Graph and download economic data for Labor Force Participation Rate - Women (LNS11300002) from Jan 1948 to Feb 2025 about females, participation, 16 years +, labor force, labor, household survey, rate, and USA.

Graph and download economic data for Infra-Annual Labor Statistics: Labor Force Participation Rate Female: From 55 to 64 Years for United States (LRAC55FEUSM156N) from Jan 1955 to Feb 2025 about 55 to 64 years, females, participation, labor force, labor, rate, and USA.

This graph shows the unadjusted female labor force participation rate in the United States from 1990 to 2023. In 2023, about 57.3 percent of the female labor force participated in the job market.

Graph and download economic data for Labor Force Participation Rate - 20 Yrs. & over, White Women (LNU01300029) from Jan 1954 to Feb 2025 about 20 years +, females, participation, civilian, white, labor force, labor, household survey, rate, and USA.

In 2023, the female labor force participation rate in China remained nearly unchanged at around 60.54 percent. Nevertheless, this was the first time during the considered period that the rate declined, albeit slowly, in China. Female labor force participation is the share of women over 15 years who are economically active. For example, all women providing labor in a specific period for the production of goods and services.Find more statistics on other topics about China with key insights such as labor force participation rate for males.

This statistic shows the female labor force participation rate in Taiwan from 2000 to 2024. In 2024, approximately 52 percent of the Taiwan female population had been eligible to work.

The average for 2023 based on 11 countries was 54.22 percent. The highest value was in Cambodia: 69.46 percent and the lowest value was in India: 32.68 percent. The indicator is available from 1991 to 2023. Below is a chart for all countries where data are available.

Abstract

This data is from a quantitative survey administered in 2023 to 2,000 married Nepali women and men from 4 provinces in the country about their own beliefs regarding norms-related behaviors, their expectations of how common it is for others in their social group to engage in those behaviors, and the expected social consequences surrounding those behaviors. It is the primary dataset used to author the working paper titled "Women’s Labor Force Participation in Nepal: An Exploration of The Role of Social Norms" - which presents rigorous evidence on whether and the extent to which social norms matter for women's labor force participation in Nepal.

Geographic coverage

The survey data includes a representative sample of households from 4 out of 7 provinces in Nepal: 1. Bagmati Province 2. Sudurpashchim Province 3. Madhesh Province 4. Gandaki Province

Analysis unit

Individual

Universe

The sampling frame is a list of all wards within each selected province.

Kind of data

Sample survey data [ssd]

Sampling procedure

Ward (cluster) selection: The sampling frame consisted of the list of all wards within each selected province. Each province comprises districts and within each district are municipalities (urban and rural municipalities) which are further broken down into wards – the smallest administrative units. The list of wards and their population figures were taken from the latest available 2021 Census. First, the universe of all districts was stratified by urban and rural to ensure greater statistical power for detecting differences between the 2 localities. The stratification by urban-rural proportionate to the population proportion of each group within a province resulted in a self-weighted sample, allowing for analysis of data at the province level and further at locality level within each province. To select the wards, a random start point was generated to negate any bias in the list and to provide an independent chance of selection from the list. The sampling method used here, probability proportionate to size (PPS), gives an independent chance of selection to each ward as per its population size, i.e., a higher chance of selection to wards with a higher population size.38 As a first step of random selection of wards, the cumulative frequency (CF) of the population of households in a ward was calculated. Since the unit of analysis for our study purpose was households having certain criteria and we expected the main outcome variables (social norms) to vary at household levels (as opposed to at an individual level), the household population figures served as the basis for sampling purpose (as opposed to the population size of individuals for a ward). Applying PPS, in the first step, the required number of wards were selected for Categories 1 and 2 households (households with working and non-working females respectively). Following this, the clusters allocated for Category 3 (households with migrant population) households were taken as a subset of the wards selected for Categories 1 and 2.

Selection of the random starting point within each ward during in-field random sampling of households: The selection of the random starting point within a PSU was done by the survey supervisors. For every ward, a predefined landmark for the starting point was chosen. The predefined landmark consisted of i) school, ii) health post, iii) central marketplace, or iv) ward office. The selection of a predefined landmark was the basis of the starting point which was made at the central office. The chosen landmark for every cluster was rotated to account for randomization and to avoid interviewer bias. Once the landmark was chosen, each enumerator used the spin-the-bottle method to randomize the direction in which the survey took place. After starting with a household, enumerators used a skip interval to survey every third household in rural and every fifth household in urban areas. Once the household was chosen, the interviewer used the screener to ascertain the eligibility as per the category quota set aside for them.

Respondent selection: The respondents were selected based on a screener instrument that surveyed the following factors: 1. Gender: Since the views about social norms and labor market outcomes vary by gender, both males and females within a household were interviewed. However, for households with migrant men, only the women were interviewed. 2. Age group: For all women, the screener was applied so as to ensure that only women within the economically active age range, i.e., between the ages of 18-59 years were interviewed. For spouses of female respondents, they had to be at least 18 years of age with no maximum age limit set. 3. Ethnicity: Nepal has more than a hundred ethnic groups residing across the country, and thus the major 8-10 groups are captured in the sample. The other objective of applying a screener for monitoring ethnic composition was to ensure that marginalized ethnic groups such as Dalits were sufficiently represented in the survey. 4. Marital Status: Only married men and women were interviewed since marriage and the responsibilities that come with are sown to impose greater social barriers and restrictions on mobility and work of females. 5. Location: The survey was carried out in both rural and urban locations in a total of 4 provinces. 6. General demographic factors include: • Perceived economic situation: Low to middle-income • It was ensured that both the respondents (male and female for Categories 1 and 2) and female respondent for Category 3 belonged to the second generation of the selected household (for example, not the in-laws residing in a household but their son and his wife.

Mode of data collection

Computer Assisted Personal Interview [capi]

India: Female labor force participation rate: The latest value from 2023 is 32.68 percent, an increase from 27.99 percent in 2022. In comparison, the world average is 51.07 percent, based on data from 178 countries. Historically, the average for India from 1991 to 2023 is 28.57 percent. The minimum value, 25.94 percent, was reached in 2020 while the maximum of 32.68 percent was recorded in 2023.

In 2023, the female labor force participation rate in Egypt increased by 0.3 percentage points (+1.85 percent) compared to 2022. While the growth is slowing down, with 16.45 percent, the rate is at its peak in the observed period. Female labor force participation is the share of women over 15 years who are economically active. For example, all women providing labor in a specific period for the production of goods and services.Find more statistics on other topics about Egypt with key insights such as labor force participation rate for males, youth unemployment rate, and labor participation rate among the total population aged between 15 and 64.

As of 2021, the female labor force participation rate in Iran was 14 percent. The female labor force participation rate in Iran peaked in 2005 at 19 percent.

Labor force participation rate, female (% of female population ages 15+) (national estimate) in Brazil was reported at 53.1 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Brazil - Labor force participation rate, female (% of female population ages 15+) (national estimate) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

The average for 2023 based on 20 countries was 50.68 percent. The highest value was in Peru: 65.9 percent and the lowest value was in Puerto Rico: 32.01 percent. The indicator is available from 1991 to 2023. Below is a chart for all countries where data are available.

Historical and Projected Labor Force Participation Rate for Females in Maryland and its Jurisdictions, 1970-2045. Projected participation rates are calculated from rounded (to the nearest 10) population and labor force totals

Ireland: Female labor force participation rate: The latest value from 2023 is 59.87 percent, an increase from 59.38 percent in 2022. In comparison, the world average is 51.07 percent, based on data from 178 countries. Historically, the average for Ireland from 1991 to 2023 is 51.74 percent. The minimum value, 38.91 percent, was reached in 1992 while the maximum of 59.87 percent was recorded in 2023.

Saudi Arabia Labour Force Participation Rate: Saudi: Female data was reported at 35.538 % in Dec 2023. This records a decrease from the previous number of 35.943 % for Sep 2023. Saudi Arabia Labour Force Participation Rate: Saudi: Female data is updated quarterly, averaging 25.977 % from Jun 2016 (Median) to Dec 2023, with 31 observations. The data reached an all-time high of 37.045 % in Sep 2022 and a record low of 17.437 % in Mar 2017. Saudi Arabia Labour Force Participation Rate: Saudi: Female data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.G011: Labour Force: Participation Rate (Discontinued).

Labor force participation rate, female (% of female population ages 15+) (national estimate) in Iran was reported at 13.58 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Iran - Labor force participation rate, female (% of female population ages 15+) (national estimate) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

In 2024, around 56.3 percent of the female population in South Korea aged 15 years and older participated in the labor force, showing a slight increase from the previous year. The female labor force participation rate in South Korea has risen steadily in recent years but is still far below the average of the member countries of the Organization for Economic Co-operation and Development (OECD). South Korean women in the labor market More and more women in South Korea are actively participating in the labor market, yet they are still severely underrepresented. The comparatively low proportion of female managers, female workers in legal professions, and female lawmakers illustrates the deep-rooted gender inequality in this society that is also reflected in pay, for example, in the significantly lower female-to-male earnings ratio.This can be attributed to various social and cultural factors. After all, it is primarily women who are induced to work less due to child-rearing responsibilities. Poor chances of finding a job again after raising children cause many women to marry later or not at all. The way towards gender equality Many South Korean women are currently actively raising their voices, not least because achieving equality is a personally important issue for them. Particularly given the rapidly aging society, South Korea is thus faced with the task of reconciling work and family life and ultimately creating a sustainable social structure for everyone in the long term.

Graph and download economic data for Labor Force Participation Rate - 20 Yrs. & over, Women (LNS11300026) from Jan 1948 to Feb 2025 about 20 years +, females, participation, labor force, labor, household survey, rate, and USA.

Vietnam VN: Labour Force Participation Rate: Modeled ILO Estimate: Female: % of Female Population Aged 15-64 data was reported at 79.283 % in 2017. This records an increase from the previous number of 79.083 % for 2016. Vietnam VN: Labour Force Participation Rate: Modeled ILO Estimate: Female: % of Female Population Aged 15-64 data is updated yearly, averaging 79.281 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 80.252 % in 1991 and a record low of 78.105 % in 2009. Vietnam VN: Labour Force Participation Rate: Modeled ILO Estimate: Female: % of Female Population Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank: Labour Force. Labor force participation rate is the proportion of the population ages 15-64 that is economically active: all people who supply labor for the production of goods and services during a specified period.; ; International Labour Organization, ILOSTAT database. Data retrieved in March 2017.; Weighted average; Caution should be used when comparing ILO estimates with national estimates.