According to the respondents, only 30 percent had companies where the employees worked distributedly before the pandemic, whereas, after the pandemic it is projected that 48 percent of respondents' companies will have distributed workplaces. To work distributedly is different than working remote, as to "work distributedly" assumes that there is not a main location to work remote from in the first place. Instead, the company itself is distributed. This has significant implications for the future of organizations following the COVID-19 crisis.

Hybrid models of working are on the rise in the United States according to survey data covering worker habits between 2019 and 2024. In the second quarter of 2024, ** percent of U.S. workers reported working in a hybrid manner. The emergence of the COVID-19 pandemic saw a record number of people working remotely to help curb the spread of the virus. Since then, many workers have found a new shape to their home and working lives, finding that a hybrid model of working is more flexible than always being required to work on-site.

Introduction

Remote Work Statistics: The traditional office-based work model has undergone a significant transformation in recent years, with remote work becoming increasingly prevalent. As of 2024, approximately 30% of the global workforce engages in remote work at least part-time. In the United States, 12.7% of full-time employees work entirely from home, while 28.2% follow a hybrid model combining home and office work.

Productivity has seen notable improvements among remote workers. Studies indicate that remote employees are 35–40% more productive than their in-office counterparts, often working 1.4 additional days per month. Moreover, 77% of remote workers report higher productivity levels when working from home.

Financial benefits are also significant. Employers can save up to USD 11,000 per remote employee annually due to reduced overhead costs. Employees, on average, save approximately USD 4,000 per year on commuting and related expenses.

Employee well-being has improved with remote work. About 82% of remote workers report lower stress levels, and 78% experience better work-life balance. Additionally, companies offering remote work options see a 25% reduction in employee turnover.

These statistics highlight the evolving landscape of work, emphasizing the productivity gains, cost savings, and enhanced employee satisfaction associated with remote work arrangements. Let's examine some statistics to gain a better understanding of the current state of remote work.

In a global survey conducted with CIOs, respondents stated that fully remote work will likely transition to hybrid work in the future. About 15 to 16 percent stated their companies’ workforce worked remotely prior to the pandemic, and as of late 2021, 30 percent of respondents expected the workforce to be working remotely permanently. By 2022, 36 percent of respondents expected to be working in a hybrid model permanently.

In 2021, ** percent of employees from a global survey want flexible remote work options to stay post-pandemic. As businesses around the world sent their employees into home office and remote work setups during the 2020 COVID-19 pandemic, both employees and employers have become accustomed to this new work situation. As a result, they appreciate the positive aspects and would like to retain them in the future.

In June 2025, approximately 12 percent of workers in Great Britain worked from home exclusively, with a further 26 percent working from home and travelling to work, while 43 percent only travelled to work. During this time period, the share of people only travelling to work was highest in March 2022, at 60 percent of respondents, with the peak for only working from home occurring in June 2020. In general, hybrid working has become steadily more popular than fully remote working, with the highest share of people hybrid working in November 2023, when 31 percent of people advising they were hybrid working. What type of workers are most likely to work from home? In 2020, over half of people working in the agriculture sector mainly worked from home, which was the highest share among UK industry sectors at that time. While this industry was one of the most accessible for mainly working at home, just six percent of workers in the accommodation and food services sector mainly did this, the lowest of any sector. In the same year, men were slightly more likely to mainly work from home than women, while the most common age group for mainly working from home was those aged 75 and over, at 45.4 percent. Over a long-term period, the share of people primarily home working has grown from 11.1 percent in 1998, to approximately 17.4 percent in 2020. Growth of Flexible working in the UK According to a survey conducted in 2023, working from home either on a regular, or ad hoc basis was the most common type of flexible working arrangement offered by organizations in the UK, at 62 percent of respondents. Other popular flexible working arrangements include the ability to work flexible hours, work part-time, or take career breaks. Since 2013, for example, the number of employees in the UK that can work flextime has increased from 3.2 million, to around 4.2 million by 2024. When asked why flexible work was important to them, most UK workers said that it supported a better work-life balance, with 41 percent expressing that it made their commute to work more manageable.

United States Employment: NF: UT: Electric Power Transmission & Distribution data was reported at 232.700 Person th in May 2018. This records a decrease from the previous number of 232.900 Person th for Apr 2018. United States Employment: NF: UT: Electric Power Transmission & Distribution data is updated monthly, averaging 175.600 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 237.700 Person th in Jul 2016 and a record low of 154.600 Person th in Jan 2001. United States Employment: NF: UT: Electric Power Transmission & Distribution data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G024: Current Employment Statistics Survey: Employment: Non Farm.

United States Employment: NF: PW: UT: Natural Gas Distribution data was reported at 92.400 Person th in May 2018. This stayed constant from the previous number of 92.400 Person th for Apr 2018. United States Employment: NF: PW: UT: Natural Gas Distribution data is updated monthly, averaging 94.400 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 135.900 Person th in Jul 1991 and a record low of 87.600 Person th in Feb 2011. United States Employment: NF: PW: UT: Natural Gas Distribution data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G030: Current Employment Statistics Survey: Employment: Production Worker: Non Farm.

The original database. There are all the raw data of this study to calculate the Gini coefficient. The others census data can be found in the web site of National Bureau of Statistics of the People's Republic of China. (XLS)

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Banks. The dataset can be utilized to gain insights into gender-based income distribution within the Banks population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Banks, among individuals aged 15 years and older with income, there were 577 men and 776 women in the workforce. Among them, 436 men were engaged in full-time, year-round employment, while 280 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 0.69% fell within the income range of under $24,999, while 10% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 40.14% of men in full-time roles earned incomes exceeding $100,000, while 12.50% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

https://i.neilsberg.com/ch/banks-or-income-distribution-by-gender-and-employment-type.jpeg" alt="Banks, OR gender and employment-based income distribution analysis (Ages 15+)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

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.

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 Banks median household income by gender. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Hopkinton town. The dataset can be utilized to gain insights into gender-based income distribution within the Hopkinton town population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Hopkinton town, among individuals aged 15 years and older with income, there were 419 men and 312 women in the workforce. Among them, 196 men were engaged in full-time, year-round employment, while 117 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 8.16% fell within the income range of under $24,999, while 7.69% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 9.69% of men in full-time roles earned incomes exceeding $100,000, while 10.26% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

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.

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 Hopkinton town median household income by race. You can refer the same here

United States AHE: PW: PB: Ads Material Distribution & Other Advertising Svcs data was reported at 29.270 USD in Mar 2025. This records a decrease from the previous number of 29.550 USD for Feb 2025. United States AHE: PW: PB: Ads Material Distribution & Other Advertising Svcs data is updated monthly, averaging 15.560 USD from Jan 1990 (Median) to Mar 2025, with 423 observations. The data reached an all-time high of 30.290 USD in Dec 2022 and a record low of 8.620 USD in Jan 1990. United States AHE: PW: PB: Ads Material Distribution & Other Advertising Svcs data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Average Hourly Earnings: Production Workers.

Distribution of gross hourly earnings of full-time and part-time employees by sex, UK, quarterly, not seasonally adjusted. Labour Force Survey. These are official statistics in development.

employment statistics per sector from 1982 to 2008

This data set contains the distribution numbers of Istanbul Metropolitan Municipality employees according to their educational status.

In 2024, almost ** percent of employed people in Thailand were employed as private sector employees. By comparison, around ** percent of the workers in the country were own-account workers in that same year.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Forestville town. The dataset can be utilized to gain insights into gender-based income distribution within the Forestville town population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Forestville town, among individuals aged 15 years and older with income, there were 408 men and 392 women in the workforce. Among them, 270 men were engaged in full-time, year-round employment, while 174 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 4.44% fell within the income range of under $24,999, while 12.07% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 11.85% of men in full-time roles earned incomes exceeding $100,000, while 2.87% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

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.

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 Forestville town median household income by race. You can refer the same here

In 2023, 43.51 percent of the workforce in India were employed in agriculture, while the other half was almost evenly distributed among the two other sectors, industry and services. While the share of Indians working in agriculture is declining, it is still the main sector of employment. A BRIC powerhouseTogether with Brazil, Russia, and China, India makes up the four so-called BRIC countries. They are the four fastest-growing emerging countries dubbed BRIC, an acronym, by Jim O’Neill at Goldman Sachs. Being major economies themselves already, these four countries are said to be at a similar economic developmental stage -- on the verge of becoming industrialized countries -- and maybe even dominating the global economy. Together, they are already larger than the rest of the world when it comes to GDP and simple population figures. Among these four, India is ranked second across almost all key indicators, right behind China. Services on the riseWhile most of the Indian workforce is still employed in the agricultural sector, it is the services sector that generates most of the country’s GDP. In fact, when looking at GDP distribution across economic sectors, agriculture lags behind with a mere 15 percent contribution. Some of the leading services industries are telecommunications, software, textiles, and chemicals, and production only seems to increase – currently, the GDP in India is growing, as is employment.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Dane County. The dataset can be utilized to gain insights into gender-based income distribution within the Dane County population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Dane County, among individuals aged 15 years and older with income, there were 218,662 men and 215,256 women in the workforce. Among them, 129,108 men were engaged in full-time, year-round employment, while 99,012 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 5.38% fell within the income range of under $24,999, while 6.55% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 33.07% of men in full-time roles earned incomes exceeding $100,000, while 20.57% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

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.

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 Dane County median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Baldwin. The dataset can be utilized to gain insights into gender-based income distribution within the Baldwin population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Baldwin, among individuals aged 15 years and older with income, there were 1,092 men and 1,152 women in the workforce. Among them, 773 men were engaged in full-time, year-round employment, while 620 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 20.70% fell within the income range of under $24,999, while 8.23% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 8.28% of men in full-time roles earned incomes exceeding $100,000, while 7.10% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

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.

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 Baldwin median household income by race. You can refer the same here