China Household Survey: Number of Dependent per Labor Force: Rural: Upper Middle Income data was reported at 1.350 Person in 2012. This records an increase from the previous number of 1.342 Person for 2011. China Household Survey: Number of Dependent per Labor Force: Rural: Upper Middle Income data is updated yearly, averaging 1.360 Person from Dec 2002 (Median) to 2012, with 11 observations. The data reached an all-time high of 1.450 Person in 2002 and a record low of 1.338 Person in 2010. China Household Survey: Number of Dependent per Labor Force: Rural: Upper Middle Income data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HC: No of Household Surveyed: Rural: By Income Level.

China Household Survey: Number of Full/Semi Labor Force per Household: Rural: Lower Middle data was reported at 2.869 Person in 2012. This records a decrease from the previous number of 2.898 Person for 2011. China Household Survey: Number of Full/Semi Labor Force per Household: Rural: Lower Middle data is updated yearly, averaging 2.910 Person from Dec 2002 (Median) to 2012, with 11 observations. The data reached an all-time high of 2.980 Person in 2009 and a record low of 2.780 Person in 2002. China Household Survey: Number of Full/Semi Labor Force per Household: Rural: Lower Middle data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HC: No of Household Surveyed: Rural: By Income Level.

The global labor force participation rate fell by 0.8 percentage points between 2014 and 2024. This is explained by structural changes in low- and middle-income countries, such as more young adults entering higher education. On the contrary, the labor force participation rate fell in high-income countries due to aging populations.

Youth labor force participation rates worldwide were highest in low income countries, explained by limited opportunities for education in these countries. On the other hand, labor force participation was lowest in lower-middle income countries, partly explained by the tendency that more people enter secondary education once countries begin to develop.

Household Survey: No of Dependent per Labor Force: Rural: Middle Income data was reported at 1.410 Person in 2012. This records an increase from the previous number of 1.400 Person for 2011. Household Survey: No of Dependent per Labor Force: Rural: Middle Income data is updated yearly, averaging 1.410 Person from Dec 2002 (Median) to 2012, with 11 observations. The data reached an all-time high of 1.500 Person in 2002 and a record low of 1.393 Person in 2010. Household Survey: No of Dependent per Labor Force: Rural: Middle Income data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HC: No of Household Surveyed: Rural: By Income Level.

The political relevance of labor market insecurity has been questioned because a) insider-outsider divides were considered to be a divide within the low-skilled and politically less active working class and b) labor market insecurity runs through the middle of the household. Outsiders might therefore align their preferences with those of insiders. This contribution provides, first, evidence that labor market insecurity extends well into the higher-skilled middle class, in particular to high-skilled young adults and high-skilled women. Second, the contribution sheds light on the “household question”, that is the question whether mixed households dampen the political relevance of labor market insecurity. If labor market insecurity is concentrated in specific social groups (young adults, women) that tend to cohabit with secure insiders, the political relevance of labor market insecurity might depend on whether or not outsiders align their preferences with those of the household. In this contribution, I discuss recent work on the relevance of the household in translating labor market divides into preferences divides presenting recent work that shows that the household does not render insider-outsider divides politically irrelevant. In sum, insider-outsider divides have all the potential to become politically relevant.

China Household Survey: Number of Full/Semi Labor Force per Household: Rural: Upper Middle Income data was reported at 2.677 Person in 2012. This records a decrease from the previous number of 2.703 Person for 2011. China Household Survey: Number of Full/Semi Labor Force per Household: Rural: Upper Middle Income data is updated yearly, averaging 2.770 Person from Dec 2002 (Median) to 2012, with 11 observations. The data reached an all-time high of 2.800 Person in 2007 and a record low of 2.677 Person in 2012. China Household Survey: Number of Full/Semi Labor Force per Household: Rural: Upper Middle Income data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HC: No of Household Surveyed: Rural: By Income Level.

The employment-to-population ratio is highest in low income countries, followed upper-middle income countries. Moreover, whereas the employment rate fell in these two groups of countries as well as in lower-middle income countries from 2000, it generally increased in high income countries since 2010.

The statistic shows the distribution of the workforce across economic sectors in China from 2014 to 2024. In 2024, around 22.2 percent of the workforce were employed in the agricultural sector, 29 percent in the industrial sector and 48.8 percent in the service sector. In 2022, the share of agriculture had increased for the first time in more than two decades, which highlights the difficult situation of the labor market due to the pandemic and economic downturn at the end of the year. Distribution of the workforce in China In 2012, China became the largest exporting country worldwide with an export value of about two trillion U.S. dollars. China’s economic system is largely based on growth and export, with the manufacturing sector being a crucial contributor to the country’s export competitiveness. Economic development was accompanied by a steady rise of labor costs, as well as a significant slowdown in labor force growth. These changes present a serious threat to the era of China as the world’s factory. The share of workforce in agriculture also steadily decreased in China until 2021, while the agricultural gross production value displayed continuous growth, amounting to approximately 7.8 trillion yuan in 2021. Development of the service sector Since 2011, the largest share of China’s labor force has been employed in the service sector. However, compared with developed countries, such as Japan or the United States, where 73 and 79 percent of the work force were active in services in 2023 respectively, the proportion of people working in the tertiary sector in China has been relatively low. The Chinese government aims to continue economic reform by moving from an emphasis on investment to consumption, among other measures. This might lead to a stronger service economy. Meanwhile, the size of the urban middle class in China is growing steadily. A growing number of affluent middle class consumers could promote consumption and help China move towards a balanced economy.

China Household Survey: Number of Dependent per Labor Force: Rural: Lower Middle data was reported at 1.468 Person in 2012. This records an increase from the previous number of 1.459 Person for 2011. China Household Survey: Number of Dependent per Labor Force: Rural: Lower Middle data is updated yearly, averaging 1.468 Person from Dec 2002 (Median) to 2012, with 11 observations. The data reached an all-time high of 1.570 Person in 2002 and a record low of 1.429 Person in 2010. China Household Survey: Number of Dependent per Labor Force: Rural: Lower Middle data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HC: No of Household Surveyed: Rural: By Income Level.

Employment, economy and welfare including labor force population, labor force participation rate, labor force participation rate - junior high school and below, labor force participation rate - senior high school (vocational), labor force participation rate - college and above, employed population, unemployment rate, unemployment rate - junior high school and below, unemployment rate - senior high school (vocational), unemployment rate - college and above, number of registered companies (gender of responsible person), number of foreign workers in industry and social welfare, number of low-income households - population, number of low-income households - households (gender of household head), number of low-income indigenous households - population, number of low-income indigenous households - households (gender of household head), number of people with disabilities, ratio of people with disabilities to the total population, number of solitary elderly people in need of care, number of insured persons under agricultural health insurance, number of insured persons under labor insurance, number of elderly farmers receiving welfare subsidies, number of actually employed persons with disabilities through quota employment, number of living allowances for people with disabilities, number of students with disabilities receiving educational subsidies, number of beneficiaries of living allowances for elderly with middle and low income, number of recipients of special care allowances for elderly with middle and low income, number of households in special circumstances (gender of parents), number of volunteers in social welfare services, registered homeless population, number of profit-making enterprises - by gender of responsible person, representative or manager, number of union members, number of first-time recipients of parental leave allowances for child care.

This is the data and code that accompanies the paper. The paper studies the effect of bank credit supply shocks on formal employment in Mexico using a proprietary data set containing information on all loans extended to firms by commercial banks during 2010-2015. We find large impacts on the formal employment of small and medium firms: a positive credit shock of one standard deviation increases yearly employment by 1.4 percentage points. The shares of uncollateralized credit, credit received by family firms, by younger firms, and by firms with no previous bank relationships also increase, suggesting that credit shocks may play a more prominent role for employment creation in credit-constrained settings.

The data and code replicate the analysis of "mandatory active labour market policies included in unemployment protection schemes, by country and type of measure", based on data from the Social Security Programs Throughout the World (SSPTW) database using the software Stata.

In the World Bank Enterprise Survey, the share of entrepreneurs who are women first rises and then falls with national income, which reverses the well-known U-shaped relationship between female labor force participation and economic development. This paper presents a model of entrepreneurship in which women face disadvantages, including discrimination from workers and household demands on their time, that deter firm formation in the poorest countries. In richer countries, these forces mean that women are less likely to start more complex organizations. In the model, women face the most level playing field in middle-income countries, where the returns to entrepreneurship are high enough to offset gender-based costs and both sexes typically form simple forms. We document three facts that are compatible with the model: male-owned firms are typically much larger than female-owned firms, large firms yield far higher revenues per employee and female-owned firms are more usually in industries with low levels of skilled workers. Despite the entrepreneurship rate’s reversal of the U-shaped link between female labor-force-participation and economic development, female labor-force-participation and the entrepreneurship rate are highly correlated across countries. The female entrepreneurship rate is also strongly associated with female education, weak kinship ties and Buddhism. The following materials include data and codes to replicate the paper.

We formalize and examine two overlapping models that show how rising inequality combined with ethnic and racial heterogeneity can explain why many advanced industrial countries have experienced a drop in support for redistribution as inequality has risen. One model, based on altruism and homophily, focuses on the effect of increasing “social distance” between the poor and the middle class, especially when minorities are increasingly overrepresented among the very poor. The other, based on self-interest, combines an “insurance” model of preferences for redistribution with increasingly segmented labor markets, in which immigration of workers without recognized skills leaves most native workers better off but intensifies competition for low-end jobs. Empirically, when we estimate parameters from the two models using data from multiple waves of ISSP surveys, we find that labor market segmentation, previously omitted in this literature, has more consistent effects than social distance. --------------------------------- Analysis of ISSP microdata 1985-2010.

Today, one in five youths who enter the labor market is born in Africa. By 2050, it will be one in three. The record figure of young Africans seeking employment is the outcome of different fertility trends across the world: fertility has been falling everywhere, but much more slowly in Africa. This paper present evidence on the labor market consequences of these differences for the young labor market entrants in Africa, compared to older generations and to their counterparts in other low- and middle-income regions of the world. We study how job opportunities depend on the demographic structure and which policies can be implemented to counteract the demographic pressure.

This study contains selected electoral and demographic national data for nine nations in the 1950s and 1960s. The data were prepared for the Data Confrontation Seminar on the Use of Ecological Data in Comparative Cross-National Research held under the auspices of the Inter-university Consortium for Political and Social Research on April 1-18, 1969. One of the primary concerns of this international seminar was the need for cooperation in the development of data resources in order to facilitate exchange of data among individual scholars and research groups. Election returns for two or more national and/or local elections are provided for each of the nine nations, as well as ecological materials for at least two time points in the general period of the 1950s and 1960s. While each dataset was received at a single level of aggregation, the data have been further aggregated to at least a second level of aggregation. In most cases, the data can be supplied at the commune or municipality level and at the province or district level as well. Part 1 (Germany, Regierungsbezirke), Part 2 (Germany, Kreise), Part 3 (Germany, Lander), and Part 4 (Germany, Wahlkreise) contain data for all kreise, laender (states), administrative districts, and electoral districts for national elections in the period 1957-1969, and for state elections in the period 1946-1969, and ecological data from 1951 and 1961. Part 5 (France, Canton), and Part 6 (France, Departemente) contain data for the cantons and departements of two regions of France (West and Central) for the national elections of 1956, 1962, and 1967, and ecological data for the years 1954 and 1962. Data are provided for election returns for selected parties: Communist, Socialist, Radical, Federation de Gauche, and the Fifth Republic. Included are raw votes and percentage of total votes for each party. Ecological data provide information on total population, proportion of total population in rural areas, agriculture, industry, labor force, and middle class in 1954, as well as urbanization, crime rates, vital statistics, migration, housing, and the index of "comforts." Part 7 (Japan, Kanagawa Prefecture), Part 8 (Japan, House of Representatives Time Series), Part 9 (Japan, House of (Councilors (Time Series)), and Part 10 (Japan, Prefecture) contain data for the 46 prefectures for 15 national elections between 1949 and 1968, including data for all communities in the prefecture of Kanagawa for 13 national elections, returns for 8 House of Representatives' elections, 7 House of Councilors' elections, descriptive data from 4 national censuses, and ecological data for 1950, 1955, 1960, and 1965. Data are provided for total number of electorate, voters, valid votes, and votes cast by such groups as the Jiyu, Minshu, Kokkyo, Minji, Shakai, Kyosan, and Mushozoku for the Communist, Socialist, Conservative, Komei, and Independent parties for all the 46 prefectures. Population characteristics include age, sex, employment, marriage and divorce rates, total number of live births, deaths, households, suicides, Shintoists, Buddhists, and Christians, and labor union members, news media subscriptions, savings rate, and population density. Part 11 (India, Administrative Districts) and Part 12 (India, State) contain data for all administrative districts and all states and union territories for the national and state elections in 1952, 1957, 1962, 1965, and 1967, the 1958 legislative election, and ecological data from the national censuses of 1951 and 1961. Data are provided for total number of votes cast for the Congress, Communist, Jan Sangh, Kisan Mazdoor Praja, Socialist, Republican, Regional, and other parties, contesting candidates, electorate, valid votes, and the percentage of valid votes cast. Also included are votes cast for the Rightist, Christian Democratic, Center, Socialist, and Communist parties in the 1958 legislative election. Ecological data include total population, urban population, sex distribution, occupation, economically active population, education, literate population, and number of Buddhists, Christians, Hindus, Jainis, Moslems, Sikhs, and other religious groups. Part 13 (Norway, Province), and Part 14 (Norway, Commune) consist of the returns for four national elections in 1949, 1953, 1957, and 1961, and descriptive data from two national censuses. Data are provided for the total number

By the middle of the 1990s, Indonesia had enjoyed over three decades of remarkable social, economic, and demographic change and was on the cusp of joining the middle-income countries. Per capita income had risen more than fifteenfold since the early 1960s, from around US$50 to more than US$800. Increases in educational attainment and decreases in fertility and infant mortality over the same period reflected impressive investments in infrastructure. In the late 1990s the economic outlook began to change as Indonesia was gripped by the economic crisis that affected much of Asia. In 1998 the rupiah collapsed, the economy went into a tailspin, and gross domestic product contracted by an estimated 12-15%-a decline rivaling the magnitude of the Great Depression. The general trend of several decades of economic progress followed by a few years of economic downturn masks considerable variation across the archipelago in the degree both of economic development and of economic setbacks related to the crisis. In part this heterogeneity reflects the great cultural and ethnic diversity of Indonesia, which in turn makes it a rich laboratory for research on a number of individual- and household-level behaviors and outcomes that interest social scientists. The Indonesia Family Life Survey is designed to provide data for studying behaviors and outcomes. The survey contains a wealth of information collected at the individual and household levels, including multiple indicators of economic and non-economic well-being: consumption, income, assets, education, migration, labor market outcomes, marriage, fertility, contraceptive use, health status, use of health care and health insurance, relationships among co-resident and non- resident family members, processes underlying household decision-making, transfers among family members and participation in community activities. In addition to individual- and household-level information, the IFLS provides detailed information from the communities in which IFLS households are located and from the facilities that serve residents of those communities. These data cover aspects of the physical and social environment, infrastructure, employment opportunities, food prices, access to health and educational facilities, and the quality and prices of services available at those facilities. By linking data from IFLS households to data from their communities, users can address many important questions regarding the impact of policies on the lives of the respondents, as well as document the effects of social, economic, and environmental change on the population. The Indonesia Family Life Survey complements and extends the existing survey data available for Indonesia, and for developing countries in general, in a number of ways. First, relatively few large-scale longitudinal surveys are available for developing countries. IFLS is the only large-scale longitudinal survey available for Indonesia. Because data are available for the same individuals from multiple points in time, IFLS affords an opportunity to understand the dynamics of behavior, at the individual, household and family and community levels. In IFLS1 7,224 households were interviewed, and detailed individual-level data were collected from over 22,000 individuals. In IFLS2, 94.4% of IFLS1 households were re-contacted (interviewed or died). In IFLS3 the re-contact rate was 95.3% of IFLS1 households. Indeed nearly 91% of IFLS1 households are complete panel households in that they were interviewed in all three waves, IFLS1, 2 and 3. These re-contact rates are as high as or higher than most longitudinal surveys in the United States and Europe. High re-interview rates were obtained in part because we were committed to tracking and interviewing individuals who had moved or split off from the origin IFLS1 households. High re-interview rates contribute significantly to data quality in a longitudinal survey because they lessen the risk of bias due to nonrandom attrition in studies using the data. Second, the multipurpose nature of IFLS instruments means that the data support analyses of interrelated issues not possible with single-purpose surveys. For example, the availability of data on household consumption together with detailed individual data on labor market outcomes, health outcomes and on health program availability and quality at the community level means that one can examine the impact of income on health outcomes, but also whether health in turn affects incomes. Third, IFLS collected both current and retrospective information on most topics. With data from multiple points of time on current status and an extensive array of retrospective information about the lives of respondents, analysts can relate dynamics to events that occurred in the past. For example, changes in labor outcomes in recent years can be explored as a function of earlier decisions about schooling and work. Fourth, IFLS collected extensive measures of health status, including self-reported measures of general health status, morbidity experience, and physical assessments conducted by a nurse (height, weight, head circumference, blood pressure, pulse, waist and hip circumference, hemoglobin level, lung capacity, and time required to repeatedly rise from a sitting position). These data provide a much richer picture of health status than is typically available in household surveys. For example, the data can be used to explore relationships between socioeconomic status and an array of health outcomes. Fifth, in all waves of the survey, detailed data were collected about respondents¹ communities and public and private facilities available for their health care and schooling. The facility data can be combined with household and individual data to examine the relationship between, for example, access to health services (or changes in access) and various aspects of health care use and health status. Sixth, because the waves of IFLS span the period from several years before the economic crisis hit Indonesia, to just prior to it hitting, to one year and then three years after, extensive research can be carried out regarding the living conditions of Indonesian households during this very tumultuous period. In sum, the breadth and depth of the longitudinal information on individuals, households, communities, and facilities make IFLS data a unique resource for scholars and policymakers interested in the processes of economic development.

39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.

Live In Nanny Services Market Outlook

The global live in nanny services market size was valued at approximately $8.1 billion in 2023 and is expected to reach around $12.9 billion by 2032, growing at a compound annual growth rate (CAGR) of 5.3% during the forecast period. The growth of this market is primarily driven by the increasing number of dual-income households, escalating workloads, and the rising awareness of the benefits associated with professional childcare services.

One of the primary growth factors for the live in nanny services market is the growing trend of dual-income families. As more households have both parents working full-time jobs, the demand for reliable, professional childcare services has surged. Parents are increasingly seeking live-in nannies who can provide consistent and personalized care for their children, helping maintain a structured and nurturing environment. This trend is particularly pronounced in urban areas where the cost of living is higher and external childcare options may be less flexible.

Another factor contributing to the market's growth is the escalating workload and longer working hours for parents. With many professionals facing increased job demands and longer commutes, the convenience of having a live-in nanny becomes highly appealing. Parents can rely on nannies for a range of tasks beyond basic childcare, including helping with homework, preparing meals, and managing extracurricular activities. This comprehensive support system allows parents to balance their professional and personal responsibilities more effectively.

Moreover, the rising awareness of the advantages of professional childcare services has significantly boosted the live in nanny services market. Parents are increasingly recognizing that professional nannies bring specialized skills, training, and experience that can contribute to their children's development and well-being. Additionally, live-in nannies can provide a higher level of consistency and stability compared to other childcare options, which is crucial for the emotional and psychological growth of children. This enhanced awareness is driving more parents to consider live-in nannies as a viable and beneficial childcare solution.

Regionally, North America holds a significant share of the live in nanny services market, driven by high disposable incomes, a large number of dual-income households, and the prevalence of professional childcare services. Europe also represents a substantial market, with countries like the UK, Germany, and France leading the charge due to favorable working conditions and supportive government policies. In the Asia Pacific region, the market is experiencing robust growth, fueled by rapid urbanization, increasing female workforce participation, and a burgeoning middle class. Latin America and the Middle East & Africa, while smaller in market size, are witnessing steady growth driven by changing societal norms and economic development.

Service Type Analysis

The service type segment of the live in nanny services market encompasses full-time, part-time, temporary, and specialized care services. Full-time services, which involve nannies living with the family and providing round-the-clock care, represent the largest share of the market. This is primarily due to the comprehensive nature of the care provided, which includes everything from daily routines to emergency situations. Full-time nannies often form close bonds with the children they care for, providing a stable and nurturing environment that parents value highly.

Part-time live-in nanny services are also significant, catering to families that need regular care but not round-the-clock supervision. These services are popular among parents who work non-traditional hours or have varying schedules. Part-time nannies typically stay with the family for a few days a week or during specific periods, such as weekends or evenings, offering flexibility and cost savings compared to full-time services.

Temporary nanny services, including short-term and emergency care, are gaining traction as an essential component of the market. These services are particularly valuable for families requiring childcare during specific periods, such as vacations, business trips, or transitions between permanent care arrangements. Temporary nannies provide a reliable solution during these times, ensuring that children's routines and care are maintained without disruption.

Specialized care services cater to families with unique needs, such as childr