In 2021, approximately 5.4 percent of the Bolivian population were living on less than 3.65 U.S. dollars per day. Since 2016, this share has been continuously decreasing until the previous year, despite the increase in 2020. Still, the unemployment rate in the South American country has reached its peak since 1999 in 2020.

The share of indigenous population in Bolivia that had an average per capita income below the poverty line totaled 35.4 percent in 2021. In comparison to the beginning of the mentioned period, this represents a decrease of 34.1 percentage points. Overall, in Latin America, the share of indigenous population living in extreme poverty reached 18.5 percent in 2021.

Historical chart and dataset showing Bolivia poverty rate by year from 1990 to 2023.

Bolivia: Poverty, percent of population: The latest value from 2021 is 36.4 percent, a decline from 39 percent in 2020. In comparison, the world average is 22.31 percent, based on data from 66 countries. Historically, the average for Bolivia from 2000 to 2021 is 48.66 percent. The minimum value, 34.5 percent, was reached in 2018 while the maximum of 66.4 percent was recorded in 2000.

Bolivia Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 23.000 % in 2021. This records an increase from the previous number of 22.800 % for 2020. Bolivia Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 28.700 % from Dec 1990 (Median) to 2021, with 24 observations. The data reached an all-time high of 38.200 % in 2000 and a record low of 22.700 % in 2019. Bolivia 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 Bolivia – Table BO.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).

Poverty headcount ratio at national poverty lines (% of population) in Bolivia was reported at 37.7 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Bolivia - Poverty headcount ratio at national poverty line (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Bolivia BO: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 36.400 % in 2021. This records a decrease from the previous number of 39.000 % for 2020. Bolivia BO: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 44.200 % from Dec 2000 (Median) to 2021, with 20 observations. The data reached an all-time high of 66.400 % in 2000 and a record low of 34.500 % in 2018. Bolivia BO: 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 Bolivia – Table BO.World Bank.WDI: Social: Poverty and Inequality. National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year.;World Bank, Poverty and Inequality Platform. 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.

This statistic shows the poverty headcount ratio at national poverty lines in Bolivia from 2011 to 2021. In 2021, the poverty headcount ratio at national poverty lines in Bolivia amounted to 36.4 percent of the population.

Bolivia BO: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 9.000 % in 2020. This records an increase from the previous number of 7.800 % for 2019. Bolivia BO: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 18.300 % from Dec 1997 (Median) to 2020, with 21 observations. The data reached an all-time high of 41.300 % in 2000 and a record low of 7.800 % in 2019. Bolivia BO: 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 Bolivia – Table BO.World Bank.WDI: Social: Poverty and Inequality. 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, 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 around 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Bolivia BO: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data was reported at 57.600 % in 2014. This records a decrease from the previous number of 59.900 % for 2013. Bolivia BO: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data is updated yearly, averaging 70.000 % from Dec 2004 (Median) to 2014, with 10 observations. The data reached an all-time high of 77.700 % in 2004 and a record low of 57.600 % in 2014. Bolivia BO: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Poverty and Inequality. Rural poverty headcount ratio is the percentage of the rural 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.

In 2022, the poverty headcount ratio at national poverty lines in Peru increased by 1.6 percentage points (+6.18 percent) compared to 2021. In total, the poverty headcount ratio amounted to 27.5 percent in 2022. The poverty headcount ratio at national poverty lines refers to the share of the population living in poverty, based on parameters set by local, regional, or national governments.Find more key insights for the poverty headcount ratio at national poverty lines in countries like Ecuador and Bolivia.

The poverty headcount ratio at national poverty lines in Ecuador declined to 25.2 percent in 2022. Nevertheless, the last two years recorded a significantly higher poverty headcount ratio than the preceding years.The poverty headcount ratio at national poverty lines refers to the share of the population living in poverty, based on parameters set by local, regional, or national governments.Find more key insights for the poverty headcount ratio at national poverty lines in countries like Bolivia and Peru.

Bolivia Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 9.100 % in 2016. Bolivia Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 9.100 % from Dec 2016 (Median) to 2016, with 1 observations. The data reached an all-time high of 9.100 % in 2016 and a record low of 9.100 % in 2016. Bolivia 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 Bolivia – Table BO.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/);;

In the majority of the analyzed countries in Latin America and the Caribbean, the share of the population living in extreme poverty was expected to grow in 2022 compared to 2021. Colombia presented the most adverse situation, as extreme poverty in the country was expected to increase by 2.5 percentage points. On the flip side, it was forecasted that exreme poverty would decline in four countries: Dominican Republic, Ecuador, Panama and Bolivia.

Abstract

The World Bank Group is interested in gauging the views of clients and partners who are either involved in development in Bolivia or who observe activities related to social and economic development. The following survey will give the World Bank Group's team that works in Bolivia, greater insight into how the Bank's work is perceived. This is one tool the World Bank Group uses to assess the views of its stakeholders, and to develop more effective strategies that support development in Bolivia. A local independent firm was hired to oversee the logistics of this survey.

This survey was designed to achieve the following objectives: - Assist the World Bank Group in gaining a better understanding of how stakeholders in Bolivia perceive the Bank Group; - Obtain systematic feedback from stakeholders in Bolivia regarding: · Their views regarding the general environment in Bolivia; · Their overall attitudes toward the World Bank Group in Bolivia; · Overall impressions of the World Bank Group's effectiveness and results, knowledge work and activities, and communication and information sharing in Bolivia; · Perceptions of the World Bank Group's future role in Bolivia. - Use data to help inform Bolivia country team's strategy.

Geographic coverage

La Paz El Alto Santa Cruz Other city in urban area Rural area

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Bolivia

Kind of data

Sample survey data [ssd]

Sampling procedure

In March-May 2014, 440 stakeholders of the World Bank Group in Bolivia were invited to provide their opinions on the WBG's work in the country by participating in a country opinion survey. Participants were drawn from the office of the President; office of a minister; office of a parliamentarian; ministries/ministerial departments; consultants/contractors working on WBG-supported projects/programs; implementation agencies overseeing implementation of a project; local government officials; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community based organizations; the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; judiciary branch; and other organizations.

Mode of data collection

Other [oth]

Research instrument

The Questionnaire consists of 8 sections:

A. General Issues Facing Bolivia: Respondents were asked to indicate whether Bolivia is headed in the right direction, what they thought were the top three most important development priorities, which areas would contribute most to reducing poverty and generating economic growth in Bolivia, and how "shared prosperity" would be best achieved.

B. Overall Attitudes toward the World Bank Group (WBG): Respondents were asked to rate their familiarity with the WBG and other regional development banks, their effectiveness in Bolivia, WBG staff preparedness to help Bolivia solve its development challenges, WBG's local presence, WBG's capacity building in Bolivia, their agreement with various statements regarding the WBG's work, and the extent to which the WBG is an effective development partner. Respondents were asked to indicate the WBG's greatest values and weaknesses, the most effective instruments in helping reduce poverty in Bolivia, and in which sectoral areas the WBG should focus most of its resources (financial and knowledge services).

C. World Bank Group's Effectiveness and Results: Respondents were asked to rate the extent to which the WBG's work helps achieve development results in Bolivia, the extent to which the WBG meets Bolivia's needs for knowledge services and financial instruments, the importance for the WBG to be involved in thirty six development areas, and the WBG's level of effectiveness across these areas, such as poverty reduction and equity, education, economic growth, and natural resource management.

D. The World Bank Group's Knowledge Work and Activities: Respondents were asked to indicate how frequently they consult WBG's knowledge work and activities and to rate the effectiveness and quality of the WBG's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality. Respondents were also asked about the most recent LAC Flagship Report, including whether it raised substantive new information, and whether it provided them with useful information in terms of work they do.

E. Working with the World Bank Group: Respondents were asked to rate WBG's technical assistance/advisory work's contribution to solving development challenges and their level of agreement with a series of statements regarding working with the WBG, such as the WBG's "Safeguard Policy" requirements being reasonable, and disbursing funds promptly.

F. The Future Role of the World Bank Group in Bolivia: Respondents were asked to indicate what the WBG should do to make itself of greater value in Bolivia, and which services the Bank should offer more of in the country. They were asked whether WBG has moved to the right direction, and the future role international development cooperation should play in Bolivia.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the WBG, and their usage and evaluation of the WBG's websites. Respondents were also asked about their awareness of the WBG's Access to Information policy, were asked to rate WBG's responsiveness to information requests, value of its social media channels, and levels of easiness to find information they needed.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the WBG, their exposure to the WBG in Bolivia, which WBG agencies they work with, and their geographic location.

Questionnaires were in English and Spanish

Response rate

A total of 210 stakeholders participated in the survey (48% response rate).

Bolivia BO: Poverty Gap at $1.90 a Day: 2011 PPP: % data was reported at 1.500 % in 2020. This records an increase from the previous number of 1.000 % for 2019. Bolivia BO: Poverty Gap at $1.90 a Day: 2011 PPP: % data is updated yearly, averaging 5.000 % from Dec 1997 (Median) to 2020, with 21 observations. The data reached an all-time high of 17.500 % in 2000 and a record low of 1.000 % in 2019. Bolivia BO: Poverty Gap at $1.90 a Day: 2011 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Poverty and Inequality. 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.; ; 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 around 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Abstract

In August 2011, implementation began on the project Plan VIDA-PEEP (PPV), an initiative financed jointly between IFAD and the Bolivian Government as part of the country's National Development Plan. It aimed to reduce extreme poverty in rural areas and improve the livelihoods of households residing in vulnerable municipalities in the departments of Potosi and Cochabamba through capacity building, financing of rural development projects, and by supporting citizenship and social inclusion. The project lasted five years in total and was completed in December, 2016.

The project was designed around two main components. The first component aimed at increasing means of production and at strengthening productive assets and management practices. This would be achieved through financial support to communities for the implementation of rural development projects and to municipalities for the realization of production infrastructure projects. The second component consisted of community training and capacity building focused on organizational and productive capacity. It included campaigns aimed at documenting unregistered people in targeted municipalities which would lead to increased social inclusion and access to basic and financial services. In Bolivia, such documentation has been shown to mitigate cases of political and social exclusion (Harbitz and Tamargo 2009).

This impact assessment looks at the effects of rural development projects funded by Plan VIDA on the livelihood of rural households residing in beneficiary communities (i.e., Component 1). In particular, the evaluation focuses on a specific category of projects - Community Based Productive Investments (Proyectos Inter Comunales - PICs) - which account for more than 90 per cent of total beneficiary households reached by Plan VIDA at completion and also constitute the vast majority of the recipients of capacity building activities (i.e., Component 2).

This impact assessment investigated whether the Plan VIDA project, with its unique mechanisms, contributed to well-being of beneficiaries, measured through key outcome indicators of economic mobility, resilience and nutrition to respond to IFAD's strategic objectives and goals and to Bolivia's National Development Plan.

To answer these questions, the ex-post evaluation applied a quasi-experimental design approach that combines statistical methods and qualitative analysis to identify a valid counterfactual. As sufficient data were not collected at baseline of the project, the research team relied on one round of data collected between August and September 2017 that is, about eight months after project completion. Data were collected from 2,751 household including beneficiaries of the project, indirect beneficiaries (those in the same community but not direct recipients of intervention), and households which serve as a control group.

For more information, please, click on the following link https://www.ifad.org/en/web/knowledge/-/publication/impact-assessment-plan-vida-bolivia.

Geographic coverage

Regional coverage.

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

A qualitative survey was conducted prior to the quantitative data collection and consisted in a number of Key Informant Interviews (KIIs) and Focus Groups Discussions (FGDs) with key project stakeholders (Plan VIDA staff and implementers, members of the CPAP, etc.) as well as with participant and non-participant households. The original scope was to gain additional information to improve the design of the quantitative impact assessment, especially the sampling framework and the identification of a valid control group. In particular, the qualitative exercise focused on acquiring a better understanding of: (i) project targeting and the selection process of beneficiary communities; (ii) the characteristics of participant and non-participant communities as well as of direct and indirect beneficiaries (to be able to shed some light on possible self-selection mechanisms); (iii) potential spillover and unintended effects.

For the quantitative data, a two-stage sampling strategy was employed to ensure that the most appropriate communities and respondents were selected to be the control group. To sample control communities the community selection procedure used to identify beneficiary communities was replicated. The following steps were thus undertaken: first a high resolution map for Cohabamba and Potosí, the two areas of project intervention, was obtained divided by municipality and communities; second the beneficiary communities were located and key data on road access, population, and poverty level were reported for each participant village; third a random selection of 90 beneficiary communities was selected; fourth a set of villages similar to the selected treated villages with regard to the above mentioned criteria and located within a polygon of 10 km was also mapped; fifth a selection/validation exercise was conducted to verify selected control villages to associate with treated villages on the basis of additional criteria based on key informants' and Plan VIDA implementers' knowledge of the area. The result of this exercise consisted in the selection of 90 treated and 90 control communities.

The sample comprised a total of 180 communities (half treatment and half control) with 15 households interviewed in each community in order to reach the total estimated sample size of 2,700 households. However, due to some communities being particularly small (less than 15 households), an extra 31 communities were used as back-up options for the original sample in order to comply with the calculated sample size. Cross-sectional quantitative data was therefore collected for a total of 2,751 households from 211 communities.

More details on the sampling procedure can be found in the IA plan and reports, attached in the documentations tab.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The Questionnaire is attached in the documentations tab.

Note: some variables have missing labels. Please, refer to the questionnaire for more details.

Bolivia BO: Increase in Poverty Gap at $3.20: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data was reported at 0.540 USD in 2015. This records an increase from the previous number of 0.338 USD for 2012. Bolivia BO: Increase in Poverty Gap at $3.20: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data is updated yearly, averaging 1.276 USD from Dec 1999 (Median) to 2015, with 8 observations. The data reached an all-time high of 7.286 USD in 1999 and a record low of 0.338 USD in 2012. Bolivia BO: Increase in Poverty Gap at $3.20: Poverty Line Due To Out-of-Pocket Health Care Expenditure: 2011 PPP: USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Poverty. Increase in poverty gap at $3.20 ($ 2011 PPP) poverty line due to out-of-pocket health care expenditure, expressed in US dollars (2011 PPP). The poverty gap increase due to out-of-pocket health spending is one way to measure how much out-of-pocket health spending pushes people below or further below the poverty line (the difference in the poverty gap due to out-of-pocket health spending being included or excluded from the measure of household welfare). This difference corresponds to the total out-of-pocket health spending for households that are already below the poverty line, to the amount that exceeds the shortfall between the poverty line and total consumption for households that are impoverished by out-of-pocket health spending and to zero for households whose consumption is above the poverty line after accounting for out-of-pocket health spending.; ; World Health Organization and World Bank. 2019. Global Monitoring Report on Financial Protection in Health 2019.; Weighted average;

countries Currency Bolivian boliviano. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym

Bolivia Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 0.820 % in 2021. This records a decrease from the previous number of 0.890 % for 2019. Bolivia Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 1.140 % from Dec 1999 (Median) to 2021, with 10 observations. The data reached an all-time high of 2.270 % in 2000 and a record low of 0.820 % in 2021. Bolivia Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Poverty and Inequality. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This indicator is related to Sustainable Development Goal 3.8.2 [https://unstats.un.org/sdgs/metadata/].