According to an annual survey about Chinese women's workplace, the average monthly income of the female respondents in 2025 amounted to ***** yuan, about ** percent lower than the monthly salary of the male respondents. In the previous year, the average monthly income of female respondents was 8,958 yuan.

Although the Chinese government has implemented a variety of measures, the gender wage gap in 21st century China has not decreased. A significant body of literature has studied this phenomenon using sector segmentation theory, but these studies have overlooked the importance of the collective economy beyond the public and private sectors. Moreover, they have lacked assessment of the gender wage gap across different wage groups, hindering an accurate estimation of the gender wage gap in China, and the formulation of appropriate recommendations. Utilizing micro-level data from 2004, 2008, and 2013, this paper examines trends in the gender wage gap within the public sector, private sector, and collective economy. Employing a selection bias correction based on the multinomial logit model, this study finds that the gender wage gap is smallest and most stable within the public sector. Furthermore, the private sector surpasses the collective economy in this period, becoming the sector with the largest gender wage gap. Meanwhile, a recentered influence function regression reveals a substantial gender wage gap among the low-wage population in all three sectors, as well as among the high-wage population in the private sector. Additionally, employing Brown wage decomposition, this study concludes that inter-sector, rather than intra-sector, differences account for the largest share of the gender wage gap, with gender discrimination in certain sectors identified as the primary cause. Finally, this paper provides policy recommendations aimed at addressing the gender wage gap among low-wage groups and within the private sector.

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 China Grove. 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 China Grove, the median income for all workers aged 15 years and older, regardless of work hours, was $39,760 for males and $37,615 for females.

Based on these incomes, we observe a gender gap percentage of approximately 5%, indicating a significant disparity between the median incomes of males and females in China Grove. Women, regardless of work hours, still earn 95 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

- Full-time workers, aged 15 years and older: In China Grove, among full-time, year-round workers aged 15 years and older, males earned a median income of $50,568, while females earned $51,468

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.02 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

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 China Grove median household income by race. 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 China 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 China town, the median income for all workers aged 15 years and older, regardless of work hours, was $54,295 for males and $31,032 for females.

These income figures highlight a substantial gender-based income gap in China town. Women, regardless of work hours, earn 57 cents for each dollar earned by men. This significant gender pay gap, approximately 43%, underscores concerning gender-based income inequality in the town of China town.

- Full-time workers, aged 15 years and older: In China town, among full-time, year-round workers aged 15 years and older, males earned a median income of $58,056, while females earned $43,750, leading to a 25% gender pay gap among full-time workers. This illustrates that women earn 75 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.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in China town.

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

This statistic shows the gender pay gap for service workers in South Korea from 2009 to 2019. In 2019, female service workers earned about **** million South Korean won a month while male service workers earned about **** million won, indicating that female workers earned around ** percent of what male workers earned on average.

Although the Chinese government has implemented a variety of measures, the gender wage gap in 21st century China has not decreased. A significant body of literature has studied this phenomenon using sector segmentation theory, but these studies have overlooked the importance of the collective economy beyond the public and private sectors. Moreover, they have lacked assessment of the gender wage gap across different wage groups, hindering an accurate estimation of the gender wage gap in China, and the formulation of appropriate recommendations. Utilizing micro-level data from 2004, 2008, and 2013, this paper examines trends in the gender wage gap within the public sector, private sector, and collective economy. Employing a selection bias correction based on the multinomial logit model, this study finds that the gender wage gap is smallest and most stable within the public sector. Furthermore, the private sector surpasses the collective economy in this period, becoming the sector with the largest gender wage gap. Meanwhile, a recentered influence function regression reveals a substantial gender wage gap among the low-wage population in all three sectors, as well as among the high-wage population in the private sector. Additionally, employing Brown wage decomposition, this study concludes that inter-sector, rather than intra-sector, differences account for the largest share of the gender wage gap, with gender discrimination in certain sectors identified as the primary cause. Finally, this paper provides policy recommendations aimed at addressing the gender wage gap among low-wage groups and within the private sector.

The unadjusted gender pay gap in Russia reached **** percent in 2021. In other words, the difference between the average hourly wages of men and women amounted to nearly ** percent of the average hourly male wages. The higher this share is, the higher the difference is between male and female earnings in a country. Gender pay gap situation in Russia Over the period under consideration from 2005, Russia's gender pay gap generally decreased. In 2005, it peaked at nearly ** percent, while the lowest figure was marked in 2013, at below ** percent. Despite the recent decreases, as of 2021, there was not a single industry where women earned more than men in Russia. For example, in the information and communication industry, female employees earned on average **** thousand less than a month than male employees. Overall, across industries, a female's salary constituted **** percent of that of a man in Russia. Is gender pay equality likely in Russia? In the ranking of most gender-equal countries in the world, Russia placed 49th with an index of *** where zero referred to full equality and one meant full inequality. Furthermore, almost a half of Russians believed that full gender equality with respect to pay is unlikely in the country. To compare, ** percent of respondents in China believed the opposite, according to a survey from 2021.

The global gender gap index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2025, the country offering the most gender equal conditions was Iceland, with a score of 0.93. Overall, the Nordic countries make up 3 of the 5 most gender equal countries worldwide. The Nordic countries are known for their high levels of gender equality, including high female employment rates and evenly divided parental leave. Sudan is the second-least gender equal country Pakistan is found on the other end of the scale, ranked as the least gender equal country in the world. Conditions for civilians in the North African country have worsened significantly after a civil war broke out in April 2023. Especially girls and women are suffering and have become victims of sexual violence. Moreover, nearly 9 million people are estimated to be at acute risk of famine. The Middle East and North Africa have the largest gender gap Looking at the different world regions, the Middle East and North Africa have the largest gender gap as of 2023, just ahead of South Asia. Moreover, it is estimated that it will take another 152 years before the gender gap in the Middle East and North Africa is closed. On the other hand, Europe has the lowest gender gap in the world.

Although the Chinese government has implemented a variety of measures, the gender wage gap in 21st century China has not decreased. A significant body of literature has studied this phenomenon using sector segmentation theory, but these studies have overlooked the importance of the collective economy beyond the public and private sectors. Moreover, they have lacked assessment of the gender wage gap across different wage groups, hindering an accurate estimation of the gender wage gap in China, and the formulation of appropriate recommendations. Utilizing micro-level data from 2004, 2008, and 2013, this paper examines trends in the gender wage gap within the public sector, private sector, and collective economy. Employing a selection bias correction based on the multinomial logit model, this study finds that the gender wage gap is smallest and most stable within the public sector. Furthermore, the private sector surpasses the collective economy in this period, becoming the sector with the largest gender wage gap. Meanwhile, a recentered influence function regression reveals a substantial gender wage gap among the low-wage population in all three sectors, as well as among the high-wage population in the private sector. Additionally, employing Brown wage decomposition, this study concludes that inter-sector, rather than intra-sector, differences account for the largest share of the gender wage gap, with gender discrimination in certain sectors identified as the primary cause. Finally, this paper provides policy recommendations aimed at addressing the gender wage gap among low-wage groups and within the private sector.

China is the largest labor force market in the world. China’s economic prosperity wouldn’t exist without the large number of people working in this country. With increasing living standards and growing inflation, the wages of employees in China are increasing as well. As of 2022, average wages in China increased to ******* yuan from ****** yuan in 2012. Wage gap between regions The wages vary in China depending on sector, position, gender and region like in any other country. Since China’s different regions have developed unequally, the wage gaps between people working in different regions can also be very large. This is a reason for no single minimum wage being set for the entire nation. The local governments set minimum wages based on local living standards. Considering the city tier, the wage standards are higher in cities with higher rankings. ******** and ******* have the highest minimum wage standards in China. Although the minimum wages in China have been increasing, the standards are still lower than in developed countries. Challenges of increasing labor costs Increasing wages also make the labor force market less attractive. Affected by increasing labor costs and the China-United States trade war, many companies are transferring their investment destinations, especially in the manufacturing sector. Local governments are also taking measures to ensure the living costs remain at a reasonable level to retain companies and employees. These measures include regulating the residential housing market more strictly.

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 China township. 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 China township, the median income for all workers aged 15 years and older, regardless of work hours, was $59,101 for males and $27,440 for females.

These income figures highlight a substantial gender-based income gap in China township. Women, regardless of work hours, earn 46 cents for each dollar earned by men. This significant gender pay gap, approximately 54%, underscores concerning gender-based income inequality in the township of China township.

- Full-time workers, aged 15 years and older: In China township, among full-time, year-round workers aged 15 years and older, males earned a median income of $82,611, while females earned $46,667, leading to a 44% gender pay gap among full-time workers. This illustrates that women earn 56 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in China township, showcasing a consistent income pattern irrespective of employment status.

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

Parametric and semiparametric estimated wage equations, which correct for sample selection bias, are used to assess the returns to eduction and extent of ethnic discrimination in (Peninsular) Malaysia. In particular, this paper focuses on the level of discrimination between Malay and Chinese men and women. The Andrews-Schafgans (1998) estimator is used to estimate consistently the wage equation intercept in the semiparametric case. The results show that the Chinese-Malay offered wage difference typically is larger in absolute value among women than men. The strong discrimination favouring Chinese over Malays observed using the parametric results is negated by the semiparametric results.

This statistic shows the inequality of income distribution in China from 2005 to 2023 based on the Gini Index. In 2023, China reached a score of ************ points. The Gini Index is a statistical measure that is used to represent unequal distributions, e.g. income distribution. It can take any value between 1 and 100 points (or 0 and 1). The closer the value is to 100 the greater is the inequality. 40 or 0.4 is the warning level set by the United Nations. The Gini Index for South Korea had ranged at about **** in 2022. Income distribution in China The Gini coefficient is used to measure the income inequality of a country. The United States, the World Bank, the US Central Intelligence Agency, and the Organization for Economic Co-operation and Development all provide their own measurement of the Gini coefficient, varying in data collection and survey methods. According to the United Nations Development Programme, countries with the largest income inequality based on the Gini index are mainly located in Africa and Latin America, with South Africa displaying the world's highest value in 2022. The world's most equal countries, on the contrary, are situated mostly in Europe. The United States' Gini for household income has increased by around ten percent since 1990, to **** in 2023. Development of inequality in China Growing inequality counts as one of the biggest social, economic, and political challenges to many countries, especially emerging markets. Over the last 20 years, China has become one of the world's largest economies. As parts of the society have become more and more affluent, the country's Gini coefficient has also grown sharply over the last decades. As shown by the graph at hand, China's Gini coefficient ranged at a level higher than the warning line for increasing risk of social unrest over the last decade. However, the situation has slightly improved since 2008, when the Gini coefficient had reached the highest value of recent times.

This statistic shows the gender pay gap for workers in elementary occupations in South Korea from 2009 to 2019. In 2019, female workers earned about **** million South Korean won a month while male workers earned about **** million won, indicating that female workers in the occupation earned around **** percent of what male workers earned on average.

As of September 2021, the average salary of male Gen-Z employees in China reached ***** yuan, almost 1,000 yuan more than their female peers. The same source also revealed that nearly ** percent of male Gen-Zs had been promoted to management roles, while only ** percent of female employees said the same.

In 2024, the average annual per capita disposable income of rural households in China was approximately ****** yuan, roughly ** percent of the income of urban households. Although living standards in China’s rural areas have improved significantly over the past 20 years, the income gap between rural and urban households is still large. Income increase of China’s households From 2000 to 2020, disposable income per capita in China increased by around *** percent. The fast-growing economy has inevitably led to the rapid income increase. Furthermore, inflation has been maintained at a lower rate in recent years compared to other countries. While the number of millionaires in China has increased, many of its population are still living in humble conditions. Consequently, the significant wealth gap between China’s rich and poor has become a social problem across the country. However, in recent years rural areas have been catching up and disposable income has been growing faster than in the cities. This development is also reflected in the Gini coefficient for China, which has decreased since 2008. Urbanization in China The urban population in China surpassed its rural population for the first time in 2011. In fact, the share of the population residing in urban areas is continuing to increase. This is not surprising considering remote, rural areas are among the poorest areas in China. Currently, poverty alleviation has been prioritized by the Chinese government. The measures that the government has taken are related to relocation and job placement. With the transformation and expansion of cities to accommodate the influx of city dwellers, neighboring rural areas are required for the development of infrastructure. Accordingly, land acquisition by the government has resulted in monetary gain by some rural households.

data used in the article "Convergence effect of the Belt and Road Initiative on income disparity: evidence from China" in Humanities and Social Sciences Communications

In China, men are still considered as the major bread earner in a relationship. In 2020, women aged between 21 and 30 years expected their future partners to have a monthly salary above ****** yuan, while men at the same age only expected their partners to earn ***** yuan. The gender gap of salary expectations narrowed when it came to older generations.

IntroductionThis study conducted a survey of domestic violence victimization among women in China. Previously little research has been conducted on the subject of domestic violence against Chinese women as well as its relevance to their own economic power.MethodsUsing online questionnaires, this study collected data about 412 women with current or previous marital status who came from four income brackets in Beijing and Shanghai.ResultsIt revealed that the proportions of physical, emotional, economic, and sexual violence they experienced were about 27.91%, 62.38%, 21.12%, and 30.10%, respectively. Women belonging to the highest income bracket faced almost the same risk of domestic violence compared with other income groups. Furthermore, there was a slight upward tendency in physical and emotional violence victimization in the highest-income group. The binary logistic regression analysis showed that adverse childhood experiences, arguments between couples due to different opinions regarding gender ideologies, and the approval level for specific gender ideologies were common significant factors across different income brackets. When all income brackets were considered, a higher income was tested as a protective factor with regard to sexual violence. As for the income gap between couples, women whose incomes were “once higher than that of the husband but now lower/almost the same” or “always higher than that of the husband” faced a higher risk of physical violence than women whose incomes were “always lower than/almost the same as that of the husband.”DiscussionThis study not only revealed the reality of domestic violence victimization in China but also suggested that more attention should be paid to high-income women's domestic violence victimization as well as the importance of helping them both through academia and domestic violence support institutions.

The exponential growth of China’s digital economy has exerted a profound influence on economic advancement and income distribution. To effectively tackle income inequality, it is essential to incorporate the analysis of digital economy development within the framework of fiscal expenditure. This study utilizes a comprehensive panel dataset encompassing 276 cities in China during the period from 2011 to 2020. Employing the fixed-effect model and instrumental variable method, the research investigates the influence of fiscal expenditure on the income gap while investigating the moderating effect of the digital economy. The key findings of the study can be summarized as follows: (1) In general, fiscal expenditure demonstrates a propensity to reduce the income gap. (2) Different categories of fiscal expenditure exhibit distinct effects on the income gap. Social security and employment expenditures do not significantly alleviate the income gap. Conversely, education expenditures and health expenditures tend to exacerbate the income gap. On the other hand, expenditures in agriculture, forestry, and water resources, as well as urban and rural affairs, effectively narrow the income gap. (3) The development of the digital economy enhances the capacity of fiscal expenditure to adjust income distribution, showcasing non-linear effects. From a fiscal expenditure classification perspective, the digital economy primarily enhances the effectiveness of income distribution adjustment for expenditures in sectors such as agriculture, forestry, water resources, and others. Based on these findings, this study proposes a set of future measures aimed at facilitating China’s efforts to reduce the income gap within the framework of the digital economy. These measures encompass expediting the integration of the digital economy with government governance and advocating for the widespread adoption of digital government affairs platforms. By implementing these measures, China can gain valuable insights into effectively addressing income inequality and promoting more equitable economic outcomes within the context of the digital economy.