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

The average for 2024 based on 176 countries was 51.13 percent. The highest value was in Madagascar: 82.56 percent and the lowest value was in Yemen: 4.91 percent. The indicator is available from 1990 to 2024. Below is a chart for all countries where data are available.

Graph and download economic data for Labor Force Participation Rate - 20 Yrs. & over, White Women (LNS11300029) from Jan 1954 to Aug 2025 about 20 years +, white, females, participation, labor force, labor, household survey, rate, and USA.

The average for 2024 based on 11 countries was 55.17 percent. The highest value was in Cambodia: 73.96 percent and the lowest value was in India: 32.8 percent. The indicator is available from 1990 to 2024. Below is a chart for all countries where data are available.

Afghanistan: Female labor force participation rate: The latest value from 2024 is 5.1 percent, a decline from 5.16 percent in 2023. In comparison, the world average is 51.13 percent, based on data from 176 countries. Historically, the average for Afghanistan from 1990 to 2024 is 15.01 percent. The minimum value, 5.1 percent, was reached in 2024 while the maximum of 21.24 percent was recorded in 2017.

In 2024, the female labor force participation rate in Egypt amounted to ***** percent. Between 1990 and 2024, the figure dropped by **** percentage points, though the decline followed an uneven course rather than a steady trajectory.

Ukraine: Female labor force participation rate: The latest value from 2021 is 47.74 percent, a decline from 48.1 percent in 2020. In comparison, the world average is 50.21 percent, based on data from 180 countries. Historically, the average for Ukraine from 1990 to 2021 is 51.88 percent. The minimum value, 47.74 percent, was reached in 2021 while the maximum of 53.57 percent was recorded in 1990.

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

Nigeria: Female labor force participation rate: The latest value from 2024 is 80.71 percent, a decline from 80.77 percent in 2023. In comparison, the world average is 51.13 percent, based on data from 176 countries. Historically, the average for Nigeria from 1990 to 2024 is 77.7 percent. The minimum value, 76.93 percent, was reached in 2014 while the maximum of 80.77 percent was recorded in 2023.

In 2024, the female labor force participation rate in China was ***** percent. Between 1990 and 2024, the figure dropped by ***** percentage points, though the decline followed an uneven course rather than a steady trajectory.

Graph and download economic data for Labor Force Participation Rate - 20 Yrs. & over, Women (LNU01300026) from Jan 1948 to Aug 2025 about 20 years +, participation, females, civilian, labor force, labor, household survey, rate, and USA.

South Korea: Female labor force participation rate: The latest value from 2024 is 56.02 percent, a decline from 56.04 percent in 2023. In comparison, the world average is 51.13 percent, based on data from 176 countries. Historically, the average for South Korea from 1990 to 2024 is 50.63 percent. The minimum value, 47.12 percent, was reached in 1998 while the maximum of 56.04 percent was recorded in 2023.

Chad: Female labor force participation rate: The latest value from 2024 is 48.45 percent, a decline from 48.7 percent in 2023. In comparison, the world average is 51.13 percent, based on data from 176 countries. Historically, the average for Chad from 1990 to 2024 is 55.9 percent. The minimum value, 48.06 percent, was reached in 2020 while the maximum of 64.6 percent was recorded in 1992.

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 October of 2025.

Data showing labour force participation for women 1990 - 2021

Ratio of female to male labor force participation rate (%) (national estimate) in Indonesia was reported at 64.93 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Indonesia - Ratio of female to male labor force participation rate (national estimate) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

Labor force participation rate, female (% of female population ages 15+) (national estimate) in Kosovo was reported at 21.24 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kosovo - 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 October of 2025.

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]