As of 2024, employees with doctorate degrees earned an average annual salary of **** million Indian rupees, the highest among other educational qualifications. Employees with high school or below high school level degree earned average salaries of just over ********* rupees in a year.

Wages in India increased to 21103 INR/Month in the second quarter of 2024 from 21036 INR/Month in the first quarter of 2024. This dataset provides the latest reported value for - India Average Daily Real Wage Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

As of January 2024, the state of Uttar Pradesh in India has the highest average monthly salary of about ** thousand Indian rupees. In contrast, Lakshadweep has the lowest average monthly salary of ***** thousand rupees during the same year.

In 2024, the average monthly salary was **** thousand Indian rupees in Mumbai city of India. The average monthly salary in the capital city of Delhi was around **** thousand Indian rupees. In comparison, the average monthly salary was over ** thousand Indian rupees in Madurai during the same year.

Data and insights on earnings & Wages in India - minimum wage, hours worked, employee benefits, and more.

The average salary for male employees in urban area was the highest during the months of April to June 2020 at about ** thousand Indian rupees. The average salary drawn by female workers was the highest in the months of April to June 2020, however, lesser compared to their male counterparts. Unsurprisingly, the urban earnings in terms of wages and salaries are always higher than rural employees. Urban versus rural employment The gender gap in salaries was more prominent in rural areas, where, the male workers earned nearly an average of *** times more. However, urban employees just earn a few thousands more than their rural counterpart, while, the cost of living in cities is twice as expensive as villages. Moreover, a majority of the Indian households belonged to the middle-income bracket and this is expected to increase in the future. Wage disparity Wage inequalities are present in almost every sector and widens with higher skill levels. With the evident gender disparity in the country, women with lower educational qualifications, such as a high school diplomas continue working despite the pay gap. This is among women who primarily come from the lower economic sector. Moreover, the social mobility index for fair wage distribution was **** as of 2020, indicating a need for improvement.

Explore the progression of average salaries for graduates in Computer Engineering-Based On Bs From India from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Computer Engineering-Based On Bs From India relative to other fields. This data is essential for students assessing the return on investment of their education in Computer Engineering-Based On Bs From India, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Computer Engineering India Diploma from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Computer Engineering India Diploma relative to other fields. This data is essential for students assessing the return on investment of their education in Computer Engineering India Diploma, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Indian Studies from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Indian Studies relative to other fields. This data is essential for students assessing the return on investment of their education in Indian Studies, providing a clear picture of financial prospects post-graduation.

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.

Explore the progression of average salaries for graduates in Computer Science (Edge Eval) (Ms Cs In India) from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Computer Science (Edge Eval) (Ms Cs In India) relative to other fields. This data is essential for students assessing the return on investment of their education in Computer Science (Edge Eval) (Ms Cs In India), providing a clear picture of financial prospects post-graduation.

India Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.800 % in 2021. This records a decrease from the previous number of 10.000 % for 2020. India Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 6.200 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 10.300 % in 2019 and a record low of 5.100 % in 2004. India 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 India – Table IN.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).

Explore the progression of average salaries for graduates in The University Of Burdwan, India from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of The University Of Burdwan, India relative to other fields. This data is essential for students assessing the return on investment of their education in The University Of Burdwan, India, providing a clear picture of financial prospects post-graduation.

The statistic displays the average salaries for selected jobs in the information technology industry in India per annum in *******, broken down by type. Entry-level employees working as Android developers had an average yearly salary of more than *** million Indian rupees in the IT sector during that time period.

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 Indian Beach. 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 Indian Beach, the median income for all workers aged 15 years and older, regardless of work hours, was $54,046 for males and $24,321 for females.

These income figures highlight a substantial gender-based income gap in Indian Beach. Women, regardless of work hours, earn 45 cents for each dollar earned by men. This significant gender pay gap, approximately 55%, underscores concerning gender-based income inequality in the town of Indian Beach.

As income data for both males and females was unavailable, conducting a comprehensive analysis of gender-based pay disparity in the town of Indian Beach was not possible.

https://i.neilsberg.com/ch/indian-beach-nc-income-by-gender.jpeg" alt="Indian Beach, NC 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 Indian Beach median household income by gender. You can refer the same here

ASI: Wages per Manday Worked: All Workers: All India data was reported at 363.760 INR in 2013. This records an increase from the previous number of 313.000 INR for 2012. ASI: Wages per Manday Worked: All Workers: All India data is updated yearly, averaging 180.270 INR from Mar 2000 (Median) to 2013, with 14 observations. The data reached an all-time high of 363.760 INR in 2013 and a record low of 138.090 INR in 2000. ASI: Wages per Manday Worked: All Workers: All India data remains active status in CEIC and is reported by Labour Bureau Government of India. The data is categorized under India Premium Database’s Labour Market – Table IN.GBB049: Annual Survey of Industries: Wages per Manday Worked: All Workers: by States.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Indian Head Park. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Indian Head Park. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Indian Head Park, the median household income stands at $226,538 for householders within the 25 to 44 years age group, followed by $143,201 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $73,929.

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.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

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 Indian Head Park median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Indian Creek. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Indian Creek. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Indian Creek, the median household income stands at $211,875 for householders within the 25 to 44 years age group, followed by $168,438 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $99,000.

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.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

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 Indian Creek median household income by age. You can refer the same here

Explore the progression of average salaries for graduates in Indian & Tandoori Cooking from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Indian & Tandoori Cooking relative to other fields. This data is essential for students assessing the return on investment of their education in Indian & Tandoori Cooking, providing a clear picture of financial prospects post-graduation.

The statistic illustrates the average salaries of selected senior level jobs in the information technology industry in India per annum in *******, broken down by type. App developers had an average yearly salary of more than *** million Indian rupees during that time period in the IT sector.