Graph and download economic data for Expenditures: Personal Insurance and Pensions by Type of Area: Rural (CXUINSPENSNLB1805M) from 1984 to 2020 about rural, pension, insurance, expenditures, personal, and USA.

In 2023, the percentage of trained labor force in Vietnam's rural regions amounted to roughly **** percent for males and ** percent for females. The trained labor force accounted for **** percent of Vietnam's overall labor force in that particular year.

In 2024, around *** million people were employed in urban areas of China, while around *** million were employed in rural areas. The number of urban employees has increased considerably over the last decades. However, the growth of the urban workforce is slowing down as the total number of employees in China has already been decreasing since 2014.

Graph and download economic data for Income Before Taxes: Other Income by Type of Area: Rural (CXUOTHRINCLB1805M) from 1984 to 2020 about rural, tax, income, and USA.

Ecuador Employment Rate: Rural: Unpaid Labor: White data was reported at 18.425 % in Jun 2019. This records an increase from the previous number of 17.012 % for Mar 2019. Ecuador Employment Rate: Rural: Unpaid Labor: White data is updated quarterly, averaging 12.680 % from Dec 2013 (Median) to Jun 2019, with 23 observations. The data reached an all-time high of 21.906 % in Sep 2016 and a record low of 5.174 % in Mar 2016. Ecuador Employment Rate: Rural: Unpaid Labor: White data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.G021: ENEMDU: Employment Rate: Rural.

Graph and download economic data for Net Change in Total Assets and Liabilities by Type of Area: Rural (CXUCHGASLILB1805M) from 1990 to 2020 about rural, change, liabilities, Net, assets, and USA.

Ecuador Employment Rate: Rural: Unpaid Labor: Afro Ecuatorian data was reported at 11.317 % in Jun 2019. This records an increase from the previous number of 11.315 % for Mar 2019. Ecuador Employment Rate: Rural: Unpaid Labor: Afro Ecuatorian data is updated quarterly, averaging 9.991 % from Dec 2013 (Median) to Jun 2019, with 23 observations. The data reached an all-time high of 15.505 % in Mar 2018 and a record low of 4.471 % in Dec 2018. Ecuador Employment Rate: Rural: Unpaid Labor: Afro Ecuatorian data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.G021: ENEMDU: Employment Rate: Rural.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employment-to-population ratio is the number of persons who are employed as a percent of the total of working-age population. For more information, refer to the Rural and Urban Labour Market Statistics (RURBAN) database description.

Ecuador Employment: Rural: Unpaid Labor: Indigenous data was reported at 229,183.402 Person in Jun 2019. This records a decrease from the previous number of 274,073.774 Person for Mar 2019. Ecuador Employment: Rural: Unpaid Labor: Indigenous data is updated quarterly, averaging 183,330.196 Person from Dec 2013 (Median) to Jun 2019, with 23 observations. The data reached an all-time high of 274,073.774 Person in Mar 2019 and a record low of 96,587.114 Person in Jun 2014. Ecuador Employment: Rural: Unpaid Labor: Indigenous data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.G018: ENEMDU: Employment: Rural.

Graph and download economic data for Consumer Unit Characteristics: Number of Children Under 18 by Type of Area: Rural (CXU980050LB1805M) from 1984 to 2020 about rural, consumer unit, child, and USA.

Transaction history of property transfers, consolidations, and sales within the USDA Rural Development Multifamily Direct Loan programs: Section 515 Rural Rental Housing and Section 514 Farm Labor Housing. Includes new property ID numbers and associated old property ID numbers, transaction type indicators, and effective dates. Requires merging with “USDA Rural Development Multifamily Section 515 Rural Rental Housing and Section 514 Farm Labor Housing Property Characteristics” to obtain property address and other characteristics based on new property ID number.

This scatter chart displays unemployment (% of total labor force) against rural population (people). The data is about countries.

This scatter chart displays rural population (people) against unemployment (% of total labor force) in the United States. The data is about countries per year.

This link contains downloadable data for the Atlas of Rural and Small-Town America which provides statistics by broad categories of socioeconomic factors: People: Demographic data from the American Community Survey (ACS), including age, race and ethnicity, migration and immigration, education, household size, and family composition. Jobs: Economic data from the Bureau of Labor Statistics and other sources, including information on employment trends, unemployment, and industrial composition of employment from the ACS. County classifications: Categorical variables including the rural-urban continuum codes, economic dependence codes, persistent poverty, persistent child poverty, population loss, onshore oil/natural gas counties, and other ERS county typology codes. Income: Data on median household income, per capita income, and poverty (including child poverty). Veterans: Data on veterans, including service period, education, unemployment, income, and other demographic characteristics.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..Armed Forces data are not shown for the population 65 years and over..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

In 2014, the United States Department of Agriculture's Economic Research Service (USDA ERS) conducted the Rural Establishment Innovation Survey (REIS). This survey provides a nationally representative sample of innovation processes in rural businesses. REIS defines innovation as the introduction of new goods, services, or ways of doing business that are valued by consumers. Traditional measures from secondary data sources, such as patents or research and development (R&D) expenditures, focus on science and engineering-based innovation, which usually depict rural innovation as rare or idiosyncratic. By focusing instead on a broader definition of innovation, the REIS provides a fuller assessment of rural innovative capacity. The main research questions for this survey were: Are rural firms as innovative as urban firms? What constraints are impeding the innovative capacity of firms? What strategies are innovative firms using to mitigate these constraints? The target population for the survey was Nonmetro and metro establishments with 5 or more employees in tradable sectors (mining, manufacturing, wholesale trade, transportation and warehousing, finance, information, professional/technical/scientific services, arts and management of businesses). REIS used the Bureau of Labor Statistics (BLS) Quarterly Census of Employment and Wages Business Register for its sampling frame. Responses from 11,600 businesses were usable. These data include responses from businesses in the Arts & Museums industry category. These businesses were oversampled by a factor of 3.3 to ensure reliable statistics. The REIS data are restricted and require users to apply for access to the data. For permission to access to these data, visit the ERS Rural Economy Population: Business Industry page and scroll to the bottom of the page for contact information. If permission to access the data is granted, the data can be viewed through the NORC data enclave.

Ecuador Employment Rate: Rural: Unpaid Labor: Male data was reported at 11.623 % in Jun 2019. This records a decrease from the previous number of 11.974 % for Mar 2019. Ecuador Employment Rate: Rural: Unpaid Labor: Male data is updated quarterly, averaging 9.953 % from Dec 2013 (Median) to Jun 2019, with 23 observations. The data reached an all-time high of 11.974 % in Mar 2019 and a record low of 5.806 % in Jun 2014. Ecuador Employment Rate: Rural: Unpaid Labor: Male data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.G021: ENEMDU: Employment Rate: Rural.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2014 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Armed Forces data are not shown for the population 65 years and over..Employment and unemployment estimates may vary from the official labor force data released by the Bureau of Labor Statistics because of differences in survey design and data collection. For guidance on differences in employment and unemployment estimates from different sources go to Labor Force Guidance..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2014 American Community Survey 1-Year Estimates

In 2023, the proportion of the trained labor force reached approximately ** percent in urban areas and **** percent in rural areas in Vietnam. The trained labor force constituted **** percent of Vietnam's total labor force during that period.

This scatter chart displays unemployment (% of total labor force) against rural population (people) in Georgia. The data is about countries per year.