Uruguay UY: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 39.700 % in 2016. This records a decrease from the previous number of 40.200 % for 2015. Uruguay UY: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 42.400 % from Dec 1981 (Median) to 2016, with 13 observations. The data reached an all-time high of 46.400 % in 2007 and a record low of 39.700 % in 2016. Uruguay UY: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uruguay – Table UY.World Bank.WDI: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. 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.

Uruguay UY: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 10.100 % in 2014. This records a decrease from the previous number of 12.000 % for 2013. Uruguay UY: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 24.400 % from Dec 2002 (Median) to 2014, with 13 observations. The data reached an all-time high of 39.900 % in 2004 and a record low of 10.100 % in 2014. Uruguay UY: 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 Uruguay – Table UY.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.

Poverty rate at $1.9 a day of Uruguay remained stable at 0.20 % over the last 2 years. 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.

In 2024, 6.6 percent of the indigenous population in Uruguay was living impoverished. Overall, indigenous Uruguayans benefited from a tendency of poverty reduction until 2019. Furthermore, the share of afro-descendants living under the poverty line in this South American country was almost double that of the indigenous population, a rarity in Latin America.

Historical dataset showing Uruguay poverty rate by year from 1981 to 2023.

The percentage of Afro-descendants living in a situation of poverty in Uruguay experienced a steep decline between 2010 to 2019. In 2018, it was estimated that **** percent of Afro-descendant people in Uruguay were living below the poverty line, up from **** percent the previous year. Poverty in the Latin American country is more extended among the Afro-descendant population, as the general poverty rate in Uruguay stood at *** percent in 2019, more than ten percent lower.

Guyana was the South American country 20360the highest gross national income per capita, with 20,360 U.S. dollars per person in 2023. Uruguay ranked second, registering a GNI of 19,530 U.S. dollars per person, based on current prices. Gross national income (GNI) is the aggregated sum of the value added by residents in an economy, plus net taxes (minus subsidies) and net receipts of primary income from abroad. Which are the largest Latin American economies? Based on annual gross domestic product, which is the total amount of goods and services produced in a country per year, Brazil leads the regional ranking, followed by Mexico, Argentina, and Chile. Many Caribbean countries and territories hold the highest GDP per capita in this region, measurement that reflects how GDP would be divided if it was perfectly equally distributed among the population. GNI per capita is, however, a more exact calculation of wealth than GDP per capita, as it takes into consideration taxes paid and income receipts from abroad. How much inequality is there in Latin America? In many Latin American countries, more than half the total wealth created in their economies is held by the richest 20 percent of the population. When a small share of the population concentrates most of the wealth, millions of people don't have enough to make ends meet. For instance, in Brazil, about 5.32 percent of the population lives on less than 3.2 U.S. dollars per day.

Uruguay UY: Income Share Held by Highest 20% data was reported at 45.900 % in 2016. This records a decrease from the previous number of 46.100 % for 2015. Uruguay UY: Income Share Held by Highest 20% data is updated yearly, averaging 48.100 % from Dec 1981 (Median) to 2016, with 13 observations. The data reached an all-time high of 52.000 % in 2007 and a record low of 45.900 % in 2016. Uruguay UY: 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 Uruguay – Table UY.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.

This report focuses on understanding key issues related to poverty, vulnerability and social policy in the context of a changing Uruguayan economy. Because the country is highly urbanized (90 percent), and data on rural areas are scant, most of the analysis in this study focuses on urban areas. Chapter 1 presents a profile of poverty and its trends in the nineties using household survey data. Chapter 2 looks at changes in the structure of the economy and the link with problems of unemployment, underemployment, and labor insecurity over the past decade. Chapter 3 focuses on the specific issues of marginalization and vulnerability based on a qualitative study carried out in poor urban neighborhoods surrounding Montevideo. Chapter 4 analyzes Government social expenditures, with particular emphasis on how effective these expenditures are at reaching the poor and meeting the needs of vulnerable groups. Background papers with detailed analysis are also available under separate cover. Policy recommendations are included in this summary.

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

Sample survey data [ssd]

Frequency of data collection

Triennial

Sampling procedure

As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or 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 by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid 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 Kish grid 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 in Uruguay was 1,000 individuals.

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 142 languages upon request.

Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, 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 Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.

Uruguay UY: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 17.800 % in 2022. This records an increase from the previous number of 17.300 % for 2021. Uruguay UY: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 18.000 % from Dec 2006 (Median) to 2022, with 17 observations. The data reached an all-time high of 19.800 % in 2009 and a record low of 16.900 % in 2018. Uruguay UY: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uruguay – Table UY.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. 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.;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).

Among Latin American countries in 2023, Colombia had the highest share of both Afro-descendants and indigenous people living impoverished, with 45.6 percent and 63.5 percent, respectively. Additionally, Colombia also had the highest share of indigenous people living under extreme poverty that year. Ecuador had the second-highest share of indigenous population whose average per capita income was below the poverty line, with 50.4 percent. Uruguay was the only nation where Afro-descendants were the ethnic group with the largest share of the poor population, as in the other selected countries such group was indigenous people.

Link to this report's codebookExecutive SummaryThe world is still in the midst of the worst public health crisis in a century. Mobility restriction measures taken to respond to the COVID-19 threat have led to a global economic crisis, with massive job losses and major impacts amounting to a significant setback in the world’s progress towards achieving the SDGs, especially for poor countries and vulnerable population groups. In line with SDG 3 (Good Health and Well-Being), all countries need to strengthen the resilience of their health systems and their disease and pandemic prevention programs. Besides greater investments, the crisis has highlighted the need for better measurement and reporting to track disease and pandemic prevention programs, healthcare system preparedness, and resilience to pandemics.This report presents a special edition of the SDG Index and Dashboards, in which Uruguay is benchmarked against OECD countries using a specific set of SDG indicators available for these countries. Due to time lags in data generation and reporting, however, the SDG Index and Dashboards for Uruguay do not reflect the impact of COVID-19. The projection of country trajectories based on recent progress (business-as-usual scenarios) may therefore not provide a realistic sense of the likely future, as COVID-19 is likely to alter trajectories relating to many SDGs. Nevertheless, the Index and Dashboards remain useful for understanding, goal by goal, the progress of Uruguay compared to these other countries. The SDG data and the Six Transformations Framework presented in this report help to identify the key vulnerabilities and challenges that Uruguay was facing before the COVID-19 crisis and provide a useful framework to inform its long-term recovery from COVID-19.Uruguay ranks 30th of the 39 countries covered in this special edition. Its overall score is, however, above the average for OECD countries in the Latin America and Caribbean region and only slightly below the population-weighted average of OECD countries overall. Uruguay performs well and is showing progress on most of the socio-economic goals (SDGs 1–10) although progress is lagging on SDG 4 (Quality Education), SDG 9 (Industry, Innovation and Infrastructure) and SDG 10 (Reduced Inequalities). As with other OECD countries, and particularly the OECD countries in the Latin America and Caribbean region, further effort is needed to meet goals related to sustainable consumption and production, or to climate and biodiversity (SDGs 12 to 15), and to address governance and security issues covered under SDG 16 (Peace, Justice and Strong Institutions).As part of its commitment to the 2030 Agenda, Uruguay has already submitted four voluntary national reviews to the UN High Level Political Forum: in 2017, 2018, 2019 and 2021. Incorporating exhaustive statistical data, these comprehensive reports show Uruguay’s progress on the 17 SDGs and provide detailed information on regulatory frameworks and specific actions contributing to progress towards each goal. The government’s recent submission of the 2021 voluntary national review, which incorporates the results in this report, presents an opportunity to reinforce Uruguay’s commitment to the 2030 Agenda by defining strategies to address remaining challenges and further accelerate progress.Reliable, relevant and timely information is essential to successfully align national strategies to the SDGs: to identify priorities, mobilize resources, measure results and ensure transparency. Uruguay must encourage and advance the strategic use of data and digital technologies towards improving its policies for sustainable development.Achieving the SDGs requires closing the financing gap. The private sector plays a key role in mobilizing resources for sustained economic growth and contributing to social inclusion and environmental protection. The private sector contributes directly to SDG 12 (Responsible Consumption and Production) and indirectly, through its actions and financing, to the achievement of all 17 SDGs. Uruguay has already started to move in this direction, initiating the country’s first private issuance of green bonds to finance sustainable investment portfolios. Uruguay’s Central Bank has now joined the Network for Greening the Financial System, and the Uruguayan Private Banks Association has established a sustainability committee to accelerate the transition towards sustainable finance in the banking system.

Based on the degree of inequality in income distribution measured by the Gini coefficient, Colombia was the most unequal country in Latin America as of 2022. Colombia's Gini coefficient amounted to 54.8. The Dominican Republic recorded the lowest Gini coefficient at 37, even below Uruguay and Chile, which are some of the countries with the highest human development indexes in Latin America. The Gini coefficient explained The Gini coefficient measures the deviation of the distribution of income among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality. This measurement reflects the degree of wealth inequality at a certain moment in time, though it may fail to capture how average levels of income improve or worsen over time. What affects the Gini coefficient in Latin America? Latin America, as other developing regions in the world, generally records high rates of inequality, with a Gini coefficient ranging between 37 and 55 points according to the latest available data from the reporting period 2010-2023. According to the Human Development Report, wealth redistribution by means of tax transfers improves Latin America's Gini coefficient to a lesser degree than it does in advanced economies. Wider access to education and health services, on the other hand, have been proven to have a greater direct effect in improving Gini coefficient measurements in the region.

Uruguay UY: Income Share Held by Third 20% data was reported at 15.400 % in 2016. This stayed constant from the previous number of 15.400 % for 2015. Uruguay UY: Income Share Held by Third 20% data is updated yearly, averaging 14.700 % from Dec 1981 (Median) to 2016, with 13 observations. The data reached an all-time high of 15.400 % in 2016 and a record low of 13.400 % in 2007. Uruguay UY: 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 Uruguay – Table UY.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.

Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 21.700 % in 2022. This records an increase from the previous number of 21.600 % for 2021. Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 22.700 % from Dec 1981 (Median) to 2022, with 30 observations. The data reached an all-time high of 27.000 % in 2004 and a record low of 20.500 % in 2017. 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 Uruguay – Table UY.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).

The poverty headcount ratio at national poverty lines in Paraguay declined to 24.7 percent in 2022. This decrease was preceded by an increase in poverty headcount ratio.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 Uruguay.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

The Survey covers Uruguay.

Analysis unit

• Household
• Individual

Universe

The WVS for Uruguay covers national population aged 18 years and over, for both sexes.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling method is a stratified probabilistic sampling, multistage, with quota control in the final stage. The sample is stratified by region -Montevideo (capital city) and Interior (rest of the country). The interviewees are selected through multiple stages: in the first one are chosen the cities on each stratum; in the second one are selected the zones used as sample points (manzanas); in the third one, the house-holds in which the survey is made; and finally, the interviewees.

In the first stage are selected automatically Montevideo (capital city), three cities of the first stratum (cities between 50.001 to 100.000 inhabitants), two of the cities of the second stratum (cities between 40.001 to 50.000 inhabitants), eight cities of the third stratum (cities between 20001 to 40000 inhabitants), ten cities of the fourth stratum (cities between 10001 to 20000 inhabitants), four cities of the fifth stratum (cities between 5001 to 10000 inhabitants), four of the sixth stratum (cities with less than 5000 inhabitants) and finally six rural areas of the seventh stratum (rural zone). These cities are selected randomly with proportional probabilities to their size. In the second stage are selected the census zones (manzanas) that are used as sample points, with proportional probabilities to their size. In the third stage, the households are selected randomly through a systematic procedure. In each block a starting point is randomly chosen and the interval between the houses is predetermined by the general population density. In the fourth stage are selected the interviewees by quota (sex and age).

Remarks about sampling: Substitution permitted: Response refusal, empty house hold, psychologically ill or physically challenged (eg, deaf-mute).

The sample size for Uruguay is N=1000 and includes national population aged 18 years and over, for both sexes.

Mode of data collection

Face-to-face [f2f]

Sampling error estimates

+/- 3,2%

Uruguay was the Latin American country with the highest average monthly salary as of 2024, with a net value of around ***** U.S. dollars per month, followed by Costa Rica, with *** U.S. dollars per month. Employment development areas in Latin America Following the recuperation in this sector after the job losses endured throughout the COVID-19 pandemic, the unemployment rate persists in its endeavor to stabilize. Informal employment remains as the predominant actor across most Latin American countries, serving as a primary avenue for economic sustenance. Notably, the construction sector has experienced substantial growth, outpacing other relevant industries like tourism and hospitality. Poverty Throughout the past two decades, poverty levels in Latin America remain unchanged. Honduras takes the lead as the country bearing the highest poverty rate, with nearly half of its population dwelling in these circumstances. Across the region, the prevalent delineation is that of individuals classified within the non-extreme and lower-middle poverty strata, characterized by modest income levels.

Uruguay UY: Income Share Held by Highest 10% data was reported at 29.700 % in 2016. This records a decrease from the previous number of 29.900 % for 2015. Uruguay UY: Income Share Held by Highest 10% data is updated yearly, averaging 32.200 % from Dec 1981 (Median) to 2016, with 13 observations. The data reached an all-time high of 35.500 % in 2007 and a record low of 29.300 % in 2012. Uruguay UY: 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 Uruguay – Table UY.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.