Zimbabwe poverty rate for 2019 was 86.20%, a 0.7% increase from 2017.

<ul style='margin-top:20px;'>

<li>Zimbabwe poverty rate for 2017 was <strong>85.50%</strong>, a <strong>2.3% increase</strong> from 2011.</li>
<li>Zimbabwe poverty rate for 2011 was <strong>83.20%</strong>, a <strong>83.2% increase</strong> from .</li>
<li>Zimbabwe poverty rate for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
</ul>Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 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.

Poverty headcount ratio at national poverty lines (% of population) in Zimbabwe was reported at 38.3 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Zimbabwe - Poverty headcount ratio at national poverty line (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Zimbabwe Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 46.700 % in 2019. This records an increase from the previous number of 44.000 % for 2017. Zimbabwe Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 44.000 % from Dec 2011 (Median) to 2019, with 3 observations. The data reached an all-time high of 46.700 % in 2019 and a record low of 38.300 % in 2011. Zimbabwe Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zimbabwe – Table ZW.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Zimbabwe ZW: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 46.500 % in 2011. Zimbabwe ZW: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 46.500 % from Dec 2011 (Median) to 2011, with 1 observations. Zimbabwe ZW: 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 Zimbabwe – Table ZW.World Bank.WDI: 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.

Abstract

The Poverty, Income, Consumption, and Expenditure Survey 2017 is the main data source for the compilation of the informal sector, living conditions, poverty levels, and weights for the Consumer Price Index (CPI). The survey is based on a sample of 32,256 households, representative at Province and District Levels.

The objectives of the survey are to: - Estimate private consumption expenditure and disposable income of the household sector - Compile the production account of the agricultural sector - Study income/expenditure disparities among socio-economic groups - Estimate the contribution of the informal sector to GDP in Zimbabwe - Estimate the size of household transfer incomes within and outside the country - Calculate weights for the Consumer Price Index (CPI) - Calculate the poverty line, measure the poverty rate and inequality - Provide data useful to formulate national policies for social welfare programmes - Obtain data for poverty mapping - Obtain data useful in measuring the demographic dividend for Zimbabwe

Geographic coverage

• National Coverage: 62 administrative districts of Zimbabwe
• Rural and Urban areas
• Land-use sectors: Communal Lands (CL), Small Scale Commercial Farms (SSCF), Large Scale Commercial Farms (LSCF), Resettlement Areas (includes Old Resettlement Areas (ORA), A1 Farms and A2 Farms), Urban Council Areas (UCA), Administrative Centres (AC), and Growth Point (GP) and Other Urban Areas (OUA), e.g. Services Center and Mines.

Analysis unit

• Individuals
• Households

Universe

The sample is representative of the whole population of Zimbabwe living in private households. The population living in collective households or in institutions such as military barracks, prisons and hospitals are excluded from the sampling frame.

Kind of data

Sample survey data [ssd]

Sampling procedure

At the first sampling stage, the sample EAs for the PICES 2017 are selected within each stratum (administrative district) using random systematic sampling with Probability Proportional to Size (PPS) from the ordered list of EAs in the sampling frame. The measure of size for each EA are based on the total number of households identified in the 2012 Population Census sampling frame. The EAs within each district are ordered first by rural and urban codes, land-use sector, ward and EA number. This provides implicit land-use and geographic stratification of the sampling frame within each district, and ensures a proportional allocation of the sample to the urban and rural areas of each district.The Complex Samples module of the SAS software is used for selecting the sample EAs systematically with PPS within each stratum at the first stage. The module uses the “SURVEY SELECT” sampling procedure.

At the second sampling stage, a random systematic sample of 14 households are selected with equal probability from the listing of each sample EA. Reserve households are selected for replacements. The reason why the replacement of non interview households are considered was to maintain the effective sample size and enumerator workload in each sample EA. Four households are selected for possible replacement, and thus a total of 18 households are selected from each sample EA. A systematic subsample of 4 households are then selected from the 18 households, and the remaining 14 sample households are considered the original sample for the survey. A spreadsheet is developed for selecting the 14 sample households and 4 reserve households for possible replacement in each sample EA. This spreadsheet includes items for the identification of the sample EA, and formulas for the systematic selection of households once the total number of households listed has been entered.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The PICES 2017 data entry is conducted by the ZIMSTAT Data Entry Unit using the CSPro software to enter the data. Data entry was done from January 2018 to June 2018. Data is captured twice by different people for purposes of verification. Data from the daily record books (the household food consumption diaries) have been entered from July to November 2018. SAS and STATA software is used for data processing. Data cleaning is done at all stages i.e. during data entry and data processing to check for the consistency of the data. Tables are then generated for use in report writing.

Response rate

Out of a total of 32,256 sampled households, a total of 31,195 households successfully completed interviews. This gives a response rate of 96.7 percent of the sampled households.

Sampling error estimates

The standard error, or square root of the variance, is used to measure the sampling error, although it may also include a small variable part of the non-sampling error. The variance estimator should take into account the different aspects of the sample design, such as the stratification and clustering. Programs available for calculating the variances for survey data from stratified multi stage sample designs such as the PICES 2017 include STATA and the Complex Samples module of SPSS as well as SAS and Wesvar. All these software packages use an ultimate cluster (linearized Taylor series) variance estimator. The Complex Samples module of STATA is used with the PICES 2017 data to produce the sampling errors.

In 2025, nearly 11.7 percent of the world population in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day, lived in Nigeria. Moreover, the Democratic Republic of the Congo accounted for around 11.7 percent of the global population in extreme poverty. Other African nations with a large poor population were Tanzania, Mozambique, and Madagascar. Poverty levels remain high despite the forecast decline Poverty is a widespread issue across Africa. Around 429 million people on the continent were living below the extreme poverty line of 2.15 U.S. dollars a day in 2024. Since the continent had approximately 1.4 billion inhabitants, roughly a third of Africa’s population was in extreme poverty that year. Mozambique, Malawi, Central African Republic, and Niger had Africa’s highest extreme poverty rates based on the 2.15 U.S. dollars per day extreme poverty indicator (updated from 1.90 U.S. dollars in September 2022). Although the levels of poverty on the continent are forecast to decrease in the coming years, Africa will remain the poorest region compared to the rest of the world. Prevalence of poverty and malnutrition across Africa Multiple factors are linked to increased poverty. Regions with critical situations of employment, education, health, nutrition, war, and conflict usually have larger poor populations. Consequently, poverty tends to be more prevalent in least-developed and developing countries worldwide. For similar reasons, rural households also face higher poverty levels. In 2024, the extreme poverty rate in Africa stood at around 45 percent among the rural population, compared to seven percent in urban areas. Together with poverty, malnutrition is also widespread in Africa. Limited access to food leads to low health conditions, increasing the poverty risk. At the same time, poverty can determine inadequate nutrition. Almost 38.3 percent of the global undernourished population lived in Africa in 2022.

39,80 (%) in 2019. Population below $1.9 a day is the percentage of the population living on less than $1.9 a day at 2005 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.

Zimbabwe ZW: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % of Population data was reported at 39.800 % in 2019. This records an increase from the previous number of 34.200 % for 2017. Zimbabwe ZW: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % of Population data is updated yearly, averaging 34.200 % from Dec 2011 (Median) to 2019, with 3 observations. The data reached an all-time high of 39.800 % in 2019 and a record low of 21.600 % in 2011. Zimbabwe ZW: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zimbabwe – Table ZW.World Bank.WDI: Social: Poverty and Inequality. Poverty headcount ratio at $2.15 a day is the percentage of the population living on less than $2.15 a day at 2017 purchasing power adjusted 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.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

13,4 (%) in 2019. Poverty gap at $1.90 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $1.90 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Zimbabwe ZW: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 74.000 % in 2011. Zimbabwe ZW: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 74.000 % from Dec 2011 (Median) to 2011, with 1 observations. Zimbabwe ZW: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zimbabwe – Table ZW.World Bank.WDI: Poverty. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 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.; ; 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. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include 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). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Zimbabwe: Poverty, percent of population: Pour cet indicateur, La Banque mondiale fournit des données pour la Zimbabwe de 2001 à 2019. La valeur moyenne pour Zimbabwe pendant cette période était de 30.85 pour cent avec un minimum de 22.5 pour cent en 2011 et un maximum de 38.3 pour cent en 2019.

Zimbabwe Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 25.800 % in 2019. Zimbabwe Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 25.800 % from Dec 2019 (Median) to 2019, with 1 observations. The data reached an all-time high of 25.800 % in 2019 and a record low of 25.800 % in 2019. Zimbabwe Multidimensional Poverty Headcount Ratio: UNDP: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zimbabwe – Table ZW.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;

Zimbabwe ZW: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 70.900 % in 2001. Zimbabwe ZW: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 70.900 % from Dec 2001 (Median) to 2001, with 1 observations. Zimbabwe ZW: Poverty Headcount Ratio at National Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zimbabwe – Table ZW.World Bank.WDI: Poverty. 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.; ; 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.

38,0 (%) in 2003.

38,3 (%) in 2019. National poverty rate is the percentage of the population living below the national poverty line. National estimates are based on population-weighted subgroup estimates from household surveys.

Poverty gap index (household) of Mashonaland East plummeted by 99.38% from 46.7 % in 1995 to 0.3 % in 2003. Since the 99.38% drop in 2003, poverty gap index (household) remained constant by 0.00% in 2003.

40,0 (%) in 2003.

Zimbabwe ZW: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 47.200 % in 2011. Zimbabwe ZW: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 47.200 % from Dec 2011 (Median) to 2011, with 1 observations. Zimbabwe ZW: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zimbabwe – Table ZW.World Bank.WDI: Poverty. 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.; ; 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. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include 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). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

34,0 (%) in 2003.

37,0 (%) in 2003.