This dataset covers a Nationally Representative Sample of the Suriname population. It measures all main aspects of living conditions and reports consumption based poverty rates. The survey was executed between January and December 2022 (12 full months of fieldwork).

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 conducted an online survey investigating people’s everyday financial practices, evolving perceptions of trust and risk, and their unmet financial needs. The general population survey data was collected between April 15 and April 22, 2022. The credit union data was collected between May 3 and July 18, 2022. This data set contains the responses of the survey participants after excluding any personally identifying data. All study materials and procedures were approved by the University of California, Irvine Office of Human Research Protections and the Institutional Review Board (protocol ID 20216839)...., Survey data was collected via the Qualtrics platform. The survey contains 52 questions. It was distributed to the general population in zip codes within the counties of Los Angeles and Orange. It was also distributed directly to members of a large credit union headquartered in Orange County (“large†according to NCUA asset classes). Participants were eligible to complete the survey if they live in Orange County or Los Angeles County, are older than 18, and have a combined household income of less than $100,000. Incomplete responses have been removed. The survey yielded 1,370 complete responses (1,213 from the general population participants and 157 from members of the large credit union)., Note that the files do not contain all the responses from the survey questions. Responses that provided potentially identifying information were removed. Survey participants’ gender, education status, employment status, and marital status were removed; data on these elements are provided in aggregate in the readme file. Responses are segmented into two files reflecting participants from the general population (“Gen Pop†) and from the credit union (“CU†).

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.

Background:
A household food consumption and expenditure survey has been conducted each year in Great Britain (excluding Northern Ireland) since 1940. At that time the National Food Survey (NFS) covered a sample drawn solely from urban working-class households, but this was extended to a fully demographically representative sample in 1950. From 1957 onwards the Family Expenditure Survey (FES) provided information on all household expenditure patterns including food expenditure, with the NFS providing more detailed information on food consumption and expenditure. The NFS was extended to cover Northern Ireland from 1996 onwards. In April 2001 these surveys were combined to form the Expenditure and Food Survey (EFS), which completely replaced both series. From January 2008, the EFS became known as the Living Costs and Food (LCF) module of the Integrated Household Survey (IHS). As a consequence of this change, the questionnaire was altered to accommodate the insertion of a core set of questions, common to all of the separate modules which together comprised the IHS. Some of these core questions are simply questions which were previously asked in the same or a similar format on all of the IHS component surveys. For further information on the LCF questionnaire, see Volume A of the LCF 2008 User Guide, held with SN 6385. Further information about the LCF, including links to published reports based on the survey, may be found by searching for 'Living Costs and Food Survey' on the ONS website. Further information on the NFS and Living Costs and Food Module of the IHS can be found by searching for 'Family Food' on the GOV.UK website.

History:
The LCF (then EFS) was the result of more than two years' development work to bring together the FES and NFS; both survey series were well-established and important sources of information for government and the wider community, and had charted changes and patterns in spending and food consumption since the 1950s. Whilst the NFS and FES series are now finished, users should note that previous data from both series are still available from the UK Data Archive, under GNs 33071 (NFS) and 33057 (FES).

Purpose of the LCF
The Office for National Statistics (ONS) has overall project management and financial responsibility for the LCF, while the Department for Environment, Food and Rural Affairs (DEFRA) sponsors the food data element. As with the FES and NFS, the LCF continues to be primarily used to provide information for the Retail Prices Index, National Accounts estimates of household expenditure, analysis of the effect of taxes and benefits, and trends in nutrition. The results are multi-purpose, however, providing an invaluable supply of economic and social data. The merger of the two surveys also brings benefits for users, as a single survey on food expenditure removes the difficulties of reconciling data from two sources. Design and methodology The design of the LCF is based on the old FES, although the use of new processing software by the data creators has resulted in a dataset which differs from the previous structure. The most significant change in terms of reporting expenditure, however, is the introduction of the European Standard Classification of Individual Consumption by Purpose (COICOP), in place of the codes previously used. An additional level of hierarchy has been developed to improve the mapping to the previous codes. The LCF was conducted on a financial year basis from 2001, then moved to a calendar year basis from January 2006 (to complement the IHS) until 2015-16, when the financial year survey was reinstated at the request of users. Therefore, whilst SN 5688 covers April 2005 - March 2006, SN 5986 covers January-December 2006. Subsequent years cover January-December until 2014. SN 8210 returns to the financial year survey and currently covers April 2015 - March 2016.

Northern Ireland sample
Users should note that, due to funding constraints, from January 2010 the Northern Ireland (NI) sample used for the LCF was reduced to a sample proportionate to the NI population relative to the UK.

Family Food database:
'Family Food' is an annual publication which provides detailed statistical information on purchased quantities, expenditure and nutrient intakes derived from both household and eating out food and drink. Data is collected for a sample of households in the United Kingdom using self-reported diaries of all purchases, including food eaten out, over a two week period. Where possible quantities are recorded in the diaries but otherwise estimated. Energy and nutrient intakes are calculated using standard nutrient composition data for each of some 500 types of food. Current estimates are based on data collected in the Family Food Module of the LCFS. Further information about the LCF food databases can be found on the GOV.UK Family Food Statistics web pages.

Secure Access version
A Secure Access version of the LCF from 2006 onwards is available from the UK Data Archive under SN 7047, subject to stringent access conditions. The Secure Access version includes variables that are not included in the standard End User Licence (EUL) version, including geographical variables with detail below Government Office Region, to postcode level; urban/rural area indicators; other sensitive variables; raw diary information files (derived variables are available in the EUL) and the family expenditure codes files. Users are strongly advised to check whether the EUL version is sufficient for their needs before considering an application for the Secure Access version.

Occupation data for 2021 and 2022 data files
The ONS have identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. For further information on this issue, please see: https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys.

Latest edition information

For the second edition (March 2025) the DEFRA Family Food database was added to the study. This is available as a separate Access download zip file for those users who require it.

For the third edition (April 2025), the following previously unpopulated variables in the dvhh files were replaced with new versions: a111p (Rooms used solely by household - anonymised), a112 (Rooms shared by household), a114p (Rooms in accomodation - anonymised), p200p (Number of rooms occupied (DE basis) anonymised) and oecd (OECD Scale factor).

SCE: Credit Availability: Year Ago: Somewhat Easier data was reported at 8.882 % in Apr 2025. This records an increase from the previous number of 7.468 % for Mar 2025. SCE: Credit Availability: Year Ago: Somewhat Easier data is updated monthly, averaging 17.195 % from Jun 2013 (Median) to Apr 2025, with 143 observations. The data reached an all-time high of 24.215 % in Jan 2018 and a record low of 5.976 % in Aug 2022. SCE: Credit Availability: Year Ago: Somewhat Easier data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.H085: Survey of Consumer Expectations: Financial.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world’s most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of almost 145,000 people in 139 economies, representing 97 percent of the world’s population. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

Some communes in the Agadez region and Diffa region were excluded because of insecurity. In addition PSUs with fewer than 25 households were also excluded. The excluded area represents approximately 8% of the population.

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19–related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Additionally, phone surveys were not a viable option in 16 economies in 2021, which were then surveyed in 2022.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Niger is 1000.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

This NeuroVERSE record contains two files: ALSFocus_Wave1_Public.csv – This data file contains responses from both the Demographics survey and the survey on Insurance Needs and Financial Burdens, which were fielded in Wave 1 of ALS Focus. This file includes responses collected from February 13, 2020 through April 3, 2020, the launch date and close date of Wave 1, respectively. The file uses a ‘flattened’ format with one record per subject. Variables are organized across the columns with variable names corresponding to the data dictionary. Subject_ID 199 is a test case and has been removed from the data file as of January 5, 2022. Wave 1_Data Dictionary_Public.xlsx – This file is the data dictionary for surveys fielded in ALS Focus Wave 1, including the Demographics survey and the survey on Insurance Needs and Financial Burdens.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world’s most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of almost 145,000 people in 139 economies, representing 97 percent of the world’s population. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19–related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Additionally, phone surveys were not a viable option in 16 economies in 2021, which were then surveyed in 2022.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Eswatini is 1000.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

Abstract

The survey was commissioned by the World Bank and it is aligned with the objectives of the World Bank's (WB) Global Program on Consumer Protection and Financial literacy that was launched in 2010. The aim of the WB program is to help targeted countries achieve better consumer protection in financial services. The WB initiative has targeted both public and private sector agencies, and has sponsored comprehensive research projects with the objective of finding the best solutions for each individual country/region. The survey focuses on financial services such as banking, insurance, microfinance in terms of credit, savings and payment systems, and was designed to identify the level of financial awareness and familiarity with financial services providers in the West Bank and Gaza. The survey also tried to identify appropriate methods for expanding consumer education and strengthening consumer rights in the West Bank and Gaza.

It is expected that the survey will support the objectives outlined by the Word Bank's Financial Governance/Consumer Protection in Financial Services Program. A major objective of this survey is to provide regional data for the World Bank's multi-national database. Thus, the inherent strengths of this initiative is that it will allow regional stakeholders the opportunity to draw upon both local and international data. Local, international, small and large-scale strategies can then be formulated by comparing the diagnostic reviews of local data to that of other survey countries. By learning from the successes and failures of other survey countries, more effective mechanisms for the improvement of consumer protection and financial literacy in the West Bank and Gaza can be established.

Geographic coverage

National

Analysis unit

Household, individual

Universe

The target population is comprised of all Palestinians of the age group 18 - 65 years old residing in the territories of the West Bank and Gaza.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey collected data from 2022 Palestinians in the West Bank and Gaza. The sample distribution was 66.8% West Bank and 33.2% Gaza Strip.

Sampling Frame

The sampling frame included all geographical locations in which the target population resides. The sampling frame was used to select the sample of locations for the survey. It also included the type of localities (urban, rural and refugee camps) and population size in each location. This information was taken into consideration in designing the survey sample.

The following table provides the distribution of Palestinian households by governorates according to data available on the Census of 2007:

Sampling Frame according to Number of Households:

Governorate Total Number of Households West Bank: Jenin 47,437 Tubas 9,004 Tulkarem 29,938 Nablus 59,663 Qalqilia 16,483 Salfit 11,103 Ramallah Al Bireh 52,834 Jericho 7,615 Jerusalem 70,434 Bethlehem 32,667 Hebron 89,919 Subtotal 427,097

Gaza Strip: North Gaza 40,262 Gaza 76,810 Deir Al Balah 32,083 Khan Yonis 43,203 Rafah 26,863 Subtotal 219,221

Total 646,318

The following table shows the distribution of Palestinian households according to type of locality:

Sampling Frame according to Type of Locality Type of Locality Number of Households

Urban 472,736 Rural 113,386 Refugee Camps 60,196

Total 646,318

The frame was divided into strata depending on the homogeneity of the divided parts as follows: A) Governorates: 16 in the West Bank and Gaza. B) The type of locality: city, village and refugee camp.

Sample Design and Type

Three Stage Stratified Cluster Sample of 2022 persons (2022 households). The sample design was as follows: 1. Stage one: selection a sample of 60 representative localities covering all strata. 2. Stage two: selection a random sample of Palestinian households from each location selected in the first stage. 3. Stage three: random selection of one person from each household using Kish table within the age group of 18 years old and above. Half of the sample will be male and half is female respondents.

Sample Size The sample size was 2022 persons from all Palestinian territories aged 18 years and above. Main regions covered by the sample are: the West Bank (excluding Ramallah), Ramallah and Gaza Strip. The sample was distributed as follows:

Region / # of Households

Ramallah and Al Bireh 350 West Bank 1000 Gaza Strip 672 Total 2022

The margin of error in the main key variables is approximately 2.5% on the entire sample size and it should be bigger in the detailed domains.

Sample Representation:

The researchers ensured that the sample is representative of the following during the field work:

1) Geographical representation: the sample distribution covers all governorates of the West Bank (including Jerusalem) and Gaza strip, thus provides a comprehensive geographical representation. 2) Economic Activity: in general, Ramallah and Al Bireh governorate is considered the economic and commercial center and thus was given a higher weight in the sample compared to the rest of the localities. 3) Economic Sectors: the sample covered different economical sectors such as employees of industrial, services and commercial sectors (usually in the main cities), workers in the agricultural sector (rural areas) and workers in the informal sector (mostly in Gaza). 4) Poverty levels: the sample covers poor localities as provided by statistics. In general, Gaza is considered poorer than the West Bank. Also, refugee camps and some localities particularly in North West Bank are considered poorer than the rest of localities and the above sample distribution provides coverage of such localities. 5) Age Groups: the sample covered all age groups above the age of 18. The reason behind selecting the starting age to be 18 is the fact that it is within this age that an individual is expected to become involved with financial transactions and thus will be dealing with financial services. 6) Gender: the sample was gender balanced; half of the respondents were males and half were females. This corresponds with the gender distribution of the Palestinian Territories. 7) Infrastructure: the sample covered central and remote localities to guarantee representation of poor versus good infrastructure and availability of services including financial services.

Mode of data collection

Face-to-face [f2f]

Research instrument

A standard questionnaire was previously developed by the World Bank and was adapted to the Palestinian context by Riyada Consulting. The questionnaire was also shared with local stakeholders such as the Palestinian Monetary Authority, USAID and other departments of the World Bank.

ABOUT THE COMMUNITY SURVEY REPORTFinal Reports for ETC Institute conducted annual community attitude surveys for the City of Tempe. These survey reports help determine priorities for the community as part of the City's on-going strategic planning process.In many of the survey questions, survey respondents are asked to rate their satisfaction level on a scale of 5 to 1, where 5 means "Very Satisfied" and 1 means "Very Dissatisfied" (while some questions follow another scale). The survey is mailed to a random sample of households in the City of Tempe and has a 95% confidence level.PERFORMANCE MEASURESData collected in these surveys applies directly to a number of performance measures for the City of Tempe including the following (as of 2022):1. Safe and Secure Communities1.04 Fire Services Satisfaction1.06 Crime Reporting1.07 Police Services Satisfaction1.09 Victim of Crime1.10 Worry About Being a Victim1.11 Feeling Safe in City Facilities1.23 Feeling of Safety in Parks2. Strong Community Connections2.02 Customer Service Satisfaction2.04 City Website Satisfaction2.05 Online Services Satisfaction Rate2.15 Feeling Invited to Participate in City Decisions2.21 Satisfaction with Availability of City Information3. Quality of Life3.16 City Recreation, Arts, and Cultural Centers3.17 Community Services Programs3.19 Value of Special Events3.23 Right of Way Landscape Maintenance3.36 Quality of City Services4. Sustainable Growth & DevelopmentNo Performance Measures in this category presently relate directly to the Community Survey5. Financial Stability & VitalityNo Performance Measures in this category presently relate directly to the Community SurveyMethodsThe survey is mailed to a random sample of households in the City of Tempe. Follow up emails and texts are also sent to encourage participation. A link to the survey is provided with each communication. To prevent people who do not live in Tempe or who were not selected as part of the random sample from completing the survey, everyone who completed the survey was required to provide their address. These addresses were then matched to those used for the random representative sample. If the respondent’s address did not match, the response was not used. To better understand how services are being delivered across the city, individual results were mapped to determine overall distribution across the city. Additionally, demographic data were used to monitor the distribution of responses to ensure the responding population of each survey is representative of city population. The 2022 Annual Community Survey data are available on data.tempe.gov. The individual survey questions as well as the definition of the response scale (for example, 1 means “very dissatisfied” and 5 means “very satisfied”) are provided in the data dictionary.More survey information may be found on the Strategic Management and Innovation Signature Surveys, Research and Data page at https://www.tempe.gov/government/strategic-management-and-innovation/signature-surveys-research-and-data.Additional InformationSource: Community Attitude SurveyContact (author): Adam SamuelsContact E-Mail (author): Adam_Samuels@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Data received from vendor after report is completedPublish Frequency: AnnualPublish Method: ManualData Dictionary

South Korea Average: HPL: Others: TL: Receiving Money from a Lease data was reported at 42,488.056 KRW th in 2024. This records an increase from the previous number of 41,327.915 KRW th for 2023. South Korea Average: HPL: Others: TL: Receiving Money from a Lease data is updated yearly, averaging 40,447.548 KRW th from Mar 2017 (Median) to 2024, with 8 observations. The data reached an all-time high of 42,488.056 KRW th in 2024 and a record low of 29,940.560 KRW th in 2019. South Korea Average: HPL: Others: TL: Receiving Money from a Lease data remains active status in CEIC and is reported by Statistics Korea. The data is categorized under Global Database’s South Korea – Table KR.H139: 2022 Survey of Household Finances & Living Conditions: by the Kind of House.

ABOUT THE CITY OF TEMPE EMPLOYEE SURVEY REPORT (DATASET)This report (dataset) includes the results from the Tempe Employee Survey, conducted every other year, to gather input from employees about issues in six major areas: professional development and career mobility; organizational support; supervisions and working environment; compensation and benefits; employee engagement; and peer relationships. Participation in the survey is voluntary and confidential. Employees are able to complete the survey during work hours or at home, with surveys directly returned to the vendor conducting the survey.In many of the survey questions, survey respondents are asked to rate their agreement level with a given statement on a scale of 5 to 1, where 5 means "Strongly Agree" and 1 means "Strongly Disagree" (while some questions follow another scale). The survey has a 95% confidence level.PERFORMANCE MEASURESData collected in this survey applies directly to the following Performance Measures for the City of Tempe:1. Safe and Secure Communities1.11 Feeling Safe in City Facilities2. Strong Community Connections2.13 Employee Engagement2.25 Employee Work-Related Needs3. Quality of LifeNo performance measures in this category presently relate directly to the Employee Survey4. Sustainable Growth & DevelopmentNo performance measures in this category presently relate directly to the Employee Survey5. Financial Stability & VitalityNo performance measures in this category presently relate directly to the Employee Survey The City of Tempe Employee Survey was first conducted in 2016 and occurs every two years.Additional InformationSource: Community Attitude SurveyContact (author): Adam SamuelsContact E-Mail (author): Adam_Samuels@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Data received from vendor after report is completedPublish Frequency: BiennialPublish Method: ManualData Dictionary (pending)

Household variables for the 2022 Annual Survey on Income and Living Conditions are presented. The aim of the survey is to produce statistical information comparable with other European Union (EU) countries on gross and disposable household income, housing conditions, the physical and social environment of the household, access to some needs, employment, work, health status and problems and access to health care for household members over 16 years of age, and to assess the indicators of the at-risk-of-poverty rate, material deprivation and social exclusion. Statistical data are collected on household composition (and changes in households participating in previous surveys), housing conditions, household financial situation, etc. at the time of the survey, i.e. the interview. Statistics on income received and taxes paid are collected for the previous calendar year.

According to a survey conducted by Voxburner in 2022, approximately 69 percent of students in the UK thought that the government should be responsible for providing financial support during the Cost of Living Crisis.

The financial behaviours survey aim to collect general information on financial and digital literacy of refugees and asylum-seekers in Malaysia for the purpose of understanding their familiarity with and interest in financial and digital services. The survey was administered via phone calls, where respondents were identified through a random sampling of individuals aged 18-59 registered with UNHCR, and have updated their contact numbers with UNHCR in the last 6 months.

A majority of respondents are able to confidently make calculations and transact with money without errors. As a result of regulatory challenges, only 35.8% of respondents owned SIM cards registered under their own names. 89% of respondents own a smartphone, with the most frequently used mobile apps being Whatsapp, followed by Facebook, Youtube, imo and TikTok. While respondents seem to understand the value of financial services, only 11% actually own an account at a financial institutions due to regulatory barriers. A majority of respondents also rely on informal services for sending or receiving money either locally (within Malaysia) or internationally. In addition to this, 84.9% reported not having any savings whatsoever, which indicates respondents' limited resilience capacities to withstand sudden shocks or stressors.

In association with the July/August 2022 process for 43rd ward residents to apply for the opportunity to fill the aldermanic vacancy in that ward, residents were also invited to fill out an online survey, seeking their opinions on issues. The results of that survey are shown in this dataset.

Respondents were presented with eight issues plus "other" and asked to rank each one as being between Not a Priority (1) and Urgent Priority (5). There was no limit to how often each ranking could be used, although respondents were encouraged to rank only a few issues as Urgent Priority.

The final question was free text, intended to capture descriptions of "other" issues but if the respondent provided other text, it is included except in limited cases where it is redacted for privacy or similar reasons.

Please note that the survey is not and was not intended to be a random sample or otherwise scientifically or statistically valid. There were no formal barriers to people not residents of the 43rd ward responding, people responding more than once, or other things of that nature. It was intended only as a simple tool to collect such information as people cared to submit and should be interpreted in that spirit.

A copy of the original survey is at https://www.chicago.gov/content/dam/city/about/wards/ward-43-application-processs/Survey.pdf.

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.

Context

The World Happiness Report may be a point of interest survey of the state of worldwide bliss. The primary report was distributed in 2012, the second in 2013, the third in 2015, and the fourth within the 2016 Upgrade. The World Joy 2017, which positions 155 nations by their bliss levels, was discharged at the Joined together Countries at an occasion celebrating Universal Day of Joy on Walk 20th. The report proceeds to pick up worldwide acknowledgment as governments, organizations and respectful society progressively utilize joy pointers to educate their policy-making choices. Driving specialists over areas – financial matters, brain research, overview investigation, national insights, wellbeing, open approach and more – depict how estimations of well-being can be used effectively to evaluate the advance of countries. The reports survey the state of bliss within the world nowadays and appear how the modern science of bliss clarifies individual and national varieties in bliss.

Content

The joy scores and rankings utilize information from the Gallup World Survey. The scores are based on answers to the most life evaluation address inquired within the survey. This address, known as the Cantril step, asks respondents to think of a step with the most excellent conceivable life for them being a 10 and the most exceedingly bad conceivable life being a and to rate their claim current lives on that scale. The scores are from broadly agent tests for the a long time 2013-2016 and utilize the Gallup weights to create the gauges agent. The columns taking after the bliss score assess the degree to which each of six variables – financial generation, social back, life anticipation, flexibility, nonattendance of debasement, and liberality – contribute to making life assessments higher in each nation than they are in Dystopia, a theoretical nation that has values rise to to the world’s least national midpoints for each of the six variables. They have no affect on the full score detailed for each nation, but they do exp

This file contains the Happiness Score for 153 countries along with the factors used to explain the score.

The Happiness Score is a national average of the responses to the main life evaluation question asked in the Gallup World Poll (GWP), which uses the Cantril Ladder.

The Happiness Score is explained by the following factors:

GDP per capita Healthy Life Expectancy Social support Freedom to make life choices Generosity Corruption Perception Residual error The data is described in much more detail here: link

Acknowledgements

I did not create this data, only sourced it. The credit goes to the original Authors:

Editors: John Helliwell, Richard Layard, Jeffrey D. Sachs, and Jan Emmanuel De Neve, Co-Editors; Lara Aknin, Haifang Huang and Shun Wang, Associate Editors; and Sharon Paculor, Production Editor

Citation: Helliwell, John F., Richard Layard, Jeffrey Sachs, and Jan-Emmanuel De Neve, eds. 2020. World Happiness Report 2020. New York: Sustainable Development Solutions Network

Russia Central Bank Survey: CO: Other Non Financial Organizations: FC: Loans data was reported at 0.000 RUB mn in Jan 2022. This stayed constant from the previous number of 0.000 RUB mn for Dec 2021. Russia Central Bank Survey: CO: Other Non Financial Organizations: FC: Loans data is updated monthly, averaging 0.000 RUB mn from Dec 2014 (Median) to Jan 2022, with 86 observations. The data reached an all-time high of 0.000 RUB mn in Jan 2022 and a record low of 0.000 RUB mn in Jan 2022. Russia Central Bank Survey: CO: Other Non Financial Organizations: FC: Loans data remains active status in CEIC and is reported by Bank of Russia. The data is categorized under Russia Premium Database’s Monetary and Banking Statistics – Table RU.KAA009: Central Bank Survey.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world’s most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of almost 145,000 people in 139 economies, representing 97 percent of the world’s population. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

Kelbadjaro-Lacha, Nakhichevan, East Zangezur, and Nagorno-Karabakh territories not included. These areas represent approximately 18% of the total population.

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19–related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Additionally, phone surveys were not a viable option in 16 economies in 2021, which were then surveyed in 2022.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Azerbaijan is 1028.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.