Abstract

The Armenian Household Budget Survey (HBS) 1996 was designed to be a nationally representative survey capable of measuring the standard of living in the Republic of Armenia (ROA) through the collection of data on the family, demographic, socio-economic and financial status of households. The survey was conducted in November - December 1996, on the whole territory of the republic by the State Department of Statistics (SDS) of ROA with technical and financial assistance from the World Bank.

The data collected included information on household composition, housing conditions, education level of household members, employment and income, savings, borrowing, as well as details on levels of expenditure including those on food, non-food, health, tourism and business. The survey covered about 100 villages and 28 towns. The size of the sample was 5,040 households of which 4,920 responded which makes the survey the largest carried out in Armenia to date and one with a very high response rate for a transition economy. The expenditure part of the data was collected using two different methods administered for different households. The methods are: recall method in which households were asked, during the interview, about their expenditures made during the last 30 days preceding the date of the interview; and a diary method where households were given a diary they used to record details about their income and expenditure on a daily basis for 30 days during the interview period. About 25% of the total sample of interviewed households used diaries and 75% used the recall method. The unit of study in the survey was the household, defined as a group of co-resident individuals with a common living budget. As will be explained in detail, the AHBS 96 was generally designed as a two stage stratified sampling, but for large urban areas with an almost definite probability of being selected, a one stage sampling was adopted.

The Armenian HBS 1996 is not a standard Living Standards Measurement Study (LSMS) survey - the questionnaire used is more limited in scope and much different in format from a typical LSMS. This survey used no community or price questionnaires; it did not use most of LSMS’ prototypical fieldwork and data quality procedures, and the technical assistance did not come from the LSMS group in the World Bank. Nonetheless, the goals are some what LSMS-like and the data is certainly worth archiving. They are therefore being entered into the LSMS archives to guarantee their future accessibility to World Bank and other users.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The State Department of Statistics specified 3 domains of interest for this study. These are Yerevan (the capital of ROA), Other Urban areas and Rural areas. Recent estimates of earthquake zones assigned almost equal populations to these domain zones of interest, and as a result there was no need for special targeting and no particular reason was implied for departing from a proportionate (or self-weighting) design.

A self-weighting sample was derived by selecting Primary Sampling Units (PSUs) with probability proportional to their size (where size is defined as the number of households) and then taking a constant number of households from each selected. The sample, therefore, was designed to be self-weighted and representative at the administrative regions (Marzes) level, for urban and rural areas, and within urban areas by the size of cities, and in rural areas by elevation. The number of households to be selected in each PSU was 20, so 250 PSUs were required to make up 5000 households.

Note: See detailed sample design and sample implementation information in the technical document, which is provided in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Armenia HBS 96 questionnaire was designed to collect information on several aspects of household behavior -- demographic composition, housing, health, consumption expenditures as well as income by source and employment. Information was collected about all the household members, not just about the head of the household alone.

Household Questionnaire

The main household questionnaire used in Armenia HBS 96 contained 13 sections, each of which covered a separate aspect of household activity. The various sections of the household questionnaire are described below followed by a brief description of the diary used to record the daily income and expenditure activities of participating households. All households completed sections A through J, L, and M. Households selected to receive the recall method for expenditures completed section K as well; the remainder filled out the diary instead of being interviewed for section K.

A . FAMILY CHARACTERISTICS AND HOUSING: This section collected basic demographic data such as name, age, sex, education, health, marital status and economic status of everyone living in the household, number of people in the household, etc. In addition, information collected included data on the type of educational institutions attended (private/public), special groups (disabled, single parents, orphan...), dwelling amenities and conditions of the household such as type of dwelling (apartment, house, hostel...) and available facilities (electricity, hot water, telephone...)

B. INCOME FROM EMPLOYMENT: This section collected information on income from employment, type of industry each household member is engaged in, type of ownership of the organization where each person works, salary and other cash payments received, employment subsidies in terms of services (e.g. transport and health ). The recall period covers the 30 days prior to the interview date.

C. INCOME FROM SELF EMPLOYMENT: This section collected information about self-employed persons, their income from selfemployment, costs of equipment and raw materials owned by their business, sector in which the individual is self-employed, etc. The recall period covers 30 days prior to the interview.

D. STATE BENEFITS: This section included information on entitlements and receipt of state benefits such as pension, disability, child benefit, unemployment benefit, single-mother benefit, etc. during the last 30 days preceding the date of the interview.

E. OTHER CASH INCOMES: Included in this section are approximate values of the various types of cash incomes such as those from sale of property, valuables, alimony, rent from properties, dividends and interest, help from relatives, etc. the household received during the last 30 days preceding the date of the interview.

F. AID (ASSISTANCE): This section included information on whether food and non-food (e.g. medical help) assistance were received by the household in forms other than cash from friends, relatives, humanitarian organizations, etc. and the values of such assistance received during the last 30 days preceding the date of the interview.

G. SAVINGS, ASSETS AND LOANS: This section collected information on savings, assets and loans made by the household to others, amount of borrowing from others, and the associated interest rates during the past 30 days.

H. GENERAL ECONOMIC SITUATION: This section collected information about the current economic situation as perceived by the household, how it changed over the past 90 days and the household’s future expectations over the next 90 days.

I. LAND OWNERSHIP AND AGRICULTURAL PRODUCE: This section collected information on the amount of land owned by the household in hectares, each crop type harvested and consumed, crop in storage for own household use, home produced food such as diary products, milk, eggs, etc. and animal stock. The recall period for this section generally is the current year, but for the value of household consumption, and crops sold in the market, it uses a recall period of the past 30 days.

J. FOOD IN STOCK (RESERVES): This section collected data on the amount of food in stock the household currently has such as bread, meat, cereals vegetables, etc.

K. EXPENDITURE FOR 30 DAYS (RECALL METHOD): This section collected expenditure information for the last 30 days on food purchases by item; clothing and foot wear for adults; children’s clothes; fabrics; household furniture, cars, carpets, and electrical appliances; household consumables such as soap and stationary; building materials, bathroom appliances and household tools; household utensils; household services; utilities; leisure activities; health; transport; education; domestic animals; land; tourism; and business activities.

L. EMIGRATION: This section collected information on whether anybody in the household worked outside Armenia for more than three months over the past five years; if the emigrating household member is still abroad and his/her final destination country.

M. "PAROS" social program:2 This section collected information on whether the household is in the PAROS program and points the family has in the PAROS system in their social passport.

Z. GUESTS AND EATING OUT This section collected information on how many people ate in the household during the 30 days prior to the interview, how many times the household invited guests for dinner; and was invited; amount of food given to friends and relatives by the household. The codes for these variables are available in the data dictionary.

Diary Questionnaire

The diary questionnaire was used to collect daily income and expenditure activities of the participating households for 30 consecutive days during the interview period. It was administered to 25% of the households in the sample who also completed sections A through J, L and M from the

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_69e2faf86a05da2128954414de859076/view

In Portugal, during 2022/2023, each household devoted, on average, more than 39 percent of its total expenses to housing, water, electricity, gas, and other fuels. Almost 13 percent of the total household expenditure went to food and non-alcoholic beverages, while only 1.4 percent of household consumption expenses was allocated to education services.

1. Average annual regular expenditure per household (before 1997)2. Unit: New Taiwan Dollar3. For detailed explanations of each field, please refer to the New Taipei City Statistical Yearbook (website: http://www.bas.ntpc.gov.tw/home.jsp?idOTE) or contact the Department of Budget, Accounting and Statistics for inquiries.

Average disposable income and consumption expenditure per household by quintile of disposable income and by age group of household head in economic households (2022)

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 25% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Surveys related to the family budget are considered one of the most important surveys types carried out by the Department Of Statistics, since it provides data on household expenditure and income and their relationship with different indicators. Therefore, most of the countries undertake periodic surveys on household income and expenditures. The Department Of Statistics, since established, conducted a series of Expenditure and Income Surveys during the years 1966, 1980, 1986/1987, 1992, 1997, 2002/2003, 2006/2007, 2008/2009, 2010/2011 and because of continuous changes in spending patterns, income levels and prices, as well as in the population internal and external migration, it was necessary to update data for household income and expenditure over time. Hence, the need to implement the Household Expenditure and Income Survey for the year 2013 arises.

The survey was then conducted to achieve the following objectives: 1. Provide data on income and expenditure to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. 2. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index. 3. Provide the necessary data for the national accounts related to overall consumption and income of the household sector. 4. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty. 5. Identify consumer spending patterns prevailing in the society, and the impact of demographic, social and economic variables on those patterns. 6. Calculate the average annual income of the household and the individual, and identify the relationship between income and different socio-economic factors, such as profession and educational level of the head of the household and other indicators. 7. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

The General Census of Population and Housing in 2004 provided a detailed framework for housing and households for different administrative levels in the Kingdom. Where the Kingdom is administratively divided into 12 governorates, each governorate is composed of a number of districts, each district (Liwa) includes one or more sub-district (Qada). In each sub-district, there are a number of communities (cities and villages). Each community was divided into a number of blocks. Where in each block, the number of houses ranged between 60 and 100 houses. Nomads, persons living in collective dwellings such as hotels, hospitals and prison were excluded from the survey framework.

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 CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 25% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Household Expenditure and Income survey sample, for the year 2013, was designed to serve the basic objectives of the survey through providing a relatively large sample in each sub-district to enable drawing a poverty map in Jordan. A two stage stratified cluster sampling technique was used. In the first stage, a cluster sample proportional to the size was uniformly selected, where the number of households in each cluster was considered the weight of the cluster. At the second stage, a sample of 10 households was selected from each cluster, in addition to another 5 households selected as a backup for the basic sample, using a systematic sampling technique. Those 5 households were sampled to be used during the first visit to the block in case the visit to the original household selected is not possible for any reason. For the purposes of this survey, each sub-district was considered a separate stratum to ensure the possibility of producing results on the sub-district level. In this respect, the survey framework adopted that provided by the General Census of Population and Housing Census in dividing the sample strata. To estimate the sample size, the coefficient of variation and the design effect of the expenditure variable provided in the Household Expenditure and Income Survey for the year 2010 was calculated for each sub-district. These results were used to estimate the sample size on the sub-district level so that the coefficient of variation for the expenditure variable in each sub-district is less than 10%, at a minimum, of the number of clusters in the same sub-district (8 clusters). This is to ensure adequate presentation of clusters in different administrative areas to enable drawing an indicative poverty map. It should be noted that in addition to the standard non response rate assumed, higher rates were expected in areas where poor households are concentrated in major cities. Therefore, those were taken into consideration during the sampling design phase, and a higher number of households were selected from those areas, aiming at well covering all regions where poverty spreads.

Mode of data collection

Face-to-face [f2f]

Research instrument

To reach the survey objectives, 3 forms have been developed. Those forms were finalized after being tested and reviewed by specialists taking into account making the data entry, and validation, process on the computer as simple as possible.

(1) General Form/Questionnaire This form includes: - Housing characteristics such as geographic location variables, household area, building material predominant for external walls, type of tenure, monthly rent or lease, main source of water, lighting, heating and fuel cooking, sanitation type and water cycle, the number of rooms in the dwelling, in addition to providing ownership status of some home appliances and car. - Characteristics of household members: This form focused on the social characteristics of the family members such as relation to the head of the family, gender, age and educational status and marital status. It also included economic characteristics such as economic activity, and the main occupation, employment status, and the labor sector. To the additions of questions about individual continued to stay with the family, in order to update the information at the end of each of the four rounds of the survey. - Income section which included three parts · Family ownership of assets · Productive activities for the family · Current income sources

(2) Expenditure on food commodities form/Questionnaire This form indicates expenditure data on 17 consumption groups. Each group includes a number of food commodities, with the exception of the latter group, which was confined to some of the non-food goods and services because of their frequent spending pattern on daily basis like food commodities. For the purposes of the efficient use of results, expenditure data of the latter group was moved with the non-food commodities expenditure. The form also includes estimated amounts of own-produced food items and those received as gifts or in an in-kind form, as well as servants living with the family spending on themselves from their own wages to buy food.

(3) Expenditure on non-food commodities form/Questionnaire This form indicates expenditure data on 11 groups of non-food items, and 5 sets of spending on services, in addition to a group of consumption expenditure. It also includes an estimate of self-consumption, and non-food gifts or other items in an in-kind form received or sent by the household, as well as servants living with the family spending on themselves from their own wages to buy non-food items.

Cleaning operations

----> Raw Data

The data collection phase was then followed by the data processing stage accomplished through the following procedures: 1- Organizing forms/questionnaires A compatible archive system, with the nature of the subsequent operations, was used to classify the forms according to different round throughout the year. This is to effectively enable extracting the forms when required for processing. A registry was prepared to indicate different stages of the process of data checking, coding and entry till forms are back to the archive system. 2- Data office checking This phase is achieved concurrently with the data collection phase in the field, where questionnaires completed in the fieldwork are immediately sent to data office checking phase. 3- Data coding A team was trained to work on the data coding phase, which in this survey is only limited to education specialization, profession and economic activity. In this respect, international classifications were use, while for the rest of the questions, all coding were predefined

Abstract

The main purpose of a Household Income and Expenditure Survey (HIES) survey was to present high quality and representative national household data on income and expenditure in order to update Consumer Price Index (CPI), improve statistics on National Accounts and measure poverty within the country. These statistics are a requirement for evidence based policy-making in reducing poverty within the country and monitor progress in the national strategic plan in place.

Geographic coverage

Urban (Funafuti) and rural areas (outer islands).

Analysis unit

Household and Individual.

Universe

Private households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the Tuvalu 2022 HIES consists in the random selection of the appropriate numbers of households (within each strata urban and rural) in order to be able to disaggregate HIES results at the strata level (in addition to National level). The urban strata of Tuvalu is made of the island of Funafuti (as a whole) and the rest of the country (all outer islands) compose the rural strata. The statistical unit used to run this sampling analysis is the household. The sample procedure is based on the following steps: - Assessment of the accuracy of the previous 2015 HIES in terms of per capita total expenditure (variable of interest) and check whether the sample size at that time were appropriate and correctly distributed among both stratas, - Update this assessment process by using the most recent population count to get the new sample size and distribution, - Proceed to the random selection of households using this most recent population count. The sampling frame (most recent household listing and population count) used to update and select is the 2021 Tuvalu Household Listing conducted by the Central Statistics Division of Tuvalu. At the National level, the 2015 Tuvalu HIES reported a good accuracy of the per capita total expenditure (less than 5%) but the disaggregation results by strata showed a lower quality of the result in Tuvalu urban. The Tuvalu 2021 household listing provides the most recent distribution of the households across all the islands of Tuvalu. This step consists in updating the accuracy of the previous 2015 HIES by using this recent household count and get the appropriate RSE by changing the sample size. For budget constraint, the total sample size cannot get increased, as the funding situation does not allow higher sample size. It means that the only parameter that can be modified is the distribution of the sample across the strata. Sample size by stratum: -Urban: 350 (out of 1,010 urban households as per the 2021 listing) -Rural: 310 (out of 835 rural households as per the 2021 listing) -National: 660 (out of 1,845 total households as per the 2021 listing)

2015 per capita mean total expenditure (AUD): -Urban: 3,190 -Rural: 2,780 -National: 3,000

Relative Standard Error (RSE): -Urban: 5.1% -Rural: 4.1% -National: 3.3%

It results from this new sample design a new distribution that shows an increase in Funafuti urban, mainly due to: - The low quality of the survey results from the 2015 HIES, - The number of households that have increased by more than 15% between 2015 and 2020 in Tuvalu urban area.

The household selection process is based on a simple random procedure within each stratum: - The 350 households in Funafuti are selected using the same probability of selection across all villages of the islands - The 310 household in rural Tuvalu are distributed proportionally to the size of each rural island of Tuvalu. This proportional allocation of the sample across rural Tuvalu islands generates the best accuracy at the strata level.

Distribution of sample accross strata: Urban: Funafuti 350 Rural: Nanumea 42
Nanumaga 37 Niutao 46
Nui 39
Vaitupu 75
Nukufetau 45
Nukulaelae 23
Niukalita 4

Non-response is a problem in surveys, and it is crucial that the field teams interview the selected households (the location on the map and the name of the household head are used to help to determine the selected households). During the first visit, interviewers must do their best to convince the household head to participate in the survey (and get his/her approval to proceed to interview). It may happen in the field that the first visit results in: I. A refusal: the household head does not show any interest in the survey and is reluctant to participate, II. The house is empty (household members away at the time of the visit).

(I) Refusal: if the interviewer cannot convince the household head to participate, he has to liaise with the survey management, and the supervisor will help in the discussion to convince the household head to respond. In this case, it is important to mention that all responses are kept confidential and insist on the importance of it for the benefit of Tuvalu population. (II) Empty house: the interviewer must investigate (checking with neighbours) whether or not the house is still inhabited by the family: o If it is not the case, the dwelling is then vacant, and the replacement procedure must be activated. o If the dwelling is still occupied, interviewer must come back later the same day or the day after at different time

Only in extreme cases of persistent refusal or empty house (household members away during the time of the collection) the replacement procedure must be activated. The replacement procedure consists in changing the selected household to the closest neighbour who is available.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2022 Tuvalu Household Income and Expenditure Survey (HIES) questionnaire was developed in English language and it follows the Pacific Standard HIES questionnaire structure. It is administered on CAPI using Survey Solution, and the diary is no longer part of the form. All transactions (food, non food, home production and gifts) are collected through different recall sections during the same visit. The traditional 14 days diary is no longer recommended in the region. This new method of implementing the HIES present some interesting and valuable advantages such as: cost saving, data quality, time reduction for data processing and reporting. The 2022 HIES of Tuvalu was directly integrated to a census through a Long Form Census (LFC). The LFC was an experiment led by the World Bank and the Pacific Community to try and group a census and a HIES collection. All households were normally enumerated during the 2022 Census and households selected to participate to the HIES were then asked the HIES questions.

Below is a list of all modules in this questionnaire: -Household ID -Demographic characteristics -Education -Health -Functional difficulties -Communication -Alcohol -Other individual expenses -Labour force -Fisheries -Handicraft and home-processed food -Dwelling characteristics -Assets -Home maintenance -Vehicles -International trips -Domestic trips -Household services -Financial support -Other household expenditure -Ceremonies -Remittances -Food insecurity -Financial inclusion -Livestock & aquaculture -Agriculture parcel -Agriculture vegetables -Agriculture rootcrops -Agriculture fruits

The survey questionnaire can be found in this documentation.

Cleaning operations

Data was edited, cleaned and imputed using the software Stata.

Response rate

There was a total of 662 households from the original selection of the sample. 592 of them were contacted 528 accepted the interviews. The number of valid households is 464, or 70% of households before replacement. After replacement, 54 households were considered valid making the final completion rate at 78% (73% in urban and 85% in rural area).

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_4f54aa1e1f925789af8c6efd3cd04418/view

Abstract

Household Income and Expenditure Survey (HIES) collects a wealth of information on household 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 Tonga Statistics Department (TSD) 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 Tonga.

The 2015/2016 HIES was conducted to update the 2009 HIES data and aimed to estimate the total amount HH spent and earnt over the past 12 months at the national and island group level (total expenditure and income).

Geographic coverage

National coverage.

Analysis unit

Individuals and Households.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2 stages sample method used in the 2015 Household Income and Expenditure Survey (HIES) aims to select randomly: Census blocks (with probability proportional to size - each blocks will have a different probability of selection) - based on the 2011 population census; and households (HHs) (within each selected blocks all the HHs have the same probability of selection) - based on a update of the HH listing conducted by the HIES field team.

To make the probability of selection more even, some small census blocks were merged and some large census blocks split. There's more detail in the methodological report on this process. Before each round, the field teams updated the HH listing in each randomly selected block (stage 1 sample selection) and, after the listing was updated, the team randomly selected 18 HHs, which were 12 HHs as primary target HHs to interview; and 6 HHs in case that a primary selected HH cannot participate and a replacement is needed (e.g., refusal, absence, etc.) - this is done in order to achieve a high response rate.

Sampling deviation

Two-stage selection is used in Tongatapu (urban and rural), Vava’u, Ha’apai and ‘Eua, with the selection of census blocks (merged and split) in the first stage and the selection of households (HHs) in the second stage. HHs in Ongo Niua were selected directly from the updated HH listing (one-stage).

Mode of data collection

Face-to-face [f2f]

Research instrument

The use of a common questionnaire developed by the Statistics for Development Division (SDD) of the Pacific Community (SPC) was adopted by Tonga Statistics Department (TSD) to conduct Household Income and Expenditure Survey (HIES) 2015. Addition to the 4 Modules was a section on Deprivation.

4 modules to collect socio-demographic information, and expenditure and income; and o a two-week diary to collect daily expenditure, gifts received and home produced items Four modules are completed by paper-based personal interview, including: 1. Demographic information – characteristics of household (HH) members, including activity and education profile; 2. Household characteristics and expenditure (Housing characteristics, Housing tenure expenditure, Utilities and communication...etc); 3. Individual expenditure (Education, Health, Clothing, Communication...etc); 4. Individual and HH income (Wages and salaries, Agricultural and Forestry activities, Fishing, gatehring and hunting activities...etc).

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 Household (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 4 Modules were published in English but with a Tongan version that was made available to enumerators to help them with the interview. For the diaries they were published in both Tongan and English which ever version that the household find easy to fill in.

Cleaning operations

A first set of edits was done on the raw data via questionnaire checks, which was the first set of corrections. A summary of findings includes: 1820 questionnaires retrieved from the field in which 17 households with no diaries were removed. The process for the manual cleaning included checking the following information in the questionnaire: Labour force section (waged job) declared in module 1 and salaries declared in module 4 (income section). Imputation of wages in households: 30011, 40176, 40190, 40097. Electricity connection and payment of electric bill (module 2). Imputation of electricity bill in households: 20290, 20302, 20304, 30051. Households who are using butane for cooking and payment for butane.Ages and relationship to the household head.Check all the government pension in the salary section. Check the remittances sent by household members who are currently picking fruits overseas (that have to be transferred in wages & salary section).Check if the household members who are in Australia/NZ for fruit picking have declared their resident status in the household accordingly (option 4). After the first clean of the raw data, 1803 valid questionnaires were kept.

Further edits that was done to the raw data set was done using the software STATA.

Response rate

The table below shows the response rates by strata: -Tongatapu - urban: 99.8% -Tongatapu - rura: 99.8% -Vava'u: 100.0% -Ha'apai: 94.3% -Eua: 96.4% -Ongo Niua: 99.0% -Total: 99%

Sampling error estimates

Standard error, the relative sampling errors (RSE) and 95 percentage confidence interval were calculated for the total household expenditure, total household consumption expenditure, total household non consumption expenditure, total household cash expenditure, total household subsistence expenditure, total household expenditure on COICOP division 1, total household net income, total household net cash income, total net wages and salary cash income and total net primary cash income by strata. At the national level the RSE calculated was of good quality however caution should be made at the strata level.

Details of the sampling errors are presented in the sampling errors appendix 2 of the report presented in the external resources.

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 household (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 Tongan; HHs were given the opportunity to complete a Tongan written diary; and enumerators could mostly converse in Tongan when required); and the inability to interview HHs members living abroad but remain dependent on the HH (e.g., students living in school dormitories) or are working to support the HH (e.g., seamen living on a ship), but who have not formed another HH outside of Tonga.

This dataset presents a comprehensive overview of household and per-capita income and expenditure patterns in various demographic, geographic, and socioeconomic contexts. It encompasses three main categories:Disposable IncomeConsumption ExpenditureFinal Monetary Consumption ExpenditureWithin each category, indicators detail averages, medians, and percentages across dimensions such as administrative region, nationality of the household head, age group, educational level, marital status, type of dwelling, type of ownership, household size, and income sources. The dataset thus enables in-depth analysis of how different factors influence income and expenditure.esearchers, policymakers, and analysts can employ these indicators to:Understand how household and per-capita incomes vary by social and economic factors.Examine consumption patterns and their drivers, including demographic variables.Analyze the final monetary consumption expenditure in more detail using COICOP divisions for targeted economic and social policy insights.In doing so, users can identify disparities, assess living standards, and formulate data-driven strategies to address economic and social challenges at both the household and regional levels.Notes:For the first time the methodology for calculating household disposable income and consumption expenditure is used in Household Income and Consumption Expenditure Survey of 2023

Abstract

The primary purpose of this survey was to gather more accurate and detailed information on income and expenditure levels and flows in the Marshall Islands (MHL) and to update and revise the MHL Consumer Price Index (a separate series of publications document the CPI revision efforts).

Geographic coverage

National coverage; urban and rural.

Analysis unit

Household and Individual.

Universe

All usual household residents in private dwellings.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SIZE: In determining an appropriate sample size for a survey of this nature, numerous factors come into the equation. These include:

a) The degree of accuracy required for key estimates; b) The population size of the country; c) The manner in which the sample is selected; d) Cost or staffing constraints which may exist; e) Whether or not estimates are required for sub-populations; f) The level of variability in the data being collected.

Each of these factors have different magnitudes of importance, but the major priority should always be on selecting a sample big enough to produce results of suitable accuracy. Many of these issues are generally known as well - for instance:

· A user group may pre-specify what level of accuracy they may wish to achieve for the survey · The population of a country can normally be estimated to a reasonable level of accuracy · The sample selection technique adopted is known · Cost and staff constraints are generally known, and · A user group can once again provide information on whether estimates for sub-populations are required.

The Marshall Islands 2020 Household Income and Expenditure Survey (HIES) aims to release outputs at the Urban Rural level and National level.

The sampling strategy has been developed around a stratification of urban and rural domains of the Marshall Islands. This stratification aims to improve the robustness of the indicators at urban and rural level. The urban sector has been stratified in 2 different atolls (Majuro and Kwajalein) and the rural region has been stratified in group of atolls that show similarities as follow: - Rural 1: peri urban atolls; located close to Majuro and Kwajalein (Arno, Mili) - Rural 2: most important rural atolls with facilities (boarding schools; health center…) (Jaluit; Wotje) - Rural 3: atolls where population benefit from US Government for nuclear testing (Enewatak, Kili, Utirik) - Rural 4: other atolls

The targeted sample size has been determined around 880 households based on the results of the previous 2011 population census that provided the mean and standard deviation of the total cash household income at the strata level:

The cluster size has been determined at 12 households.

-Urban 1 & 2: respectively 400 and 150 households spread across 33 and 13 EAs lead to 7.9% RSE in Urban domain
-Rural: respectively 2, 3, 10 and 13 EAs in rural1, 2, 3 and 4 (24, 36, 120 and 150 households) lead to 7.3% RSE in Rural domain -At the National level this total sample size of 880 households spead across those 6 stratas as mentioned lead to a RSE of 7.1%

SAMPLE SELECTION: The 2020 Marshall Islands HIES is based on a stratified cluster sampling strategy. The households are selected in 2 steps: - Step1: the random selection of EA based on the sampling strategy parameters (Primary sampling unit) - Step2: the random selection of 12 households (+6 replacements) within each selected EA

The final probability of selection combines both probabilities of EA getting selected within the strata and households getting selected with the EA.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was produced in English and Marshallese languages. The English questionnaire can be found in the External Resources.

Below is the list of all questionnaire modules: -1. Household ID -2. Household member roster -3. Person details: Profile; Education; Health; Physical; Communication; Alcohol & tobacco; Other individual expenses; Labour force; Fisheries hunting; Handicraft & home processed food) -4. Food away from home: Breakfast; Lunch; Dinner; Snacks; Hot drinks; Bottked water; Non-alcoholic drinks -5. Own production -6. Deprivation (persons) -7. Food recall -7.1. Partaker -8. Non-food recall -9. Household details: Dwelling characteristics; Household assets; Other household items & services; Ceremonies; Remittances; Food insecurity; Copra production; Livestock & aquaculture; Agriculture; Legal services -10. Deprivation and financial inclusion (household) -11. Migrant worker -12. Geographic information + photo.

Cleaning operations

Data editing was done using the software Stata.

Response rate

Below are the response rates by urban-rural region for Set A (households selected from the sample): -Urban: 85.3% -Rural: 89% -NATIONAL: 86.7%

Below are the response rates by urban-rural region for Set B (households selected from the sample + replacements): -Urban: 99.8% -Rural: 95.8% -NATIONAL: 98.3%

Sampling error estimates

-RELATIVE SAMPLING ERRORS (RSEs): Below are the RSEs for total expenditure throughout all COICOP divisions, by urban and rural areas: .Urban: 3.6%; Mean expenditure: 5,119; Lower 95% confidence interval: 4,747; Upper 95% confidence interval: 5,490. .Rural: 6.3%; Mean expenditure: 3,280; Lower 95% confidence interval: 2,870; Upper 95% confidence interval: 3,691. .NATIONAL: 3.3%; Mean expenditure: 4,659; Lower 95% confidence interval: 4,348; Upper 95% confidence interval: 4,969.

Below are the RSEs for total income throughout all PACCOI divisions, by urban and rural areas: .Urban: 7.6%; Mean income: 3,612; Lower 95% confidence interval: 3,061; Upper 95% confidence interval: 4,162. .Rural: 9.2%; Mean income: 3,585; Lower 95% confidence interval: 2,928; Upper 95% confidence interval: 2,928. .NATIONAL: 6.2%; Mean income: 3,605; Lower 95% confidence interval: 3,161; Upper 95% confidence interval: 3,161.

The detailed relative sampling errors (RSEs) for the 2019 Marshall Islands Household Income and Expenditure Survey (HIES) will be included in the Appendix section of the final analytical report (when released).

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_7a24e1f85969c45ad68a89f7acf4e7a8/view

Abstract

The Household Income, Expenditure and Consumption Survey (HIECS) 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 survey's 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.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

• Household
• Individual

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 below.

• Sample Size : It was 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 was proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates.

• Cluster size : The cluster size was 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, a cluster size of only 16 households was used (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.

• Core Sample: 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(1004800 household) that is distributed across urban and rural areas of all governorates.

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document that is provided as an external resources in both Arabic and English.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires were used: 1- Expenditure and Consumption Questionnaire: This questionnaire comprises 14 tables in addition to identification and geographic data of household. 2- Diary Questionnaire (Assisting questionnaire): This questionnaire was prepared to help households record - on a daily basis- the quantity and value of food and beverages consumed during the reference period (15 days). 3- Income Questionnaire: This questionnaire consists of several tables; each designated to a specific income source.

Cleaning operations

The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets.

Response rate

For the total sample, the response rate was 93.0% (91.2% in urban areas and 95.6% in rural areas).

Sampling error estimates

The sampling error of major survey estimates has been derived using the Ultimate Cluster Method as applied in the CENVAR Module of the Integrated Microcomputer Processing System (IMPS) Package. In addition to the estimate of sampling error, the output includes estimates of coefficient of variation, design effect (DEFF) and 95% confidence intervals.

Data appraisal

Quality Control Procedures included: 1) Procedures implemented by the survey division a - Applying the recent international recommendations of different concepts and definitions of income and expenditure considering maintaining the consistency with the previous surveys in order to compare and study the changes in pertinent indicators. b - Evaluating the quality of data in all different Implementation stages to avoid or minimize errors to the lowest extent possible through:

Implementing field editing after finishing data collection for households in governorates to avoid any errors in suitable time. Setting up a program for the Survey Technical Committee Members and survey staff for visiting fieldwork in all governorates (each 15 days) to solve any problem in the proper time. For the purpose of quality assurance, tables were generated for each survey round where internal consistency checks were performed to study the plausibility of consistency of data collected.

2) Procedures implemented by the quality control general division a - It was put into consideration during the survey implementation to assign the quality control general division a core role in controlling the quality of the fieldwork 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, and announce the results to all those working in the survey. b - 24 quality control rounds (2 rounds weekly) covering all governorates were implemented. A complete report on the results of each round was produced and distributed to all workers in the survey.

The quality control procedures covered 73.2% of total kism/district in urban areas, 48.3% of rural districts, and 48% of total EAs of the new sample, where the percentage of inconsistencies did not exceed 2%. As for the panel sample, the quality control procedures covered 50.3% of total kism/district in urban areas, 16.9% of rural districts, and 14.2% of total EAs of the new sample, where the percentage of inconsistencies did not exceed 2.1%.

This service shows the proportion of average total income of households which is spent on shelter costs by census division. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001. Shelter-cost-to-income ratio is calculated for private households living in owned or rented dwellings who reported a total household income greater than zero. Private households living in band housing, located on an agricultural operation that is operated by a member of the household, and households who reported a zero or negative total household income are excluded. The relatively high shelter-costs-to-household income ratios for some households may have resulted from the difference in the reference period for shelter costs and household total income data. The reference period for shelter cost data is 2016, while household total income is reported for the year 2015. As well, for some households, the 2015 household total income may represent income for only part of a year. For additional information refer to the 2016 Census Dictionary for 'Total income' and 'Shelter cost'. To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_4185f25981aec9ed4e0d5c0401319a75/view

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_58f445505d677cc58b91c8fe4df2626f/view

From 2009 to 2022, the average household income and expenditure in Taoyuan City included income, consumption expenditure, non-consumption expenditure, and so on.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_babdc4b2d2dd817021ed66d53555fc4c/view

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 Kiribati. 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; 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 Kiribati.

In addition, newly developed modules were incorporated in the 2019 HIES including: -Person Details; -Anaemia & Diabetic Test; -Food Recall; -Food Away From Home; -Partaker; -Non-Food Recall; -Household Details; -Dietary Recall; -Disability, Healthy Living & Time-Use; -Deprivation And Financial Inclusion; -Migrant Worker; -Geographic Information + Photo; -Market Survey; -Village Resource Survey (Vrs).

Geographic coverage

National Coverage and Regional Island Groups (Northern Gilberts, South Tarawa, Central Giberts, Southern Gilberts, Linix).

There are five main populations of interest for which estimates are required for this survey: South Tarawa, Northern, Central and Southern Gilbert Islands, and the Line Islands.

Analysis unit

Individuals and Households.

Universe

The survey covered all persons resident in private households.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SIZE:

In determining an appropriate sample size for a survey of this nature, numerous factors come into the equation. These include:

a) The degree of accuracy required for key estimates; b) The population size of the country; c) The manner in which the sample is selected; d) Cost or staffing constraints which may exist; e) Whether or not estimates are required for sub-populations; f) The level of variability in the data being collected.

Each of these factors have different magnitudes of importance, but the major priority should always be on selecting a sample big enough to produce results of suitable accuracy. Many of these issues are generally known as well - for instance:

· A user group may pre-specify what level of accuracy they may wish to achieve for the survey · The population of a country can normally be estimated to a reasonable level of accuracy · The sample selection technique adopted is known · Cost and staff constraints are generally known, and · A user group can once again provide information on whether estimates for sub-populations are required.

The Kiribati 2019 Household Income and Expenditure Survey (HIES) aims to release outputs at the island division level and National level.

The targeted sample size has been determined around 2,000 households based on the results of the previous 2006 HIES that provided the following Relative Sampling Error (RSE) at the strata level:

-Sth. Tarawa: 230 with an average cluster size of 10,5 and a Relative Sampling Error (RSE) of: 6,3%;
-Northern: 245 with an average cluster size of 11,1 and a Relative Sampling Error (RSE) of: 5,7%; -Central: 217 with an average cluster size of 12,1 and a Relative Sampling Error (RSE) of: 6,7%; -Southern: 244 with an average cluster size of 11,1 and a Relative Sampling Error (RSE) of: 19,0%; -Line Is. & Phoenix: 225 with an average cluster size of 13,2 and a Relative Sampling Error (RSE) of: 14,7%; -TOTAL: 1,161 with an average cluster size of 11,6 and a Relative Sampling Error (RSE) of: 5,4%.

The 2006 Kiribati HIES was based on stratified cluster sampling strategy. The selection of households was based on a three stages selection: island, EA and households. This is the reason why the RSE are above 5% in all domains. In order to improve the quality of the 2019 HIES results, decisions were made to increase the total sample size (making sur we will not over pass the allocated budget) and to use a stratified cluster sampling strategy based on a 2 stage selection (selection of EA and households).

The optimal allocation of 1,800 households was used as a first step to the sample allocation, and through several adjustments, the total sample size is 2,180 households with a cluster size of 12 households.

-Sth. Tarawa: 600 with an average cluster size of 12, a number of EAS of 50 and RSE is: 3,8%;
-Northern: 400 with an average cluster size of 12, a number of EAS of 33 and RSE is: 4,3%; -Central: 300 with an average cluster size of 12, a number of EAS of 25 and RSE is: 5,2%; -Southern: 480 with an average cluster size of 12, a number of EAS of 40 and RSE is: 13,1%; -Line Is. & Phoenix: 400 with an average cluster size of 12, a number of EAS of 33 and RSE is: 9,3%; -Total: 2,180 with a number of EAS of 182 and RSE is: 2,9%.

SAMPLE SELECTION: The random selection of PSU (EAs) was based on a probability proportional to size selection within each domain. Within each selected EA, a total of 18 households are selected in order to have a replacement list of 6 households (list B) and 12 to contact in priority (list A).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaires were published in English.

There are 16 sections in the Household Income and Expenditure Survey questionnaire which relate to the following: -1. Household ID -2. Household member roster -3. Person details -4. Anaemia & diabetic test -5. Food recall -6. Food away from home -7. Partaker -8. Non-food recall -9. Household details -10. Dietary recall -11. Disability, healthy living & time-use -12. Deprivation and financial inclusion -13. Migrant worker -14. Geographic information + photo -15. Market survey -16. Village resource survey (vrs).

Cleaning operations

Data editing was done using the software Stata Version 15.

Response rate

Below is a table showing the response rates based on list A (households selected from the sample): -South Tarawa: 85.8%; -Northern: 91.2%; -Central: 80%; -Is. & Phoenix: 87.5%; -TOTAL: 81.1%.

Below is the table showing the completion rates based on valid households from lists A and B (households from the sample + replacements): -South Tarawa: 99.7%; -Northern: 100%; -Central: 100%; -Is. & Phoenix: 100%; -TOTAL: 100%.