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

This data collection includes detailed information on the purchasing habits of Americans in 1960-1961, with over 200 types of expenditures coded. For the first time since 1941, the Consumer Expenditure Survey sampled both urban, non-farm and rural, farm households in an attempt to provide a complete picture of consumer expenditures in the United States. Personal interviews were conducted in 1960 and 1961 (and a small number in 1959) with 9,476 urban families, 2,285 rural non-farm families, and 1,967 rural farm families, for a total of 13,728 consumer units interviewed. A complete account of family income and outlays was compiled for a calendar year, as well as household characteristics. The expenditures covered by the survey were those which respondents could recall fairly accurately for three months or longer. In general, these expenditures included relatively large purchases, such as those for property, automobiles, and major appliances, or expenditures that occurred on a fairly regular basis, such as rent, utilities, or insurance premiums. Expenditures incurred while on trips were also covered by the survey. Information to determine net changes in the family's assets and liabilities during the year was also gathered. The estimated value of goods and services received, as gifts or otherwise, without direct expenditures by the family, was requested also. In addition, farm families provided farm receipts, disbursements, changes in farm assets, and value of home-produced food. To supplement the annual data, non-farm families who prepared meals at home provided a detailed seven-day record, during the week prior to the interview, of expenditures for food and related items purchased frequently (e.g., tobacco, personal care, and household supplies). For selected items of clothing, house furnishings, and food, the record of expenditures was supplemented by information on quantities purchased and prices paid. Characteristics of the housing occupied by homeowners and renters and an inventory of the major items of house furnishing they owned also were recorded. Demographic information includes sex, age, years of school completed, occupation, race, and marital status of each family member.

The Consumer Expenditure Surveys (CE) program provides data on expenditures, income, and demographic characteristics of consumers in the United States. The CE program provides these data in tables, LABSTAT database, news releases, reports, and public use microdata files. CE data are collected by the Census Bureau for BLS in two surveys, the Interview Survey for major and/or recurring items and the Diary Survey for more minor or frequently purchased items. CE data are primarily used to revise the relative importance of goods and services in the market basket of the Consumer Price Index. The CE is the only Federal household survey to provide information on the complete range of consumers' expenditures and incomes. For more information and data, visit: https://www.bls.gov/cex/

Abstract

Survey based Harmonized Indicators (SHIP) files are harmonized data files from household surveys that are conducted by countries in Africa. To ensure the quality and transparency of the data, it is critical to document the procedures of compiling consumption aggregation and other indicators so that the results can be duplicated with ease. This process enables consistency and continuity that make temporal and cross-country comparisons consistent and more reliable.

Four harmonized data files are prepared for each survey to generate a set of harmonized variables that have the same variable names. Invariably, in each survey, questions are asked in a slightly different way, which poses challenges on consistent definition of harmonized variables. The harmonized household survey data present the best available variables with harmonized definitions, but not identical variables. The four harmonized data files are

a) Individual level file (Labor force indicators in a separate file): This file has information on basic characteristics of individuals such as age and sex, literacy, education, health, anthropometry and child survival. b) Labor force file: This file has information on labor force including employment/unemployment, earnings, sectors of employment, etc. c) Household level file: This file has information on household expenditure, household head characteristics (age and sex, level of education, employment), housing amenities, assets, and access to infrastructure and services. d) Household Expenditure file: This file has consumption/expenditure aggregates by consumption groups according to Purpose (COICOP) of Household Consumption of the UN.

Geographic coverage

National

Analysis unit

• Individual level for datasets with suffix _I and _L
• Household level for datasets with suffix _H and _E

Universe

The survey covered all de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The list of households obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration (EASE) was used as a frame to select EAs from the rural part of the country. On the other hand, the list consisting of households by EA, which was obtained from the 2004 Ethiopian Urban Economic Establishment Census, (EUEEC), was used as a frame in order to select sample enumeration areas for the urban HICE survey. A fresh list of households from each urban and rural EA was prepared at the beginning of the survey period. This list was, thus, used as a frame in order to select households from sample EAs.

Sample Design For the purpose of the survey the country was divided into three broad categories. That is; rural, major urban center and other urban center categories.

Category I: Rural: - This category consists of the rural areas of eight regional states and two administrative councils (Addis Ababa and Dire Dawa) of the country, except Gambella region. Each region was considered to be a domain (Reporting Level) for which major findings of the survey are reported. This category comprises 10 reporting levels. A stratified two-stage cluster sample design was used to select samples in which the primary sampling units (PSUs) were EAs. Twelve households per sample EA were selected as a Second Stage Sampling Unit (SSU) to which the survey questionnaire were administered.

Category II:- Major urban centers:- In this category all regional capitals (except Gambella region) and four additional urban centers having higher population sizes as compared to other urban centers were included. Each urban center in this category was considered as a reporting level. However, each sub-city of Addis Ababa was considered to be a domain (reporting levels). Since there is a high variation in the standards of living of the residents of these urban centers (that may have a significant impact on the final results of the survey), each urban center was further stratified into the following three sub-strata. Sub-stratum 1:- Households having a relatively high standards of living Sub-stratum 2:- Households having a relatively medium standards of living and Sub-stratum 3:- Households having a relatively low standards of living. The category has a total of 14 reporting levels. A stratified two-stage cluster sample design was also adopted in this instance. The primary sampling units were EAs of each urban center. Allocation of sample EAs of a reporting level among the above mentioned strata were accomplished in proportion to the number of EAs each stratum consists of. Sixteen households from each sample EA were inally selected as a Secondary Sampling Unit (SSU).

Category III: - Other urban centers: - Urban centers in the country other than those under category II were grouped into this category. Excluding Gambella region a domain of "other urban centers" is formed for each region. Consequently, 7 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category II. Hence, no domain was formed for these regions under this category. Unlike the above two categories a stratified three-stage cluster sample design was adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. Sixteen households from each EA were lastly selected at the third stage and the survey questionnaires administered for all of them.

Mode of data collection

Face-to-face [f2f]

This table contains 1904 series, with data for years 1997 - 2009 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...); Household spending, household operation (34 items: Total household operation; Communications; Telephone; Purchase of telephones and equipment; ...); Statistics (4 items: Average expenditure; Percent of households reporting; Estimated number of households reporting; Median expenditure per household reporting).

Abstract

Household Income and Expenditure Survey (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 (as a proxy for HH food consumption and nutrition analysis), and gender.

The Pacific Islands regionally standardized HIES instruments and procedures were adopted by the Government of Tokelau for the 2015/16 Tokelau HIES. These standards were designed to feed high-quality data to HIES data end users for:

1. deriving expenditure weights and other useful data for the revision of the consumer price index;
2. supplementing the data available for use in compiling official estimates of various components in the System of National Accounts;
3. supplementing the data available for production of the balance of payments; and
4. gathering information on poverty lines and the incidence of poverty in Tokelau.

The data allow for the production of useful indicators and information on the sectors covered in the survey, including providing data to inform indicators under the UN Sustainable Development Goals (SDGs). This report, the above listed outputs, and any thematic analyses of HIES data, collectively provide information to assist with social and economic planning and policy formation.

Geographic coverage

National coverage.

Analysis unit

Households and Individuals.

Universe

The universe of the 2015/16 Tokelau Household Income and Expenditure Survey (HIES) is all occupied households (HHs) in Tokelau. HHs are the sampling unit, defined as a group of people (related or not) who pool their money, cook and eat together. It is not the physical structure (dwelling) in which people live. The HH must have been living in Tokelau for a period of six months, or have had the intention to live in Tokelau for a period of twelve months in order to be included in the survey.

Household members covered in the survey include: -usual residents currently living in the HH; -usual residents who are temporarily away (e.g., for work or a holiday); -usual residents who are away for an extended period, but are financially dependent on, or supporting, the HH (e.g., students living in school dormitories outside Tokelau, or a provider working overseas who hasn't formed or joined another HH in the host country) and plan to return; -persons who frequently come and go from the HH, but consider the HH being interviewed as their main place of stay; -any person who lives with the HH and is employed (paid or in-kind) as a domestic worker and who shares accommodation and eats with the host HH; and -visitors currently living with the HH for a period of six months or more.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2015/16 Tokelau Household Income and Expenditure Survey (HIES) sampling approach was designed to generate reliable results at the national level. That is, the survey was not designed to produce reliable results at any lower level, such as for the three individual atolls. The reason for this is partly budgetary constraint, but also because the HIES will serve its primary objectives with a sample size that will provide reliable national aggregates.

The sampling frame used for the random selection of HHs was from December 2013, i.e. the HH listing updated in the 2013 Population Count.

The 2015/16 Tokelau HIES had a quota of 120 HHs. The sample covered all three populated atolls in Tokelau (Fakaofo, Nukunonu and Atafu) and the sample was evenly allocated between the three atoll clusters (i.e., 40 HHs per atoll surveyed over a ten-month period). The HHs within each cluster were randomly selected using a single-stage selection process.

In addition to the 120 selected HHs, 60 HHs (20 per cluster) were randomly selected as replacement HHs to ensure that the desired sample was met. The replacement HHs were only approached for interview in the case that one of the primarily selected HHs could not be interviewed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for this Household Income and Expenditure Survey (HIES) are composed of a diary and 4 modules published in English and in Tokelauan. All English questionnaires and modules are provided as external resources.

Here is the list of the questionnaires for this 2015-2016 HIES: - Diary: week 1 an 2; - Module 1: Demographic information (Household listing, Demographic profile, Activities, Educational status, Communication status...); - Module 2: Household expenditure (Housing characteristics, Housing tenure expenditure, Utilities and communication, Land and home...etc); - Module 3: Individual expenditure (Education, Health, Clothing, Communication, Luxury items, Alcohonl & tobacco); - Module 4: Household and individual income (Wages and salary, Agricultural and forestry activities, Fishing gathering and hunting activities, livestock and aquaculture activities...etc).

Cleaning operations

All inconsistencies and missing values were corrected using a variety of methods: 1. Manual correction: verified on actual questionnaires (double check on the form, questionnaire notes, local knowledge, manual verifications) 2. Subjective: the answer is obvious and be deducted from other questions 3. Donor hot deck: the value is imputed based on similar characteristics from other HHs or individuals (see example below) 4. Donor median: the missing or outliers were imputed from similar items reported median value 5. Record deletion: the record was filled by mistake and had to be removed.

Several questions used the hotdeck method of imputation to impute missing and outlying values. This method can use one to three dimensions and is dependent on which section and module the question was placed. The process works by placing correct values in a coded matrix. For example in Tokelau the “Drink Alcohol” questions used a three dimension hotdeck to store in-range reported data. The constraining dimensions used are AGE, SEX and RELATIONSHIP questions and act as a key for the hotdeck. On the first pass the valid yes/no responses are place into this 3-dimension hotdeck. On the second pass the data in the matrix is updated one person at a time. If a “Drink Alcohol” question contained a missing response then the person's coded age, sex and relationship key is searched in the “valid” matrix. Once a key is found the result contained in the matrix is imputed for the missing value. The first preferred method to correct missing or outlying data is the manual correction (trying to obtain the real value, it could have been miss-keyed or reported incorrectly). If the manual correction was unsuccessful at correcting the values, a subjective approach was used, the next method would be the hotdeck, then the donor median and the last correction is the record deletion. The survey procedure and enumeration team structure allow for in-round data entry, which gives the field staff the opportunity to correct the data by manual review and by using the entry system-generated error messages. This process was designed to improve data quality. The data entry system used system-controlled entry, interactive coding and validity and consistency checks. Despite the validity and consistency checks put in place, the data still required cleaning. The cleaning was a two-stage process, which included manual cleaning while referencing the questionnaire, whereas the second stage involved computer-assisted code verification and, in some cases, imputation. Once the data were clean, verified and consistent, they were recoded to form a final aggregated database, consisting of: Person level record - characteristics of every (household) HH member, including activity and education profile; HH level record - characteristics of the dwelling and access to services; Final aggregated income - all HH income streams, by category and type; Final aggregated expenditure - all HH expenditure items, by category and type.

The cleaning was a two-stage process, which included manual cleaning while referencing the questionnaire, whereas the second stage involved computer-assisted code verification and, in some cases, imputation. Once the data were clean, verified and consistent, they were recoded to form a final aggregated database.

Response rate

Overall, 99% of the response rate objective was achieved.

Sampling error estimates

Refer to Appendix 2 of the Tokelau 2015/2016 Household Income and Expenditure Survey report attached as an external resource.

Bangladesh HIES: Household Expenditure per Month: Consumption data was reported at 30,603.000 BDT in 2022. This records an increase from the previous number of 15,420.000 BDT for 2016. Bangladesh HIES: Household Expenditure per Month: Consumption data is updated yearly, averaging 8,483.500 BDT from Dec 1996 (Median) to 2022, with 6 observations. The data reached an all-time high of 30,603.000 BDT in 2022 and a record low of 4,026.000 BDT in 1996. Bangladesh HIES: Household Expenditure per Month: Consumption data remains active status in CEIC and is reported by Bangladesh Bureau of Statistics. The data is categorized under Global Database’s Bangladesh – Table BD.H011: Household Income and Expenditure Survey: Average Monthly Expenditure per Household.

Germany IES: Average Monthly Household Expenditure (AMHE) data was reported at 2,704.000 EUR in 2018. This records an increase from the previous number of 2,448.000 EUR for 2013. Germany IES: Average Monthly Household Expenditure (AMHE) data is updated yearly, averaging 2,245.000 EUR from Dec 1998 (Median) to 2018, with 5 observations. The data reached an all-time high of 2,704.000 EUR in 2018 and a record low of 2,061.000 EUR in 1998. Germany IES: Average Monthly Household Expenditure (AMHE) data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.H025: Household Income and Expenditure Survey.

Abstract

A household budget survey or Household Income and Expenditure survey (HES) as it is commonly called, is one of the most important economic surveys carried out by the Management and Information Systems Division (MISD). The survey is household-based and serves to provide up-to-date and comprehensive information on the components of the average household budget.

Household expenditure surveys are normally carried out every five to seven years so that updated information can be obtained on spending patterns and most importantly, on the composition of the 'basket of goods'.

In a HES, information on both income and expenditure is collected. Background variables such as household composition, age and sex structure and economic activity are also included to help classify the households in various demographic and socio-economic groups and to provide updated estimates on previous household surveys.

The primary purpose of the HES was to collect up-to-date detailed information on the expenditure of households to provide new weights for the calculation of the Cost of Living Index estimated here by the Retail Price Index (RPI).

A second important use of this survey is to provide data on aggregate consumers' expenditure and income to be used in the compilation of the Gross Domestic Product (GDP) and National Income accounts. The 'expenditure approach' of the GDP calculation usually estimates the consumer expenditure component. Results from this survey will thus provide data to crosscheck those estimates.

Another key purpose of the HES survey is that it makes available information on the level and distribution of household incomes. Such information is useful in the assessment of the social and economic planning systems. The distribution of household income provides an approximate measure of poverty in society.

In general, the survey provides the public with useful and interesting information on current spending patterns of the households in Seychelles. These patterns are expected to have changed considerably over the last decade.

Geographic coverage

The survey covered households on Mahe, Praslin and La Digue (the three mainly inhabited islands), and for practical consideration, excluded those on the outer islands.

Analysis unit

• Households
• Individuals
• Consumption expenditure commodities / items

Universe

Persons living in hospitals, military barracks, prisons etc. were excluded. Households headed by expatriates were also excluded, because the income and spending patterns of such households are expected to be different from those of the average Seychellois household.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Design The most appropriate sampling frame available was the list of households obtained from the 1997 Population and Housing Census. Although not updated over the two years prior to the survey, the database provided the ideal frame for direct sampling given that the sampling units would be the households themselves.

The frame listed 17,878 households enumerated during the 1997 census covering all the islands. In consideration of logistic and administrative problems, the geographical coverage was restricted to the three main islands (Mahe, Praslin and La Digue), which account for 99% of all households.

The sampling was done in two stages. An overall sample of 10% (around 1788 households) was desired. In the first stage the households were stratified by district. The sample size was distributed among the districts representative of their size (number of households), to determine the number of households to be drawn from each district (i.e. proportional allocation). From each district, the allocated number of households was then drawn using systematic sampling method whereby households are selected at equal intervals starting from a chosen random number. With each household having the same probability of being selected, the sample becomes self-weighting.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The data were captured on personal computers using a programme written in DELPHI. The software for data capturing made provisions to enter all details collected. For the account book (Form HES3) items purchased or acquired (although it would not be possible to analyse all the descriptive details because of the variety of specifications, units, packaging etc, description and units of items) were captured to help identify commonly purchased items for future pricing.

The data files were then merged into one database and processed in SPSS and MS EXCEL for tabulation .

Response rate

The original sample drawn included 1696 households representing around 9.5 percent of households on Mahe, Praslin and La Digue. The enumeration covered 1219 households but after post-enumeration checks, data from just over 800 or 67% of these households were used in the final analysis.

Abstract

Household Income and Expenditure Survey (HIES) is one of the core activities of the BBS; it contains a wide range of socio-economic information at the household level that has strong influence in the decision making process for the government.

The main objectives of HIES 2016/17 were to:

• Obtain detailed data on household income, expenditure and consumption. • Determine poverty profile with urban and rural breakdown and district-level poverty. • Provide information about standard of living and nutritional status of the population. • Provide data to determine the weights of Consumer Price Indices (CPI). • Provide household level consumption data for compiling national accounts estimates. • Provide detailed information on health status and educational level of the population. • Determine poverty estimates by administrative divisions, districts, and detailed socio-economic characteristics of the population and household. • Provide benchmark data for formulation of appropriate policy for poverty reduction, improvement in standard of living and nutritional status of the population. • Provide relevant data for monitoring of the Poverty Reduction Strategy (PRS), Five year plan and the Millennium Development Goals (MDGs). • Provide data on type, volume and distribution of resources under different Social Safety Nets Programmes (SSNP). • Provide data on disability, migration, remittances, microcredit and disasters management.

Geographic coverage

National

Analysis unit

Household, individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified, two-stage sample design was adopted for the HIES 2016/17 with 2304 Primary Sampling Units (PSU) selected from the list of the 2011 Housing and Population Census enumeration areas. Within each PSU, 20 households were selected for interviews. The final sample size was 46,080 households (Ahmed et.al, 2017).

In Bangladesh, divisions are the first-level administrative geographical partitions of the country. As of 2016, the country has eight divisions: Barisal, Chittagong, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet. Each division is subsequently divided into 64 districts, or zilas.

Each district is further subdivided into smaller geographic areas, with clear rural and urban designations. In addition, urban areas in the main divisions of Chittagong, Dhaka, Khulna, and Rajshahi are classified into City Corporations (CCs), and other urban areas.

PSUs in the HIES 2016/17 were allocated at the district level. Therefore, the sample was stratified at the district level. Since there were a total of 64 districts in Bangladesh, the sample design included a total of 132 sub-strata: 64 urban, 64 rural, and four main CCs. The sample was also implicitly stratified by month.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey data was collected using a questionnaire that consisted of nine sections.

Cleaning operations

The data collection, entry and data transferring process for the HIES 2016 was developed using Paper and Pencil (PAPI) combined with Computer Assisted Field Entry (CAFE). With this method, the interviewers regularly collected all the information during the interview using PAPI and entered the data in to Laptop Computers at the end of the day. If they found any inconsistencies in the data, they went back to the relevant households of the PSU and made required changes or corrections to remove the discrepancies while they were still in that locality. Once they had completed and checked the information, they also ensured that the data entered through data entry program were accurate and consistent. Thus the data were substantially cleaned and validated right at the field level.

The data entry program was developed in CSPro and contained with a cloud based data transferring system, which allowed enumerators to transfer data from the field almost in real time using mobile internet connection. After the data was transferred to BBS headquarter, this was compiled and exported to a readable version by standard statistical software using a built-in routine in the data entry program.

After the data entry was completed in the field, the filled-in questionnaires were also sent to the BBS headquarter office. The transferred data were then promptly examined and verified with the questionnaires if necessary to ensure that the errors and inconsistencies that were required to be removed by the enumerators were done properly. The data sets then re-examined by programmers and senior officials. It may be mentioned that the software for the data entry task was developed in such a manner as to detect most of the errors, omissions or inconsistencies right at the data entry level. However, some more editing specially inter record consistencies were required to be done by the senior officials at BBS headquarter.

Sampling error estimates

Information on Standard Errors (SE), Relative Standard Errors (Rel. SE), and Confidence Intervals of some selected estimates is presented in Appendix 4 of the survey Preliminary Report

Abstract

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

Some more specific outputs from the survey are listed below:

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

Geographic coverage

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

Analysis unit

• Households;
• Individuals.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

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

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

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

All questionnaires are provided as external resources in this documentation.

Cleaning operations

Program: CSPro 5.1x

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

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

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

Response rate

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

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

A Household Income and Expenditure Survey (HIES) collects a wealth of information on household expenditure, income, own-account production and consumption. HIES also collects information on sectoral and thematic areas such as gender, education, health, labour, primary activities, transport, information and communication and cash transfers and remittances. The HIES data will be used to: · derive expenditure weights for the revision of the Consumer Price Index (CPI); · supplement the data available for use in compiling official estimates of various components in the System of National Accounts; and · gather information on welfare and food security in Palau. The data will inform indicators under the United Nations Sustainable Development Goals (SDGs) and guide social and economic policy.

Version 01: Cleaned and de-identified version of the Master file.

• Collection start: 2023
• Collection end: 2024

Sri Lanka HIES: Household Expenditure per Month data was reported at 63,130.000 LKR in 2019. This records an increase from the previous number of 54,999.000 LKR for 2016. Sri Lanka HIES: Household Expenditure per Month data is updated yearly, averaging 19,151.000 LKR from Jun 1981 (Median) to 2019, with 11 observations. The data reached an all-time high of 63,130.000 LKR in 2019 and a record low of 1,232.000 LKR in 1981. Sri Lanka HIES: Household Expenditure per Month data remains active status in CEIC and is reported by Department of Census and Statistics. The data is categorized under Global Database’s Sri Lanka – Table LK.H003: Household Income and Expenditure Survey: Household Expenditure per Month.

Abstract

The main purpose of the Household Income Expenditure Survey (HIES) 2016 was to offer high quality and nationwide representative household data that provided information on incomes and expenditure in order to update the Consumer Price Index (CPI), improve National Accounts statistics, provide agricultural data and measure poverty as well as other socio-economic indicators. These statistics were urgently required for evidence-based policy making and monitoring of implementation results supported by the Poverty Reduction Strategy (I & II), the AfT and the Liberia National Vision 2030. The survey was implemented by the Liberia Institute of Statistics and Geo-Information Services (LISGIS) over a 12-month period, starting from January 2016 and was completed in January 2017. LISGIS completed a total of 8,350 interviews, thus providing sufficient observations to make the data statistically significant at the county level. The data captured the effects of seasonality, making it the first of its kind in Liberia. Support for the survey was offered by the Government of Liberia, the World Bank, the European Union, the Swedish International Development Corporation Agency, the United States Agency for International Development and the African Development Bank. The objectives of the 2016 HIES were:

1. Update the Consumer Price Index (CPI): To obtain a new set of weights for the basket of goods and services that upgrade the Monrovia Consumer Price Index (MCPI) and the National Consumer Price Index (NCPI) and to revise the CPI basket of goods and services in Liberia to reflect the current consumption pattern of residence.
2. Improve National Accounts Statistics: To get information on annual household expenditure patterns in order to update the household component of the National Accounts.
3. Measure Poverty: To prepare robust poverty indices that enable the understanding of poverty dynamics across the country and of the factors influencing them.
4. Improve Agricultural Statistics: To obtain nationally representative and policy relevant agricultural statistics in order to undertake in-depth analysis of agricultural households.
5. Capture Socio-economic Impact of Ebola Virus Disease (EVD): To obtain a post-EVD dataset which allows for an in-depth analysis of the socioeconomic impact of EVD on households.
6. Benchmark Agenda for Transformation Indicators: To provide an update on selected socioeconomic indicators used to benchmark the government’s policies embedded within the Agenda for Transformation.
7. Develop Statistical Capacity: Emphasize capacity building and development of sustainable statistical systems through every stage of the project to produce accurate and timely information about Liberia.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The original sample design for the HIES exploited two-phased clustered sampling methods, encompassing a nationally representative sample of households in every quarter and was obtained using the 2008 National Housing and Population Census sampling frame. The procedures used for each sampling stage are as follows:
i. First stage
Selection of sample EAs. The sample EAs for the 2016 HIES were selected within each stratum systematically with Probability Proportional to Size from the ordered list of EAs in the sampling frame. They are selected separately for each county by urban/rural stratum. The measure of size for each EA was based on the number of households from the sampling frame of EAs based on the 2008 Liberia Census. Within each stratum the EAs were ordered geographically by district, clan and EA codes. This provided implicit geographic stratification of the sampling frame.

ii. Second stage
Selection of sample households within a sample EA. A random systematic sample of 10 households were selected from the listing for each sample EA. Using this type of table, the supervisor only has to look up the total number of households listed, and a specific systematic sample of households is identified in the corresponding row of the table.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were three questionnaires administered for this survey: 1. Household and Individual Questionnaire 2. Market Price Questionnaire 3. Agricultural Recall Questionnaire

Cleaning operations

The data entry clerk for each team, using data entry software called CSPro, entered data for each household in the field. For each household, an error report was generated on-site, which identified key problems with the data collected (outliers, incorrect entries, inconsistencies with skip patterns, basic filters for age and gender specific questions etc.). The Supervisor along with the Data Entry Clerk and the Enumerator that collected the data reviewed these errors. Callbacks were made to households if necessary to verify information and rectify the errors while in that EA.

Once the data were collected in each EA, they were sent to LISGIS headquarters for further processing along with EA reports for each area visited. The HIES Technical committee converted the data into STATA and ran several consistency checks to manage overall data quality and prepared reports to identify key problems with the data set and called the field teams to update them about the same. Monthly reports were prepared by summarizing observations from data received from the field alongside statistics on data collection status to share with the field teams and LISGIS Management.

Bangladesh HIES: Household Expenditure per Month: Urban: Consumption data was reported at 39,971.000 BDT in 2022. This records an increase from the previous number of 19,383.000 BDT for 2016. Bangladesh HIES: Household Expenditure per Month: Urban: Consumption data is updated yearly, averaging 11,795.500 BDT from Dec 1996 (Median) to 2022, with 6 observations. The data reached an all-time high of 39,971.000 BDT in 2022 and a record low of 7,084.000 BDT in 1996. Bangladesh HIES: Household Expenditure per Month: Urban: Consumption data remains active status in CEIC and is reported by Bangladesh Bureau of Statistics. The data is categorized under Global Database’s Bangladesh – Table BD.H011: Household Income and Expenditure Survey: Average Monthly Expenditure per Household.

Average household consumption expenditure in the fifth quintile (since 1998)

Abstract

The Annual Household Income and Expenditure Survey (AHIES) is the first nationally representative high-frequency household panel survey in Ghana. The AHIES is being conducted to obtain quarterly and annual data on household final consumption expenditure and a wide scope of demographic, economic and welfare variables including statistics on labour, food security, multi-dimensional poverty and health status for research, policy, and planning. Some of the key macroeconomic indicators to be generated include quarterly GDP, regional GDP, quarterly unemployment, underemployment, inequality, consumption expenditure poverty, multidimensional poverty and food security. The data from the AHIES is classified, tabulated and disseminated so that researchers, administrators, policy makers and development partners can use the information in formulating and implementing various development programs at the national and community levels and also to monitor targets under the Sustainable Development Goals.

Geographic coverage

Nation - Wide

Analysis unit

Individuals, Households

Universe

The universe covers the population living within individual households in Ghana. However, such population which is defined as institutionalised population as persons living at elderly houses, rest homes, correction facilities, military baracks, and hospitals with special characteristics, nursery,and also nomadic population are excluded.

Sampling procedure

With the sampling procedure, 10,800 households in 600 EAs, consisting of 304 (50.67%) urban and 296 (49.33%) rural households were drawn from the 2021 Population and Housing Census listing frame to form the secondary sampling units. A random sampling methodology was adopted to select eighteen (18) households per selected EAs in all regions to form the full sample for the fieldwork to be able to produce regionally representative expenditures for GDP.

Mode of data collection

Computer Assisted Personal Interview [CAPI]

1999/2000 Household Expenditure Survey - Table 140-09001 : 1999/2000 Household Expenditure Survey - Average Monthly Household Expenditure by Commodity/Service Section/Group by Type of Housing

The household economic survey (HES) is an annual survey designed to measure the economic wellbeing of New Zealanders. HES has three components: HES income, HES expenditure, and HES net worth. - HES income is the main vehicle, and it is run every year. It includes household income, housing costs, and material wellbeing – this is ‘core’ HES. - HES expenditure includes additional components – an expenditure diary and an expanded household expenditure questionnaire. It runs every three years. - HES net worth includes additional questions on household assets and liabilities. It also runs every three years.

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