71 datasets found
  1. Distribution of wealth held by percentile in Mexico 2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 4, 2025
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    Statista (2025). Distribution of wealth held by percentile in Mexico 2023 [Dataset]. https://www.statista.com/statistics/1294751/distribution-wealth-by-percentile-mexico/
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    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Mexico
    Description

    In 2023, from the total national wealth in Mexico, 70.2 percent belonged to the top ten percent group. Meanwhile, the bottom 50 percent had a total of 2.3 percent.

  2. Gini coefficient income distribution inequality in Mexico 2000-2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 4, 2025
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    Statista (2025). Gini coefficient income distribution inequality in Mexico 2000-2023 [Dataset]. https://www.statista.com/statistics/983198/income-distribution-gini-coefficient-mexico/
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    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Mexico
    Description

    Between 2010 and 2023, Mexico's data on the degree of inequality in income distribution based on the Gini coefficient decreased compared to the previous period, at 45.4. The Gini coefficient measures the deviation of the distribution of income (or consumption) 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. Poverty still one of the major problems During the last four years, the minimum wage in Mexico has been increasing substantially, going from 141.7 to 248.93 Mexican pesos per day. The main reason for this was to pull people out of poverty. In 2014, the population under the poverty line was over 46 percent, that is almost half of Mexicans living with conditions of vulnerability. Eight years later, the rate was about 36 percent, still a significant number of people living in poverty but a considerable decrease. Gender inequality Mexico does not score particularly well in gender inequality, in fact, it ranks 33rd in the world in the Global Gender Gap Index. Despite some advances, the Aztec country performs poorly in most of the metrics that measure inequality. During late 2022, women recorded a pay disparity of –13.15 percent when compared to them male counterparts. That is to say, that for the same job a woman is paid 87.85 MXP when a man receives 100 MXP.

  3. Mexico: Gini coefficient income distribution inequality 2022, by state

    • statista.com
    • ai-chatbox.pro
    Updated Jul 5, 2024
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    Statista (2024). Mexico: Gini coefficient income distribution inequality 2022, by state [Dataset]. https://www.statista.com/statistics/1040573/income-distribution-gini-coefficient-mexico-state/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Mexico
    Description

    Chiapas, the state with the highest share of population living in poverty, had the highest wealth inequality in the country based on the Gini coefficient as well. This index measures the deviation of the income distribution situation in a given country from a perfectly equal distribution. A value of 0 represents an ideal situation of equality, whereas 1 would be the highest possible degree of inequality. As of 2022, Mexico City, the country's capital, had a Gini coefficient of 0.46, second highest recorded figure.

  4. N

    Income Distribution by Quintile: Mean Household Income in Mexico, MO // 2025...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Mexico, MO // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/48335882-f81d-11ef-a994-3860777c1fe6/
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    json, csvAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Mexico, Missouri
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the mean household income for each of the five quintiles in Mexico, MO, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 10,617, while the mean income for the highest quintile (20% of households with the highest income) is 160,507. This indicates that the top earners earn 15 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 284,944, which is 177.53% higher compared to the highest quintile, and 2683.85% higher compared to the lowest quintile.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income Levels:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Mexico median household income. You can refer the same here

  5. Mexico MX: Gini Coefficient (GINI Index): World Bank Estimate

    • ceicdata.com
    Updated Feb 15, 2019
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    CEICdata.com (2019). Mexico MX: Gini Coefficient (GINI Index): World Bank Estimate [Dataset]. https://www.ceicdata.com/en/mexico/poverty/mx-gini-coefficient-gini-index-world-bank-estimate
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    Dataset updated
    Feb 15, 2019
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1996 - Dec 1, 2016
    Area covered
    Mexico
    Description

    Mexico MX: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 43.400 % in 2016. This records a decrease from the previous number of 45.800 % for 2014. Mexico MX: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 48.300 % from Dec 1984 (Median) to 2016, with 15 observations. The data reached an all-time high of 51.400 % in 2000 and a record low of 43.400 % in 2016. Mexico MX: 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 Mexico – Table MX.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.

  6. M

    Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total population [Dataset]. https://www.ceicdata.com/en/mexico/social-poverty-and-inequality/multidimensional-poverty-headcount-ratio-world-bank--of-total-population
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2010 - Dec 1, 2022
    Area covered
    Mexico
    Description

    Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 1.700 % in 2022. This records a decrease from the previous number of 2.600 % for 2020. Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 2.900 % from Dec 2010 (Median) to 2022, with 7 observations. The data reached an all-time high of 5.700 % in 2010 and a record low of 1.700 % in 2022. Mexico 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 Mexico – Table MX.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).

  7. Average monthly wages in Mexico in 2023, by gender

    • ai-chatbox.pro
    • statista.com
    Updated Jun 4, 2025
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    Statista (2025). Average monthly wages in Mexico in 2023, by gender [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstatistics%2F1350708%2Faverage-monthly-wages-by-gender-mexico%2F%23XgboD02vawLbpWJjSPEePEUG%2FVFd%2Bik%3D
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    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 2023
    Area covered
    Mexico
    Description

    In Mexico as of the third quarter of 2023, there was a higher standard monthly wage for the male population with 8,473 Mexican pesos, while women got 7,281 MXP. Thus, the male population got a higher income around 16 percent more than the female population.

  8. Gender pay gap in Mexico in 2022, by educational attainment

    • ai-chatbox.pro
    • statista.com
    Updated May 22, 2025
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    Statista (2025). Gender pay gap in Mexico in 2022, by educational attainment [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstatistics%2F1350664%2Fgender-pay-disparity-by-educational-attainment-mexico%2F%23XgboD02vawLKoDs%2BT%2BQLIV8B6B4Q9itA
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    Dataset updated
    May 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2022
    Area covered
    Mexico
    Description

    As of March 2022, there was a positive correlation between the educational attainment and the income Mexican women would get. The lowest income that women got for every 100 Mexican pesos that a man would get by educational attainment was for the women with pre-primary education and lower with 58 pesos. In the contrast, the women with higher education got 92 pesos.

  9. M

    Mexico Poverty Headcount Ratio at Societal Poverty Lines: % of Population

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Mexico Poverty Headcount Ratio at Societal Poverty Lines: % of Population [Dataset]. https://www.ceicdata.com/en/mexico/social-poverty-and-inequality/poverty-headcount-ratio-at-societal-poverty-lines--of-population
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2002 - Dec 1, 2022
    Area covered
    Mexico
    Description

    Mexico Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 22.500 % in 2022. This records a decrease from the previous number of 24.700 % for 2020. Mexico Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 29.450 % from Dec 1989 (Median) to 2022, with 18 observations. The data reached an all-time high of 34.600 % in 1998 and a record low of 22.500 % in 2022. Mexico 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 Mexico – Table MX.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).

  10. Mexico Income share held by highest 20%

    • knoema.com
    csv, json, sdmx, xls
    Updated Jun 30, 2025
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    Knoema (2025). Mexico Income share held by highest 20% [Dataset]. https://knoema.com/atlas/Mexico/topics/Poverty/Income-Inequality/Income-share-held-by-highest-20percent
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    csv, sdmx, xls, jsonAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    2002 - 2022
    Area covered
    Mexico
    Variables measured
    Income share held by highest 20%
    Description

    Income share held by highest 20% of Mexico dipped by 1.78% from 50.70 % in 2020 to 49.80 % in 2022. Since the 3.76% rise in 2012, income share held by highest 20% dropped by 9.78% in 2022. 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.

  11. Mexico MX: Proportion of People Living Below 50 Percent Of Median Income: %

    • ceicdata.com
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    CEICdata.com, Mexico MX: Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/mexico/social-poverty-and-inequality/mx-proportion-of-people-living-below-50-percent-of-median-income-
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    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2002 - Dec 1, 2022
    Area covered
    Mexico
    Description

    Mexico MX: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 15.300 % in 2022. This records a decrease from the previous number of 18.100 % for 2020. Mexico MX: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 18.650 % from Dec 1989 (Median) to 2022, with 18 observations. The data reached an all-time high of 24.800 % in 1996 and a record low of 15.300 % in 2022. Mexico MX: 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 Mexico – Table MX.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).

  12. Mexico MX: Survey Mean Consumption or Income per Capita: Total Population:...

    • ceicdata.com
    + more versions
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    CEICdata.com, Mexico MX: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day [Dataset]. https://www.ceicdata.com/en/mexico/social-poverty-and-inequality/mx-survey-mean-consumption-or-income-per-capita-total-population-2017-ppp-per-day
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    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2016 - Dec 1, 2022
    Area covered
    Mexico
    Description

    Mexico MX: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 16.590 Intl $/Day in 2022. This records an increase from the previous number of 14.770 Intl $/Day for 2016. Mexico MX: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 15.680 Intl $/Day from Dec 2016 (Median) to 2022, with 2 observations. The data reached an all-time high of 16.590 Intl $/Day in 2022 and a record low of 14.770 Intl $/Day in 2016. Mexico MX: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

  13. b

    Macroeconomic model (GAMS) for poverty reduction in Mexico

    • bonndata.uni-bonn.de
    • daten.zef.de
    csv, png, txt, xml +1
    Updated Sep 18, 2023
    + more versions
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    José Luis Viveros Añorve; José Luis Viveros Añorve (2023). Macroeconomic model (GAMS) for poverty reduction in Mexico [Dataset]. http://doi.org/10.60507/FK2/CNOY41
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    txt(1754), zip(470183), csv(6032), png(70512), xml(31068)Available download formats
    Dataset updated
    Sep 18, 2023
    Dataset provided by
    bonndata
    Authors
    José Luis Viveros Añorve; José Luis Viveros Añorve
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Dec 31, 2012
    Area covered
    Chiapas, Mexico
    Description

    A Computable General Equilibrium (CGE) model in a bottom-up approach - based on microfoundations - and a Social Accounting Matrix (SAM) for the regional economy of Chiapas are built. Methodology: This research applies a Computable General Equilibrium (CGE) model. It is a system of equations that describes an entire economy and all the interactions between productive sectors, commodity and factor markets, and institutions. All of the equations are solved simultaneously to find an economy-wide equilibrium in which demand and supply quantities are equal in every market at a certain level of prices (Burfisher, 2011). Two of the features of this model are that, on one hand, it implements a “bottom-up” approach, that is, it is focused on individual markets and economic agents. On the other hand, it is partially synthetic. In other words, most parameters can be calibrated with data from the SAM. Data framework: A Social Accounting Matrix (SAM) is a balanced square matrix that represents all income and expenditure flows between productive sectors, markets, and economic agents of an economy at a given period of time (Müller, Perez & Hubertus, 2009). It is based on the double entry bookkeeping in accounting, which requires that total revenue equals total expenditure in each single account included in the SAM (Breisinger, Thomas & Thurlow, 2010). The main features of the Chiapas SAM are that production activities are broken down in 10 sectors, according to the North American Industry Classification System (NAICS). There is one commodity per economic activity. Factors of production are disaggregated into formal and informal labor, and capital. Direct taxes are broken up into activity tax, social security contributions, household and corporate income taxes, ‘tenencia’ tax (ownership tax, i.e. a tax associated with the possession or use of vehicles), and regional payroll tax (‘nomina’). Indirect taxes, in turn, are value-added, sales and export taxes, and import tariffs. Subsidies on production by economic activity are also included. Households are disaggregated by income quintiles. Social transfers are split in non-conditional (Procampo, universal pension, PAL-Sin Hambre , temporary employment program, and the regional program Amanecer ) and Oportunidades. The latter is also broken down into its five components: food, elderly, education, child, and energy. The introduction of conditional cash transfers in the SAM is particularly relevant because it allows assessing the impact of changes in their amount and distribution on household income, poverty reduction, income inequality, and economic growth at the regional level. Data sources: - National Institute of Statistics and Geography (INEGI): 2012 National Employment and Occupation Survey 2013 Chiapas Statistical Yearbook 2012 National Household Income-Expenditure Survey 2012 Chiapas Statistical Perspective 2003-2012 Goods and Services Accounts (SCNM) 2003-2012 Institutional Sector Accounts (SCNM) 2008 Input-Output Table 2008 Supply and Use Tables - Chiapas State Committee of Statistical and Geographical Information (CEIEG): 2012 Chiapas Employment and Occupation Survey 2012 Chiapas Monthly Statistical Reports of IMSS-insured Workers - Federal Ministry of Labor and Social Welfare (STYPS): 2012 IMSS-registered Daily Salary by Economic Activity 2012 IMSS-insured Workers Quality/Lineage: With the raw data a Social Accounting Matrix for the regional economy of Chiapas was built Features: - Oportunidades broken down by component - Other non-conditional social transfers such as Procampo, PAL-Sin Hambre, Employment program, Universal pension, and the regional program 'Amanecer' - Informal wages - Satellites tables of formal and informal employment - Productive activities according to the North American Industry Classification System (NAICS) used in Mexico, Canada, and the United States of America - 10 economic activities - 10 Commodities (one per economic activity) - Factors of production: formal and informal labor and capital Purpose: 1. To assess the opportunity cost of financing "Oportunidades", Mexico's conditional cash transfers program, and its implications for rural development and rural economic growth in the regional setting of Chiapas. Moreover, 2. Pro-growth and pro-poor tax structures are also evaluated by applying standard economic analysis tools and modeling to substantially raise the federal non-oil tax revenue to finance social policy for poverty and inequality reduction. Dissertation: Viveros Añorve, J. L. (2015): The opportunity cost of financing "Oportunidades": a general equilibrium assessment for poverty reduction in Mexico. Ph.D. dissertation. Center for Development Research, Faculty of Agriculture, University of Bonn

  14. o

    Long-Term Income Inequality in Latin America

    • openicpsr.org
    Updated Aug 13, 2024
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    Pablo Astorga (2024). Long-Term Income Inequality in Latin America [Dataset]. http://doi.org/10.3886/E208482V1
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    Dataset updated
    Aug 13, 2024
    Dataset provided by
    Institut Barcelona d'Estudis Internacionals
    Authors
    Pablo Astorga
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    1920 - 2011
    Area covered
    Latin America
    Description

    This is the replication package for Astorga, Pablo. 2024. Revealing the diversity and complexity of long-term income inequality in Latin America: 1920-2011. Journal of Economic History, 84(4).This paper analyses and documents new long-term income inequality series for Argentina, Brazil, Chile, Colombia, Mexico and Venezuela based on dynamic social tables with four occupational groups. This enables the calculation of comparable Overall (4 groups) and Labor Ginis (3 groups) with their between- and within-groups components. The main findings are: the absence of a unique inequality pattern over time; country outcomes characterized by trajectory diversity and level divergence during industrialization, and by commonality and convergence post 1980; the occurrence of inequality-levelling episodes with different timing and length; and significant changes in trends, but also evidence indicating persistence.

  15. M

    Mexico MX: Poverty Gap at $2.15 a Day: 2017 PPP: %

    • ceicdata.com
    + more versions
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    CEICdata.com, Mexico MX: Poverty Gap at $2.15 a Day: 2017 PPP: % [Dataset]. https://www.ceicdata.com/en/mexico/social-poverty-and-inequality/mx-poverty-gap-at-215-a-day-2017-ppp-
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2002 - Dec 1, 2022
    Area covered
    Mexico
    Description

    Mexico MX: Poverty Gap at $2.15 a Day: 2017 PPP: % data was reported at 0.300 % in 2022. This records a decrease from the previous number of 0.600 % for 2020. Mexico MX: Poverty Gap at $2.15 a Day: 2017 PPP: % data is updated yearly, averaging 2.000 % from Dec 1989 (Median) to 2022, with 18 observations. The data reached an all-time high of 5.200 % in 1998 and a record low of 0.300 % in 2022. Mexico MX: Poverty Gap at $2.15 a Day: 2017 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Social: Poverty and Inequality. Poverty gap at $2.15 a day (2017 PPP) is the mean shortfall in income or consumption from the poverty line $2.15 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.;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).

  16. Mexico Income share held by lowest 20%

    • knoema.com
    csv, json, sdmx, xls
    Updated Jun 30, 2025
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    Knoema (2025). Mexico Income share held by lowest 20% [Dataset]. https://knoema.com/atlas/Mexico/topics/Poverty/Income-Inequality/Income-share-held-by-lowest-20percent
    Explore at:
    csv, sdmx, json, xlsAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    2002 - 2022
    Variables measured
    Income share held by lowest 20%
    Description

    Income share held by lowest 20% of Mexico leapt by 5.66% from 5.30 % in 2020 to 5.60 % in 2022. Since the 4.35% downward trend in 2012, income share held by lowest 20% rocketed by 27.27% in 2022. 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.

  17. Mexico: per capita income 2022, by deciles

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Mexico: per capita income 2022, by deciles [Dataset]. https://www.statista.com/statistics/1040568/per-capita-income-value-deciles-mexico/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Mexico
    Description

    In 2022, it was reported that ten percent of the Mexican population with the highest monthly income made, on average, almost ** times more money than the ten percent of the population with the lowest income. While a person in the highest earning segment of the population (decile X) received approximately ****** Mexican pesos per month, a person in the decile with the lowest monthly income (decile I) earned nearly ***** pesos. In that same year, it was estimated that ** percent of the population in Mexico lived in poverty. Chiapas was the state in Mexico with the highest average poverty rate, with ** percent of the population in this state classified as living in poverty.

  18. N

    Mexico Town, New York annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
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    Neilsberg Research (2025). Mexico Town, New York annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/mexico-town-ny-income-by-gender/
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    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New York
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Mexico town. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Mexico town, the median income for all workers aged 15 years and older, regardless of work hours, was $41,639 for males and $30,074 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Mexico town. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Mexico town.

    - Full-time workers, aged 15 years and older: In Mexico town, among full-time, year-round workers aged 15 years and older, males earned a median income of $64,934, while females earned $37,429, leading to a 42% gender pay gap among full-time workers. This illustrates that women earn 58 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

    Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that Mexico town offers better opportunities for women in non-full-time positions.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Mexico town median household income by race. You can refer the same here

  19. Mexico MX: Multidimensional Poverty Intensity (average share of deprivations...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Mexico MX: Multidimensional Poverty Intensity (average share of deprivations experienced by the poor) [Dataset]. https://www.ceicdata.com/en/mexico/social-poverty-and-inequality/mx-multidimensional-poverty-intensity-average-share-of-deprivations-experienced-by-the-poor
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2010 - Dec 1, 2020
    Area covered
    Mexico
    Description

    Mexico MX: Multidimensional Poverty Intensity (average share of deprivations experienced by the poor) data was reported at 2.400 % in 2020. This records an increase from the previous number of 2.300 % for 2018. Mexico MX: Multidimensional Poverty Intensity (average share of deprivations experienced by the poor) data is updated yearly, averaging 2.350 % from Dec 2010 (Median) to 2020, with 6 observations. The data reached an all-time high of 2.600 % in 2010 and a record low of 2.200 % in 2016. Mexico MX: 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 Mexico – Table MX.World Bank.WDI: Social: Poverty and Inequality. ;Government statistical agencies. Data for EU countires are from the EUROSTAT;;

  20. Mexico MX: Income Share Held by Lowest 20%

    • ceicdata.com
    Updated Feb 15, 2019
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    CEICdata.com (2019). Mexico MX: Income Share Held by Lowest 20% [Dataset]. https://www.ceicdata.com/en/mexico/poverty/mx-income-share-held-by-lowest-20
    Explore at:
    Dataset updated
    Feb 15, 2019
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1996 - Dec 1, 2016
    Area covered
    Mexico
    Description

    Mexico MX: Income Share Held by Lowest 20% data was reported at 5.700 % in 2016. This records an increase from the previous number of 5.400 % for 2014. Mexico MX: Income Share Held by Lowest 20% data is updated yearly, averaging 4.500 % from Dec 1984 (Median) to 2016, with 15 observations. The data reached an all-time high of 5.700 % in 2016 and a record low of 3.900 % in 2000. Mexico MX: Income Share Held by Lowest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.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.

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Statista (2025). Distribution of wealth held by percentile in Mexico 2023 [Dataset]. https://www.statista.com/statistics/1294751/distribution-wealth-by-percentile-mexico/
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Distribution of wealth held by percentile in Mexico 2023

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 4, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
Mexico
Description

In 2023, from the total national wealth in Mexico, 70.2 percent belonged to the top ten percent group. Meanwhile, the bottom 50 percent had a total of 2.3 percent.

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