West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

Household income is a potential predictor for a number of environmental influences, for example, application of urban pesticides. This product is a U.S. conterminous mapping of block group income derived from the 2010-2014 Census American Community Survey (ACS), adjusted by a 2013 county-level Cost-of-Living index obtained from the Council for Community and Economic Research. The resultant raster is provided at 200-m spatial resolution, in units of adjusted household income in thousands of dollars per year.

Living Cost: Average per Month: SF: Republic of Crimea data was reported at 11,074.000 RUB in Dec 2020. This records an increase from the previous number of 10,945.000 RUB for Sep 2020. Living Cost: Average per Month: SF: Republic of Crimea data is updated quarterly, averaging 9,798.500 RUB from Sep 2014 (Median) to Dec 2020, with 26 observations. The data reached an all-time high of 11,074.000 RUB in Dec 2020 and a record low of 5,786.000 RUB in Sep 2014. Living Cost: Average per Month: SF: Republic of Crimea data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HF001: Living Cost.

In the United States, Hawaii was the state with the most expensive housing, with the typical value of single-family homes in the 35th to 65th percentile range exceeding ******* U.S. dollars. Unsurprisingly, Hawaii also ranked top as the state with the highest cost of living. Meanwhile, a property was the least expensive in West Virginia, where it cost under ******* U.S. dollars to buy the typical single-family home. Single-family home prices increased across most states in the United States between December 2023 and December 2024, except in Louisiana, Florida, and the District of Colombia. According to the Federal Housing Association, house appreciation in 13 states exceeded **** percent in 2023.

This statistic presents the distribution of Millennials in the United States whose monthly expenses were paid for by their parents in 2014, sorted by item paid. During the survey, 12 percent of the polled U.S. Millennials stated that their parents paid their cell phone bills.

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.

DEFRA Family Food database:
This is available as a separate Access download zip file for those users who require it.

Latest edition information:
For the second edition (May 2023), the DEFRA Family Food database has been added to the study.

This web mapping service contains data from the American Community Survey (ACS), which is an ongoing survey that provides data every year in order to give communities the current information they need to plan investments and services. Information from the survey generates data that help determine how more than $400 billion in federal and state funds are distributed each year. This survey contains information about the age, sex, race, family and relationships, income and benefits, health insurance, education, veteran status, disabilities and the cost of living of the communities surveyed. The Census ACS 2014 WMS web mapping service contains data as of January 1, 2014.

This statistic shows the median household income in the United States from 1990 to 2023 in 2023 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023, an increase from the previous year. Household incomeThe median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varies from state to state. In 2020, the median household income was 86,725 U.S. dollars in Massachusetts, while the median household income in Mississippi was approximately 44,966 U.S. dollars at that time. Household income is also used to determine the poverty line in the United States. In 2021, about 11.6 percent of the U.S. population was living in poverty. The child poverty rate, which represents people under the age of 18 living in poverty, has been growing steadily over the first decade since the turn of the century, from 16.2 percent of the children living below the poverty line in year 2000 to 22 percent in 2010. In 2021, it had lowered to 15.3 percent. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.51 in 2019. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing.

Population with Income per Capita below Living Cost: % of Total: NC: Chechen Republic data was reported at 15.200 % in 2024. This records a decrease from the previous number of 17.400 % for 2023. Population with Income per Capita below Living Cost: % of Total: NC: Chechen Republic data is updated yearly, averaging 19.700 % from Dec 2012 (Median) to 2024, with 13 observations. The data reached an all-time high of 21.700 % in 2012 and a record low of 14.200 % in 2014. Population with Income per Capita below Living Cost: % of Total: NC: Chechen Republic data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA015: Population with Income per Capita below Living Cost.

Average monthly disposable salary Years: 2013-2014 DEFINITION: Average Monthly Disposable Salary (After Tax). Based on 0-50 contributions for Afghanistan, Aland Islands, Andorra and 81 more countries and 50-100 contributions for Albania, Algeria, Armenia and 19 more countries and over 100 contributions for Argentina, Australia, Austria and 82 more countries. The surveys were conducted by numbeo.com from May, 2011 to February, 2014. See this sample survey for the United States, respondents were asked "Average Monthly Disposable Salary (After Tax)". Prices in current USD.

Source: https://www.nationmaster.com/country-info/stats/Cost-of-living/Average-monthly-disposable-salary/After-tax#

Living Cost: Children: Average per Month: SF: City of Sevastopol data was reported at 12,113.000 RUB in Dec 2020. This records a decrease from the previous number of 12,551.000 RUB for Sep 2020. Living Cost: Children: Average per Month: SF: City of Sevastopol data is updated quarterly, averaging 10,631.500 RUB from Sep 2014 (Median) to Dec 2020, with 26 observations. The data reached an all-time high of 12,551.000 RUB in Sep 2020 and a record low of 6,034.000 RUB in Sep 2014. Living Cost: Children: Average per Month: SF: City of Sevastopol data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HF004: Living Cost: Children.

The GLA undertakes regular polling of Londoners' views. The results from these polls appear on this page. December 2017 – Rail services Link to PDF of topline (PDF) November 2017 – Workplace equality Link to PDF of topline (PDF) November 2017 - YouGov/GLA poll results Link to PDF of topline (PDF) October 2017 - YouGov/GLA poll results Link to PDF of topline (PDF) September 2017 – Keeping Londoners safe Link to PDF of topline (PDF) August 2017 – World Athletics Championships Link to PDF of topline (PDF) July 2017 – World Para-athletics Championships Link to PDF of topline (PDF) July 2017 – Food Link to PDF of topline (PDF) June 2017 – YouGov/GLA poll results Link to PDF of topline (PDF) June 2017 – YouGov/GLA poll results Link to PDF of topline (PDF) April 2017 – YouGov/GLA poll results Link to PDF of topline (PDF) March 2017 – Contacting City Hall Link to PDF of topline (PDF) February 2017 – YouGov/GLA poll results Link to PDF of topline (PDF) February 2017 – YouGov/GLA poll results Link to PDF of topline (PDF) January 2017 – YouGov/GLA poll results Link to PDF of topline (PDF) December 2016 – YouGov/GLA poll results Link to PDF of topline (PDF) December 2016 – Transport Link to PDF of topline (PDF) November 2016 – YouGov/GLA poll results Link to PDF of topline (PDF) October 2016 – Public spending and taxation Link to PDF of topline (PDF) Link to analysis of results (PDF) August 2016 – Promoting London Abroad Link to PDF of topline (PDF) August 2016 – Pubs and Clubs Link to PDF of topline (PDF) July 2016 – Devolution Link to PDF of topline (PDF) March 2016 – congestion, night-tube, noise, volunteering and growth Link to PDF of toplines (PDF) Link to crosstabs tables (XLS) January 2016 – culture, anti-social behaviour, sport & exercise, digital technology Link to PDF of toplines (PDF) Link to crosstabs tables (XLS) September 2015 - economy, sugar, awareness of London government and work of Mayor Link to PDF of toplines (PDF) Link to crosstabs tables (XLS) July 2015 - Energy, renting, online shopping and airports Link to PDF of toplines (PDF) Link to Excel tables (XLS) March 2015 - Growth, recycling and reuse Link to PDF of toplines (PDF) Link to PDF of tables January 2015 – Economy, cost of living, living wage, affordable eating, cooking fats, physical activity major events Link to PDF of toplines (PDF) Link to Excel tables (XLS) September 2014 - Awareness, sources, carrier bags and big dance Link to PDF of toplines (PDF) Link to Excel tables (XLS) August 2014 - Health Survey Link to PDF of toplines (PDF) Link to Excel tables (XLS) June 2014 - Economy, cost of living, personal finance, housing and airports Link to PDF of toplines (PDF) May 2014 - Priorities for Safety Link to PDF of toplines (PDF) Link to Excel tables (XLS) March 2014 - Health Survey Link to PDF of toplines (PDF) Link to Excel tables (XLS) February 2014 - Economy, cost of living, priorities and culture Link to PDF of toplines (PDF) Link to Excel tables (XLS) February 2014 - Water Cannon Link to Data Full Tables (XLS) Tables – rebased (XLS) Tables - ethnicity (XLS) Tables - summary (XLS) November 2013 - Economy, cost of living, technology and aiports Link to PDF of toplines (PDF) Link to Excel tables (XLS) September 2013 - Economy, Mayoral responsibilities Link to PDF of toplines (PDF) Link to Excel tables (XLS) June 2013 - Economy, culture and community cohesion Link to PDF of toplines (PDF) Link to PDF tables (PDF) March 2013 – Economy, volunteering, ULEZ, stamp duty, cycling Link to PDF of toplines (PDF) Link to Excel tables (XLS) January 2013 - Economy, apprenticeships, aiport, housing and EU Link to PDF of toplines (PDF) Link to Excel tables (XLS) October 2012 - Economy, Mayoral responsibilities and 2012 Games Link to PDF of toplines (PDF) Link to PDF tables (PDF) June 2012 - Economy and Londoners priorities Link to PDF of toplines (PDF) Link to PDF tables (PDF) February 2012 - Economy and volunteering Link to PDF of toplines (PDF) Link to PDF tables (PDF) November 2011 - Economy, community cohesion, young people, sports Link to PDF of toplines (PDF) Link to PDF tables (PDF) September 2011 - Community cohesion and festivals Link to PDF of toplines (PDF) Link to PDF tables (PDF) June 2011 - Housing, economy, sport, 2012 games Link to PDF of toplines (PDF) Link to PDF tables (PDF) March 2011 - Volunteering Link to PDF of toplines (PDF) Link to PDF tables (PDF) December 2010 - Mayoral Priorities Link to PDF of toplines (PDF) Link to PDF tables (PDF) August 2010 - Energy, and Safety in Parks Link to PDF of toplines (PDF) Link to PDF tables (PDF) May 2010 - Climate Change Link to PDF of toplines (PDF) Link to PDF tables (PDF) March 2010 - Culture Link to PDF of toplines (PDF) Link to PDF tables (PDF) November 2009 - Waste and recycling Link to PDF of toplines (PDF) Link to PDF tables (PDF) June 2009 - Quality of life Link to PDF of toplines (PDF) Link to PDF tables (PDF) April 2009 - Economic outlook, and the Mayor's role Link to PDF of topl

Monthly indexes and percentage changes for all components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.

Living Cost: Average per Month: SF: City of Sevastopol data was reported at 11,396.000 RUB in Dec 2020. This records a decrease from the previous number of 11,494.000 RUB for Sep 2020. Living Cost: Average per Month: SF: City of Sevastopol data is updated quarterly, averaging 10,052.000 RUB from Sep 2014 (Median) to Dec 2020, with 26 observations. The data reached an all-time high of 11,538.000 RUB in Jun 2019 and a record low of 5,728.000 RUB in Sep 2014. Living Cost: Average per Month: SF: City of Sevastopol data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HF001: Living Cost.

In 2023, the U.S. Consumer Price Index was 309.42, and is projected to increase to 352.27 by 2029. The base period was 1982-84. The monthly CPI for all urban consumers in the U.S. can be accessed here. After a time of high inflation, the U.S. inflation rateis projected fall to two percent by 2027. United States Consumer Price Index ForecastIt is projected that the CPI will continue to rise year over year, reaching 325.6 in 2027. The Consumer Price Index of all urban consumers in previous years was lower, and has risen every year since 1992, except in 2009, when the CPI went from 215.30 in 2008 to 214.54 in 2009. The monthly unadjusted Consumer Price Index was 296.17 for the month of August in 2022. The U.S. CPI measures changes in the price of consumer goods and services purchased by households and is thought to reflect inflation in the U.S. as well as the health of the economy. The U.S. Bureau of Labor Statistics calculates the CPI and defines it as, "a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services." The BLS records the price of thousands of goods and services month by month. They consider goods and services within eight main categories: food and beverage, housing, apparel, transportation, medical care, recreation, education, and other goods and services. They aggregate the data collected in order to compare how much it would cost a consumer to buy the same market basket of goods and services within one month or one year compared with the previous month or year. Given that the CPI is used to calculate U.S. inflation, the CPI influences the annual adjustments of many financial institutions in the United States, both private and public. Wages, social security payments, and pensions are all affected by the CPI.

Abstract

The purpose of the Household Income and Expenditure Survey (HIES) survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in Palau. This information will be used to guide policy makers in framing socio-economic developmental policies and in initiating financial measures for improving economic conditions of the people.

Some more specific outputs from the survey are listed below:

a) To obtain expenditure weights and other useful data for the revision of the consumer price index; b) To supplement the data available for use in compiling official estimates of household accounts in the systems of national accounts; c) To supply basic data needed for policy making in connection with social and economic planning, including producing as many of Palau's National Minimum Development Indicators (NMDI's) as possible; d) To provide data for assessing the impact on household living conditions of existing or proposed economic and social measures, particularly changes in the structure of household expenditures and in household consumption; e) To gather information on poverty lines and incidence of poverty throughout Palau.

Geographic coverage

National Coverage, excluding Sonsorol and Hatohobei. Urban and Rural.

Analysis unit

• Households;
• Individuals.

Universe

All private households and group quarters (people living in Work dormitories, as it is an important aspect of the subject matter focused on in this survey, and not addressed elsewhere).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used was the 2012 Palau census, which provided population figures for everyone living in both private households and group quarters (e.g. worker barracks, school dormitories, prison). The sampling selection was done separately in private dwellings and group quarters.

It is an accepted practice for the Household Income and Expenditure Survey (HIES) to cover all living quarters regarded as private dwellings, and the Palau 2013/14 HIES will follow this recommendation.

For group quarters it is also recommended to exclude the prison, as it is not considered appropriate to include such institutions in a survey such as HIES.

A decision as to whether the remaining group quarters should be included is based on the following criteria:

1) Ease in accessing and covering them in a survey such as HIES 2) Relevance to the subject matter of the survey 3) Whether their impact on the subject matter is mostly covered already

Under these criteria, the following recommendations are made: -School/college dormitories: Will exclude from HIES as these individuals will be covered in the households from which they came (if selected) -Work dormitories: Aim to include in the HIES as they are an important aspect of the subject matter focused on in this survey, and not addressed elsewhere -Live aboard: Will exclude due to the movement of such vehicles, and the minimal impact they may have on such a survey -Convents/religious quarters: Will exclude based on their expected minimum impact on the survey subject matter

NB: Given students in dorms are expected to have a high portion of their income and expenses covered in their original household of origin, and there were no religious group quarters identified during the census, only persons in the prison and living aboard are expected to be excluded from the survey. These people account for 81 out of 2,322 group quarters residents (only 3.6%).

Although the response rates were down in the 2006 HIES, with a smaller more experienced team working over 12 months, it is expected there will be improvements in this area. However, the expected sample loss of 10 per cent was probably too ambitious, and given the actual rate ended up at 287/1,063 = 27 per cent, it is more realistic to assume a sample loss of around 15 per cent with improvements for the 2013/14 HIES. Based on the RSEs presented in 2.3.2, it also appears that the 20 per cent desirable sample produced sound results for the survey, and with higher response rates anticipated, these results from a sample error perspective should improve. It is therefore proposed for the 2013/14 Palau HIES that a sample size of 20 per cent be adopted, which also allows for sample loss of 15 per cent.

In the 2006 Palau HIES, effort was made to design a sample which could produce results for the six domains (stratum). Whilst reasonable results were generated for each of these domains, it was felt that post survey, there was no great use of these results at that level. For the 2013 HIES it is proposed to focus on generating reliable results at the national level, with focus also being place on producing results for the urban/rural split. In the case of Palau, the urban population is considered to consist of the states of Koror and Airai.

The last phase to finalizing the sample numbers was to adjust the desirable sample numbers, so that they could be easily applied by the HIES team in a practical manner over the course of the 12 month fieldwork. This was achieved by modifying the sample counts (not too much) to enable sample sizes each round would be of a similar size, and workloads for each enumerator were the same size each round. The desirable workload for an enumerator covering the PD population was 10 households, whereas this figure was increased to 14 persons for GQs as it was envisaged the amount of time required to cover a person in a GQ would be significantly less. With this in mind, we wanted to ideally have the PD sample to be divisible by 160 so this would enable an even number of households each round, whilst maintaining a workload of 10 households for interviewers covering these areas. For the GQ sample, given the desirable number of GQs was already 225, and 16x14=224, then a simple reduction of 1 in the GQ sample would result in a nice even workload of 14 persons per round for 1 interviewer. This logic was also applied to the split between urban and rural resulting in 14 workloads in urban and 2 workloads in rural.

Mode of data collection

Face-to-face [f2f]

Research instrument

Developped in English, a questionnaire consisting of four Modules and a Weekly Diary covering 2 weeks was used for the Republic of Palau Household Income and Expenditure Survey (HIES) 2013. Each Module covers distinct but connected portion of the Household.

The Modules are as follows: -Module 1 - Demographic Information: · Demographic Profile · Labor Force Status · Health Status · Communication Status -Module 2 - Household Expenditure: · Housing Characteristics · Housing Tenure Expenditure · Utilities & Communication Details · Utilities & Communication Expenditure · Land & Home Details · Land & Home Expenditure · Household Goods & Assets Details · Household Goods & Assets Expenditures · Vehicles & Accessories Details · Vehicles & Accessories Expenditures · Private Travel Details · Private Travel Expenditures · Household Services Expenditure · Contributions to Special Occasions · Provisions of Financial Support · Loans · Household Assets Insurance & Taxes · Personal Insurance -Module 3 - Individual Expenditures: · Education grants and scholarships · Education Identifications · Education Expenditures · Health Identifications · Health Expenditures · Clothing Identification · Clothing Expenditure · Communication Identification · Communication Expenditures · Luxury Items Identification · Luxury Items Expenditures -Module 4 - Income: · Wages & Salary: In country (current) · Wages & Salary: Overseas (last 12 months) · Wages & Salary: In country (last 12 months) · Income from Non Subsistence Business · Description of Agriculture & Forestry Activities · Income from Agriculture & Forestry Activities · Description of Handicraft & Home Processed Food Activities · Income from Handicraft & Home Processed Food Activities · Description of Livestock & Aquaculture Activities · Income from Livestock & Aquaculture Activities · Description of Fishing & Hunting Activities · Income from Fishing & Hunting Activities · Property Income, Transfer Income & Other Receipts · Remittances & Other Cash Gifts -Weekly Diary - Covering 14 Days (2 weeks): · Daily expenditure of food and non-food items · Payments of service made · Gambling winning and losses · Items received for free · Home produced food and non-food items.

All questionnaires are provided as external resources in this documentation.

Cleaning operations

Program: CSPro 5.1x

Data editing took place at a number of stages throughout the processing, including:

a) Office editing and coding b) During data entry; Error report correction; Secondary editing by Quality Control Officer (QCO) c) Structure checking and completeness

Detailed documentation of the editing of data can be found in the "Data processing guidelines" document provided as an external resource.

Response rate

Some 1,145 households were selected (in private dwellings and workers quarters) to participate in the survey, and the response rate was 75.8% (i.e. 869 households responded). This response rate allows for statistically significant analysis at the national, urban and rural level.

Response rates for private households by State: -Koror: 355 households responded out of 480 selected => 73.9%; -Airai: 119 households responded out of 160 selected => 74.4%; -URBAN: 474 households responded out of 640 selected => 74.1%; -Kayangel: 0 households responded out of 10 selected => 0%; -Ngarchelong: 27 households responded out of 30 selected => 90%; -Ngaraard: 22 households responded

Living Cost: Children: Average per Month: SF: Republic of Crimea data was reported at 11,643.000 RUB in Dec 2020. This records a decrease from the previous number of 11,713.000 RUB for Sep 2020. Living Cost: Children: Average per Month: SF: Republic of Crimea data is updated quarterly, averaging 10,321.500 RUB from Sep 2014 (Median) to Dec 2020, with 26 observations. The data reached an all-time high of 11,713.000 RUB in Sep 2020 and a record low of 5,884.000 RUB in Sep 2014. Living Cost: Children: Average per Month: SF: Republic of Crimea data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HF004: Living Cost: Children.

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.

For the second edition (May 2011), the variables A012p and A013p in file dvper were replaced with new versions to correct data errors. For the third edition (June 2011), a new version of the DV Set89 data file was deposited. The variable COI_PLUS (Coicop-plus expenditure code) has been updated to correct truncated codes that were present in the previous version. For the fourth edition (July 2011), the Specs2009 document was replaced with an updated version. The previous version contained some notes that were no longer needed.

DEFRA Family Food database:
This is available as a separate Access download zip file for those users who require it.