As of January 2022, the largest share of Chinese middle-class families had an annual income of between 100 thousand and 300 thousand yuan per year. According to the same survey, almost 90 percent of respondents have at least one child. Many middle-class families in China face significant financial burdens because not only do living costs continuously increase but they also often have to support their parents. In that case, one family has to care for four elders and least one kid.

This statistic shows the average income of a middle class family in the United States in 2014, by state. In 2014, the average middle-class family in Alaska had an income of 80,230 U.S. dollars per year. This was significantly higher than the national average of 72,919 U.S. dollars.

Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2023 about family, median, income, real, and USA.

Income statistics by economic family type and income source, annual.

This statistic shows the median household income in the United States from 1970 to 2020, by income tier. In 2020, the median household income for the middle class stood at 90,131 U.S. dollars, which was approximately a 50 percent increase from 1970. However, the median income of upper income households in the U.S. increased by almost 70 percent compared to 1970.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Middle Inlet, Wisconsin, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 21,360, while the mean income for the highest quintile (20% of households with the highest income) is 162,915. This indicates that the top earners earn 8 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 282,509, which is 173.41% higher compared to the highest quintile, and 1322.61% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

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 Middle Inlet town median household income. You can refer the same here

Abstract copyright UK Data Service and data collection copyright owner. This study was concerned with middle class men and women typically living in privately built houses on suburban estates around the major industrial cities of Britain. It was based upon 172 completed questionnaires and extensive interview notes. The research endeavoured to present some of the dilemmas which such people faced in relating their work life to their family life, and considered related issues of value, ambition, success and reward.

This collection is not currently digitised and is available as a hard copy only. If you are interested in a project which involves the digitisation of this collection, please contact our Collections team at collections@ukdataservice.ac.uk. We'd be delighted to work with you in enhancing this collection.

Main topics: Managers; middle class; employment; marriage; family life; fathers; husbands; mothers; housewives; women's role; social mobility; geographical mobility; social class; social life; social values; career development; community life; community participation.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Amherst, New York, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Amherst, New York reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Amherst town households based on income levels.

Key observations

• For Family Households: In Amherst town, the majority of family households, representing 25.29%, earn $200,000 or more, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.94%, have incomes falling $15,000 to $19,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Amherst town, the majority of non-family households, accounting for 11.35%, have income $60,000 to $74,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 3.62%, earn $15,000 to $19,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Amherst, New York (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Amherst, New York
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Amherst, New York
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Amherst, New York

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 Amherst town median household income. You can refer the same here

The project adopted a broad approach, employing quantitative as well as qualitative methods. It covered both public and private forms of risk protection, and it analysed attitudes as well as actual behavior. First, we reviewed Britain's current 'mixed economy of welfare' in the aforementioned five key areas. We mapped the social programmes, occupational schemes and private options that have been available since the early 1990s. The second phase was based on quantitative data analysis, making use of the Family Resources Survey (FRS) and the ABI Risk and Protection Survey. We analysed the take-up of insurances and how it was influenced by attitudes and socio-demographic characteristics. Third, we conducted 61 qualitative interviews, where we explored personal risk management strategies of middle-income households from Scotland and England. The main result was a typology of risk management rationales that guide household economies. This stage also explored the ramifications of the recent financial uncertainties and economic downturn.

Comparing England and Scotland, the purpose was to review Britain's current 'mixed economy of welfare' in key areas: unemployment, sickness, costs of higher education for children, retirement and infirmity in old age. The aim was to map the types of statutory protection against such risks and contingencies and examine changes in the scope of public provision. In parallel, we will examine the scope of non-statutory (occupational and personal) provision, investigating how 'private welfare markets' have developed since the early 1990s. The second phase is based on quantitative data analysis of household savings and investment behaviour in insurances and private market-based contracts for risk protection. Finally, via qualitative interviews, we explore personal risk management of socially and economically similar families from Scotland and England. This stage will also explore the potential ramifications of the most recent financial uncertainties and economic downturn.

The project investigated risk management strategies of above average income households in England and Scotland. In the UK especially those with above average incomes are often assumed to have access to or seek private forms of risk protection, partly based on company provision or private voluntary protection complementing or substituting public social protection. The project investigated how households protect themselves against income loss due to unemployment, sickness or retirement and plan for expenses like long term care and higher education costs. We focused our analysis on how households balance these risks between public, occupational and private forms of protection. Moreover, we explored how the recent financial crisis has influenced the attitudes and behavior of households regarding their personal protection. The project sought to answer how and why some middle class households plan for contingencies and engage in private risk management strategies while others do not.

The dataset is a file of the raw interview scripts with my interviewees during the fieldwork conducted between 2021.6 to 2022.2.

This thesis investigates how urban middle-class working women with two children make sense of work, childcare, and self under the universal two-child policy of China. This thesis also explores how the idea of individual and family interact in these women's construction of a sense of self. On January 1st, 2016, the one-child policy was replaced by the universal two-child policy, under which all married couples in China are allowed to have two children. In the scholarships of motherhood, it is widely documented across cultures that it is a site of patriarchal oppression where women are expected to meet the unrealistic ideal of intensive mothering to be a good mother, suffer from the motherhood wage penalty and face more work-family conflict than fathers. Emprical studies of China also came to similar conclusions and such findings are not only widely regonized in scholarship but is also widespread in popular discourse in China. Despite that marriage and having children is still universal for the generation of the research target, women born in the 1970s and 1980s, due to compounding influence fo the one-child policy, increasing financial burden of raising a child etcs, having only one child has become widely acceptable and normal. Given this context, this study intend to investigate how these middle-class women, who are relatively empowered and resourceful, come to a decision that is seemingly against their own interest. Moreover, unlike in the west where the issue of childbearing and childcaring is mainly an issue of the conjugal couple and the gender realtions is at the center of the discussion, in China, extended family, especially grandparents also play a role in both the decision making process and the subsequent childcare arrangement. Therefore, to study the second-time mothers’ childcare and work experiences in contemporary urban China, we also need to situate them, as individuals, in their family. To investigate how they make sense of childcare and work is also to understand the tension between individual and family. By interviewing twenty-one parents from middle-class family in Guangzhou with a second child under six years old, this study finds that these urban working women with two children consider themselves as an individual unit and full-time paid employment is something that cannot be given up since it is the means of securing that independent self . However, they did not prioritize their personal interest to that of other family members, especially the elder child and thus the decision of having a second child is mainly for the sake of the elder child. Moreover, grandparents played an essential role to provide a childcare safety net, without which, these urban working women would not be able to work full-time and maintain the independent self as they defined it. The portrayal of these women’s experiences reflected the individualization process in China where people are indivdualized without individualism, and family are evoked as strategy to achieve personal as well as family goals. The findings of this study contributs to theories of motherhood by adding an intergenerational perspective to the existing gender perspective and also contributes to the studies of family by understanding the relation and interaction between individual and family in thse women’s construction of sense of self in the context of contemporary China.

When it came to selecting investment services in 2022, middle-class families cared most about the professionalism of the advisors and the variety and profitability of the products. Both factors had been prioritized by over 60 percent of respondents. Other important factors include brand image, information disclosure, and customization of products and services.

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.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Middle Point, OH, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Middle Point, OH reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Middle Point households based on income levels.

Key observations

• For Family Households: In Middle Point, the majority of family households, representing 19.58%, earn $60,000 to $74,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $100,000 to $124,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Middle Point, the majority of non-family households, accounting for 25.47%, have income $40,000 to $44,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $100,000 to $124,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Middle Point, OH (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Middle Point, OH
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Middle Point, OH
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Middle Point, OH

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 Middle Point median household income. You can refer the same here

This statistic shows the median net worth of families in the United States from 1983 to 2013, by income tier. In 2013, middle class families had a median net worth of about 98,057 U.S. dollars.

This study defined middle class income households as those with an income between 67 and 200 percent of the U.S. median household income, after adjustment for household size. In 2014, the middle class income ranged from about 42,000 U.S. dollars to about 126,000 U.S. dollars per year for a three-person household.

As of January 2022, almost 70 percent of middle class families were planning to invest in public funds. Other popular financial products among this demographic included commercial insurance, stocks, and wealth management products. Only around one-fifth of respondents stated that they were going to deposit their money in a savings account.

Abstract copyright UK Data Service and data collection copyright owner.

This is a mixed method data collection.

The importance of understanding young people's health and eating habits has been firmly stated by policymakers and there is an ongoing need to improve awareness of the factors which contribute to class inequalities in health between different population groups. There is little empirical research, however, which has looked at how the everyday practices and perceptions of middle-class young people and their families might contribute to class-based inequalities in diet, weight and overall health.

This study aimed to examine the dietary practices and health and weight conceptualisations of BMI-defined obese/overweight and non-obese/overweight young teenagers (aged 13-15 years) from middle-class families. These observations were situated within the 'habitus' of the family by exploring the aforementioned issues from the perspectives of teenagers' parents.

Whilst it is widely accepted that the unequal material circumstances associated with class distinctions influence people's lives and health, it is through attention to the everyday lived experience of deprivation or affluence that it can be seen how class might underpin growing inequalities in health. Bourdieu, in his work on habitus, argued that social distinctions are maintained through the production and control of bodily practices, which are, often, mundane and taken-for-granted. Bourdieu and others postulated that people from middle-class groups may be more likely to value enhanced wellbeing, rather than merely a functional absence of disease. In light of this, some commentators have argued that higher social class groups are protected against obesity because of the value they place on maintaining a socially acceptable thinner body. It is not known how such classed dispositions influence the food and eating practices of young middle-class teenagers and their families.

Further information about this study can be found at the project's ESRC award web page.


Main Topics:

Diet, weight, health, food practices, eating habits, young teenagers, family and social class.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Greenville, NC, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Greenville, NC reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Greenville households based on income levels.

Key observations

• For Family Households: In Greenville, the majority of family households, representing 15.71%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 1.71%, have incomes falling $150,000 to $199,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Greenville, the majority of non-family households, accounting for 16.58%, have income Less than $10,000, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 1.02%, earn $150,000 to $199,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Greenville, NC (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Greenville, NC
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Greenville, NC
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Greenville, NC

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 Greenville median household income. You can refer the same here

Families of tax filers; Census families by total income, family type and number of children (final T1 Family File; T1FF).

The social assistance explorer contains a harmonised panel dataset of social assistance indicators spanning 2000-2015. It has been developed to support comparative research on emerging welfare institutions. Comparative analysis of social protection institutions in low and middle income countries is scarce. Yet social assistance accounts for most of the recent expansion of welfare institutions. The project collected data on programme design and objectives, institutionalisation, reach, and financial resources. Key indicators can be aggregated at country and region levels.

Since the turn of the century low and middle income countries have introduced or expanded programmes providing direct transfers to families in poverty or extreme poverty as a means of strengthening their capacity to exit poverty. The rationale underpinning these programmes is that stabilising and enhancing family income through transfers in cash and in kind will enable programme participants to improve their nutrition, ensure investment in children's schooling and health, and help overcome economic and social exclusion. The expansion of antipoverty transfer programmes has accelerated. Estimates suggest that around 1 billion people in developing countries reside with someone in receipt of a transfer. As would be expected, the spread of social assistance has been slower and more tentative in low income countries due to implementation and finance constraints and limited elite political support. Antipoverty transfer programmes in developing countries show large variation in design, effectiveness, scale, and objectives. In most countries, there are several interventions running alongside one another with diverse priorities and designs, and often targeting different groups. In many countries social public assistance programmes work alongside social insurance programmes for formal sector workers and humanitarian or emergency assistance. Social assistance focuses on groups in poverty, provides medium term support, and is budget-financed. The spread of social assistance in developing countries has revealed significant gaps in the knowledge, for example as regards their effectiveness, reach, and sustainability. Comparative analysis is essential to fill in these gaps and improve national, regional and global policy. For example, achieving a zero target for extreme poverty, as has been suggested in the context of the post-2015 international development agenda, would require effective and permanent institutions ensuring the benefits from economic growth reach the poorest. Social assistance is essential to achieving this goal. This research project focuses on improving research infrastructure on social assistance, in terms of concepts, indicators and data. This is urgently needed to support comparative analysis of emerging social assistance institutions. The project will identify indicators to assess social assistance programmes and will collect information on these for 2000 to 2015 for all developing countries. The database will be made available online to researchers and policy makers globally. As part of the project, the database will be analysed to examine patterns or configurations in social assistance programmes and institutions. Our interest is in identifying ideal types, broad features of social assistance programmes or institutions which enable reducing the large diversity of programmes and interventions to their core characteristics. These ideal types are social assistance regimes. Further analysis will test for potential combinations of political, demographic, economic and social factors linked to specific social assistance regimes. This analysis will allow us to examine what conditions can help explain the expansion of social assistance in developing countries; what factors influence the specific configuration of social assistance institutions in different countries and regions; and what conditions are needed for their effectiveness and sustainability. This research will throw light on the contribution of social assistance to the reduction of poverty and vulnerability and to economic and social development.

In 2021, the birth rate in the United States was highest in families that had under 10,000 U.S. dollars in income per year, at 62.75 births per 1,000 women. As the income scale increases, the birth rate decreases, with families making 200,000 U.S. dollars or more per year having the second-lowest birth rate, at 47.57 births per 1,000 women. Income and the birth rate Income and high birth rates are strongly linked, not just in the United States, but around the world. Women in lower income brackets tend to have higher birth rates across the board. There are many factors at play in birth rates, such as the education level of the mother, ethnicity of the mother, and even where someone lives. The fertility rate in the United States The fertility rate in the United States has declined in recent years, and it seems that more and more women are waiting longer to begin having children. Studies have shown that the average age of the mother at the birth of their first child in the United States was 27.4 years old, although this figure varies for different ethnic origins.