Wages in the United States increased 4.78 percent in June of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In 2024, the salary increase across India was *** percent, a slight decline since last year. The salary increase in India was the highest among the Asia-Pacific countries. The salary growth is expected to stay the same in 2025 at *** percent. Sectors driving growth Sectors like Pharmaceuticals, manufacturing, insurance, captives, and SSO are projecting above the general industry salary median for 2025. With its highly skilled talent pool, India’s global capability centers (GCCs) are driving the projected salary increases. Outlook The projected increase in salary in 2025 is expected to be similar to 2024. Cost management, inflation, fear of recession, and a tighter labor market are some factors leading to 2025 projections. 2023 witnessed the highest salary increase during the recorded period, with a ** percent growth.

Graph and download economic data for Average Hourly Earnings of All Employees, Total Private (CES0500000003) from Mar 2006 to Jul 2025 about earnings, average, establishment survey, hours, wages, private, employment, and USA.

In March 2025, inflation amounted to 2.4 percent, while wages grew by 4.3 percent. The inflation rate has not exceeded the rate of wage growth since January 2023. Inflation in 2022 The high rates of inflation in 2022 meant that the real terms value of American wages took a hit. Many Americans report feelings of concern over the economy and a worsening of their financial situation. The inflation situation in the United States is one that was experienced globally in 2022, mainly due to COVID-19 related supply chain constraints and disruption due to the Russian invasion of Ukraine. The monthly inflation rate for the U.S. reached a 40-year high in June 2022 at 9.1 percent, and annual inflation for 2022 reached eight percent. Without appropriate wage increases, Americans will continue to see a decline in their purchasing power. Wages in the U.S. Despite the level of wage growth reaching 6.7 percent in the summer of 2022, it has not been enough to curb the impact of even higher inflation rates. The federally mandated minimum wage in the United States has not increased since 2009, meaning that individuals working minimum wage jobs have taken a real terms pay cut for the last twelve years. There are discrepancies between states - the minimum wage in California can be as high as 15.50 U.S. dollars per hour, while a business in Oklahoma may be as low as two U.S. dollars per hour. However, even the higher wage rates in states like California and Washington may be lacking - one analysis found that if minimum wage had kept up with productivity, the minimum hourly wage in the U.S. should have been 22.88 dollars per hour in 2021. Additionally, the impact of decreased purchasing power due to inflation will impact different parts of society in different ways with stark contrast in average wages due to both gender and race.

Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over (LES1252881600Q) from Q1 1979 to Q2 2025 about full-time, salaries, workers, earnings, 16 years +, wages, median, real, employment, and USA.

Wages in the United States increased to 31.34 USD/Hour in July from 31.26 USD/Hour in June of 2025. This dataset provides - United States Average Hourly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.

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 Mercer 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Mercer town, the median income for all workers aged 15 years and older, regardless of work hours, was $31,076 for males and $22,248 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 Mercer 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 Mercer town.

- Full-time workers, aged 15 years and older: In Mercer town, among full-time, year-round workers aged 15 years and older, males earned a median income of $71,273, while females earned $58,329, leading to a 18% gender pay gap among full-time workers. This illustrates that women earn 82 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Mercer town, showcasing a consistent income pattern irrespective of employment status.

https://i.neilsberg.com/ch/mercer-me-income-by-gender.jpeg" alt="Mercer, Maine gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-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 2022
• 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 Mercer town median household income by gender. You can refer the same here

Wages in China increased to 120698 CNY/Year in 2023 from 114029 CNY/Year in 2022. This dataset provides - China Average Yearly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Wages In the Euro Area increased 3.40 percent in March of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Euro Area Wage Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

As of November 2021, an average of ** percent of Poles had a pay rise in the past three months; relatively fewer employees aged between 45 and 65 received a salary increase than those in other age groups.

Wages in Manufacturing in the United States remained unchanged at 28.96 USD/Hour in July. This dataset provides - United States Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

As of November 2021, an average of ** percent of Poles had a pay rise in the past three months; relatively fewer women received a salary increase than men.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

The minimum wage per day guaranteed by law in Mexico was decreed to increase by approximately 12 percent between 2024 and 2025, reaching 278.8 Mexican pesos in 2025. The Northern Free Zone located near the northern border was the exception, where the minimum daily wage increased to 419.88 Mexican pesos. Education and income disparity The income distribution is entirely a new story than minimum wages, in fact, there are many factors that influence the level of salaries for Mexican workers. One of the main differences is by the number of schooling years, someone with more than 18 years of study earns on average double than employees with seven to nine years. Moreover, the area of study, while statistics and finance mean salaries, the highest wages by degree, are above 30,000 Mexican pesos per month, others such as performing arts and theology rank as the lowest paying degrees in Mexico.
Poverty still among the main problems
Despite one of the main reasons for minimum wage increases being moving people out from poverty conditions, poverty continues to be one of the main problems Mexican society faces. The number of people living under poverty conditions has decreased by 8.54 million inhabitants from 2014 to 2022, nonetheless, the figure is still higher than 46.5 million. The poverty rate varies among states, with Chiapas leading the ranking with 67.4 percent of the population under such conditions, while both Baja California and Baja California Sur recorded less than 14 percent.

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 Vian. 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Vian, the median income for all workers aged 15 years and older, regardless of work hours, was $23,355 for males and $16,833 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 Vian. 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 Vian.

- Full-time workers, aged 15 years and older: In Vian, among full-time, year-round workers aged 15 years and older, males earned a median income of $39,183, while females earned $30,401, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Vian, showcasing a consistent income pattern irrespective of employment status.

https://i.neilsberg.com/ch/vian-ok-income-by-gender.jpeg" alt="Vian, OK gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-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 2022
• 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 Vian median household income by gender. You can refer the same here

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 Florida 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Florida town, the median income for all workers aged 15 years and older, regardless of work hours, was $44,317 for males and $33,526 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 24% between the median incomes of males and females in Florida town. With women, regardless of work hours, earning 76 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Florida town.

- Full-time workers, aged 15 years and older: In Florida town, among full-time, year-round workers aged 15 years and older, males earned a median income of $61,072, while females earned $52,830, resulting in a 13% gender pay gap among full-time workers. This illustrates that women earn 87 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the town of Florida town.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Florida town.

https://i.neilsberg.com/ch/florida-ma-income-by-gender.jpeg" alt="Florida, Massachusetts gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-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 2022
• 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 Florida town median household income by gender. You can refer the same here

Wages in the United Kingdom increased 5 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United Kingdom Average Weekly Earnings Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Pakistan Average Monthly Wages data was reported at 24,028.000 PKR in 2021. This records an increase from the previous number of 21,326.000 PKR for 2019. Pakistan Average Monthly Wages data is updated yearly, averaging 12,636.500 PKR from Jun 2008 (Median) to 2021, with 10 observations. The data reached an all-time high of 24,028.000 PKR in 2021 and a record low of 6,612.000 PKR in 2008. Pakistan Average Monthly Wages data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G004: Average Monthly Wages: by Industry. No data for 2016-2017 as per source. Labour Force Survey has not been conducted for these two years due to Population Census.

Graph and download economic data for Employment Cost Index: Wages and Salaries: Private Industry Workers (ECIWAG) from Q1 2001 to Q2 2025 about cost, ECI, salaries, workers, private industries, wages, private, employment, industry, inflation, indexes, and USA.