This dataset contains a series of indicators related to income and expenditure for Kiribati, Tuvalu and Vanuatu based on Household Income and Expenditure Surveys (HIES). Indicators included are the following: Number of households, Proportion of households, Number of persons, Proportion of persons, Income, Income per household, Income per person, Proportion of income, Expenditure, Expenditure per household, Expenditure per person, Proportion of expenditure. The table provides a breakdown by geography (1 sub-national level), sex, age and urbanization, poverty status (2 categories) and food security status (2 categories). This dataset has been compiled as a result of a collaborative project on food security between the Pacific Community (SPC) and the Food and Agriculture Organization of the United Nations (FAO).

Find more Pacific data on PDH.stat.

This dataset shows the expenditure on food and drink by country. Information is given on expenditure as a percentage of total income and in dollars. what you can see from the data is areas where upto 50% of total household expenditure is devoted to food. These areas tend to be poorer developing nations in Africa. The developed countries spend less, as a percentage, on food, but obviously much more in terms of actual dollars. The data was sourced from the USDA Economic Research Service (http://www.ers.usda.gov/) and there is an interesting article here (http://www.vox.com/2014/7/6/5874499/map-heres-how-much-every-country-spends-on-food). The data was a flat excel document and has been linked to geographical boundaries in ArcGIS in order to display the data as map. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2014-07-08 and migrated to Edinburgh DataShare on 2017-02-22.

Survey of Household Spending (SHS), average household spending on detailed food categories.

The ongoing Consumer Expenditure Survey (CES) provides a continuous flow of information on the buying habits of American consumers and also furnishes data to support periodic revisions of the Consumer Price Index. The Survey consists of two separate components: (1) a quarterly Interview panel survey in which each consumer unit in the sample is interviewed every three months over a 15-month period, and (2) a Diary or recordkeeping survey completed by the sample consumer units for two consecutive one-week periods. The Interview survey was designed to collect data on major items of expense, household characteristics, and income. The expenditures covered by the survey are those which respondents can recall fairly accurately for three months or longer. In general, these expenditures include relatively large purchases, such as those for property, automobiles, and major appliances, or expenditures which occur on a fairly regular basis, such as rent, utilities, or insurance premiums. Expenditures incurred while on trips are also covered by the survey. Excluded are nonprescription drugs, household supplies, and personal care items. Including global estimates on spending for food, it is estimated that about 90 to 95 percent of expenditures are covered in the Interview survey. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08904.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The ongoing Consumer Expenditure Survey (CES) provides a continuous flow of information on the buying habits of American consumers and also furnishes data to support periodic revisions of the Consumer Price Index. The survey consists of two separate components: (1) a quarterly Interview Survey in which each consumer unit in the sample is interviewed every three months over a 15-month period, and (2) a Diary Survey completed by the sample consumer units for two consecutive one-week periods. The Interview Survey was designed to collect data on major items of expense, household characteristics, and income. The expenditures covered by the survey are those that respondents can recall fairly accurately for three months or longer. In general, these expenditures include relatively large purchases, such as those for property, or expenditures that occur on a fairly regular basis, such as rent, utilities, or insurance premiums. Excluded are nonprescription drugs, household supplies, and personal care items. Including global estimates on spending for food, it is estimated that about 90 to 95 percent of expenditures are covered in the Interview Survey. The Detailed Expenditure Files that comprise this data collection were created from all the major expenditure sections of the Interview Survey questionnaires and contain more detailed expenditure records than those found in the Interview Survey data (CONSUMER EXPENDITURE SURVEY, 1993: INTERVIEW SURVEY [ICPSR 6580]). In addition, the Detailed Expenditure Files include Consumer Unit Characteristics (FMLY) Files and Income and Member Characteristics (MEMB) Files identical to those found in the Interview Survey. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR06543.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Survey of Household Spending (SHS), average household spending by household type.

Survey of Household Spending (SHS), average household spending, Canada, regions and provinces.

This dataset provides numbers and proportions of households involved in primary activities (crop, livestock, fishing), by geography (1 sub-national level), sex, age and urbanization for the Pacific island countries, based on Household Income and Expenditure Surveys (HIES). The table has been compiled as a result of a collaborative project on food security between the Pacific Community (SPC) and the pacific island countries.

Find more Pacific data on PDH.stat.

This dataset provides numbers and proportions of households involved in primary activities (livestock, fishing, handicraft), by geography (1 sub-national level), sex, age and urbanization, poverty status (2 categories) and food security status (2 categories) for Pacific island countries based on Household Income and Expenditure Surveys (HIES). The table has been compiled as a result of a collaborative project on food security between the Pacific Community (SPC) and the Food and Agriculture Organization of the United Nations (FAO).

Find more Pacific data on PDH.stat.

Philippines Percentage to Total Expenditure (PTE): Food Expenditure (FE) data was reported at 41.900 % in 2015. This records a decrease from the previous number of 42.800 % for 2012. Philippines Percentage to Total Expenditure (PTE): Food Expenditure (FE) data is updated yearly, averaging 42.800 % from Dec 1997 (Median) to 2015, with 7 observations. The data reached an all-time high of 44.200 % in 1997 and a record low of 41.400 % in 2006. Philippines Percentage to Total Expenditure (PTE): Food Expenditure (FE) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Overview

The report presents updated estimates of household food expenditure trends and examines further issues relating to Australia's household food expenditure. The analysis builds on a June 2017 ABARES report that examined recent trends in food demand in Australia and a range of food security issues.

Key Issues

Between 2009-10 and 2016-17, the key drivers of Australia's household food demand growth were, in order of importance, population growth, changes in tastes and preferences (including lifestyle choices), lower real food prices and real income growth. While population growth is important, increasing the number of people seeking to meet their energy and nutrition requirements, there has also been a broadly-based shift toward spending on meals out and fast foods, with the share of meals out and fast foods in household food expenditure in Australia increasing from 31 per cent in 2009-10 to 34 per cent in 2015-16. This increases food expenditure per person, all else constant.

Domestic household consumption is still the most important market for food producers (based on value), but food exports have recovered strongly in recent years, from $25 billion in 2009-10 to $39 billion in 2016-17 (in 2015-16 prices); the share of exports in Australia's indicative food production increased from a recent low of 25 per cent in 2009-10 to 33 per cent in 2016-17.

Two key questions posed in the report relate to food security across population sub-groups and economic opportunities for farmers and other food product and service providers. • Food security-based on average outcomes in population sub-groups in 2015-16 using HES data, the Australian Government's transfer system is important in ensuring a high level of food security across households in Australia; some households, such as those highly reliant on family support payments, may require complementary support, for example, from non-government organisations.

• Economic opportunities in the domestic food supply chain-future food demand growth in Australia will be underpinned by population and income growth. For people living in higher income and/or net worth households, there is a demonstrated willingness to pay a premium for quality attributes of food products and services, including convenience factors. Food labelling is a key approach to inform consumers about quality attributes that may earn a price premium.

A key challenge in the long-term trend toward increased demand for meals out and fast foods is to ensure people have information about food attributes such as nutrition content. Reliable and well understood food product and service labelling may enhance nutrition security in Australia, and allow consumers to make food choices that are more closely aligned with their tastes and preferences (including in relation to nutrition and health), and wider circumstances, as well as contributing to reducing food waste.

Abstract

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation. The HIECS 2010/2011 is the tenth Household Income, Expenditure and Consumption Survey that was carried out in 2010/2011, among a long series of similar surveys that started back in 1955. The survey main objectives are:

• To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials.

• To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates.

• To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period.

• To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation.

• To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands.

• To define average household and per-capita income from different sources.

• To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey.

• To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas.

• To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure.

• To study the relationships between demographic, geographical, housing characteristics of households and their income.

• To provide data necessary for national accounts especially in compiling inputs and outputs tables.

• To identify consumers behavior changes among socio-economic groups in urban and rural areas.

• To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas.

• To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services.

• To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index.

• To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household.

Compared to previous surveys, the current survey experienced certain peculiarities, among which :

1- The total sample of the current survey (26.5 thousand households) is divided into two sections:

a- A new sample of 16.5 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, etc.

b- A panel sample with 2008/2009 survey data of around 10 thousand households was selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2- The number of enumeration area segments is reduced from 2526 in the previous survey to 1000 segments for the new sample, with decreasing the number of households selected from each segment to be (16/18) households instead of (19/20) in the previous survey.

3- Some additional questions that showed to be important based on previous surveys results, were added, such as:

a- Collect the expenditure data on education and health on the person level and not on the household level to enable assessing the real level of average expenditure on those services based on the number of beneficiaries.

b- The extent of health services provided to monitor the level of services available in the Egyptian society.

c- Smoking patterns and behaviors (tobacco types- consumption level- quantities purchased and their values).

d- Counting the number of household members younger than 18 years of age registered in ration cards.

e- Add more details to social security pensions data (for adults, children, scholarships, families of civilian martyrs due to military actions) to match new systems of social security.

f- Duration of usage and current value of durable goods aiming at estimating the service cost of personal consumption, as in the case of imputed rents.

4- Quality control procedures especially for fieldwork, are increased, to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

National

Analysis unit

1- Household/family

2- Individual/Person

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of HIECS, 2010-2011 is a self-weighted two-stage stratified cluster sample, of around 26500 households. The main elements of the sampling design are described in the following:

1- Sample Size It has been deemed important to collect a smaller sample size (around 26.5 thousand households) compared to previous rounds due to the convergence in the time period over which the survey is conducted to be every two years instead of five years because of its importance. The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 26500 households has been considered, and was distributed between urban and rural with the percentages of 47.1 % and 52.9, respectively. This sample is divided into two parts: a- A new sample of 16.5 thousand households selected from main enumeration areas. b- A panel sample with 2008/2009 survey data of around 10 thousand households.

2- Cluster size The cluster size in the previous survey has been decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, it has been decided to use a cluster size of only 16 households (that was increased to 18 households in urban governorates and Giza, in addition to urban areas in Helwan and 6th of October, to account for anticipated non-response in those governorates: in view of past experience indicating that non-response may almost be nil in rural governorates). While the cluster size for the panel sample was 4 households.

3- Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2010 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area

Detailed breakdown of average weekly household expenditure on goods and services in the UK. Data are shown by place of purchase, income group (deciles) and age of household reference person.

Definition: Output rate: Share of expenditure in net household income. Reported expenditure includes both final consumption expenditure and other expenditure. The largest share of household expenditure is consumer spending. These are in detail the expenses for food, housing, clothing, health, leisure, education, communication, transport as well as accommodation and restaurant services. In addition to final consumption expenditure, households have other expenditure, which is recorded as so-called ‘other expenditure’ or expenditure for non-consumption purposes. These include: - Voluntary contributions to the statutory pension insurance - Insurance contributions (additional health and long-term care insurance, expenditure on motor vehicle, household contents, liability, accident and other insurance) - Other transfers made and expenditure incurred: (e.g. cash gifts and donations, maintenance payments) - Other taxes not elsewhere specified (e.g. motor vehicle, dog, inheritance or gift tax) - Interest on loans (construction loans, etc., consumer loans) - The statistical differences. These arise when, in individual cases, certain small amounts have not been entered in the budget books. Net household income is calculated by deducting income tax/wage tax, church tax and solidarity surcharge as well as compulsory social security contributions from the household gross income (all household income from gainful employment, from assets, from public and non-public transfer payments and from (sub-)letting). In order to form income quintiles, households are sorted by household type according to the level of equivalised income and divided into five groups of equal size. The first qunitil contains the 20 percent of households with the lowest equivalised incomes, the fifth those with the highest equivalised incomes. Data source: IT.NRW, Income and Consumption Sample (EVS)

This dataset contains a series of indicators related to nutritional facts for Kiribati, Solomon Islands and Vanuatu based on Household Income and Expenditure Surveys (HIES). Indicators included are the following: Average edible quantity, Average Dietary Energy Consumption, Average expenditures, Percentage of HH who consumed at least one product of the group, Average quantity as acquired, Percentage of households who consumed more than the average number of products consumed in the group, Percentage of households who consumed less than the average number of products consumed in the group, Average number of products consumed by household by food group. The table provides a breakdown by type of food (21 FAO groups), geography (1 sub-national level), sex, age and urbanization, poverty status (2 categories) and food security status (2 categories). This dataset has been compiled as a result of a collaborative project on food security between the Pacific Community (SPC) and the Food and Agriculture Organization of the United Nations (FAO).

Find more Pacific data on PDH.stat.

Information on farm household income and farm household composition. Source agency: Environment, Food and Rural Affairs Designation: National Statistics Language: English Alternative title: Farm Household Income and Household Composition, England

If you require the datasets in a more accessible format, please contact fbs.queries@defra.gsi.gov.uk

Background and guidance on the statistics

Information on farm household income and farm household composition was collected in the Farm Business Survey (FBS) for England for the first time in 2004/05. Collection of household income data is restricted to the household of the principal farmer from each farm business. For practical reasons, data is not collected for the households of any other farmers and partners. Two-thirds of farm businesses have an input only from the principal farmer’s household (see table 5). However, details of household composition are collected for the households of all farmers and partners in the business, but not employed farm workers.

Data on the income of farm households is used in conjunction with other economic information for the agricultural sector (e.g. farm business income) to help inform policy decisions and to help monitor and evaluate current policies relating to agriculture in the United Kingdom by Government. It also informs wider research into the economic performance of the agricultural industry.

This release gives the main results from the income and composition of farm households and the off-farm activities of the farmer and their spouse (Including common law partners) sections of the FBS. These sections include information on the household income of the principal farmer’s household, off-farm income sources for the farmer and spouse and incomes of other members of their household and the number of working age and pensionable adults and children in each of the households on the farm (the information on household composition can be found in Appendix B).

This release provides the main results from the 2013/14 FBS. The results are presented together with confidence intervals.

Survey content and methodology

The Farm Business Survey (FBS) is an annual survey providing information on the financial position and physical and economic performance of farm businesses in England. The sample of around 1,900 farm businesses covers all regions of England and all types of farming with the data being collected by face to face interview with the farmer. Results are weighted to represent the whole population of farm businesses that have at least 25 thousand Euros of standard output as recorded in the annual June Survey of Agriculture and Horticulture. In 2013 there were just over 58 thousand farm businesses meeting this criteria.

Since 2009/10 a sub-sample of around 1,000 farms in the FBS has taken part in both the additional surveys on the income and composition of farm households and the off-farm activities of the farmer and their spouse. In previous years, the sub-sample had included over 1,600 farms. As such, caution should be taken when comparing to earlier years.

The farms that responded to the additional survey on household incomes and off-farm activities of the farmer and spouse had similar characteristics to those farms in the main FBS in terms of farm type and geographical location. However, there is a smaller proportion of very large farms in the additional survey than in the main FBS. Full details of the characteristic of responding farms can be found at Appendix A of the notice.

For further information about the Farm Business Survey please see: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey

Data analysis

The results from the FBS relate to farms which have a standard output of at least 25,000 Euros. Initial weights are applied to the FBS records based on the inverse sampling fraction for each design stratum (farm type by farm size). These weights are then adjusted (calibration weighting) so that they can produce unbiased estimators of a number of different target variables. Completion of the additional survey on household incomes and off-farm activities of the farmer and spouse was voluntary and a sample of around 1,000 farms was achieved. In order to take account of non-response, the results have been reweighted using a method that preserves marginal totals for populations according to farm type and farm size groups. As such, farm population totals for other classifications (e.g. regions) will not be in-line with results using the main FBS weights, nor will any results produced for variables derived from the rest of the FBS (e.g. farm business income).

Accuracy and reliability of the results

We show 95% confidence intervals against the results. These show the range of values that may apply to the figures. They mean that we are 95% confident that this range contains the true value. They are calculated as the standard errors (se) multiplied by 1.96 to give the 95% confidence interval. The standard errors only give an indication of the sampling error. They do not reflect any other sources of survey errors, such as non-response bias. For the Farm Business Survey, the confidence limits shown are appropriate for comparing groups within the same year only; they should not be used for comparing with previous years since they do not allow for the fact that many of the same farms will have contributed to the Farm Business Survey in both years.

Availability of results

This release contains headline results for each section. The full set of results can be found at: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey#publications

Defra statistical notices can be viewed on the on the statistics pages of the Defra website at https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/about/statistics. This site also shows details of future publications, with pre-announced dates.

Data Uses

Data from the Farm Business Survey (FBS) are provided to the EU as part of the Farm Accountancy Data Network (FADN). The data have been used to help inform policy decisions (e.g. Reform of Pillar 1 and Pillar 2 of Common Agricultural Policy) and to help monitor and evaluate current policies relating to agriculture in England (and the EU). It is also widely used by the industry for benchmarking and informs wider research into the economic performance of the agricultural industry.

User engagement

As part of our ongoing commitment to compliance with the Code of Practice for Official Statistics http://www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html, we wish to strengthen our engagement with users of these statistics and better understand the use made of them and the types of decisions that they inform. Consequently, we invite users to make themselves known, to advise us of the use they do, or might, make of these statistics, and what their wishes are in terms of engagement. Feedback on this notice and enquiries about these statistics are also welcome.

Definitions

Household income of the principal farmer Principal farmer’s household income has the following components: (1) The share of farm business income (FBI) (including income from farm diversification) attributable to the principal farmer and their spouse. (2) Principal farmer’s and spouse’s off farm income from employment and self-employment, investment income, pensions and social payments. (3) Income of other household members. The share of farm business income and all employment and self-employment incomes, investment income and pension income are recorded as gross of income tax payments and National Insurance contributions, but after pension contributions. In addition, no deduction is made for council tax.

Household A household is defined as a single person or group of people living at the same address as their only or main residence, who either share one meal a day together or share the living accommodation. A household must contain at least one person who received drawings from the farm business or who took a share of the profit from the business.

Drawings Drawings represent the monies which the farmer takes from the business for their own personal use. The percentage of total drawings going to each household is collected and is used to calculate the total share of farm business income for the principal farmer’s household.

Mean Mean household income of individuals is the ”average”, found by adding up the weighted household incomes for each individual farm in the population for analysis and dividing the result by the corresponding weighted number of farms. In this report average is usually taken to refer to the mean.

Percentiles These are the values which divide the population for analysis, when ranked by an output variable (e.g. household income or net worth), into 100 equal-sized groups. E.g. twenty five per cent of the population would have incomes below the 25th percentile.

Median Median household income divides the population, when ranked by an output variable, into two equal sized groups. The median of the whole population is the same as the 50th percentile. The term is also used for the midpoint of the subsets of the income distribution

Quartiles Quartiles are values which divide the population, when ranked by an output variable, into four equal-sized groups. The lowest quartile is the same as the 25th percentile. The divisions of a population split by quartiles are referred to as quarters in this publication.

Quintiles Quintiles are values which divide the population, when ranked by an output variable, into five equal-sized groups. The divisions of a population split by quintiles are referred to as fifths in this publication.

Assets Assets include

Low-income cut-offs, after tax (LICO-AT) - The Low-income cut-offs, after tax refers to an income threshold, defined using 1992 expenditure data, below which economic families or persons not in economic families would likely have devoted a larger share of their after-tax income than average to the necessities of food, shelter and clothing. More specifically, the thresholds represented income levels at which these families or persons were expected to spend 20 percentage points or more of their after-tax income than average on food, shelter and clothing. These thresholds have been adjusted to current dollars using the all-items Consumer Price Index (CPI).The LICO-AT has 35 cut-offs varying by seven family sizes and five different sizes of area of residence to account for economies of scale and potential differences in cost of living in communities of different sizes. These thresholds are presented in Table 4.3 Low-income cut-offs, after tax (LICO-AT - 1992 base) for economic families and persons not in economic families, 2015, Dictionary, Census of Population, 2016.When the after-tax income of an economic family member or a person not in an economic family falls below the threshold applicable to the person, the person is considered to be in low income according to LICO-AT. Since the LICO-AT threshold and family income are unique within each economic family, low-income status based on LICO-AT can also be reported for economic families.Return to footnote1referrerFootnote 2Low-income status - The income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income.For the 2016 Census, the reference period is the calendar year 2015 for all income variables.Return to footnote2referrerFootnote 3The low-income concepts are not applied in the territories and in certain areas based on census subdivision type (such as Indian reserves). The existence of substantial in-kind transfers (such as subsidized housing and First Nations band housing) and sizeable barter economies or consumption from own production (such as product from hunting, farming or fishing) could make the interpretation of low-income statistics more difficult in these situations.Return to footnote3referrerFootnote 4Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.

Abstract

HIES collects a wealth of information on HH income and expenditure, such as source of income by industry, HH expenditure on goods and services, and income and expenditure associated with subsistence production and consumption. In addition to this, HIES collects information on sectoral and thematic areas, such as education, health, labour force, primary activities, transport, information and communication, transfers and remittances, food expenditure (acquisition) and gender. The Pacific Islands regionally standardized HIES instruments and procedures were adopted by NSO for the 2015/2016 HIES. These standards, were designed to feed high-quality data to HIES data end users for: • deriving expenditure weights and other useful data for the revision of the CPI; • supplementing the data available for use in compiling official estimates of various components in the System of NA; • supplementing the data available for production of the balance of payments; and • gathering information on poverty lines and the incidence of poverty in Niue.

The data allow for the production of useful indicators and information on the industries covered in the survey, including providing data to inform indicators under the United Nations Sustainable Development Goals (SDGs). This report, the above listed outputs, and additional thematic analyses, collectively provide information to assist with multisector planning and policy formation. The 2015/2016 HIES was conducted to update the 2002 HIES data and aimed to estimate the total amount HH spent and earnt over the past 12 months at the national level (total expenditure and income).

Geographic coverage

National coverage.

Analysis unit

Household (private) Individual

Universe

HIES covered all persons who were considered to be usual residents of private dwellings (must have been living in Niue for a period of 12-months, or have intention to live in Niue for a period of 12-months in order to be included in the survey).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample frame used for the selection was the latest HH listing available in 2015. In total 513 resident HHs were listed, and 224 HHs were randomly selected out of this updated list. This sample of 224 HHs is divided in 2 different lists, a first list (list A) of 160 HHs to interview in priority, and an extra list (list B) of 64 HHs to use in case of replacement required (unavailability of the HHs to respond to the interview, or refusal).

The sample distribution for the 2015/16 Household Income and Expenditure Survey (HIES). Small island surveys are inevitably subject to sampling error. In the case of Niue, financial and human resource constraints prevent increasing the sample size, however it is important to note that the application of the results will be limited due to sampling error. Despite this, small-island sampling is a common phenomenon in the Pacific and the aggregated results of HIES will be sufficient to serve the primary objectives of HIES. Given the sample size, the 2015/16 HIES will only report aggregated results at the national level (i.e., no disaggregation by urban/rural, for example). Compared with the 2002 HIES, the sampling strategy for the 2015/16 HIES has an increased overall sample size (by 59 households). As a result, the projected RSEs will be lower than in the previous HIES, which is indicative that the 2015/16 sampling strategy will improve the statistical validity of the results.

HIES schedule The HIES is scheduled to begin on 2 November 2011. Prior to this, the Statistics Niue Office will collaborate with SPC to deliver a two week training of enumerators, data entry operators and supervisors. The training is scheduled for 20 to 30 October 2015. The field operations will occur over eight rounds consisting of three-weeks per round. During each round, 20 households will be interviewed and all of the data will be entered into the database. Table 3 presents the HIES schedule with the corresponding staff requirements.

HIES method Each team will interview and enter data of a randomly selected set of households (10 per team, 20 in total per round) over a period of 3-weeks. Each 3-week block is called a round and there will be 8 rounds in total for Niue 2015/16 HIES. The round schedule for an enumerator, data entry operator and supervisor is presented below. In summary, each enumerator will visit each of the 5 households 7 times per round. They will visit households 1 to 3 on every odd day and households 4 and 5 on every even day over 14 days. The data entry of all Modules starts from the beginning of each round as soon as the first visits to the households are completed. Their activities during each visit is summarised below. · Module questionnaires have to be filled in by the enumerator during week 1 (visits 1, 2, 3 and 4) and entered by the data entry operator in the same week. During the second week module data are edited and checked during visits 5, 6 and 7. · Household diary 1 is delivered to the household during the first visit and picked during the fourth visit. Diary 2 is dropped during the fourth visit and picked during the seventh visit. During each visit the diary has to be properly checked by the enumerator. · Day 17 to 19 in week 3 are used to catch up with any delay during the round, to prepare the team for the next round and for the data entry operator and supervisor to complete data entry of the diaries.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four modules are completed by paper-based personal interview, including: 1. Demographic information - characteristics of Household (HH) members, including activity and education profile; 2. HH characteristics and expenditure; 3. Individual expenditure; and 4. Individual and HH income.

Depending on the information being collected, a recall period (ranging from the last 7 days to the last 12 months) is applied to various sections of the questionnaire. The forms were completed by face-to-face interview, usually with the HH head providing most of the information, with other HH members being interviewed when necessary. The interviews took place over a 2-week period such that the HH diary, which is completed by the HH on a daily basis for 2 weeks, can be monitored while the module interviews take place. The HH diary collects information on the HH's daily expenditure on goods and services; and the harvest, capture, collection or slaughter of primary produce (fruit, vegetables and animals) by intended purpose (home consumption, sale or to give away). The income and expenditure data from the modules and the diary are concatenated (ensuring that double counting does not occur), annualised, and extrapolated to form the income and expenditure aggregates presented herein.

The questionnaire being in English, which could be a second language for both the interviewers and respondents, and the need to complete a written diary (noting that: three-quarters of diaries were in Niuean; HHs were given the opportunity to complete a Niuen written diary; and enumerators could mostly converse in Niuean when required).

Cleaning operations

Software used was CSPro.

Response rate

On the overall 156 HHs were successfully interviewed (98 per cent of the sample), and 118 (74 percent) come from the list A (original list of HHs to interview). 38 HHs come from the replacement list (replacements occurred in 24 percent of the cases). Finally, it is interesting to note that 4 HHs are missing (interview incomplete or poor data quality) and were dropped from the final dataset.

Sampling error estimates

Amount SE RSE Total amount 95% Interval
Total expenditure 19,282,670 957,770 4.97% 17,405,440 21,159,890
Total consumption expendiutre 16,827,260 708,250 4.21% 15,439,090 18,215,440
Total non consumption expnditure (inc investment) 2,455,410 442,050 18.00% 1,589,000 3,321,820
Total cash expenditure 16,246,310 861,460 5.30% 14,557,850 17,934,770
Total subsistence expenditure 1,395,160 155,870 11.17% 1,089,650 1,700,660
Total food expenditure 5,118,690 277,330 5.42% 4,575,120 5,662,260

Data appraisal

Non-sampling errors cannot be readily measured, however it is worth noting the issues associated with non-sampling errors, including: • both respondents and interviewers may not entirely understand the information required from the survey, which can result in misinterpretation of the question being asked and the incorrect response; • enumerator and respondent fatigue, resulting in underreporting, especially in completion of the HH diary; • unwillingness to fully disclose information - especially in a small-island context - such as income and expenditure on some items (e.g., alcohol, tobacco and cash donations); • the questionnaire being in English, which could be a second language for both the interviewers and respondents, and the need to complete a written diary (noting that: three-quarters of diaries were in Niuean; HHs were given the opportunity to complete a Niuen written diary; and enumerators could mostly converse in Niuean when required); and • the

Data is collected the Household Income and Expenditure Surveys (HIES) contacted by the regional countries.

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Low-income cut-offs, after tax (LICO-AT) - The Low-income cut-offs, after tax refers to an income threshold, defined using 1992 expenditure data, below which economic families or persons not in economic families would likely have devoted a larger share of their after-tax income than average to the necessities of food, shelter and clothing. More specifically, the thresholds represented income levels at which these families or persons were expected to spend 20 percentage points or more of their after-tax income than average on food, shelter and clothing. These thresholds have been adjusted to current dollars using the all-items Consumer Price Index (CPI).The LICO-AT has 35 cut-offs varying by seven family sizes and five different sizes of area of residence to account for economies of scale and potential differences in cost of living in communities of different sizes. These thresholds are presented in Table 4.3 Low-income cut-offs, after tax (LICO-AT - 1992 base) for economic families and persons not in economic families, 2015, Dictionary, Census of Population, 2016.When the after-tax income of an economic family member or a person not in an economic family falls below the threshold applicable to the person, the person is considered to be in low income according to LICO-AT. Since the LICO-AT threshold and family income are unique within each economic family, low-income status based on LICO-AT can also be reported for economic families.Return to footnote1referrerFootnote 2Low-income status - The income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income.For the 2016 Census, the reference period is the calendar year 2015 for all income variables.Return to footnote2referrerFootnote 3The low-income concepts are not applied in the territories and in certain areas based on census subdivision type (such as Indian reserves). The existence of substantial in-kind transfers (such as subsidized housing and First Nations band housing) and sizeable barter economies or consumption from own production (such as product from hunting, farming or fishing) could make the interpretation of low-income statistics more difficult in these situations.Return to footnote3referrerFootnote 4Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.