This statistic displays the average student support per household in the United Kingdom (UK) in 2017/18, by decile group. Households in the seventh decile received, on average, 148 British pounds in student support. This was the highest income received from student support of any decile group.

Financial burdens of the parental home through education of children.

Topics: Start of studies; length of studies; amount of money available to the student monthly; current income and burden conditions of parents; opportunities to finance studies; stay of student in semester breaks; attitude of student to work in semester breaks; readiness of parents to finance studies; degree of familiarity of the Honnef Model; detailed information on income and contributions of the student as well as the remaining children; housing situation and rent costs of respondent.

Demography: income; household income; size of household; social origins; city size; state; refugee status; possession of durable economic goods; possession of assets.

This report summarizes the findings of the Consortium's third annual survey, which involved 25 colleges and more than 9,400 students. Participating colleges were responsible for sampling (based on a standardized procedure) and administering the survey in class. Completed questionnaires were then shipped to PRA Inc. for coding, data entry and analysis. The objectives of the research are to: provide national data on student access, time use and financing for Canadian college students from participating colleges; identify issues particular to certain learner groups or regions; and provide each institution with topline survey results (based on representative samples of their students), which may then be compared against the "national average". This dataset was freely received from the Canada Millennium Scholarship Foundation. Some work was required for the variable and value labels, and missing values. They were corrected as best as possible with the documentation received. Caution should be used with this dataset as some variables are lacking information.

The Canadian College Student Survey Consortium (the Consortium, CCSSC) includes the Association of Canadian Community Colleges (ACCC), individual participating colleges and the Canada Millennium Scholarship Foundation (CMSF). Established in late 2001, the Consortium conducted its first survey of college students in the spring of 2002. In 2003, it conducted a second survey, involving 27 colleges and approximately 9,900 students. This report summarizes the findings of the second annual survey. The survey collects data on college students' income, expenditures and use of time. The survey is unique in that it provides national-level information on the challenges Canadian college students face in terms of financial and access issues. Approximately 9,900 students completed the survey. Of which most students who responded to the survey are enrolled full-time in programs that take two years or longer to complete. Students' financial situations and time use vary greatly by program type as well as region. Many of the differences arise because of students' personal characteristics are correlated with the program they are enrolled in. The fact that some programs are more predominant in certain regions adds another dimension to this variation. This dataset was freely received from the Canada Millennium Scholarship Foundation. Some work was required for the variable and value labels, and missing values. They were corrected as best as possible with the documentation received. Caution should be used with this dataset as some variables are lacking information.

In 2023, households in South Korea with a monthly income of eight million South Korean won or more spent an average of 671,000 won per month on their child's private education. The average monthly expenditure per student in South Korea for private education was approximately 431,000 won that year.

This research is a joint effort of the Foundation, all participating colleges and the Association of Canadian Community Colleges (ACCC). The survey collects data on college students' income, expenditures and use of time. The survey is unique in that it provides national-level information on the challenges Canadian college students face in terms of financial and access issues. The objectives of the research are to: provide national-level data on student access; time use and financing for Canadian college students from participating colleges; identify issues particular to certain learner groups and/or regions; and provide each institution with top-line survey results (based on representative samples of their students), which may then be compared against the "national average". In January 2003, the Foundation engaged Prairie Research Associates (PRA) Inc. to oversee this research. This dataset was freely received from the Canada Millennium Scholarship Foundation. Some work was required for the variable and value labels, and missing values. They were corrected as best as possible with the documentation received. Caution should be used with this dataset as some variables are lacking information.

The University of Washington - Beyond High School (UW-BHS) project surveyed students in Washington State to examine factors impacting educational attainment and the transition to adulthood among high school seniors. The project began in 1999 in an effort to assess the impact of I-200 (the referendum that ended Affirmative Action) on minority enrollment in higher education in Washington. The research objectives of the project were: (1) to describe and explain differences in the transition from high school to college by race and ethnicity, socioeconomic origins, and other characteristics, (2) to evaluate the impact of the Washington State Achievers Program, and (3) to explore the implications of multiple race and ethnic identities. Following a successful pilot survey in the spring of 2000, the project eventually included baseline and one-year follow-up surveys (conducted in 2002, 2003, 2004, and 2005) of almost 10,000 high school seniors in five cohorts across several Washington school districts. The high school senior surveys included questions that explored students' educational aspirations and future career plans, as well as questions on family background, home life, perceptions of school and home environments, self-esteem, and participation in school related and non-school related activities. To supplement the 2000, 2002, and 2003 student surveys, parents of high school seniors were also queried to determine their expectations and aspirations for their child's education, as well as their own educational backgrounds and fields of employment. Parents were also asked to report any financial measures undertaken to prepare for their child's continued education, and whether the household received any form of financial assistance. In 2010, a ten-year follow-up with the 2000 senior cohort was conducted to assess educational, career, and familial outcomes. The ten year follow-up surveys collected information on educational attainment, early employment experiences, family and partnership, civic engagement, and health status. The baseline, parent, and follow-up surveys also collected detailed demographic information, including age, sex, ethnicity, language, religion, education level, employment, income, marital status, and parental status.

The Canadian College Student Survey was conducted by the Canada Millennium Scholarship Foundation to provide data on student finances in Canada. The primary objective of the survey was to track the expenses and income of students on a monthly basis, in order to profile the financial circumstances of Canadian students and the adequacy of available funding. The survey will allow the Canada Millennium Scholarship Foundation to understand the financial circumstances of students who are in a post- secondary environment on an annual basis. This research is a joint effort of the Foundation, all participating colleges and the Association of Canadian Community Colleges (ACCC). The survey collects data on college students' income, expenditures and use of time. The survey is unique in that it provides national-level information on the challenges Canadian college students face in terms of financial and access issues. The objectives of the research are to: provide national-level data on student access; time use and financing for Canadian college students from participating colleges; identify issues particular to certain learner groups and/or regions; and provide each institution with top-line survey results (based on representative samples of their students); which may then be compared against the "national average". In January 2003, the Foundation engaged Prairie Research Associates (PRA) Inc. to oversee this research. This dataset was freely received from the Canada Millennium Scholarship Foundation. Some work was required for the variable and value labels, and missing values. They were corrected as best as possible with the documentation received. Caution should be used with this dataset as some variables are lacking information. This dataset was freely received by the Canada Millennium Scholarship Foundation. Some work was required for the variable and value labels, and missing values. The y were corrected as best as possible with the documentation received. Caution should be used with this dataset as some variables are lacking documentation.

This data collection contains information from the first wave of High School and Beyond (HSB), a longitudinal study of American youth conducted by the National Opinion Research Center on behalf of the National Center for Education Statistics (NCES). Data were collected from 58,270 high school students (28,240 seniors and 30,030 sophomores) and 1,015 secondary schools in the spring of 1980. Many items overlap with the NCES's NATIONAL LONGITUDINAL STUDY OF THE CLASS OF 1972 (ICPSR 8085). The HSB study's data are contained in eight files. Part 1 (School Data) contains data from questionnaires completed by high school principals about various school attributes and programs. Part 2 (Student Data) contains data from surveys administered to students. Included are questionnaire responses on family and religious background, perceptions of self and others, personal values, extracurricular activities, type of high school program, and educational expectations and aspirations. Also supplied are scores on a battery of cognitive tests including vocabulary, reading, mathematics, science, writing, civics, spatial orientation, and visualization. To gather the data in Part 3 (Parent Data), a subsample of the seniors and sophomores surveyed in HSB was drawn, and questionnaires were administered to one parent of each of 3,367 sophomores and of 3,197 seniors. The questionnaires contain a number of items in common with the student questionnaires, and there are a number of items in common between the parent-of-sophomore and the parent-of-senior questionnaires. This is a revised file from the one originally released in Autumn 1981, and it includes 22 new analytically constructed variables imputed by NCES from the original survey data gathered from parents. The new data are concerned primarily with the areas of family income, liabilities, and assets. Other data in the file concentrate on financing of post-secondary education, including numerous parent opinions and projections concerning the educational future of the student, anticipated financial aid, student's plans after high school, expected ages for student's marriage and childbearing, estimated costs of post-secondary education, and government financial aid policies. Also supplied are data on family size, value of property and other assets, home financing, family income and debts, and the age, sex, marital, and employment status of parents, plus current income and expenses for the student. Part 4 (Language Data) provides information on each student who reported some non-English language experience, with data on past and current exposure to and use of languages. In Parts 5-6, there are responses from 14,103 teachers about 18,291 senior and sophomore students from 616 schools. Students were evaluated by an average of four different teachers who had the opportunity to express knowledge or opinions of HSB students whom they had taught during the 1979-1980 school year. Part 5 (Teacher Comment Data: Seniors) contains 67,053 records, and Part 6 (Teacher Comment Data: Sophomores) contains 76,560 records. Questions were asked regarding the teacher's opinions of their student's likelihood of attending college, popularity, and physical or emotional handicaps affecting school work. The sophomore file also contains questions on teacher characteristics, e.g., sex, ethnic origin, subjects taught, and time devoted to maintaining order. The data in Part 7 (Twins and Siblings Data) are from students in the HSB sample identified as twins, triplets, or other siblings. Of the 1,348 families included, 524 had twins or triplets only, 810 contained non-twin siblings only, and the remaining 14 contained both types of siblings. Finally, Part 8 (Friends Data) contained the first-, second-, and third-choice friends listed by each of the students in Part 2, along with identifying information allowing links between friendship pairs. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR as four separate datasets here:

1980: https://doi.org/10.3886/ICPSR07896.v2

1982: https://doi.org/10.3886/ICPSR08297.v3

1984: https://doi.org/10.3886/ICPSR08443.v1

1986: https://doi.org/10.3886/ICPSR08896.v3

We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Consumers in the United States had over 16 trillion dollars in debt as of the third quarter of 2023. The majority of that debt were home mortgages, amounting to approximately 11.4 trillion U.S. dollars. Student and car loans were the second and third largest component of household debt. Why is consumer debt important?Debt influences the Consumer Sentiment Index, which is an important indicator assessing the state of the U.S. economy. The U.S. housing market is also seen a bellwether of the economic conditions in the country. The housing industry employs a large number of people, and mortgages are large investments that consumers will pay off over the course of years, sometimes decades. Because of this, financial analysts closely watch consumer debt and its effects on the demand for housing. Attitudes towards debt Consumer perception of debt differed, depending on the kind of debt in question. While most saw a home mortgage as a positive investment, they increasingly looked at student loan debt as a negative debt. With education costs increasing, people are incurring more student loan debt in the United States. Credit card debt also had negative connotations.

The survey is the Finnish contribution to the international Euro Student Report survey. Topics in the survey dealt with the students' housing, studies, economic situation and how they experience it, gainful employment, studying abroad, and the socio-economic position of the students' parents. The respondents were asked what examination they were going to take next, how many years they had studied in a university, how many years they estimated their studies would take, and what their field of studies was. With regard to living conditions, the respondents were asked where they lived during the academic year, how far their apartments were from their place of study, how much money a month they had at their disposal, whether they received financial assistance from their parents, and what their economic situation had been during the last six months. In addition, the respondents were asked to estimate their material well-being, the strenuousness of studies, balancing study and work, and their weekly use of time. Concerning internationality, the respondents were asked about their language skills and whether they had ever been or studied abroad. Those who had studied abroad were asked about the nature, duration and financing of their studies, in which phase of them they studied abroad, and through which programme this took place. Background variables included the respondent's age, sex, marital status, number of children, citizenship, educational background as well as the education, profession, and income of parents.

Abstract copyright UK Data Service and data collection copyright owner.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. Safe Room Access FRS data In addition to the standard End User Licence (EUL) version, Safe Room access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 7196, where the extra contents are listed. The Safe Room version also includes secure access versions of the Households Below Average Income (HBAI) and Pensioners' Incomes (PI) datasets. The Safe Room access data are currently only available to UK HE/FE applicants and for access at the UK Data Archive's Safe Room at the University of Essex, Colchester. Prospective users of the Safe Room access version of the FRS/HBAI/PI will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from Guidance on applying for the Family Resources Survey: Secure Access.FRS, HBAI and PIThe 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 within the Safe Room FRS study under SN 7196 (see above). The Family Resources Survey aims to: support the monitoring of the social security programme; support the costing and modelling of changes to national insurance contributions and social security benefits; provide better information for the forecasting of benefit expenditure. For the fifth edition of the 1995-1996 survey, the new grossing regime, GROSS 3, has been included. Main Topics: Household characteristics (eg. size, tenure type); income and benefit receipt; tenure and housing costs; assets and savings; informal care (given and received); occupation and employment. Standard Measures Standard Occupational Classification The additional derived water and sewerage variables include : a) the water company and sewerage company; b) total annual estimated water consumption in cubic metres; c) estimated water consumption over the summer (taken to be May to August) in cubic metres; d) estimated water consumption over the remainder of the year in cubic metres. Multi-stage stratified random sample Face-to-face interview 1995 1996 ABSENTEEISM ADMINISTRATIVE AREAS AGE AGRICULTURE APARTMENTS APPOINTMENT TO JOB ATTITUDES BEDROOMS BONDS BONUS PAYMENTS CAR SHARING CARE OF DEPENDANTS CARE OF THE DISABLED CARE OF THE ELDERLY CENTRAL HEATING CHARITABLE ORGANIZA... CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILD MINDING CHILD WORKERS CHILDREN COAL COLOUR TELEVISION R... COMMERCIAL BUILDINGS COMMUTING COMPANY CARS COMPUTERS CONSUMER GOODS CONSUMPTION COSTS COUNCIL TAX Consumption and con... DAY NURSERIES DEBTS DENTISTS DIESEL OIL DISABLED CHILDREN DISABLED PERSONS DISMISSAL DISTANCE MEASUREMENT DOMESTIC APPLIANCES DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATION EDUCATIONAL BACKGROUND EDUCATIONAL FEES EDUCATIONAL GRANTS EDUCATIONAL INSTITU... ELDERLY ELECTRIC POWER SUPPLY EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ETHNIC GROUPS EXPENDITURE FAMILIES FAMILY MEMBERS FINANCIAL INSTITUTIONS FINANCIAL RESOURCES FINANCIAL SUPPORT FOOD FOSSIL FUELS FOSTER PARENTS FRIENDS FRINGE BENEFITS FUEL OILS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION Family life and mar... GAS SUPPLY GENDER GIFTS GRANTS HEADS OF HOUSEHOLD HEARING IMPAIRMENTS HEATING SYSTEMS HIGHER EDUCATION HOLIDAYS HOME BASED WORK HOME OWNERSHIP HOME SHARING HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD HEAD S OC... HOUSEHOLDS HOUSING HOUSING FACILITIES HOUSING FINANCE HOUSING TENURE INCOME INCOME TAX INDUSTRIES INSURANCE INSURANCE PREMIUMS INTEREST FINANCE INVESTMENT INVESTMENT RETURN Income JOB DESCRIPTION JOB HUNTING LANDLORDS LAVATORIES LEAVE LOANS LODGERS MANAGERS MARITAL STATUS MARRIED WOMEN MARRIED WOMEN WORKERS MATERNITY LEAVE MATERNITY PAY MEALS MEDICAL PRESCRIPTIONS MILK MORTGAGE PROTECTION... MORTGAGES MOTOR VEHICLES NEIGHBOURS OCCUPATIONAL PENSIONS OCCUPATIONS ONE PARENT FAMILIES OVERTIME PART TIME COURSES PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PENSION CONTRIBUTIONS PETROL PHYSICALLY DISABLED... PHYSICIANS PRICES PRIVATE EDUCATION PRIVATE PERSONAL PE... PRIVATE SCHOOLS PROFITS PUBLIC TRANSPORT QUALIFICATIONS RATES REBATES REDUNDANCY REDUNDANCY PAY RENTED ACCOMMODATION RENTS RESIDENTIAL MOBILITY RETIREMENT ROOM SHARING ROOMS ROYALTIES SAVINGS SCHOLARSHIPS SCHOOL MEALS SCHOOL MILK PROVISION SCHOOLCHILDREN SCHOOLS SEASONAL EMPLOYMENT SECONDARY EDUCATION SECONDARY SCHOOLS SELF EMPLOYED SEWAGE DISPOSAL AND... SHARES SHIFT WORK SICK LEAVE SICK PAY SICK PERSONS SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIAL SERVICES SOCIAL SUPPORT SOCIO ECONOMIC STATUS SOLID FUEL HEATING SPECIAL EDUCATION STATE EDUCATION STATE RETIREMENT PE... STRIKES STUDENT HOUSING STUDENT LOANS STUDENTS STUDY SUBSIDIARY EMPLOYMENT SUPERVISORS Social stratificati... TAX RELIEF TAXATION TELEPHONES TELEVISION RECEIVERS TEMPORARY EMPLOYMENT TERMINATION OF SERVICE TIED HOUSING TOP MANAGEMENT TRAINING TRANSPORT TRAVEL UNEARNED INCOME UNEMPLOYED UNEMPLOYMENT BENEFITS UNFURNISHED ACCOMMO... VIDEO RECORDERS VISION IMPAIRMENTS VOLUNTARY WORK WAGES WATER SUPPLY INDUSTRY WIDOWED WORKING MOTHERS WORKING WOMEN property and invest...

Abstract

In order to elucidate the financial lives of smallholder households and build the evidence base on this important client group, Consultative Group to Assist the Poor (CGAP) of the World Bank launched the year-long Financial Diaries with Smallholder Families (the "Smallholder Diaries"). The study captured the financial and in-kind transactions of 270 households in Tanzania, Pakistan and Mozambique, of which 94 households are in the Punjab province, the breadbasket of Pakistan. The sample was drawn from 2 villages in Pakistan. Villages were selected based on their involvement in agriculture, and convenience in reaching them. Between June 2014 and July 2015, enumerators visited sample families every fortnight to conduct comprehensive face-to-face interviews to track all the money flowing into and out of their households.

Geographic coverage

In Pakistan, the Smallholder Diaries were conducted in Bahawalnagar, southern Punjab, within the country's breadbasket. Rice, wheat, and cotton are commonly grown and typically sold through a network of local commission agents (known as arthis) and village traders. Given the dominance of agricultural middlemen in Pakistan, two villages in the district of Bahawalnagar were selected as representative of an area with relatively looser connections to agricultural value chains and middlemen.

Analysis unit

The main unit for data collection for transactions was the household. However, each income source and financial instrument was ascribed to a specific household member during the initial questionnaire. Thus all transactions associated with that instrument or income source are registered under its owner. Similarly, transactions related to expenses were individually attributed to the member who initiated the respective transaction.

There was a small number of cash flows where the interviewer was not able to unambiguously identify the initiating household member. In these cases, the cash flow was recorded as belonging to the entire household (in the dataset the member ID field would be blank).

Analysis can be performed at two different levels of aggregation: a) The household itself b) Individual household members

In our study the household is defined as including those who consistently share financial resources, live together, share the same cooking arrangement, and report to the same household head. This includes babies, children, people who travel for work or school during the week and consider the household to be their main residence. However, the definition does not include people who are currently spending an extended period of time away from the household, including college students, students away at boarding school, military personnel, people in prison, or people who live in the house but maintain completely separate expenses (e.g. roommates, other families).

Universe

Once the villages for the Smallholder Diaries were selected, the research teams used a screening process to help identify a range of families with 5 acres of land or less, diverse income sources, access to agricultural inputs, wealth levels, and crops to participate in the research.

In Pakistan, the sample was selected using a traditional screener survey with questions related to household demographics, crops and livestock, main income sources, and wealth indicators, administered to all households in the selected villages. As a supplement to this process, village leaders and community representatives were consulted to help ensure local participation and eliminate households with large landholdings.

Kind of data

Event/Transaction data [evn]

Sampling procedure

The methodology and sample size of the Smallholder Diaries was designed to generate a rich pool of detailed information and insights on a targeted population. The Smallholder Diaries are not intended to be statistically representative of smallholder families in participating countries.

Total number of households in sample: 93 (Mozambique); 86 (Tanzania); 94 (Pakistan). The sample came was drawn from 3 villages in Mozambique, 2 villages in Tanzania, and 2 villages in Pakistan. Villages were selected based on their involvement in agriculture, and convenience in reaching them.

The research teams used a screening process to help identify a range of families with 5 acres of land or less, diverse income sources, access to agricultural inputs, wealth levels, and crops to participate in the research. In Pakistan, the sample was selected using a traditional screener survey with questions related to household demographics, crops and livestock, main income sources, and wealth indicators, administered to all households in the selected villages. As a supplement to this process, village leaders and community representatives were consulted to help ensure local participation and eliminate households with large landholdings, harvests per year, use of inputs, and integration with local markets and a variety of families were chosen.

In Pakistan, the sample was selected using a traditional screener survey with questions related to household demographics, crops and livestock, main income sources, and wealth indicators. As a supplement to this process, village leaders and community representatives were consulted to help ensure local ownership and eliminate households with large landholdings.

Mode of data collection

Face-to-face [f2f]

Research instrument

Interviewers visited each household and conducted three initial questionnaires. They 1) collected a household roster and demographic information about household members; 2) captured a register of physical assets and income sources for each household member and 3) registered the unique financial instruments used by each household member. This baseline information was then used to generate a custom cash flows questionnaire for each household, built to collect income, expenditure, and financial transactions for each individual. This customized cash flows questionnaire was then used for the collection of cash flows data. During regular visits about every two weeks, interviewers captured a complete set of daily, individual transactions from the preceding two-week period. Households were asked only about transactions using financial instruments and income sources that they actually have, rather than going through a generic list of questions. However, the cash flows questionnaire was continuously updated as new members joined the household, members acquired new financial instruments or income sources, or as the interviewers became aware of previously undisclosed ones.

Cleaning operations

All data editing was done manually.

Response rate

The sample initially included 286 households in all three countries, and the study ended with 273 households in total – an attrition rate similar to what has been observed in the past in similar Financial Diaries exercises. Households left the study due to moving from the study villages, seasonal migration, and occasionally by the prompting of the research team due to concerns about the household’s willingness to be forthcoming about important sources of income.

This is a development key figure, see questions and answers on kolada.se for more information. Refers only to the situational perspective of municipal schools’ results. Municipal schools also include schools run by municipal associations. The task is based on a regression model developed by Statistics Sweden and SKR to take into account the different socio-economic conditions of different municipalities. The explanatory variables include the level of education of the parents, the parents’ income, gender, share of newly immigrated pupils and the need for financial assistance. Students who do not have a Swedish personal identity number at the beginning of their education (e.g. newly arrived pupils who have not yet been registered in the population register) are not included. Municipalities whose assignments are based on fewer than 30 students have been subject to confidentiality. For more information, see the report Open Comparisons – Upper Secondary School.

Abstract

In order to elucidate the financial lives of smallholder households and build the evidence base on this important client group, Consultative Group to Assist the Poor (CGAP) of the World Bank launched the year-long Financial Diaries with Smallholder Families (the "Smallholder Diaries"). The study captured the financial and in-kind transactions of 270 households in Tanzania, Pakistan and Mozambique, of which 93 households are in impoverished northern Mozambique. The sample came was drawn from 3 villages in Mozambique. Villages were selected based on their involvement in agriculture, and convenience in reaching them. Between June 2014 and July 2015, enumerators visited sample families every fortnight to conduct comprehensive face-to-face interviews to track all the money flowing into and out of their households.

Geographic coverage

In Mozambique, three villages in the Rapale district of northern Nampula Province were selected based on strong recommendations from local stakeholders. While some large companies buy cash crops in the province, smallholders tend to practice the subsistence, rain-fed agriculture that is more commonly found throughout Mozambique.

Analysis unit

The main unit for data collection for transactions was the household. However, each income source and financial instrument was ascribed to a specific household member during the initial questionnaire. Thus all transactions associated with that instrument or income source are registered under its owner. Similarly, transactions related to expenses were individually attributed to the member who initiated the respective transaction.

There was a small number of cash flows where the interviewer was not able to unambiguously identify the initiating household member. In these cases, the cash flow was recorded as belonging to the entire household (in the dataset the member ID field would be blank).

Analysis can be performed at two different levels of aggregation: a) The household itself b) Individual household members

In our study the household is defined as including those who consistently share financial resources, live together, share the same cooking arrangement, and report to the same household head. This includes babies, children, people who travel for work or school during the week and consider the household to be their main residence. However, the definition does not include people who are currently spending an extended period of time away from the household, including college students, students away at boarding school, military personnel, people in prison, or people who live in the house but maintain completely separate expenses (e.g. roommates, other families).

Universe

Once the villages for the Smallholder Diaries were selected, the research teams used a screening process to help identify a range of families with 5 acres of land or less, diverse income sources, access to agricultural inputs, wealth levels, and crops to participate in the research.

In Mozambique, these eligible households were identified using a participatory rural appraisal wealth-ranking technique. Working with committees of village representatives, the research teams conducted wealth-ranking exercises to assess the relative wealth of households in village hamlets or subareas.

Kind of data

Event/Transaction data [evn]

Sampling procedure

The methodology and sample size of the Smallholder Diaries was designed to generate a rich pool of detailed information and insights on a targeted population. The Smallholder Diaries are not intended to be statistically representative of smallholder families in participating countries.

Total number of households in sample: 93 (Mozambique); 86 (Tanzania); 94 (Pakistan). The sample came was drawn from 3 villages in Mozambique, 2 villages in Tanzania, and 2 villages in Pakistan. Villages were selected based on their involvement in agriculture, and convenience in reaching them.

The research teams used a screening process to help identify a range of families with 5 acres of land or less, diverse income sources, access to agricultural inputs, wealth levels, and crops to participate in the research. In Mozambique, these eligible households were identified using a participatory rural appraisal wealth-ranking technique. Working with committees of village representatives, the research teams conducted wealth-ranking exercises to assess the relative wealth of households in village hamlets or subareas.

Mode of data collection

Face-to-face [f2f]

Research instrument

Interviewers visited each household and conducted three initial questionnaires. They 1) collected a household roster and demographic information about household members; 2) captured a register of physical assets and income sources for each household member and 3) registered the unique financial instruments used by each household member. This baseline information was then used to generate a custom cash flows questionnaire for each household, built to collect income, expenditure, and financial transactions for each individual. This customized cash flows questionnaire was then used for the collection of cash flows data. During regular visits about every two weeks, interviewers captured a complete set of daily, individual transactions from the preceding two-week period. Households were asked only about transactions using financial instruments and income sources that they actually have, rather than going through a generic list of questions. However, the cash flows questionnaire was continuously updated as new members joined the household, members acquired new financial instruments or income sources, or as the interviewers became aware of previously undisclosed ones.

Cleaning operations

All data editing was done manually.

Response rate

The sample initially included 286 households in all three countries, and the study ended with 273 households in total – an attrition rate similar to what has been observed in the past in similar Financial Diaries exercises. Households left the study due to moving from the study villages, seasonal migration, and occasionally by the prompting of the research team due to concerns about the household’s willingness to be forthcoming about important sources of income.

Low-income Working Family Allowance Scheme - No. of approved applications based on the household size

Denmark, the Netherlands, and Norway were among the European countries with most indebted households in 2023 and 2024. The debt of Dutch households amounted to 200 percent their disposable income in , as they had a ratio of over 180 percent in the second quarter of 2024. Meanwhile, Norwegian households' debt represented 233 percent of their income. However, households in most countries were less indebted, with that ratio amounting to 97 percent in the Euro area. Less indebtedness in Western and Northern Europe There were several European countries where household's debts outweighed their disposable income. Most of those countries were North or West European. However, the indebtedness ratio in Denmark has been decreasing during the past decade. As the debt of Danish households represented nearly 273 percent in the last quarter of 2014, which has fallen very significantly by 2024. Other countries with indebted households have been following similar trends. The households' debt-to-income ratio in the Netherlands has also fallen from over 275 percent in 2013 to 200 percent in 2024. Debt per adult in Europe In Europe, the value of debt per adult varies considerably from an average of around 10,000 U.S. dollars in Europe to a much higher level in certain countries such as Switzerland. Debts can be formed in a number of ways. The most common forms of debt include credit cards, medical debt, student loans, overdrafts, mortgages, automobile financing and personal loans.

The principal purposes of this national longitudinal study of the higher education system in the United States are to describe the characteristics of new college freshmen and to explore the effects of college on students. For each wave of this survey, each student completes a questionnaire during freshman orientation or registration that asks for information on academic skills and preparation, high school activities and experiences, educational and career plans, majors and careers, student values, and financing college. Other questions elicit demographic information, including sex, age, parental education and occupation, household income, race, religious preference, and state of birth. Specific questions asked of respondents in the 1980 survey included information regarding the BEOG (Basic Educational Opportunity Grant) and GSL (Guaranteed Student Loan) financial aid programs, students' number of brothers and sisters, whether students considered themselves born-again Christians, and whether students considered themselves physically handicapped.

2020 2022 ACADEMIC ACHIEVEMENT ACCIDENTS ADOLESCENTS ADOPTED CHILDREN ADOPTIVE PARENTS ADULTS AGE ALCOHOL USE APPLICATION FOR EMP... BEDROOMS BIRTH WEIGHT BREAST FEEDING BROADBAND BULLYING BUSINESSES CABLE TELEVISION CARE OF DEPENDANTS CENTRAL HEATING CHILD BENEFITS CHILD CARE CHILD SUPPORT PAYMENTS CHILDBIRTH CHILDREN CITIZENSHIP CIVIL PARTNERSHIPS COHABITATION COHABITING COLOUR TELEVISION R... COMPACT DISC PLAYERS COMPUTERS CONSUMER GOODS COSTS COUNCIL TAX CULTURAL GOODS DEBILITATIVE ILLNESS DEBTS DEGREES DEPRESSION DIGITAL GAMES DISABILITIES DISABLED PERSONS DISEASES DIVORCE DOMESTIC APPLIANCES DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL EXPECTA... EMOTIONAL STATES EMPLOYEES EMPLOYERS EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT OPPORTUN... EMPLOYMENT PROGRAMMES ENVIRONMENTAL CONSE... ENVIRONMENTAL ISSUES ETHNIC GROUPS ETHNIC MINORITIES EXPENDITURE Education FAMILIES FAMILY COHESION FAMILY ENVIRONMENT FAMILY LIFE FAMILY MEMBERS FAMILY SIZE FATHER S ECONOMIC A... FATHER S PLACE OF B... FATHERS FINANCIAL DIFFICULTIES FINANCIAL EXPECTATIONS FINANCIAL RESOURCES FINANCIAL SUPPORT FRIENDS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION GENDER GRANDPARENTS HAPPINESS HEALTH HEALTH STATUS HIGHER EDUCATION HOLIDAYS HOME BUYING HOME OWNERSHIP HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD INCOME HOUSEHOLDS HOUSES HOUSEWORK HOUSING HOUSING BENEFITS HOUSING CONDITIONS HOUSING FACILITIES HOUSING FINANCE HOUSING TENURE Health Housing ILL HEALTH INCOME INFORMAL CARE INTERNET ACCESS INTERNET USE INVESTMENT Income JOB CHANGING JOB HUNTING JOB SATISFACTION JUVENILE DELINQUENCY LANDLORDS LANGUAGES LEAVING HOME YOUTH LEISURE TIME ACTIVI... LIFE SATISFACTION LOANS Labour and employment MANAGERS MARITAL HISTORY MARITAL STATUS MARRIAGE MARRIAGE DISSOLUTION MOBILE PHONES MORTGAGE ARREARS MORTGAGES MOTHER S ECONOMIC A... MOTHER S PLACE OF B... MOTHERS MOTOR VEHICLES Minorities NATIONALITY NEIGHBOURHOODS NEIGHBOURS OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONAL TRAINING OCCUPATIONS ONE PARENT FAMILIES OVERTIME PARENT CHILD RELATI... PARENT RESPONSIBILITY PARENTAL ROLE PARENTAL SUPERVISION PART TIME EMPLOYMENT PARTICIPATION PAYMENTS PERSONAL DEBT REPAY... PHYSICAL MOBILITY PLACE OF BIRTH PLACE OF RESIDENCE PRIVATE PERSONAL PE... PRIVATE SCHOOLS PRIVATE SECTOR PROFITS PUBLIC SECTOR QUALIFICATIONS QUALITY OF LIFE RECREATIONAL FACILI... RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RELIGIOUS DOCTRINES RENTED ACCOMMODATION RENTS RESIDENTIAL MOBILITY RETIREMENT ROOMS RURAL AREAS SATELLITE RECEIVERS SAVINGS SCHOOL LEAVING AGE SCHOOL PUNISHMENTS SCHOOLS SEASONAL EMPLOYMENT SELF EMPLOYED SELF ESTEEM SHOPPING SIBLINGS SLEEP SMOKING SOCIAL ATTITUDES SOCIAL CAPITAL SOCIAL CLASS SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIO ECONOMIC STATUS SPOUSES STANDARD OF LIVING STATE EDUCATION STATE RETIREMENT PE... STEPCHILDREN STUDENT TRANSPORTATION STUDENTS SUBCONTRACTING SUBSIDIARY EMPLOYMENT SUPERVISORS Social behaviour an... TELEPHONES TELEVISION RECEIVERS TELEVISION VIEWING TEMPORARY EMPLOYMENT TIED HOUSING TRAINING TRUANCY UNEARNED INCOME UNEMPLOYED UNEMPLOYMENT UNFURNISHED ACCOMMO... URBAN AREAS United Kingdom WAGES WEIGHT PHYSIOLOGY WELSH LANGUAGE WIDOWED WORKING WOMEN WORKPLACE YOUTH property and invest...

This refers only to the results of municipal schools. Municipal schools also include schools run by municipal associations. The task is based on a regression model developed by Statistics Sweden and SKR to take into account the different socio-economic conditions of different municipalities. The explanatory variables include the level of education of the parents, the parents’ income, gender, share of newly immigrated pupils and the need for financial assistance. Students who do not have a Swedish personal identity number at the beginning of their education (e.g. newly arrived pupils who have not yet been registered in the population register) are not included. Municipalities whose assignments are based on fewer than 30 students have been subject to confidentiality. For more information, see the report Open Comparisons – Upper Secondary School.