El Salvador Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 5.500 % in 2022. This records a decrease from the previous number of 6.300 % for 2021. El Salvador Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 6.650 % from Dec 2010 (Median) to 2022, with 12 observations. The data reached an all-time high of 13.000 % in 2010 and a record low of 4.400 % in 2019. El Salvador Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;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).

El Salvador SV: Multidimensional Poverty Headcount Ratio: Female: % of female population data was reported at 31.000 % in 2019. This records a decrease from the previous number of 32.800 % for 2018. El Salvador SV: Multidimensional Poverty Headcount Ratio: Female: % of female population data is updated yearly, averaging 37.100 % from Dec 2014 (Median) to 2019, with 5 observations. The data reached an all-time high of 40.900 % in 2016 and a record low of 31.000 % in 2019. El Salvador SV: Multidimensional Poverty Headcount Ratio: Female: % of female population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

Actual value and historical data chart for El Salvador Poverty Headcount Ratio At National Poverty Line Percent Of Population

El Salvador Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 23.900 % in 2022. This records a decrease from the previous number of 24.700 % for 2021. El Salvador Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 29.700 % from Dec 1989 (Median) to 2022, with 28 observations. The data reached an all-time high of 37.400 % in 1991 and a record low of 23.000 % in 2019. El Salvador 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 El Salvador – Table SV.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).

Abstract

The World Bank Group is interested in gauging the views of clients and partners who are either involved in development in El Salvador or who observe activities related to social and economic development. The following survey will give the World Bank Group's team that works in El Salvador, 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 El Salvador. 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 El Salvador perceive the Bank Group; - Obtain systematic feedback from stakeholders in El Salvador regarding: · Their views regarding the general environment in El Salvador; · Their overall attitudes toward the World Bank Group in El Salvador; · Overall impressions of the World Bank Group's effectiveness and results, knowledge work and activities, and communication and information sharing in El Salvador; · Perceptions of the World Bank Group's future role in El Salvador. - Use data to help inform El Salvador country team's strategy.

Geographic coverage

• Western Zone
• Central Zone
• Eastern Zone

Analysis unit

Stakeholders in El Salvador

Universe

Stakeholders in El Salvador

Kind of data

Sample survey data [ssd]

Sampling procedure

In March-April 2014, 135 stakeholders of the World Bank Group in El Salvador 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; the office of the Prime Minister; office of a minister; office of a parliamentarian; ministries, ministerial departments, or implementation agencies; consultants/contractors working on WBG-supported projects/programs; project management units (PMUs) 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 following sections:

A. General Issues Facing El Salvador: Respondents were asked to indicate whether El Salvador is headed in the right direction, what they thought were the top three most important development priorities in the country, which areas would contribute most to reducing poverty and generating economic growth in El Salvador, 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 El Salvador, WBG staff preparedness to help El Salvador solve its development challenges, , 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 El Salvador, in which sectoral areas the WBG should focus most of its resources (financial and knowledge services), and to what reasons respondents attributed failed or slow reform efforts. Respondents were also asked to respond to a few questions about capacity building and whether they believe the World Bank Group should have more or less local presence.

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 El Salvador, the extent to which the WBG meets El Salvador's needs for knowledge services and financial instruments, the importance for the WBG to be involved in thirty one development areas, and the WBG's level of effectiveness across twenty-eight development areas, such as education, crime and violence, public sector governance/reform, poverty reduction, and economic growth.

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 WBG reports, including if they read/consulted the most recent LAC Flagship Report, whether they raised substantive new information, and whether they 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. They were also asked to indicate whether they thing the World Bank Group takes enough risks.

F. The Future Role of the World Bank Group in El Salvador: Respondents were asked to indicate what the WBG should do to make itself of greater value in El Salvador, 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 El Salvador.

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. Respondents 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 El Salvador, which WBG agencies they work with, whether IFC and the Bank work well together, and their geographic location.

Response rate

A total of 97 stakeholders participated in the survey (72% response rate).

Fiscal policy in El Salvador has the capacity to consolidate economic growth, providing greater resilience to the population against possible risks or boosting income generation. This note analyzes the impact of subsidies for energy, water and liquefied petroleum gas (LPG), on poverty and household welfare. We use the Commitment to Equity (CEQ) approach with data from the Multipurpose Household Survey of El Salvador (EHPM) to simulate different policy scenarios. The results indicate that if subsidies were eliminated, poverty would increase by 1.3 percentage points and extreme poverty by 0.5 percentage points, negatively affecting the welfare of families. However, in the scenario where the elimination of subsidies is accompanied by an increase of other social transfers, are transformed into targeted subsidies, or the previous scenarios are combined, the impact on poverty could be mitigated. These results show that there is room for efficiency gains on the goal of improving households’ welfare and promoting equitable results.

Previous research on educational aspirations and educational decision-making has mostly focused on high-income countries and thus on a relatively homogeneous socio-economic context. However, educational decision-making may be sensitive to contextual factors such as economic deprivation, a dysfunctional welfare state or poor access to credit markets – characteristics shared by most low- and middle-income countries. To better understand how economically disadvantaged individuals in developing countries make their educational choices, we conducted a survey based on a random sample with high school students in the rural department Morazán in El Salvador, a lower middle-income country in Latin America. Our results show that regardless of the social background, almost all students aspire to pursue tertiary education, probably due to the high tertiary degree premium in earnings and the high social benefits. However, the lack of possibilities to finance their studies generally prevents the realisation of these aspirations for lower social background students. While in high-income countries, cost factors are not very important in the decision-making process, the burden of costs explains around 45 percent of the social background effect in El Salvador. Other factors such as academic confidence, expected future economic benefits, parental status maintenance wish, individual risk aversion and time discounting preferences play only a minor role.

El Salvador SV: Multidimensional Poverty Intensity (average share of deprivations experienced by the poor) data was reported at 42.400 % in 2019. This records a decrease from the previous number of 42.600 % for 2018. El Salvador SV: Multidimensional Poverty Intensity (average share of deprivations experienced by the poor) data is updated yearly, averaging 43.200 % from Dec 2014 (Median) to 2019, with 5 observations. The data reached an all-time high of 43.900 % in 2014 and a record low of 42.400 % in 2019. El Salvador SV: Multidimensional Poverty Intensity (average share of deprivations experienced by the poor) data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

El Salvador SV: Multidimensional Poverty Headcount Ratio: Children: % of population aged 0-17 data was reported at 39.600 % in 2019. This records an increase from the previous number of 39.000 % for 2018. El Salvador SV: Multidimensional Poverty Headcount Ratio: Children: % of population aged 0-17 data is updated yearly, averaging 46.300 % from Dec 2014 (Median) to 2019, with 5 observations. The data reached an all-time high of 47.700 % in 2014 and a record low of 39.000 % in 2018. El Salvador SV: Multidimensional Poverty Headcount Ratio: Children: % of population aged 0-17 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

The Non-Formal Skills Development Sub-Activity had a budget of $5 million (USD) to provide short-term training to vulnerable populations in El Salvador's Northern Zone, including women, at-risk youths, and the poor. The Sub-Activity funded short-term courses in common trades such as baking, bricklaying, and electrical installations. The short-term goal of the non-formal skills program was to increase the education and skill levels of at-risk populations in the Northern Zone. The medium-term goals were to decrease economic barriers to labor force entry, while increasing the personal income, labor market participation, and self-employment rates of vulnerable populations. Lastly, the program's long-term goal was to spur economic growth and reduce poverty in the target area. To examine the effects of the Non-Formal Skills Development Sub-Activity on employment rates and personal income, we used a pre-post survey design. With this design, we compare outcomes of enrolled participants before the start of the program with the outcomes of the same individuals approximately one year after the end of the program. This design cannot fully attribute before-after differences to the training program because other factors outside of the program-including broader economic developments during the study period-could have also affected participants' outcomes. Although we do not report impact estimates, or estimates that are fully attributable to the program, this analysis can offer valuable insight regarding the following research question: ·What was the change in participants' labor market outcomes and income approximately one year after completing a 180-400 hour non-formal skills course?

This dataset measures food availability and access for 76 low- and middle-income countries. The dataset includes annual country-level data on area, yield, production, nonfood use, trade, and consumption for grains and root and tuber crops (combined as R&T in the documentation tables), food aid, total value of imports and exports, gross domestic product, and population compiled from a variety of sources. This dataset is the basis for the International Food Security Assessment 2015-2025 released in June 2015. This annual ERS report projects food availability and access for 76 low- and middle-income countries over a 10-year period. Countries (Spatial Description, continued): Democratic Republic of the Congo, Ecuador, Egypt, El Salvador, Eritrea, Ethiopia, Gambia, Georgia, Ghana, Guatemala, Guinea, Guinea-Bissau, Haiti, Honduras, India, Indonesia, Jamaica, Kenya, Kyrgyzstan, Laos, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Moldova, Mongolia, Morocco, Mozambique, Namibia, Nepal, Nicaragua, Niger, Nigeria, North Korea, Pakistan, Peru, Philippines, Rwanda, Senegal, Sierra Leone, Somalia, Sri Lanka, Sudan, Swaziland, Tajikistan, Tanzania, Togo, Tunisia, Turkmenistan, Uganda, Uzbekistan, Vietnam, Yemen, Zambia, and Zimbabwe. Resources in this dataset:Resource Title: CSV File for all years and all countries. File Name: gfa25.csvResource Title: International Food Security country data. File Name: GrainDemandProduction.xlsxResource Description: Excel files of individual country data. Please note that these files provide the data in a different layout from the CSV file. This version of the data files was updated 9-2-2021

More up-to-date files may be found at: https://www.ers.usda.gov/data-products/international-food-security.aspx

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

National coverage

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Observation data/ratings [obs]

Sampling procedure

The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world's population (see Table A.1 of the Global Findex Database 2017 Report). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size was 1000.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

El Salvador SV: Income Share Held by Highest 20% data was reported at 46.400 % in 2016. This records a decrease from the previous number of 47.200 % for 2015. El Salvador SV: Income Share Held by Highest 20% data is updated yearly, averaging 52.400 % from Dec 1991 (Median) to 2016, with 22 observations. The data reached an all-time high of 57.600 % in 1991 and a record low of 46.400 % in 2016. El Salvador SV: Income Share Held by Highest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.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.

El Salvador SV: Income Share Held by Highest 10% data was reported at 30.700 % in 2016. This records a decrease from the previous number of 31.800 % for 2015. El Salvador SV: Income Share Held by Highest 10% data is updated yearly, averaging 36.050 % from Dec 1991 (Median) to 2016, with 22 observations. The data reached an all-time high of 41.400 % in 1991 and a record low of 30.700 % in 2016. El Salvador SV: Income Share Held by Highest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.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.

El Salvador SV: Income Share Held by Third 20% data was reported at 15.200 % in 2016. This records an increase from the previous number of 14.800 % for 2015. El Salvador SV: Income Share Held by Third 20% data is updated yearly, averaging 13.500 % from Dec 1991 (Median) to 2016, with 22 observations. The data reached an all-time high of 15.200 % in 2016 and a record low of 12.300 % in 1991. El Salvador SV: Income Share Held by Third 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.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.

El Salvador SV: Income Share Held by Fourth 20% data was reported at 21.900 % in 2016. This records an increase from the previous number of 21.400 % for 2015. El Salvador SV: Income Share Held by Fourth 20% data is updated yearly, averaging 20.900 % from Dec 1991 (Median) to 2016, with 22 observations. The data reached an all-time high of 21.900 % in 2016 and a record low of 20.100 % in 1991. El Salvador SV: Income Share Held by Fourth 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.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.

El Salvador SV: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 28.500 % in 2014. This records an increase from the previous number of 26.200 % for 2013. El Salvador SV: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 30.400 % from Dec 2005 (Median) to 2014, with 10 observations. The data reached an all-time high of 35.700 % in 2008 and a record low of 26.200 % in 2013. El Salvador SV: 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 El Salvador – Table SV.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.

El Salvador Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 0.610 % in 2019. This records a decrease from the previous number of 0.630 % for 2018. El Salvador Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 0.630 % from Dec 2014 (Median) to 2019, with 5 observations. The data reached an all-time high of 0.830 % in 2016 and a record low of 0.250 % in 2014. El Salvador 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 El Salvador – Table SV.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/].

El Salvador SV: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 10.300 % in 2016. This records an increase from the previous number of 9.900 % for 2015. El Salvador SV: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 22.500 % from Dec 1989 (Median) to 2016, with 23 observations. The data reached an all-time high of 36.500 % in 1991 and a record low of 9.900 % in 2015. El Salvador SV: 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 El Salvador – Table SV.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.

El Salvador SV: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 4.080 % in 2016. El Salvador SV: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 4.080 % from Dec 2016 (Median) to 2016, with 1 observations. El Salvador SV: 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 El Salvador – Table SV.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.