The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families' balance sheets, pensions, income, and demographic characteristics.

According to a survey conducted in South Korea in May 2025, about ** percent of respondents stated that they believed their household financial situation would get better within the next year. About ** percent expressed a more pessimistic view.

According to the results of the survey, over 40 percent of Hungarians expected that their family's financial situation would worsen if the opposition won the 2022 elections. At the same time, 17 percent of the respondents believed that they would benefit financially from a change of government.

Forecast: Household Expenditure on Vehicle Finance Charges in the US 2022 - 2026 Discover more data with ReportLinker!

In a survey conducted in Japan in 2022, the average amount of debt per household with children was ***** million Japanese yen. Households consisting of single mothers and a child below the age of 20 reported **** million yen of debt on average.

China National Balance Sheet: Households: Asset: Non-financial Asset: Urban Housing data was reported at 238,558.800 RMB bn in 2022. This records a decrease from the previous number of 240,900.300 RMB bn for 2021. China National Balance Sheet: Households: Asset: Non-financial Asset: Urban Housing data is updated yearly, averaging 10,676.400 RMB bn from Dec 1978 (Median) to 2022, with 45 observations. The data reached an all-time high of 240,900.300 RMB bn in 2021 and a record low of 28.400 RMB bn in 1978. China National Balance Sheet: Households: Asset: Non-financial Asset: Urban Housing data remains active status in CEIC and is reported by Center for National Balance Sheets. The data is categorized under China Premium Database’s National Accounts – Table CN.ABS: National Balance Sheet Accounts(1978-2022): Household.

The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP.

The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.

The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.

Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage.

The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage.

Secure Access FRS data
In addition to the standard End User Licence (EUL) version, Secure Access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 9256. Prospective users of the Secure Access version of the FRS will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from http://ukdataservice.ac.uk/media/178323/secure_frs_application_guidance.pdf" style="background-color: rgb(255, 255, 255);">Guidance on applying for the Family Resources Survey: Secure Access.

FRS, HBAI and PI
The FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503, respectively. The Secure Access versions are held under SN 7196 and 9257 (see above).

FRS 2022-23

The impact of the coronavirus (COVID-19) pandemic on the FRS 2022-23 survey was much reduced when compared with the two previous survey years. Throughout the year, there was a gradual return to pre-pandemic fieldwork practices, with the majority of interviews being conducted in face-to-face mode. The achieved sample was just over 25,000 households. Users are advised to consult the FRS 2022-23 Background Information and Methodology document for detailed information on changes, developments and issues related to the 2022-23 FRS data set and publication. Alongside the usual topics covered, the 2022-2023 FRS also includes variables for Cost of Living support, including those on certain state benefits; energy bill support; and Council Tax support. See documentation for further details.

FRS 2021-22 and 2020-21 and the coronavirus (COVID-19) pandemic

The coronavirus (COVID-19) pandemic has impacted the FRS 2021-22 and 2020-21 data collection in the following ways:

• In 2020-21, fieldwork operations for the FRS were rapidly changed in response to the coronavirus (COVID-19) pandemic and the introduction of national lockdown restrictions. The established face-to-face interviewing approach employed on the FRS was suspended and replaced with telephone interviewing for the whole of the 2020-21 survey year.

• This change impacted both the size and composition of the achieved sample. This shift in mode of interview has been accompanied by a substantial reduction in the number of interviews achieved: just over 10,000 interviews were achieved this year, compared with 19,000 to 20,000 in a typical FRS year. While we made every effort to address additional biases identified (e.g. by altering our weighting regime), some residual bias remains. Please see the FRS 2020-21 Background Information and Methodology document for more information.
• The FRS team have published a technical report for the 2020-21 survey, which provides a full assessment of the impact of the pandemic on the statistics. In line with the Statistics Code of Practice, this is designed to assist users with interpreting the data and to aid transparency over decisions and data quality issues.

• In 2021-22, the interview mode was largely telephone, with partial return to face-to-face interviews towards end of survey year. The achieved sample was over 16,000 households. This is a return towards the number expected in a normal survey year (around 20,000 households).
• In both survey years, there remain areas where users are advised to exercise caution when making comparisons to other survey years. More details on how the results for the 2020 to 2021 and 2021-22 survey years were affected by the coronavirus (COVID-19) pandemic can be found in the FRS 2020 to 2021 Background Information and Methodology and FRS 2021 to 2022 Background Information and Methodology.

The FRS team are seeking users' feedback on the 2020-21 and 2021-22 FRS. Given the breadth of groups covered by the FRS data, it has not been possible for DWP statisticians to assess or validate every breakdown which is of interest to external researchers and users. Therefore, the FRS team are inviting users to let them know of any insights you may have relating to data quality or trends when analysing these data for your area of interest. Please send any feedback directly to the FRS Team Inbox: team.frs@dwp.gov.uk

Latest edition information

For the second edition (May 2025), the data were redeposited. The following changes have been made:

• An ONS-delivered fix to the highest level of qualification (EDUCQUAL) which for several adults had been erroneously recorded.
• For ESA (benefit 16 on the BENEFITS table) the associated VAR3 has now been populated using ESA admin data, to show whether cases are Support Group etc.
• For Pension Credit recipients (benefit 4 on the BENEFITS table) adding the low-income benefits and tax credits Cost of Living Payment as benefit 124; with its flag CLPAYIRB set on the ADULT table.

About this dataset

Context

The dataset tabulates the median household income in Money Creek township. It can be utilized to understand the trend in median household income and to analyze the income distribution in Money Creek township by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Money Creek Township, Minnesota Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Money Creek Township, Minnesota: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Money Creek Township, Minnesota
• Money Creek Township, Minnesota households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Money Creek township median household income. You can refer the same here

Forecast: Life Insurance Reserves as Household Financial Assets in Sweden 2022 - 2026 Discover more data with ReportLinker!

Total Union Budget allocation for the Department of Health and Family Welfare under the Ministry of Health and Family Welfare. It contains budgetary allocations for expenditures related to various Medical Institutions, Central Government Health Scheme (CGHS), Medical Education Training and Research, National Health Mission etc.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Money Creek Township, Minnesota, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Money Creek township did not include 5, 6, or 7-person households. Across the different household sizes in Money Creek township the mean income is $99,257, and the standard deviation is $53,799. The coefficient of variation (CV) is 54.20%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $60,594. It then further increased to $177,675 for 4-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/money-creek-township-mn-median-household-income-by-household-size.jpeg" alt="Money Creek Township, Minnesota median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

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

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Money Creek township median household income. You can refer the same here

The share of American families, in which the family head was self-employed, that managed to save money decreased between 2019 and 2022. Self-employed households were the more likely to save than those in other work status. For families in which the breadwinner was retired, 51 percent managed to save money in the same year.

The Community Credit research project explores pathways for trusted collaboration between credit unions and the communities they serve. To understand the experiences of people historically underserved by the consumer financial services industry, we focused in particular on the lived experience of low-income residents in Southern California. As part of a larger, mixed-methods study, in 2022 we mapped the landscape of financial services providers and advertisements in low-income neighborhoods in Orange County. Through documenting the presence of alternative financial services (AFS) providers and fringe financial advertisements, alongside traditional financial services providers, we investigated the spatial relationship between these businesses, as well as the factors that create consumers’ sense of (dis)trust in them. This data set contains photographs taken as part of this mapping research. All study materials and procedures were approved by the University of California, Irvine Office of..., Data was collected over the course of five trips throughout Orange County, California, between November 2021 and February 2022, yielding 420 photographs. Areas of focus were determined by utilizing the 2019 Family Financial Stability Index (FFSI; Parsons et al.), a multivariate metric developed for Orange County United Way to measure the financial stability of families with children under 18. Each trip, researchers navigated to financial services providers in neighborhoods of low family financial stability. In addition to photographing these providers, researchers drove block-by-block through the area and documented traditional and fringe financial advertisements found on telephone poles, billboards, bus shelters, and the like. Photographs were only taken in public spaces of material in plain view., Photographs are organized in folders according to trip (labeled A through E). Each photo is labeled by the trip and a number (e.g. “TripX_AdMapping_X.jpeg†). The photo directory associated with each trip contains the photo file names, descriptions and notes, and type (billboard, storefront, phone pole ad, etc.). Trip A took place in southern Santa Ana and western Orange; trip B was in northern Santa Ana and southern Anaheim; trip C was in northern Anaheim, Placentia, and Fullerton; trip D was in western Anaheim and northern Garden Grove; and trip E was in western Anaheim, northern Garden Grove, and Westminster. A map of Orange County coded according to the FFSI is included in the supplemental information (where red and dark orange indicate a neighborhood with a low score). The map also identifies local credit unions, community research partners, alternative financial services providers, and a selection of photographs from the mapping research.,

Appendix 2 is the Summary of the Local Property Tax Allocation. It contains –

Discretionary Local Property Tax Allocation (Table A) for the Budget Year.
Self Funding Local Property Tax for Revenue Budget, broken down between service divisions for the Budget Year.
Self Funding Local Property Tax for Capital Budget, broken down between service divisions for the Budget Year.
The data in this dataset is best interpreted by comparison with Appendix 2 in the published Annual Budget document, which can be found at www.fingal.ie

Data fields for Appendix 2 are as follows –

Doc : Table Reference
Heading : Indicates sections in the Table – Appendix 2 is comprised of one section, therefore Heading value for all records = 1
Ref : Category of LPT funding
Desc : Description of category of LPT funding
CY_Inc : Local Property Tax Allocation for Budget Year

Fifth edition of a study covering topics: role distribution of man and woman in occupation and household, attitudes towards marriage, cohabitation without marriage, attitudes towards single-parenting and childcare by same sex female and male couples (alternative family forms), ideal number of children for a family, attitudes towards children: views on the significance of children in life, gender, care and social policy: attitude towards paid leave for full-time working parents and preferred duration of paid leave, source of finance for paid leave, preferred division of this paid leave period between mother and father, time budget for housekeeping and looking after family members for both partners, management of income in marriage or partnership, allocation of duties in the household and in family matters, estimation of fair share of the household work.

According to a survey conducted among parents in China in 2022, about ** percent of respondents saw the child's mother to be the main decision maker concerning daily necessities and food. Meanwhile, around ** percent of respondents stated that the child's father is the main decision maker for large household spending in their household.

West Bengal Budget 2022-23ː Detailed Demands for Grants - Health - Family Welfare

China National Balance Sheet: Households: Asset: Non-financial Asset data was reported at 286,815.000 RMB bn in 2022. This records a decrease from the previous number of 287,132.200 RMB bn for 2021. China National Balance Sheet: Households: Asset: Non-financial Asset data is updated yearly, averaging 15,639.100 RMB bn from Dec 1978 (Median) to 2022, with 45 observations. The data reached an all-time high of 287,132.200 RMB bn in 2021 and a record low of 180.000 RMB bn in 1978. China National Balance Sheet: Households: Asset: Non-financial Asset data remains active status in CEIC and is reported by Center for National Balance Sheets. The data is categorized under China Premium Database’s National Accounts – Table CN.ABS: National Balance Sheet Accounts(1978-2022): Household.

Total Union Budget Allocation for the expenditure on the household establishment of the Hon'ble President on account of salaries of the staff and officers, office expenses, allowances and purchase and maintenance of vehicles etc.

In a survey conducted in Japan in 2022, close to ***** percent of elderly households reported having debt. The share of households with children having debt was much higher, at around ** percent. The highest amount of debt per household was recorded among households with children.