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.

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.

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.

View yearly updates and historical trends for Mexico GINI Index. Source: World Bank. Track economic data with YCharts analytics.

Historical dataset showing Mexico income inequality - gini coefficient by year from N/A to N/A.

Gini Coefficient data was reported at 0.435 NA in 2022. This records a decrease from the previous number of 0.446 NA for 2020. Gini Coefficient data is updated yearly, averaging 0.501 NA from Dec 1984 (Median) to 2022, with 19 observations. The data reached an all-time high of 0.534 NA in 1994 and a record low of 0.435 NA in 2022. Gini Coefficient data remains active status in CEIC and is reported by Our World in Data. The data is categorized under Global Database’s Mexico – Table MX.OWID.ESG: Social: Gini Coefficient: Annual.

In 2022, the gini coefficient for rural areas in Mexico amounted to approximately 0.42 points. Between 2000 and 2022, the figure dropped by around 0.05 points, though the decline followed an uneven course rather than a steady trajectory.

In 2022, the gini coefficient for urban areas in Mexico was approximately 0.43 points. Between 2000 and 2022, the figure dropped by around 0.06 points, though the decline followed an uneven course rather than a steady trajectory.

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.

In 2022, about 40 percent of adults in Mexico held a net worth under 10,000 U.S. dollars. In contrast, merely 393,000 Mexicans (that is, 0.4 percent of the total) had a net worth of over one million U.S. dollars. Mexico is one of the most unequal countries in Latin America regarding wealth distribution, with 78.7 percent of the national wealth held by the richest ten percent of the population.

The minimum salaryThe minimum wage per day guaranteed by law in Mexico was decreed to increase by 22 percent between 2021 and 2022, reaching 172.87 Mexican pesos in 2022. In the Free Zone located near the northern border the minimum daily wage was raised to 260.34 Mexican pesos.This represented the fourth consecutive incrase since 2019, but could prove to be insufficient to maintain the wellbeing of Mexican workers after the soaring inflation rate registered in 2022 and the economic impact of the COVID-19 in Mexican households. The legal minimum salary has a long history in the North American country, it was first implemented with the approval of the Political Constitution of the United Mexican States in 1917. Income inequality in Latin AmericaLatin America, as other developing regions in the world, generally records high rates of inequality, with a Gini coefficient ranging between 38 and 54 among the region’s countries. Moreover, many of the countries with the biggest inequality in income distribution worldwide are found in Latin America. According to the Human Development Report 2019, 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.

These test data files were used to debug the code used in the following study: "Is the Gini Coefficient Enough? A Microeconomic Data Decomposition Study."

List of test data: 1. it14ih.dta - household-level dataset for Italy. 2. it14ip.dta - person-level dataset for Italy. 3. mx16ih.dta - household-level dataset for Mexico. 4. mx16ip.dta - person-level dataset for Mexico. 5. us18ih.dta - household-level dataset for the USA. 6. us18ip.dta - person-level dataset for the USA.

All files can be used for testing/debugging of the following scripts: lis_theil.R, lis_scv.R, lis_theil_functions.R, lis_scv_functions.R.

These datasets were donloaded from the following website. https://www.lisdatacenter.org/resources/self-teaching/.

MX：基尼系数（GINI系数）：世界银行估计在12-01-2016达43.400%，相较于12-01-2014的45.800%有所下降。MX：基尼系数（GINI系数）：世界银行估计数据按年更新，12-01-1984至12-01-2016期间平均值为48.300%，共15份观测结果。该数据的历史最高值出现于12-01-2000，达51.400%，而历史最低值则出现于12-01-2016，为43.400%。CEIC提供的MX：基尼系数（GINI系数）：世界银行估计数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的墨西哥 – 表 MX.世行.WDI：贫困。

The gini index in Canada was forecast to remain on a similar level in 2029 as compared to 2024 with 0.33 points. According to this forecast, the gini will stay nearly the same over the forecast period. The Gini coefficient here measures the degree of income inequality on a scale from 0 (=total equality of incomes) to one (=total inequality).The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).Find more key insights for the gini index in countries like United States and Mexico.

基尼系数在12-01-2022达0.435NA，相较于12-01-2020的0.446NA有所下降。基尼系数数据按年更新，12-01-1984至12-01-2022期间平均值为0.501NA，共19份观测结果。该数据的历史最高值出现于12-01-1994，达0.534NA，而历史最低值则出现于12-01-2022，为0.435NA。CEIC提供的基尼系数数据处于定期更新的状态，数据来源于Our World in Data，数据归类于全球数据库的墨西哥 – Table MX.OWID.ESG: Social: Gini Coefficient: Annual。

1. Change and intensification of forest use alter tropical ecosystems, influencing biodiversity and, subsequently, ecosystem functioning. The implications of eroding biodiversity may go beyond decreases in species diversity, resulting in changes of functional diversity, i.e. the diversity of ecological strategies present in the community, and functional redundancy, i.e. how redundant these strategies are to biodiversity loss. However, how environmental conditions and anthropogenic influences shape functional diversity and redundancy in tropical forests remains poorly understood.

2. Here, we examine how tropical forests respond to forest-use intensity along an extensive elevational gradient in Mexico from the tropical lowlands to high-elevational mountain forests (0 to 3500 m), in terms of functional diversity and functional redundancy, and how these biodiversity facets are related to forest structure. In our study, elevation was crossed with three levels of forest-use intensity: old-growth, degraded, and secondary forests. At eight elevational sites, five replicate plots were inventoried for each level of forest-use intensity (total n = 120 plots). Functional diversity and redundancy were calculated using leaf and wood traits of 144 tree species for Hill numbers zero, one, and two.

3. Interactive effects between elevation and forest-use intensity significantly affected biodiversity facets. However, interactive effects resulted from forest-use intensity influencing biodiversity facets at only a few elevations, and not from a consistent, negative impact of forest-use intensity. Forest structure, specifically stem density and the Gini coefficient, explained variation across biodiversity facets when these facets gave equal weight to common and rare species.

4. Synthesis and applications. High functional diversity and functional redundancy from lowland to mid-elevation tropical forests suggest that these ecosystems can be resilient to future disturbances. Our results indicate that the ability of high-elevation forests may be particularly susceptible to climate change and increasing forest-use intensity. For these high-elevation forests, we recommend that forest managers implement enrichment plantings with native species that can tolerate future environmental conditions. Finally, our study shows that efforts to conserve structurally heterogeneous forests and actively managing forests to increase structural heterogeneity will enhance the resilience of tropical forests while conserving their biodiversity.

In 2024, two of the three richest people in Latin America were Mexicans. The leader of the rank was the Mexican business magnate Carlos Slim, the 14th richest person in the world. Slim had a fortune of 102 billion U.S. dollars, derived from his multiple businesses and investments. At third place was a fellow Mexican businessman, German Larrea, with a fortune of nearly 27.3 billion dollars.

Billionaires' wealth distribution Within each country's economy, there exists a relatively small segment of wealthier individuals who contribute significantly to the Gross Domestic Product (GDP) of their respective countries. In Latin America, Chile stands out for its high concentration of wealth among billionaires, accounting for approximately 16 percent of the GDP. Mexico also exhibits a notable wealth concentration, with billionaires contributing around 12 percent of the country's GDP. Regarding the financial magnitude of these billionaires in Latin America, Mexico leads with an average individual wealth of approximately nine billion dollars, compared to an average wealth per adult of 43,140.
Income inequality In most countries within the region, the GINI Index, which measures income inequality among the population, falls within the range of 40 to 50. Notably, Colombia has the highest level of income inequality in Latin America, at 54.2. As a result of this income inequality, only around 2.8 percent of the population in the region is classified as having a high economic status, while the largest portion of the population consists of non-poor individuals with low incomes, and approximately 281 million people in the region live below the poverty line.