 218 227 183
Other Taxes on Products 326 336 252 203 206 218 243 243 325 327
Gross Domestic Product 17,310 18,366 16,930 12,163 13,259 15,024 15,512 14,234 16,167 18,407
Source: INE
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ANNEX 11. Estimates of Support to agriculture
(million meticais)
Concept Unit 2019 2020 2021 2022
I. Total value of production (at the farm gate) Mz Mill 443,524.8 502,835.6 488,594.3 527,815.5
1. Of which, standard PSE commodity share (%) % 59.9% 60.3% 60.4% 61.1%
II. Total consumption value (at the farm gate) Mz Mill 449,084.9 503,346.3 405,028.8 494,554.0
1. Of which, standard PSE commodities Mz Mill 268,913.9 303,494.9 244,484.7 301,985.4
III.1 Producer Support Estimate (PSE) Mz Mill 39,960.3 16,974.5 26,993.4 48,207.1
A.1 Market price support Mz Mill 39,260.6 16,655.0 26,885.7 48,081.1
1. Of which, standard PSE commodities Mz Mill 23,509.4 10,042.2 26,885.7 29,359.3
A.2 Production-based payments Mz Mill 485.7 152.9 4.8 15.5
B. Payments based on input use Mz Mill 156.4 155.0 84.7 98.7
1. Based on the use of variable inputs Mz Mill 86.2 83.5 64.7 73.9
Producer Support Estimate
2. Based on the use of fixed inputs Mz Mill 67.9 68.5 20.0 24.7
3. Based on usage of services Mz Mill 2.3 3.0 0.0 0.0
C. Support based on production A /An/ I. Production required Mz Mill 0.0 0.0 0.0 0.0
1. Based on revenue Mz Mill 0.0 0.0 0.0 0.0
2. Based on area or number of animals Mz Mill 0.0 0.0 0.0 0.0
D. Supports based on A/AN/I Not Current. Required
Mz Mill
production 0.0 0.0 0.0 0.0
E. Supports based on A/AN/I Not Current. Production Not
Mz Mill
required 0.0 0.0 0.0 0.0
1. Variable rates Mz Mill 0.0 0.0 0.0 0.0
2. Fixed Fees Mz Mill 0.0 0.0 0.0 0.0
F. Supports based on non-commodity criteria Mz Mill 0.0 0.0 0.0 0.0
1. Long term resource Mz Mill 0.0 0.0 0.0 0.0
2. A specific non-commodity product Mz Mill 0.0 0.0 0.0 0.0
3. Other non-commodity criteria Mz Mill 0.0 0.0 0.0 0.0
G. Miscellaneous Support Mz Mill 57.7 11.6 18.2 11.9
III.2 Estimated Percentage of Producer Support (PSE) % 9.0 3.4 5.5 9.1
IV. General Services Support Estimate (GSSE) Mz Mill 2,105.5 1,916.7 3,082.6 9,137.7
General Services Support
H. Agricultural Knowledge Mz Mill 714.1 854.7 135.4 5,455.6
Estimate (GSSE)
I. Inspection and Control Mz Mill 157.1 85.3 102.7 102.3
J. Infrastructure Development and Maintenance Mz Mill 1,208.8 927.2 2,805.8 3,525.7
K. Marketing and promotion Mz Mill 25.6 49.5 38.7 54.1
L. Cost of public shares Mz Mill 0.0 0.0 0.0 0.0
M. Miscellaneous Mz Mill 0.0 0.0 0.0 0.0
Mz Mill
Consumer Support Estimate
V.1 Consumer Support Estimate (CSE) -39,281.4 -16,679.0 -26,919.1 -48,108.4
N. Transfers from consumers to producers (-) Mz Mill -39,260.6 -16,655.0 -26,885.7 -48,081.1
1. Of which, standard PSE commodities Mz Mill -23,509.4 -10,042.2 -26,885.7 -29,359.3
(CSE)
O. Other consumer transfers (-) Mz Mill -20.8 -24.0 -33.4 -27.4
1. Of which, standard PSE commodities Mz Mill -12.5 -14.5 -20.2 -16.7
P. Transfers from taxpayers to consumers Mz Mill 0.0 0.0 0.0 0.0
V.2 CSE Percentage % -8.7 -3.3 -6.6 -9.7
VI.1. Total Support Estimate (TSE) Mz Mill 42,065.8 18,891.2 30,076.0 57,344.7
Estimate (TSE)
Total Support
Q. Consumer Transfers Mz Mill 39,281.4 16,679.0 26,919.1 48,108.4
A. Taxpayer transfers Mz Mill 2,805.2 2,236.2 3,190.3 9,263.7
S. Budget revenues (-) Mz Mill -20.8 -24.0 -33.4 -27.4
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ANNEX 12. Estimates of Total Support to
Agriculture and its components (US$ million)
Concept Unit 2019 2020 2021 2022
I. Total value of production (at the farm gate) USD Mill 7,078.7 7,181.7 7,494.2 8,266.1
1. Of which, standard PSE commodity share (%) % 59.9% 60.3% 60.4% 61.1%
II. Total consumption value (at the farm gate) USD Mill 7,167.4 7,189.0 6,212.4 7,745.2
1. Of which, standard PSE commodities USD Mill 4,291.9 4,334.7 3,750.0 4,729.4
III.1 Producer Support Estimate (PSE) USD Mill 637.8 242.4 414.0 755.0
A.1 Market price support USD Mill 626.6 237.9 412.4 753.0
1. Of which, standard PSE commodities USD Mill 375.2 143.4 412.4 459.8
A.2 Production-based payments USD Mill 7.8 2.2 0.1 0.2
B. Payments based on input use USD Mill 2.5 2.2 1.3 1.5
1. Based on the use of variable inputs USD Mill 1.4 1.2 1.0 1.2
Producer Support Estimate
2. Based on the use of fixed inputs USD Mill 1.1 1.0 0.3 0.4
3. Based on usage of services USD Mill 0.0 0.0 0.0 0.0
C. Support based on production A /An/ I. Production required USD Mill 0.0 0.0 0.0 0.0
1. Based on revenue USD Mill 0.0 0.0 0.0 0.0
2. Based on area or number of animals USD Mill 0.0 0.0 0.0 0.0
D. Supports based on A/AN/I Not Current. Required production USD Mill 0.0 0.0 0.0 0.0
E. Supports based on A/AN/I Not Current. Production Not
USD Mill
required 0.0 0.0 0.0 0.0
1. Variable rates USD Mill 0.0 0.0 0.0 0.0
2. Fixed Fees USD Mill 0.0 0.0 0.0 0.0
F. Supports based on non-commodity criteria USD Mill 0.0 0.0 0.0 0.0
1. Long term resource USD Mill 0.0 0.0 0.0 0.0
2. A specific non-commodity product USD Mill 0.0 0.0 0.0 0.0
3. Other non-commodity criteria USD Mill 0.0 0.0 0.0 0.0
G. Miscellaneous Support USD Mill 0.9 0.2 0.3 0.2
III.2 Estimated Percentage of Producer Support (PSE) % 9.0 3.4 5.5 9.1
IV. General Services Support Estimate (GSSE) USD Mill 33.6 27.4 47.3 143.1
General Services Support
H. Agricultural Knowledge USD Mill 11.4 12.2 2.1 85.4
Estimate (GSSE)
I. Inspection and Control USD Mill 2.5 1.2 1.6 1.6
J. Infrastructure Development and Maintenance USD Mill 19.3 13.2 43.0 55.2
K. Marketing and promotion USD Mill 0.4 0.7 0.6 0.8
L. Cost of public shares USD Mill 0.0 0.0 0.0 0.0
M. Miscellaneous USD Mill 0.0 0.0 0.0 0.0
USD Mill
Consumer Support Estimate Total Support
V.1 Consumer Support Estimate (CSE) -626.9 -238.2 -412.9 -753.4
N. Transfers from consumers to producers (-) USD Mill -626.6 -237.9 -412.4 -753.0
1. Of which, standard PSE commodities USD Mill -375.2 -143.4 -412.4 -459.8
(CSE)
O. Other consumer transfers (-) USD Mill -0.3 -0.3 -0.5 -0.4
1. Of which, standard PSE commodities USD Mill -0.2 -0.2 -0.3 -0.3
P. Transfers from taxpayers to consumers USD Mill 0.0 0.0 0.0 0.0
V.2 CSE Percentage % -8.7 -3.3 -6.6 -9.7
VI.1. Total Support Estimate (TSE) USD Mill 671.4 269.8 461.3 898.1
Estimate (TSE)
Q. Consumer Transfers USD Mill 626.9 238.2 412.9 753.4
A. Taxpayer transfers USD Mill 44.8 31.9 48.9 145.1
S. Budget revenues (-) USD Mill -0.3 -0.3 -0.5 -0.4
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ANNEX 13. Main Characteristics of Agricultural Selected Products for the Analysis.
Maize.
It is considered an essential commodity for food security in Mozambique. Historically, maize has been
grown by a large majority of farmers and occupies a significant share of total cultivated land. In 2020, land
allocation for maize was around 41% of total cultivated land, and nearly 84% of small and medium-holder
farmers have grown this cereal. The importance of maize is also mirrored in the burden share of its
byproducts in the household food basket expenditures. The latest household income survey (IOF 2022)
shows that maize meal remains the main food item in households’ food baskets, corresponding to about
21.3% of total households’ food expenditures. According to the survey data, the share of expenditures in
maize flour in total household food expenditures increases with household wealth status. That suggests
that poorer households rely primarily on production to self-consume maize.
Rice.
Despite being the second most grown cereal in the country, the total cultivated land is very marginal
compared to maize. Data from 2020 shows that the total cultivated area for rice was equivalent to just
slightly above 12% of the total cultivated area for maize and around 5% of the total cultivated area in the
country. Although still amongst the top five most essential food items in households’ income expenditure,
the average relative importance of this cereal decreased between the last two IOFs of 2019 and 2022,
dropping from 5.9 to 5.3% of households’ expenditures in food. However, the relative importance of rice
amongst poorer households shows the opposite trend. The share of rice expenditures has grown from 0.6
to 5% for the poorest quintile of the population. Despite a significant domestic consumption of rice,
imports remain increasingly high. Between 2019 and 2022, the volume of rice imports increased by nearly
63%. Over the same period, rice imports have been 11 times higher than domestic rice production.
Cassava.
Cassava (Manihot esculenta) is a crucial staple crop in Mozambique (ranked second in total cultivated
area), playing a significant role in the country's food security, economy, and rural livelihoods. Its
importance cannot be overstated, as it is a primary source of calories for a large portion of the
population, particularly in rural areas. With relatively low agronomic management demands, cassava
trade was negligible overall until around 2011. Over the last decade, there has been an increase in
demand for cassava due to new alternative industrial uses and international economic shocks. This has
boosted domestic production among smallholder farmers, who are now more integrated into the value
chain. The processing of cassava into various products, such as flour, chips, and starch, creates
opportunities for small-scale industries and entrepreneurs. This value addition enhances the economic
benefits derived from cassava farming. The value chain for this commodity also gathered special attention
in 2012 following the wheat price crisis derived from globally reduced inventories for these cereal and
other agricultural commodities. In response to that, and as an attempt to reduce dependency on wheat
imports, the government of Mozambique incentivized research on more productive varieties of cassava to
convert it into a partial substitute for wheat in the bakery industry. At the same time, casava has gained
importance in the beer industry, with Mozambique’s industry being the first worldwide to produce
cassava-based beer in 2011. Although increasing slowly in importance, cassava has significant potential
for export that has not yet been fully exploited. By developing better processing and quality control
mechanisms, Mozambique could tap into international markets, boosting foreign exchange earnings.
Nevertheless, total production trends for this cereal have been cyclical, and only in 2018 have some
structural changes in this value chain become apparent. Over 2018-2021, the average cassava
productivity grew nearly 75% compared to the past five-year period (2013-2017), despite a marginal
(close to 8.6%) decline in total cultivated land. The key areas are investing in research and development
to enhance cassava yield and resistance to pests and diseases, improving rural infrastructure to reduce
post-harvest losses and improve market access, and providing training and support to farmers on best
practices and modern agricultural techniques.
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Sweet potato.
It plays a vital role in food nutrition, particularly for rural households, due to its contribution as a
precursor for vitamin A and its other micronutrient composition and nutritional attributes. Between 2011
and 2016, the International Potato Center released at least 15 new orange-fleshed sweet potato varieties
in Mozambique. With the 2022 spikes in wheat prices due to Russia’s invasion of Ukraine, Mozambique's
government emphasized tubers such as cassava and sweet potato as substitutes for wheat. Between 2019
and 2022, the average domestic sweet potato production ranked it as the sixth most produced crop (in
tons), just behind cassava, sugar cane, maize, tomato, and banana.
Tomato.
Also labeled as the “red gold,” this is largely the most important consumed vegetable in the country. The
majority of tomato production is concentrated in the central region of Mozambique. According to the
2020 agricultural survey data, the provinces in the center accounted for over two-thirds of tomato’s total
cultivated land, and Tete province alone accounted for about 38%. Although production occurs
throughout the year, during the warm and rainy season, the domestic supply of vegetables is reduced in
Mozambique. To date, Mozambique remains a net importer of this vegetable as well. Between 2019 and
2021, data from Trading Economics indicate that Mozambique’s average imports of Tomato (fresh and
chilled) from South Africa were valued at $USD 1.4 million.
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ANNEX 14. Estimates of Producer Support Estimate for products by components
(million Meticais)
Cassava Units 2019 2020 2021 2022
I. Production Level 000t 6,019.20 6,026.00 6,218.14 6,466.86
II. Production value (farm gate) MZ Mill 134,830.10 84,364.00 ######## 147,121.00
III. Estimate of producer support (PSE) MZ Mill 14,445.06 85.48 13,924.23 26,133.39
A. Support based on crop production (output) MZ Mill 14,339.25 - 13,876.90 26,081.91
1. Market price support MZ Mill 14,101.08 - 13,876.90 26,081.91
2. Production based support MZ Mill 238.16 - - -
B. Payments based on input use MZ Mill 77.54 79.59 39.03 45.99
1. Based on variable income MZ Mill 43.10 43.18 29.88 34.54
2. Based on investments MZ Mill 33.29 34.89 9.15 11.45
3. Based on services MZ Mill 1.15 1.52 - -
C. Support based on production level MZ Mill - - - -
1. Based on income MZ Mill - - - -
2. Based on livestock size MZ Mill - - - -
D. Support based on required production MZ Mill - - - -
E. Support based on not required production MZ Mill - - - -
1. Variable fees MZ Mill - - - -
2. Fixed fees MZ Mill - - - -
F. Support based on criteria not related to crops MZ Mill - - - -
1. Long term resources MZ Mill - - - -
2. Other products - not specific commodities MZ Mill - - - -
3. Other criteria not related to commodities MZ Mill - - - -
G. Various supports MZ Mill 28.27 5.89 8.30 5.49
IV. PSE by unit Mz/t 2.4 0.0 2.2 4.0
V. PSE-percentage % 10.7 0.1 6.5 17.8
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TOMATOES UNITS 2019 2020 2021 2022
I. Production Level 000t 992.42 1,207.28 1,431.66 1,599.05
II. Production value (farm gate) MZ Mill 63,514.91 72,678.41 ######## ########
III. Estimate of producer support (PSE) MZ Mill 172.98 96.90 9,090.45 28.75
A. Support based on crop production (output) MZ Mill 119.77 62.98 9,068.92 5.92
1. Market price support MZ Mill - - 9,067.08 -
2. Production based support MZ Mill 119.77 62.98 1.84 5.92
B. Payments based on input use MZ Mill 39.00 31.59 17.75 20.40
1. Based on variable income MZ Mill 21.68 17.14 13.59 15.32
2. Based on investments MZ Mill 16.74 13.85 4.16 5.08
3. Based on services MZ Mill 0.58 0.60 - -
C. Support based on production level MZ Mill - - - -
1. Based on income MZ Mill - - - -
2. Based on livestock size MZ Mill - - - -
D. Support based on required production MZ Mill - - - -
E. Support based on not required production MZ Mill - - - -
1. Variable fees MZ Mill - - - -
2. Fixed fees MZ Mill - - - -
F. Support based on criteria not related to cropsMZ Mill - - - -
1. Long term resources MZ Mill - - - -
2. Other products - not specific commodities MZ Mill - - - -
3. Other criteria not related to commodities MZ Mill - - - -
G. Various supports MZ Mill 14.22 2.34 3.78 2.44
IV. PSE by unit Mz/t 0.17 0.08 6.35 0.02
V. PSE-percentage % 0.27 0.13 8.03 0.02
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MAIZE UNITS 2019 2020 2021 2022
I. Production Level 000t 1451.7 1632.3 1824.3 1952.0
II. Production value (farm gate) MZ Mill 29033.7 43936.6 48191.4 42292.9
III. Estimate of producer support (PSE) MZ Mill 115.3 1000.3 220.7 33.0
A. Support based on crop production (output) MZ Mill 79.8 968.1 196.0 6.8
1. Market price support MZ Mill 0.0 908.3 193.9 0.0
2. Production based support MZ Mill 79.8 59.7 2.1 6.8
B. Payments based on input use MZ Mill 26.0 30.0 20.4 23.4
1. Based on variable income MZ Mill 14.5 16.3 15.6 17.6
2. Based on investments MZ Mill 11.2 13.1 4.8 5.8
3. Based on services MZ Mill 0.4 0.6 0.0 0.0
C. Support based on production level MZ Mill 0.0 0.0 0.0 0.0
1. Based on income MZ Mill 0.0 0.0 0.0 0.0
2. Based on livestock size MZ Mill 0.0 0.0 0.0 0.0
D. Support based on required production MZ Mill 0.0 0.0 0.0 0.0
E. Support based on not required production MZ Mill 0.0 0.0 0.0 0.0
1. Variable fees MZ Mill 0.0 0.0 0.0 0.0
2. Fixed fees MZ Mill 0.0 0.0 0.0 0.0
F. Support based on criteria not related to crops MZ Mill 0.0 0.0 0.0 0.0
1. Long term resources MZ Mill 0.0 0.0 0.0 0.0
2. Other products - not specific commodities MZ Mill 0.0 0.0 0.0 0.0
3. Other criteria not related to commodities MZ Mill 0.0 0.0 0.0 0.0
G. Various supports MZ Mill 9.5 2.2 4.3 2.8
IV. PSE by unit Mz/t 0.1 0.6 0.1 0.0
V. PSE-percentage % 0.4 2.3 0.5 0.1
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Sweet Potatoes UNITS 2019 2020 2021 2022
I. Production Level 000t 504.8 448.6 495.4 510.2
II. Production value (farm gate) MZ Mill 11812.7 14221.7 13771.5 14439.7
III. Estimate of producer support (PSE) MZ Mill 43.3 32.5 6.6 8.1
A. Support based on crop production (output) MZ Mill 30.0 21.1 0.5 1.7
1. Market price support MZ Mill 0.0 0.0 0.0 0.0
2. Production based support MZ Mill 30.0 21.1 0.5 1.7
B. Payments based on input use MZ Mill 9.8 10.6 5.0 5.8
1. Based on variable income MZ Mill 5.4 5.7 3.8 4.3
2. Based on investments MZ Mill 4.2 4.6 1.2 1.4
3. Based on services MZ Mill 0.1 0.2 0.0 0.0
C. Support based on production level MZ Mill 0.0 0.0 0.0 0.0
1. Based on income MZ Mill 0.0 0.0 0.0 0.0
2. Based on livestock size MZ Mill 0.0 0.0 0.0 0.0
D. Support based on required production MZ Mill 0.0 0.0 0.0 0.0
E. Support based on not required production MZ Mill 0.0 0.0 0.0 0.0
1. Variable fees MZ Mill 0.0 0.0 0.0 0.0
2. Fixed fees MZ Mill 0.0 0.0 0.0 0.0
F. Support based on criteria not related to crops MZ Mill 0.0 0.0 0.0 0.0
1. Long term resources MZ Mill 0.0 0.0 0.0 0.0
2. Other products - not specific commodities MZ Mill 0.0 0.0 0.0 0.0
3. Other criteria not related to commodities MZ Mill 0.0 0.0 0.0 0.0
G. Various supports MZ Mill 3.6 0.8 1.1 0.7
IV. PSE by unit Mz/t 0.1 0.1 0.0 0.0
V. PSE-percentage % 0.4 0.2 0.0 0.1
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RICE UNITS 2019 2020 2021 2022
I. Production Level 000t 341.0 376.0 390.0 365.0
II. Production value (farm gate) MZ Mill 15345.0 15980.0 10567.4 9708.8
III. Estimate of producer support (PSE) MZ Mill 9432.4 9146.5 3751.4 3282.1
A. Support based on crop production (output) MZ Mill 9426.2 9143.0 3748.2 3278.5
1. Market price support MZ Mill 9408.3 9133.9 3747.8 3277.4
2. Production based support MZ Mill 17.9 9.1 0.3 1.1
B. Payments based on input use MZ Mill 4.1 3.2 2.6 3.1
1. Based on variable income MZ Mill 1.5 1.1 1.8 2.2
2. Based on investments MZ Mill 2.5 2.0 0.8 0.9
3. Based on services MZ Mill 0.1 0.1 0.0 0.0
C. Support based on production level MZ Mill 0.0 0.0 0.0 0.0
1. Based on income MZ Mill 0.0 0.0 0.0 0.0
2. Based on livestock size MZ Mill 0.0 0.0 0.0 0.0
D. Support based on required production MZ Mill 0.0 0.0 0.0 0.0
E. Support based on not required production MZ Mill 0.0 0.0 0.0 0.0
1. Variable fees MZ Mill 0.0 0.0 0.0 0.0
2. Fixed fees MZ Mill 0.0 0.0 0.0 0.0
MZ Mill
F. Support based on criteria not related to crops 0.0 0.0 0.0 0.0
1. Long term resources MZ Mill 0.0 0.0 0.0 0.0
MZ Mill
2. Other products - not specific commodities 0.0 0.0 0.0 0.0
MZ Mill
3. Other criteria not related to commodities 0.0 0.0 0.0 0.0
G. Various supports MZ Mill 2.1 0.3 0.7 0.5
IV. PSE by unit Mz/t 27.7 24.3 9.6 9.0
V. PSE-percentage % 61.4 57.2 35.5 33.8
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ANNEX 15. Mozambique, Tariff Profile (WTO)
Part A.1 Tariffs and imports: Summary and duty ranges
Summary Total Ag Non-Ag WTO member since 1995
Simple average final bound 97.7 100.0 26.0 Binding coverage: Total 14.3
MFN applied Non-Ag 0.5
Simple average 2022 10.3 14.0 9.7 Ag: Tariff quotas (in %) 0
Trade weighted average 2022 7.2 8.2 6.9 Ag: Special safeguards (in % ) 0
Imports in billion US$ 2021 8.6 1.7 6.9
Duty-free 0 <= 5 5 <= 10 10 <= 15 15 <= 25 25 <= 50 50 <= 100 > 100 NAV
Frequency distribution
Tariff lines and import values (in %) in %
Agricultural products
Final bound 0 0 0 0 0 0 99.9 0 0
MFN applied 2022 6.3 16.3 14.7 0 62.7 0 0 0 0
Imports 2021 4.8 41.3 27.4 0 26.6 0 0 0 0
Non-agricultural products
Final bound 0 0.3 0 0.1 0 0 0.1 0 0
MFN applied 2022 3.4 33.6 32.5 0 30.6 0 0 0 0
Imports 2021 11.5 46.0 29.4 0 13.1 0 0 0 0
Part A.2 Tariffs and imports by product groups
Final bound duties MFN applied duties Imports
Product groups AVG Duty-free Max Binding AVG Duty-free Max Share Duty-free
in % in % in % in % in %
Animal products 100.0 0 100 100 17.7 6.8 20 1.0 7.1
Dairy products 100.0 0 100 100 17.0 2.4 20 0.5 0.1
Fruit, vegetables, plants 100.0 0 100 100 17.3 1.8 20 0.9 9.2
Coffee, tea 100.0 0 100 100 18.2 0 20 0.2 0
Cereals & preparations 100.0 0 100 100 12.4 11.0 20 10.0 3.7
Oilseeds, fats & oils 100.0 0 100 98.8 9.8 13.3 20 5.7 5.6
Sugars and confectionery 100.0 0 100 100 9.0 0 20 0.1 0
Beverages & tobacco 100.0 0 100 100 18.3 0 20 1.1 0
Cotton 100.0 0 100 100 2.5 0 3 0.0 0
Other agricultural products 100.0 0 100 100 7.9 10.4 20 0.3 39.1
Fish & fish products 100.0 0 100 0.8 19.8 0.7 20 1.2 1.7
Minerals & metals - - - 0 7.5 0.2 20 16.4 3.4
Petroleum - - - 0 6.1 0 8 12.2 0
Chemicals 100.0 0 100 0.3 4.8 11.3 20 14.5 35.1
Wood, paper, etc. - - - 0 9.2 2.3 20 2.6 8.6
Textiles - - - 0 14.9 0.5 20 2.4 8.2
Clothing - - - 0 20.0 0 20 0.5 0
Leather, footwear, etc. - - - 0 11.0 1.9 20 1.5 8.6
Non-electrical machinery 6.6 0 15 3.6 5.9 5.2 20 9.6 4.5
Electrical machinery - - - 0 8.9 0 20 6.0 0
Transport equipment - - - 0 8.2 0.8 20 8.6 0.0
Manufactures, n.e.s. - - - 0 12.6 2.0 20 4.7 54.3
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ANNEX 16. Average yields for selected products and countries 2000-2020
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ANNEX 17. Programs and projects executed by the Government considered for PSE estimation.
Estimate of Support (PSE)
(Million Meticais)
Description 2019 2020 2021 2022
Estimate of Producer Support (PSE) 187.4 135.1 32.1 39.9
A. Support based on outputs 129.7 87.6 2.5 8.1
Provincial Government 0.0 9.2 2.5 8.1
Production Support for Potatoes 0.0 2.4 0.1 0.0
Production Intensification of food crops 0.0 5.1 0.0 1.9
Production Intensification of horticulture crops 0.0 0.0 0.5 4.5
Production diversification of food crops (maize, rice, cassava, beans, horticulture) 0.0 0.0 1.6 0.0
Expansion of Agricultural production 0.0 0.0 0.0 1.5
Production diversification of various fruit seedlings 0.0 0.0 0.0 0.1
Horticultural Production 0.0 1.5 0.0 0.0
Fruit seedlings Production 0.0 0.0 0.3 0.0
Relaunching of potatoes-reno production 0.0 0.3 0.0 0.0
MADER 129.7 78.0 0.0 0.0
Support to family farming production 113.1 0.0 0.0 0.0
Production Support for Reno Potatoes 3.2 0.0 0.0 0.0
Production Intensification of horticultural food 9.7 0.7 0.0 0.0
Horticultural production 2.0 0.3 0.0 0.0
Value chain development Project - Maputo and Limpopo Corridors (PROSUL) 0.0 77.0 0.0 0.0
Resizing of small irrigation for promotion of horticultural production 1.7 0.0 0.0 0.0
Ministry of Industry and Commerce 0.0 0.3 0.0 0.0
Agricultural marketing 0.0 0.3 0.0 0.0
B. Support based on inputs 42.3 44.3 24.5 28.5
Seeds 12.7 12.8 5.5 4.8
Provincial Governments 0.0 4.4 5.5 4.8
Supply of inputs and seed production 0.0 0.0 0.0 4.5
Supply of inputs and seed production 0.0 0.0 5.0 0.0
Acquisition of improved seed for the 2019/2020 agricultural campaign 0.0 0.8 0.0 0.0
Seed acquisition and distribution 0.0 0.0 0.0 0.3
Acquisition and distribution of improved seeds 0.0 0.0 0.5 0.0
Production and multiplication of corn and bean seedss 0.0 3.0 0.0 0.0
Local seed production project 0.0 0.6 0.0 0.0
Ministry of State Administration 0.0 2.0 0.0 0.0
Acquisition of improved seed for the 2019/2020 agricultural campaign 0.0 2.0 0.0 0.0
Ministry of Agriculture and Rural Development 12.7 6.5 0.0 0.0
Acquisition of 15 tons of various seeds, including vegetables 1.4 0.2 0.0 0.0
Acquisition of improved seed for the 2018/2019 agricultural season 3.0 0.0 0.0 0.0
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Estimate of Support (PSE)
(Million Meticais)
Description 2019 2020 2021 2022
Acquisition of improved seed for the 2019/2020 agricultural campaign 0.0 0.5 0.0 0.0
Production of basic seed of food crops - sweet potato vines, cassava cuttings and fruit
plants 0.0 2.6 0.0 0.0
Basic seed production of improved varieties 0.0 1.2 0.0 0.0
Seed production of various crops grown in the region 0.5 0.4 0.0 0.0
Pre-basic and basic seed production and installation of a multiple nursery for seedling
production 0.4 0.4 0.0 0.0
Production and multiplication of corn and bean seeds 0.0 0.7 0.0 0.0
Production and multiplication of Matuba corn and bean seeds 4.5 0.0 0.0 0.0
Improved local seed production 2.1 0.3 0.0 0.0
Local seed production project 0.8 0.1 0.0 0.0
B 2. Based on fixed capital formation 18.1 19.3 5.7 6.9
Provincial Government 0.0 5.5 5.7 6.3
Acquisition of agricultural equipment 0.0 0.1 0.0 0.0
Acquisition of irrigation equipment and instruments 0.0 0.6 0.0 0.0
Acquisition of hydromechanical equipment 0.0 0.0 0.5 0.0
Acquisition of hydromechanical equipment for agricultural production 0.0 1.2 0.0 0.0
Acquisition of motor pumps 0.0 0.7 1.2 0.0
Acquisition and provision of hydromechanical equipment for producers 0.0 0.0 1.7 0.0
Construction of a greenhouse with an irrigation system 0.0 0.0 0.0 0.0
Construction of acaricide tanks 0.0 0.0 0.0 6.3
Establishment of greenhouses for vegetable production 0.0 0.4 0.0 0.0
Intensification of food crop production 0.0 0.0 2.3 0.0
Intensification and diversification of crops 0.0 2.5 0.0 0.0
Ministry of State Administration 0.0 10.5 0.0 0.0
Greenhouse construction 0.0 1.1 0.0 0.0
Intensification and diversification of crops 0.0 9.3 0.0 0.0
Ministry of Agriculture and Rural Development 18.1 3.3 0.0 0.0
Acquisition of agricultural equipment 1.7 0.0 0.0 0.0
Acquisition of irrigation equipment and instruments 2.0 0.0 0.0 0.0
Acquisition of hydromechanical equipment for agricultural production 0.0 0.2 0.0 0.0
Acquisition of motor pumps 1.0 0.0 0.0 0.0
Agricultural Irrigation Equipment for Agricultural Production 2.3 0.0 0.0 0.0
Intensification and diversification of grains 0.8 1.4 0.0 0.0
Intensification and diversification of crops 10.3 1.7 0.0 0.0
Ministry of Industry and Commerce 0.0 0.0 0.0 0.6
Acquisition of machines to boost the tomato, fruit, and peanut derivatives value chains
and training on handling 0.0 0.0 0.0 0.6
B 3. On-farm services 0.7 1.2 0.3 0.7
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Estimate of Support (PSE)
(Million Meticais)
Description 2019 2020 2021 2022
Provincial Government 0.0 0.0 0.3 0.7
Marketing Project 0.0 0.0 0.0 0.7
Promotion of good food preparation and practices to increase nutritional value 0.0 0.0 0.3 0.0
Ministry of Agriculture and Rural Development 0.6 0.8 0.0 0.0
Generation of high-productivity food crop varieties 0.0 0.4 0.0 0.0
Generation of varieties of food crops with high productivity to guarantee food security in
the Northeastern Region 0.3 0.0 0.0 0.0
Conducting training and learning events in the fruit value chain 0.3 0.4 0.0 0.0
Ministry of Land and Environment 0.1 0.4 0.0 0.0
Support for production, training, and learning events for technicians in value-chain
facilities 0.0 0.4 0.0 0.0
Training and learning events to support production 0.1 0.0 0.0 0.0
B. 1. Based on the use of variable inputs 10.8 11.0 13.1 16.0
Provincial Government 0.0 7.3 13.1 16.0
Supply and availability of agricultural inputs 0.0 6.5 6.3 7.9
Acquisition of agricultural/agrarian inputs 0.0 0.8 4.2 8.2
Acquisition of various improved inputs for the agricultural season 0.0 0.0 2.5 0.0
Implementation of the fruit growing program 0.0 0.0 0.1 0.0
Ministry of State Administration 0.0 2.6 0.0 0.0
Supply and availability of agricultural inputs 0.0 1.0 0.0 0.0
Acquisition of agricultural/agrarian inputs 0.0 1.6 0.0 0.0
Ministry of Agriculture and Rural Development 10.8 1.1 0.0 0.0
Aprovisionamento e disponibilidade de insumos agrários 5.8 0.9 0.0 0.0
Aquisição de insumos agrícolas / agrários 4.2 0.2 0.0 0.0
Project to implement fairs and agricultural inputs 0.8 0.0 0.0 0.0
G. Others 15.4 3.2 5.1 3.3
Provincial Directorate of Land, Environment and Rural Development 0.1 0.0 0.0 0.0
Monitoring and inspection of territorial planning plans in the districts of Majune,
Mavago, Lago and Mecanhelas 0.1 0.0 0.0 0.0
Delegation of the National Institute for Disaster Management 0.1 0.3 0.0 0.0
Provincial Government 0.0 0.0 2.2 2.4
Planning, monitoring, and evaluation 0.0 0.0 2.2 2.4
Ministry of Agriculture and Rural Development 0.3 0.1 0.3 0.9
Institutional Support 0.0 0.0 0.3 0.9
Early warning system 0.0 0.1 0.0 0.0
Establishment of nurseries for various fruit plants 0.2 0.0 0.0 0.0
Carrying out agricultural campaign monitoring (2018/2019) 0.1 0.0 0.0 0.0
Ministry of Land and Environment 14.6 2.3 2.6 0.0
Delimitation of community lands and issuance of DUATs 4.8 0.0 0.0 0.0
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Estimate of Support (PSE)
(Million Meticais)
Description 2019 2020 2021 2022
Community development, localities, forestry, and wildlife exploration 4.3 0.0 0.0 0.0
Land use planning 0.8 0.0 0.0 0.0
Territorial planning and land use planning 2.1 0.0 0.0 0.0
Territorial planning 1.8 2.3 1.8 0.0
Promotion of planning and territorial ordering 0.8 0.0 0.0 0.0
Plant production nursery 0.0 0.0 0.8 0.0
Ministry of Public Works, Housing and Water Resources 0.3 0.5 0.0 0.0
Zambezi Regional Water Administration 0.3 0.0 0.0 0.0
Drought and flood management 0.0 0.5 0.0 0.0
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ANNEX 18. Mozambique Poverty Assessment (June 20231) and the Mozambique Country Climate
and Development Report (CCDR, 2023).
Box 18.1. POVERTY REDUCTION SETBACK IN TIMES OF COMPOUNDING SHOCKS - Mozambique Poverty
Assessment (World Bank, June 2023).
Box XX: Country Climate and Development Report for Mozambique, World Bank, June 2023.
Context.
Context
The report highlights that Mozambique's poverty reduction efforts were significantly set back due to a series of
Mozambique is amongst the countries that are most vulnerable globally to the impact of climate change and
compounding shocks, including the COVID-19 pandemic, natural disasters (cyclones, floods, and droughts), and
natural hazards. This increasingly undermines growth and affect livelihoods, impacting on poverty and
economic downturns. These events exacerbated existing vulnerabilities and reversed some of the progress
exacerbating development challenges. With tight fiscal space, Mozambique needs to prioritize policies and
made in poverty alleviation from 2015 to 2020. The increase in poverty in rural areas also appears to be linked
investments that enhance the country’s resilience. These key interventions need to be prioritized to render
to the overall demand shock associated with the economic slowdown, slowing farm and off-farm incomes in
Mozambique more resilient to climate shocks, while reducing poverty and supporting the most vulnerable.
the rural space. Rural poverty, at 72.1 percent, is 26.7 percentage points higher than urban poverty (45.4
percent). While agriculture employs a large part of the population (72 percent), its contribution to GDP is only
PRIORITY 1: Adopt Economy-wide Measures to Enhance Adaptative Capacity.
25 percent, so even if regular environmental impacts may not appear dramatic in terms of overall economic
a) Consolidate the legal and institutional framework, strengthen institutional capacity to steer climate action,
output, they do affect people’s livelihoods deeply. Furthermore, the high degree of uncertainty created by
and mobilize additional sources of financing.
erratic rainfall disincentivizes agrarian households from investing in the sunk costs (e.g., seeds and tools)
b) Mainstream climate risk into public expenditure planning to ensure the efficiency of capital expenditure
needed to improve their agricultural productivity.
and foster sustainable growth.
c) Continue strengthening institutions for disaster preparedness.
Policy Considerations.
d) Enhance the role of the private sector to accelerate climate-smart investments in key sectors.
Given the importance of shocks in increasing poverty in Mozambique, the country needs to strengthen its
focus on resilience
PRIORITY by strengthening
2: Prioritize adaptation
Critical Infrastructure and impact and
Development mitigation measures to reduce vulnerability. The
Management.
key areas of recommendation are the following.
a) Improve transport infrastructure to reduce the impact of climate change risks, while boosting development
in rural poor regions.
1.
b) Addressing vulnerability
Build climate-smart to
social environmental
infrastructure forshocks
human . capital
Mozambique’s high exposure and vulnerability to
development.
c) multidimensional shocks requires further strengthening of the
Improve water resource management to address high spatial and temporal country’s policy framework
water resource for response,
variability.
prevention, and resilience. Mozambique needs to fully mainstream climate change into its national
development
PRIORITY strategy.
3: Protect means building
This Vulnerable
the Most whilea more resilient
Promoting society
Green, while enabling
Resilient the economy
and Inclusive Growth to adjust to
the challenges and opportunities of global decarbonization. Agriculture, the primary source
a) Promote climate smart agriculture (CSA) and human capital development for structural transformation of income for
to
85 percent of rural households, is highly exposed
reduce impact on those most exposed to climate change. to various forms of extreme weather, and households
b) often cope
Promote byintegrated
the depleting their assets – including
management reduction
of land and of livestock
ocean resources to and consumption
build and
terrestrial and takingresilience,
children
coastal
out of school.
while unlocking green and blue growth potential.
c) Support the most vulnerable households through adaptive social protection programs.
2. Addressing macroeconomic shocks and structural challenges. This includes (a) Better Human Capital
requiring
results,4:
PRIORITY Leveragereforming the education
Mozambique’s Energy financing framework
Wealth to ensure that it is predominantly based on
and Mineral
spending per student; and (b) Expanding infrastructure and
a) Increase access to energy and foster clean energy solutions. narrowing gaps. The recommendations include
promoting climate-smart agriculture and improving early
b) Harness natural gas reserves while managing lock-in risks. warning systems and disaster response
mechanisms.
c) Plan for a just transition from coal mining, and harness mineral wealth in a sustainable way.
3. Addressing pandemics. To maximize impacts, it is critical to ensure efficient coverage of social protection
programs. The report recommends fiscal policy adjustments to better support poverty reduction. This
involves improving tax collection, ensuring efficient public spending, and redirecting resources towards
high-impact social and economic programs.
These policy recommendations may help Mozambique to better navigate the challenges posed by
compounding shocks and make more resilient and sustainable progress in reducing poverty. The emphasis is
on building systems that can absorb shocks, protect the most vulnerable, and promote inclusive and equitable
growth.
1 Poverty Reduction Setback in Times of Compounding Shocks –Mozambique Poverty Assessment. World Bank, June 2023.
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Box 18.2: Country Climate and Development Report for Mozambique, World Bank, June 2023.
Context
Mozambique is amongst the countries that are most vulnerable globally to the impact of climate change and
natural hazards. This increasingly undermines growth and affect livelihoods, impacting on poverty and
exacerbating development challenges. With tight fiscal space, Mozambique needs to prioritize policies and
investments that enhance the country’s resilience. These key interventions need to be prioritized to render
Mozambique more resilient to climate shocks, while reducing poverty and supporting the most vulnerable.
PRIORITY 1: Adopt Economy-wide Measures to Enhance Adaptative Capacity.
(a) Consolidate the legal and institutional framework, strengthen institutional capacity to steer climate action,
and mobilize additional sources of financing.
(b) Mainstream climate risk into public expenditure planning to ensure the efficiency of capital expenditure and
foster sustainable growth.
(c) Continue strengthening institutions for disaster preparedness.
(d) Enhance the role of the private sector to accelerate climate-smart investments in key sectors.
PRIORITY 2: Prioritize Critical Infrastructure Development and Management.
(a) Improve transport infrastructure to reduce the impact of climate change risks, while boosting development
in rural poor regions.
(b) Build climate-smart social infrastructure for human capital development.
(c) Improve water resource management to address high spatial and temporal water resource variability.
PRIORITY 3: Protect the Most Vulnerable while Promoting Green, Resilient and Inclusive Growth
(a) Promote climate smart agriculture (CSA) and human capital development for structural transformation to
reduce impact on those most exposed to climate change.
(b) Promote the integrated management of land and ocean resources to build terrestrial and coastal resilience,
while unlocking green and blue growth potential.
(c) Support the most vulnerable households through adaptive social protection programs.
PRIORITY 4: Leverage Mozambique’s Energy and Mineral Wealth
(a) Increase access to energy and foster clean energy solutions.
(b) Harness natural gas reserves while managing lock-in risks.
(c) Plan for a just transition from coal mining, and harness mineral wealth in a sustainable way.
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