In 2023, ** percent of the population in Mozambique lived in extreme poverty, with the poverty threshold at **** U.S. dollars a day. That corresponded to roughly ** million people in absolute numbers. By 2025, the extreme poverty rate is projected to decrease to ** percent.

Yearly (annual) dataset of the Mozambique Poverty Rate, including historical data, latest releases, and long-term trends from 1996-12-31 to 2019-12-31. Available for free download in CSV format.

Mozambique sub-national aggregates, % of population under sever poverty conditions (K > 50%). https://ophi.org.uk/wp-content/uploads/indicators.png" alt="Indicators"> For more, visit ophi.org.uk

Mozambique MZ: Poverty Gap at National Poverty Lines: % data was reported at 21.200 % in 2008. This records an increase from the previous number of 20.500 % for 2002. Mozambique MZ: Poverty Gap at National Poverty Lines: % data is updated yearly, averaging 21.200 % from Dec 1996 (Median) to 2008, with 3 observations. The data reached an all-time high of 29.300 % in 1996 and a record low of 20.500 % in 2002. Mozambique MZ: Poverty Gap at National Poverty Lines: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mozambique – Table MZ.World Bank: Poverty. Poverty gap at national poverty lines is the mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Historical dataset showing Mozambique poverty rate by year from 1996 to 2019.

Poverty ratio at $3.2 a day of Mozambique dropped by 7.31% from 88.9 % in 2008 to 82.4 % in 2014. Since the 0.99% upward trend in 2002, poverty ratio at $3.2 a day slumped by 10.63% in 2014. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Mozambique MZ: Income Share Held by Lowest 20% data was reported at 4.200 % in 2014. This records a decrease from the previous number of 5.200 % for 2008. Mozambique MZ: Income Share Held by Lowest 20% data is updated yearly, averaging 4.700 % from Dec 1996 (Median) to 2014, with 4 observations. The data reached an all-time high of 5.400 % in 2002 and a record low of 4.000 % in 1996. Mozambique MZ: Income Share Held by Lowest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mozambique – Table MZ.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Mozambique MZ: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 1.560 % in 2014. Mozambique MZ: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 1.560 % from Dec 2014 (Median) to 2014, with 1 observations. Mozambique MZ: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mozambique – Table MZ.World Bank: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

Mozambique MZ: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 49.600 % in 2008. This records a decrease from the previous number of 51.500 % for 2002. Mozambique MZ: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 51.500 % from Dec 1996 (Median) to 2008, with 3 observations. The data reached an all-time high of 62.000 % in 1996 and a record low of 49.600 % in 2008. Mozambique MZ: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mozambique – Table MZ.World Bank: Poverty. Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

46.1 (%) in 2014. National poverty headcount ratio is the percentage of the population living below the national poverty lines. National estimates are based on population-weighted subgroup estimates from household surveys.

This assessment, reflecting poverty's many dimensions in Mozambique, combines multiple disciplines and diagnostic tools to explore poverty. It combines quantitative and qualitative approaches to understand trends in poverty and the dynamics that shape them. The objective is to support the development and implementation of proper policies that really work by taking poverty's multiple dimensions into account. The first analysis is using multiple quantitative and qualitative indicators on levels and changes in the opportunities and outcomes for households and communities in Mozambique since 1997. The main economic developments, analyzes how changes at the macro and meson level affected household livelihoods, and how households, especially poor households, responded. Agriculture and the private sector, especially labor-intensive activities, many of them small and informal. It can build human capital by improving access to basic public services, especially for the poor, and by increasing the value for money in public spending. And it can improve governance and accountability by getting government closer to its citizens. To achieve these goals, the government will need to increase the value for money in its spending on public services. It will also need to target services for the rural poor and enlist poor communities in identifying needs and delivering those services. And it will need to put in place good tracking systems to link program outputs to targets and outcomes, using frequent high-quality household surveys. Mozambique was an extremely poor country at the time of its elections in 1994, with decimated infrastructure, a weak economy, and fragile institutions. Since then, it has been astonishingly successful at restoring growth and improving welfare. Sustained growth -- driven primarily by investments in physical capital -- reduced monetary poverty from 69 percent of the populace in 1997 to 54 percent in 2003 and the depth and severity of no income poverty even more. Broad-based, labor-intensive private-sector growth was efficient in reducing poverty until 2003 because it was equally distributed. At the same time, investments in social and economic infrastructure extended access to public services, reduced welfare inequalities, and supported the livelihoods of the average Mozambican.

Mozambique has staged a dramatic recovery from the damage of the civil war, improving infrastructure nearly to pre-war levels; reducing poverty from 69 to 54 percent; growing the economy by 8 percent annually between 1996 and 2003; expanding the agricultural, tourism construction and manufacturing sectors; and attracting mega-projects in aluminum smelting, natural gas, and titanium mining, and this tripling exports. Another factor which was a precondition for all of the above is the fact that the country was successful in bringing about reconciliation, ending the civil war, and in managing potential conflicts since that time. Mozambique has just had its third general and presidential election. Nevertheless the country remains poor, infrastructure is inadequate, there are serious unmet education and health needs, and poverty rates remain high. This Memorandum examines the growth-poverty linkage, using a wide variety of data sources, including the recently completed national household survey (2002/3). It has sought to understand the sources of growth in the recent past, to evaluate the prospects for growth in the next decade, to examine the likely implications for poverty, and to outline the policies that will be needed to achieve further growth and poverty reduction. The Country Economic Memorandum also examines the relevance of natural resource management to growth and poverty objectives.

Mozambique MZ: Poverty Gap at National Poverty Lines: Urban: % data was reported at 19.100 % in 2008. This records a decrease from the previous number of 19.700 % for 2002. Mozambique MZ: Poverty Gap at National Poverty Lines: Urban: % data is updated yearly, averaging 19.700 % from Dec 1996 (Median) to 2008, with 3 observations. The data reached an all-time high of 26.700 % in 1996 and a record low of 19.100 % in 2008. Mozambique MZ: Poverty Gap at National Poverty Lines: Urban: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mozambique – Table MZ.World Bank: Poverty. Urban poverty gap at national poverty lines is the urban population's mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

As of May 2021, ***** percent of the population in Maputo, province of Mozambique, lacked access to sufficient food for consumption. The region had the largest prevalence of food insecurity in the country. The situation was also critical in Inhambane, with ***** percent of the province's population affected. Overall, Mozambique counted *** million people facing insufficient food consumption in the same period.

In 2012, Madagascar ranked first by number of people living on less than 2.15 U.S. dollars a day among the 51 countries presented in the ranking. Madagascar's number of people amounted to ***** percent, while the Congo (Congo Kinshasa) (2020) and Mozambique (2019), the second and third countries, had records amounting to ***** percent and ***** percent, respectively.

In 2025, ** percent of the population in Mozambique lived in extreme poverty (with less than **** U.S. dollars a day), the highest score recorded in the Southern African region. Conversely, Botswana registered the lowest share, with ** percent of its population living in destitute conditions.

Income share held by lowest 10% of Mozambique surged by 6.25% from 1.60 % in 2014 to 1.70 % in 2019. Since the 9.09% slump in 2008, income share held by lowest 10% plummeted by 15.00% in 2019. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.

Abstract

Despite strong and sustained economic growth over the last two decades, poverty in Mozambique has remained high, particularly in rural areas. With over 80% of the population deriving its livelihood primarily from agricultural activities, the rural development and structural transformation agenda is central to poverty alleviation in Mozambique. In this context the European Union Delegation to Mozambique launched the PROMOVE Agribiz program, which aims to improve food security and the resilience of smallholder producers as well as boost rural competitiveness. The program is implemented across 10 districts in the rural areas of Nampula and Zambezia provinces.

As part of the PROMOVE Agribiz program, FAO will roll-out its FFS and eVoucher interventions to increase access to extension services with the aim of increasing local awareness of sustainable land management practices and boost access and adoption of modern agricultural inputs. To shed light on different constraints to adoption, FAO and DIME coordinated the FFS and eVoucher intervention roll-out in such a way that it allows for the identification of the impact of the individual interventions as well as their complementarities, providing for a richer understanding of constraints to adoption more broadly. Intervention impacts are identified by comparing communities and households that are randomized into one of four groups: i) Receiving an FFS, ii) receiving eVouchers, iii) receiving both, and iv) receiving neither – the control group. The complete experimental sample includes 388 communities and 4630 households.

Treatment assignment variables are embargoed until the study is complete.

Geographic coverage

The data collection took place in the Mozambican provinces of Nampula and Zambezia.

Analysis unit

Household, individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling procedure for the program impact evaluation includes four steps:

Step 1 – Identification of possible intervention communities. At the beginning of the program, the research team asked FAO to provide a list of extension agents (EAs) who would be responsible for identifying communities for intervention, and established the catchment for each EA. From this list, the research team assigned each EA, by random lottery, a pipeline of communities in which to establish a FFS or register farmers for eVouchers. Working with a total of 102 EAs, the team identified 799 potential intervention communities.

Step 2 – Community level randomization. From the long-list of communities in each EA’s catchment, four communities were randomly assigned to compose the experimental sample. Each of these communities was then assigned to one of the following four groups receiving either: 1. Farmer Field School 2. eVoucher 3. Farmer Field School + eVoucher 4. Control group At that time, only 56 of the 97 EAs had all 4 experimental sample communities within range of an agrodealer participating in the FAO eVoucher program. In areas where there is no eVoucher coverage, the EA is assigned two FFS and two control communities. In total, the evaluation sample includes 388 communities. 15 EAs were later dropped from the IE due to performance issues.

Step 3 – Within community identification of FFS interested participants. Participation in the FFS is voluntary and based on farmers expressing interest. This means that farmers who choose to participate are likely not representative of the average farmer in the community. To allow for identification of likely FFS participants in a similar way in both the FFS treatment and control groups, each of the EAs visited their four experimental communities to list community members interested in participating in a FFS group prior to the roll-out of the interventions. During the listing, communities were asked to also identify two likely FFS facilitators of each group. On average 29.3 members per community were listed as FFS interested participants.

Step 4 – Within community farmer randomization of eVouchers. To allow for measurement of spillovers of eVouchers within communities, a second randomization was done to select treatment and control farmers within communities. This is done among both FFS likely participants and among other members of the community. To obtain a list of all members in the experimental communities, an extensive household listing was performed in October and November 2020. The identification of treatment and control eVoucher households within communities is done for all evaluation communities, not just those assigned to receive eVouchers. This permits the identification of the equivalent households in both treatment and control groups.

The baseline survey sample is composed of all 388 evaluation communities. Within each community, 12 households are sampled from the following groups: 1. FFS interested + eVoucher treatment (6 households) 2. FFF interested + eVoucher control (3 households) 3. Not FFS interested + eVoucher treatment (2 households) 4. Not FFS interested + eVoucher control (1 household)

Both likely facilitators from the FFS listing were prioritized to be included in the survey sample. Sampling weights are applied when translating our sample averages to community wide average or other combinations of groups with different sampling probabilities.

Sampling deviation

The research team could not obtain listing from two communities and one community only had 10 households.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey was conducted in Portuguese. The questionnaire is available for download.

Response rate

Replacements were made whenever a household in the original sample could not be interviewed after three unsuccessfully attempts by the enumerators. Replacements were impact evaluation sample group specific, i.e., a household on the FFS interested list would be replaced by a household of that same status from the replacement list in that same community, maintaining the sample structure wherever possible. Replacement rate was around 4% of the original randomized sample.

Data comprise scenarios of how land use can be in the future and how will it affect ecosystem services in rural Mozambique. The scenarios were constructed from information gathered at five workshops held in Maputo, Xai Xai, Quelimane and Lichinga in 2014 and 2015. The objective of the workshops was to examine aspects that influence well-being (e.g. ecosystem services) and their causes (e.g. change in land use) in the Miombo woodland area of rural Mozambique and identify actions that could contribute to poverty alleviation and biodiversity conservation. The final objective was to construct scenarios of how the land use can be in Mozambique in the future (2035). The data were collected as part of the Abrupt Changes in Ecosystem Services and Wellbeing in Mozambican Woodlands (ACES) project and were funded by the Ecosystem Services for Poverty Alleviation (ESPA) programme, funded by NERC, the Economic & Social Research Council (ESRC) and the Department for International Development (DfID), the three are government organizations from UK. The project was led by the University of Edinburgh, with the collaboration of the Universidad Mondlane, the IIED, and other organizations.

Mozambique MZ: Income Share Held by Lowest 10% data was reported at 1.600 % in 2014. This records a decrease from the previous number of 1.900 % for 2008. Mozambique MZ: Income Share Held by Lowest 10% data is updated yearly, averaging 1.750 % from Dec 1996 (Median) to 2014, with 4 observations. The data reached an all-time high of 2.100 % in 2002 and a record low of 1.500 % in 1996. Mozambique MZ: Income Share Held by Lowest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mozambique – Table MZ.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.