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 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.

The Household Income and Expenditure Survey (HIES) is a field operation which consists of collecting information in the households based on face to face interview.

The questions asked to the households are related to living standard conditions, expenditures, purchases, incomes.... It is the only survey conducted at a national level which deals with households habits in terms of expenditure and income. As the private and public sector, households represent an economic and social actor of the country which needed to be known.

The purpose of the HIES survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in the Solomon Islands. 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 the Solomon Islands.

The previous HIES was conducted in 2005-2006, 7 years ago. All the indicators based on this survey need to be updated now. a) In the CPI, new items have appeared on the market since 2005, and the purchases habits / consumption habits of the household has changed b) The poverty assessment of the country has to be updated as well, based on the household living condition in 2012 (job opportunities have changed, income, education level...) c) In terms of national account, this survey will provide aggregates of 2012 household consumption.

This survey will highlight the level of expenditure and income of the households, situation with employment, equipment, assets of the households, education and health information, source of income and remittances... It will derive indicators that would provide Solomon Islands Government and their development partners with a core set of statistics to facilitate evidence-based policy development and planning, to monitor development progress and measure policy performance, and ultimately to describe development impact.

Version 01: Cleaned, labelled and anonymized version of the Master file.

• HOUSEHOLD: dwelling characteristics, source of water, energy, cooking fuel, commodities owned, expenditure, income;

• INDIVIDUAL: demographic characteristics, economic activity, education, health, expenditure, income.

• Collection start: 2012

• Collection end: 2013

Philippines Average Family Income: By Income Class (IC): Annual data was reported at 267,000.000 PHP in 2015. This records an increase from the previous number of 235,000.000 PHP for 2012. Philippines Average Family Income: By Income Class (IC): Annual data is updated yearly, averaging 146,019.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 267,000.000 PHP in 2015 and a record low of 40,408.000 PHP in 1988. Philippines Average Family Income: By Income Class (IC): Annual data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H018: Family Income and Expenditure Survey: Average Annual Income and Expenditure: By Income Class.

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).

Version 01: Cleaned, labelled and anonymized version of the Master file.

-INDIVIDUALS: Demographic characteristics; Education; Health; Communication; Alcohol and narcotics; Other individual expenditure; Economic activities; Income; Handicraft and processed food.
-HOUSEHOLDS: Dwelling characteristics, Housing expenditure, Household operations, Food expenditure; Sanitation; Water access; Energy; Agriculture; Fisheries; Hunting; Handicraft; Transport; Travel; Financial support; Ceremonies; Food insecurity; Copra production; Legal services.

• Collection start: 2019
• Collection end: 2020

Abstract

The purpose of the HIES survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in Nauru. 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 Nauru.

Geographic coverage

National

Analysis unit

• Household
• Person
• Expenditure Commodity

Universe

The survey covered all private households on the island of Nauru. When the survey was in the field, interviewers were further required to reduce the scope by removing those households which had not been residing in Nauru for the last 12 months and did not intend to stay in Nauru for the next 12 months.

Persons living in special dwellings (Hospital, Prison, etc) were not included in the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size adopted for the survey was 500 households which allowed for expected sample loss, whilst still maintaining a suitable responding sample for the analysis.

Before the sample was selected, the population was stratified by constituency in order to assist with the logistical issues associated with the fieldwork. There were eight constituencies in total, along with "Location" which stretches across the districts of Denigamodu and Aiwo, forming nine strata in total. Although constituency level analysis was not a priority for the survey, sample sizes within each stratum were kept to a minimum of 40 households, to enable some basic forms of analysis at this level if required.

The sample selection procedure within each stratum was then to sort each household on the frame by household size (number of people), and then run a systematic skip through the list in order to achieve the desirable sample size.

Sampling deviation

No deviations from the sample design took place.

Mode of data collection

Face-to-face [f2f] for questionnaires, self-enumeration for the diaries

Research instrument

The survey schedules adopted for the HIES included the following: · Expenditure questionnaire · Income questionnaire · Miscellaneous questionnaire · Diary (x2)

Whilst a Household Control Form collecting basic demographics is also normally included with the survey, this wasn't required for this HIES as this activity took place for all households in the mini census.

Information collected in the four schedules covered the following:

Expenditure questionnaire: Covers basic details about the dwelling structure and its access to things like water and sanitation. It was also used as the vehicle to collect expenditure on major and infrequent expenditures incurred by the household.

Income questionnaire: Covers each of the main types of household income generated by the household such as wages and salaries, business income and income from subsistence activities.

Miscellaneous questionnaire: Covers topics relating to health access, labour force status and education.

Diary: Covers all day to day expenditures incurred by the household, consumption of items produced by the household such as fish and crops, and gifts both received and given by the household.

Cleaning operations

There were 3 phases to the editing process for the 2006 Nauru HIES which included: 1. Data Verification operations 2. Data Editing operations 3. Data Auditing operations

For more information on what each phase entailed go the document HIES Processing Instructions attached to this documentation.

Response rate

The survey response rates were a lot lower than expected, especially in some districts. The district of Aiwo, Uaboe and Denigomodu had the lowest response rates with 16.7%, 20.0% and 34.8% respectively. The area of Location was also extremely low with a responses rate of 32.2%. On a more positive note, the districts of Yaren, Ewa, Anabar, Ijuw and Anibare all had response rates at 80.0% or better.

The major contributing factor to the low response rates were households refusing to take part in the survey. The figures for responding above only include fully responding households, and given there were many partial responses, this also brought the values down. The other significant contributing factor to the low response rates was the interviewers not being able to make contact with the household during the survey period.

Unfortunately, not only do low response rates often increase the sampling error of the survey estimates, because the final sample is smaller, it will also introduce response bias into the final estimates. Response bias takes place when the households responding to the survey possess different characteristics to the households not responding, thus generating different results to what would have been achieved if all selected households responded. It is extremely difficult to measure the impact of the non-response bias, as little information is generally known about the non-responding households in the survey. For the Nauru 2006 HIES however, it was noted during the fieldwork that a higher proportion of the Chinese population residing in Nauru were more likely to not respond. Given it is expected their income and expenditure patterns would differ from the rest of the population, this would contribute to the magnitude of the bias.

Sampling error estimates

To determine the impact of sampling error on the survey results, relative standard errors (RSEs) for key estimates were produced. When interpreting these results, one must remember that these figures don't include any of the non-sampling errors discussed in other sections of this documentation

To also provide a rough guide on how to interpret the RSEs provided in the main report, the following information can be used:

Category  Description
RSE < 5%  Estimate can be regarded as very reliable
5% < RSE < 10% Estimate can be regarded as good and usable
10% < RSE < 25% Estimate can be considered usable, with caution
RSE > 25%  Estimate should only be used with extreme caution

The actual RSEs for the key estimates can be found in Section 4.1 of the main report

As can be seen from these tables, the estimates for Total Income and Total Expenditure from the HIES can be considered to be very good, from a sampling error perspective. The same can also be said for the Wage and Salary estimate in income and the Food estimate in expenditure, which make up a high proportion of each respective group.

Many of the other estimates should be used with caution, depending on the magnitude of their RSE. Some of these high RSEs are to be expected, due to the expected degree of variability for how households would report for these items. For example, with Business Income (RSE 56.8%), most households would report no business income as no household members undertook this activity, whereas other households would report large business incomes as it's their main source of income.

Data appraisal

Other than the non-response issues discussed in this documentation, other quality issues were identified which included: 1) Reporting errors Some of the different aspects contributing to the reporting errors generated from the survey, with some examples/explanations for each, include the following:

a) Misinterpretation of survey questions: A common mistake which takes place when conducting a survey is that the person responding to the questionnaire may interpret a question differently to the interviewer, who in turn may have interpreted the question differently to the people who designed the questionnaire. Some examples of this for a HIES can include people providing answers in dollars and cents, instead of just dollars, or the reference/recall period for an “income” or “expenditure” is misunderstood. These errors can often see reported amounts out by a factor of 10 or even 100, which can have major impacts on final results.

b) Recall problems for the questionnaire information: The majority of questions in both of the income and expenditure questionnaires require the respondent to recall what took place over a 12 month period. As would be expected, people will often forget what took place up to 12 months ago so some information will be forgotten.

c) Intentional under-reporting for some items: For whatever reasons, a household may still participate in a survey but not be willing to provide accurate responses for some questions. Examples for a HIES include people not fully disclosing their total income, and intentionally under-reporting expenditures on items such as alcohol and tobacco.

d) Accidental under-reporting in the household diaries: Although the two diaries are left with the household for a period of two weeks, it is easy for the household to forget to enter all expenditures throughout this period - this problem most likely increases as the two

Abstract

The Household Income and Expenditure Survey is a survey collecting data on income, consumption and expenditure patterns of households, in accordance with methodological principles of statistical enquiries, which are linked to demographic and socio-economic characteristics of households. A Household Income and expenditure Survey is the sole source of information on expenditure, consumption and income patterns of households, which is used to calculate poverty and income distribution indicators. It also serves as a statistical infrastructure for the compilation of the national basket of goods used to measure changes in price levels. Furthermore, it is used for updating of the national accounts.

The main objective of the NHIES 2009/2010 is to comprehensively describe the levels of living of Namibians using actual patterns of consumption and income, as well as a range of other socio-economic indicators based on collected data. This survey was designed to inform policy making at the international, national and regional levels within the context of the Fourth National Development Plan, in support of monitoring and evaluation of Vision 2030 and the Millennium Development Goals. The NHIES was designed to provide policy decision making with reliable estimates at regional levels as well as to meet rural - urban disaggregation requirements.

Geographic coverage

National Coverage

Analysis unit

Individuals and Households

Universe

Every week of the four weeks period of a survey round all persons in the household were asked if they spent at least 4 nights of the week in the household. Any person who spent at least 4 nights in the household was taken as having spent the whole week in the household. To qualify as a household member a person must have stayed in the household for at least two weeks out of four weeks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The targeted population of NHIES 2009/2010 was the private households of Namibia. The population living in institutions, such as hospitals, hostels, police barracks and prisons were not covered in the survey. However, private households residing within institutional settings were covered. The sample design for the survey was a stratified two-stage probability sample, where the first stage units were geographical areas designated as the Primary Sampling Units (PSUs) and the second stage units were the households. The PSUs were based on the 2001 Census EAs and the list of PSUs serves as the national sample frame. The urban part of the sample frame was updated to include the changes that take place due to rural to urban migration and the new developments in housing. The sample frame is stratified first by region followed by urban and rural areas within region. In urban areas further stratification is carried out by level of living which is based on geographic location and housing characteristics. The first stage units were selected from the sampling frame of PSUs and the second stage units were selected from a current list of households within each selected PSU, which was compiled just before the interviews.

PSUs were selected using probability proportional to size sampling coupled with the systematic sampling procedure where the size measure was the number of households within the PSU in the 2001 Population and Housing Census. The households were selected from the current list of households using systematic sampling procedure.

The sample size was designed to achieve reliable estimates at the region level and for urban and rural areas within each region. However the actual sample sizes in urban or rural areas within some of the regions may not satisfy the expected precision levels for certain characteristics. The final sample consists of 10 660 households in 533 PSUs. The selected PSUs were randomly allocated to the 13 survey rounds.

Sampling deviation

All the expected sample of 533 PSUs was covered. However a number of originally selected PSUs had to be substituted by new ones due to the following reasons.

Urban areas: Movement of people for resettlement in informal settlement areas from one place to another caused a selected PSU to be empty of households.

Rural areas: In addition to Caprivi region (where one constituency is generally flooded every year) Ohangwena and Oshana regions were badly affected from an unusual flood situation. Although this situation was generally addressed by interchanging the PSUs betweensurvey rounds still some PSUs were under water close to the end of the survey period. There were five empty PSUs in the urban areas of Hardap (1), Karas (3) and Omaheke (1) regions. Since these PSUs were found in the low strata within the urban areas of the relevant regions the substituting PSUs were selected from the same strata. The PSUs under water were also five in rural areas of Caprivi (1), Ohangwena (2) and Oshana (2) regions. Wherever possible the substituting PSUs were selected from the same constituency where the original PSU was selected. If not, the selection was carried out from the rural stratum of the particular region. One sampled PSU in urban area of Khomas region (Windhoek city) had grown so large that it had to be split into 7 PSUs. This was incorporated into the geographical information system (GIS) and one PSU out of the seven was selected for the survey. In one PSU in Erongo region only fourteen households were listed and one in Omusati region listed only eleven households. All these households were interviewed and no additional selection was done to cover for the loss in sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The instruments for data collection were as in the previous survey the questionnaires and manuals. Form I questionnaire collected demographic and socio-economic information of household members, such as: sex, age, education, employment status among others. It also collected information on household possessions like animals, land, housing, household goods, utilities, household income and expenditure, etc.

Form II or the Daily Record Book is a diary for recording daily household transactions. A book was administered to each sample household each week for four consecutive weeks (survey round). Households were asked to record transactions, item by item, for all expenditures and receipts, including incomes and gifts received or given out. Own produce items were also recorded. Prices of items from different outlets were also collected in both rural and urban areas. The price collection was needed to supplement information from areas where price collection for consumer price indices (CPI) does not currently take place.

Cleaning operations

The questionnaires received from the regions were registered and counterchecked at the survey head office. The data processing team consisted of Systems administrator, IT technician, Programmers, Statisticians and Data typists.

Data capturing

The data capturing process was undertakenin the following ways: Form 1 was scanned, interpreted and verified using the “Scan”, “Interpret” & “Verify” modules of the Eyes & Hands software respectively. Some basic checks were carried out to ensure that each PSU was valid and every household was unique. Invalid characters were removed. The scanned and verified data was converted into text files using the “Transfer” module of the Eyes & Hands. Finally, the data was transferred to a SQL database for further processing, using the “TranScan” application. The Daily Record Books (DRB or form 2) were manually entered after the scanned data had been transferred to the SQL database. The reason was to ensure that all DRBs were linked to the correct Form 1, i.e. each household’s Form 1 was linked to the corresponding Daily Record Book. In total, 10 645 questionnaires (Form 1), comprising around 500 questions each, were scanned and close to one million transactions from the Form 2 (DRBs) were manually captured.

Response rate

Household response rate: Total number of responding households and non-responding households and the reason for non-response are shown below. Non-contacts and incomplete forms, which were rejected due to a lot of missing data in the questionnaire, at 3.4 and 4.0 percent, respectively, formed the largest part of non-response. At the regional level Erongo, Khomas, and Kunene reported the lowest response rate and Caprivi and Kavango the highest. See page 17 of the report for a detailed breakdown of response rates by region.

Data appraisal

To be able to compare with the previous survey in 2003/2004 and to follow up the development of the country, methodology and definitions were kept the same. Comparisons between the surveys can be found in the different chapters in this report. Experiences from the previous survey gave valuable input to this one and the data collection was improved to avoid earlier experienced errors. Also, some additional questions in the questionnaire helped to confirm the accuracy of reported data. During the data cleaning process it turned out, that some households had difficulty to separate their household consumption from their business consumption when recording their daily transactions in DRB. This was in particular applicable for the guest farms, the number of which has shown a big increase during the past five years. All households with extreme high consumption were examined manually and business transactions were recorded and separated from private consumption.

Germany Income & Expenditure Survey (IES): Households Covered data was reported at 52,782.000 Unit in 2018. This records a decrease from the previous number of 53,490.000 Unit for 2013. Germany Income & Expenditure Survey (IES): Households Covered data is updated yearly, averaging 53,490.000 Unit from Dec 1998 (Median) to 2018, with 5 observations. The data reached an all-time high of 62,150.000 Unit in 1998 and a record low of 52,782.000 Unit in 2018. Germany Income & Expenditure Survey (IES): Households Covered data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.H023: Household Income and Expenditure Survey.

Abstract

The 2008 HIES collects information on Income and Expenditure of each sampled household in order to provide information on the economic characteristics of all households in Samoa. The main objectives of this survey are: - To adjust the weights of the Consumer Price Index (CPI) using the household expenditure pattern of Samoan households and - To provide data to determine the extent of hardship and the vulnerability of households in Samoa

This undertaking was funded by the Government of Samoa, with technical assistance provided by the Asian Development Bank through the services of Mr. David Abbott

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Survey Methodology The sampling technique used for the 2008 HIES is a stratified single stage cluster design. The first stage involved the selection of the Enumeration Area (EA) using Probability Proportional to Size (PPS) while the second stage involved the selection of a fixed cluster size.

To achieve a 10% sample of households, every tenth household was selected with a cluster size of 10 for North West Upolu, Rest of Upolu, and Savaii, and a cluster size of 5 for Apia Urban Area. Due to some variation in the number of households since the last population census in 2006 in which the frame was based, and the 2008 situation, the proportions of sampled households in the frame does not come to the required sample size.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2008 Household Income and Expenditure Survey questionnaire consists of four forms: i) Household Control Form ii) Household Form iii) Individual Questionnaire iv) Diary

Sampling error estimates

Accuracy and reliability of estimates in a survey such as HIES are measured by computing the sampling errors, specifically standard errors and coefficient of variations. Although survey estimates are subject to both sampling and non sampling errors, only sampling errors can be calculated. Non sampling errors are minimized by means of quality control and operational control measures in all phases of the survey. In practice, estimates with coefficient of variations (CV) of less than 20% are considered as statistically ‘accurate’. On the other hand, those estimates with (CV) more than 20% are ‘indicative’ and should not be used at face value.

Note: Standard errors and coefficient of variation for key variables are presented in Appendix 2 of the 2008 HIES final report.

The 2021 Tonga HIES is the new update of this kind, after the 2015/2016, 2009 & 2001 versions. This survey aims to provide indicators on Household Living Standard using monetary aspect (amount of income and expenditure), non-monetary aspect (calory consumed, assets own, imputed rents…) and more social approach (education, health, food security status…). Survey outputs have multiple uses in various domains such as public health (food nutrition analysis), economic development (poverty), system of National Account (consumption aggregates), and they represent a key source of information to populate many National SDGs.

Version 01: Cleaned, labelled and anonymized version of the Master file.

-HOUSEHOLD: Dwelling characteristics; Assets; Home maintenance; Vehicles; International trips; Domestic trips; Household services; Financial support; Other household expenditure; Ceremonies; Remittances; Food insecurity; Livestock and aquaculture; Agriculture; Legal services.
-INDIVIDUAL: Individual characteristics; Education; Health; Disability; Communication; Alcohol; Other individual expenses; Labour force; Fisheries and hunting; Handicraft.

• Collection start: 2021
• Collection end: 2021

Abstract

The 1997 Family Income and Expenditute Survey had the following objectives: 1. to gather data on family income and family living expenditures and related information affecting income and expenditure levels and patterns in the Philippines;

1. to determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families;

2. to provide benchmark information to update weights in the estimation of consumer price index (CPI); and

3. to provide inputs in the estimation of the country's poverty threshold and incidence.

Geographic coverage

National coverage

Analysis unit

Household Consumption expenditure item Income by source

Universe

The 1997 FIES has as its target population, all households and members of households nationwide. A household is defined as an aggregate of persons, generally but not necessarily bound by ties of kinship, who live together under the same roof and eat together or share in common the household food. Household membership comprises the head of the household, relatives living with him such as his/her spouse, children, parent, brother/sister, son-in-law/daughter-in-law, grandson/granddaughter and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

Institutional population is not within the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the 1997 FIES adopted that of the Integrated Survey of Households (ISH). Starting July 1996, the sampling design of the ISH uses the new master sample design. The multi-stage sampling design of the master sample consists of 3,416 PSUs in the expanded sample for provincial level estimates with a sub-sample of 2,247 PSUs designated as the core master sample for regional levels estimates. The 1997 FIES was based on the expanded sample.

Domains The urban and rural areas of each province are the principal domains for the survey. In addition, areas with 150,000 or more population as of 1995 Census of Population (POPCEN) are also domains of the survey with rural and urban dimensions. The domains for the new master sample are similar to that of the previous ISH design with an addition of 23 newly created domains.

The multi-stage sampling design of the master sample involves the selection of the sample barangays for the first stage, selection of sample enumeration areas for the second stage, and the selection of sample households for the third stage in each stratum for every domain.

The frame for the first stage and second stages of sample selection were based mainly on the results of the 1995 POPCEN. The 1995 list of barangays with the household and population counts is used in the first stage of sample selection. The stratification of barangays included in the frame, however are based on the 1990 Census of Population and Housing (CPH) and other administrative reports from the field offices of NSO. An enumeration area (EA) is a physical delineated portion of the barangay. For barangays that were not divided into EAs, the barangay was treated as an EA.

The enumeration areas which constitutes the secondary sampling units are those that were formed during the 1995 POPCEN. The sample barangays were selected systematically with probability proportional to size from the list of barangays that were implicitly stratified.

The frame for the third stage of sample selection is the list of households from the 1995 POPCEN. The selection of sample households for the third stage was done systematically from the 1995 POPCEN List of Households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire has five main parts consisting of the following: Part I. Identification and Other Information (Geographic Identification, Other Information and Particulars about the Family)

Part II. Expenditures and Other Disbursements Section A. Food, Alcoholic Beverages and Tobacco Section B. Fuel, Light and Water, Transportation and Communication, Household Operations Section C. Personal Care and Effects, Clothing Footwear and Other Wear Section D. Education, Recreation, and Medical Care Section E. Furnishings and Equipment Section F. Taxes Section G. Housing, House Maintenance and Minor Repairs Section H. Miscellaneous Expenditures Section I. Other Disbursements

Part III. Income Section A. Salaries and Wages from Employment Section B. Net Share of Crops, Fruits and Vegetables Produced and/or Livestock and Poultry Raised by Other Households Section C. Other Sources of Income Section D. Other Receipts Section E. Family Sustenance Activities

Part IV. Entrepreneurial Activities Section A1. Crop Farming and Gardening Section A2. Livestock and Poultry Raising Section A3. Fishing Section A4. Forestry and Hunting Section A5. Wholesale and Retail Section A6. Manufacturing Section A7. Community, Social, Recreational and Personal Services Section A8. Transportation, Storage and Communication Services Section A9. Mining and Quarrying Section A10. Construction Section A11. Entrepreneurial Activities Not Elsewhere Classified

Part V: Health - Care Section A. Health - care Expenditures Section B. Health Insurance

Cleaning operations

The 1997 FIES questionnaire contains about 800 data items and a guide for comparing income and expenditures. The questionnaires were subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency.

The electronic data processing system developed since 1985 FIES by the Information System Development Section was used in processing the 1997 FIES with few modifications.

There were thirteen major steps in the machine processing and these are as follows: 1. Data entry and verification 2. Structural editing (minor edit) 3. Edit list verification/correction 4. Update 5. Completeness check 6. Completeness check list verification/correction 7. Identification verification 8. Identification verification extraction of summary file for preliminary results 9. Matching of visit records 10. Expansion 11. Tabulations 12. Generation of CPI weights 13. Variance analysis

Steps 1 to 8 were performed right after each visit while the remaining steps were carried out upon completion of the data collection for the first and second visits.

Steps 1 to 7 were implemented at the regional office while the concluding steps were handled at the Central Office.

Response rate

The response rate for the 1997 FIES is 96.4%.

Sampling error estimates

As in all surveys, two types of non-response were encountered in the 1997 FIES: Interview non-response and item non-response. Interview non-response refers to a sample household that could not be interviewed. Since the survey requires that the sample households be interviewed in both visits, households that transferred to another dwelling unit, temporarily away, on vacation, not at home, household unit demolished, destroyed by fire/typhoon and refusal to be interviewed in the second visit contributed to the number of interview non-response cases.

Item non-response, or the failure to obtain responses to particular survey items, resulted from factors such as respondents being unaware of the answer to a particular question, unwilling to provide the requested information or ENs' omission of questions during the interview. Deterministic imputation was done to address item nonresponse. This imputation is a process in which proper entry for a particular missing item was deduced from other items of the questionnaire where the non-response item was observed. Notes and remarks indicated in the questionnaire were likewise used as basis for imputation.

The purpose of the HIES survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in Federated States of Micronesia (FSM). 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 FSM'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 FSM.

Version 01: Cleaned, labelled and anonymized version of the Master file.

There were 5 Modules altogether which refers to different scope of the surveys.

Module 1 - contains Demographic Information:
- Demographic Profile
- Labor Force Status
- Health Status
- Communication Status

Module 2 - collects information on Household Expenditure which include:
- 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 Identification
- Education Expenditures
- Health Identification
- Health Expenditures
- Clothing Identification
- Clothing Expenditure
- Communication Identification
- Communication 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

• Collection start: 2013
• Collection end: 2014

Abstract

The Household Income Expenditure Survey (HIES) collected detailed information at the household level on the following topics: education, health, employment, water and sanitary practices, household resources, grants, crime, conflicts and recent shocks to household wealth. The survey was also expected to provide reliable and policy relevant agricultural statistics and served as a baseline of information for the “Agenda for Transformation” set by the Government of Liberia. Other components of the HIES included capacity building and cross-country knowledge, sharing alongside efforts to improve survey methodologies in Liberia. Among other features were the design and implementation of a household survey that focused on the household income and expenditure that fed into Consumer Price Index (CPI) construction. The data collection exercise for the survey was conducted from January to December 2014.The survey covered 8,360 randomly selected households over the 12-month period. The objectives of the HIES were:

1. Evaluation and analysis of poverty levels and quality of life at the household level.
2. Analysis of primary indicators on economic productivity, employment, and social welfare.
3. Preparation of a 'weighting system' for a Consumer Price Index.
4. Generation of general economic (macroeconomic) indicators; e.g. estimates of national income. (Gross Domestic Product - GDP)
5. Analysis of household ownership of productive assets and their linkages with household income activities.

Geographic coverage

National

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The main Household Income Expenditure Survey (HIES) was administered to a representative sample of households. The sampling frame was defined by all Enumeration Areas (EA's) from each county across Liberia. The survey used a two stage sampling methodology. At the first stage 836 enumeration areas were selected. At the second stage 8,360 households were randomly selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were two questionnaires administered for this survey: 1. Household and Individual Questionnaire
2. Price Questionnaire

Abstract

The 2001 Myanmar Household Income and Expenditure Survey (HIES) is a major nation-wide survey of Central Statistical Organization.

Geographic coverage

National

Kind of data

Sample survey data [ssd]

Sampling procedure

Multi-stage stratified random sample Sample size: 30000 Adult Females

Mode of data collection

Face-to-face

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.

Philippines Average Family Income: Region VII, Central Visayas data was reported at 239,000.000 PHP in 2015. This records an increase from the previous number of 209,000.000 PHP for 2012. Philippines Average Family Income: Region VII, Central Visayas data is updated yearly, averaging 110,265.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 239,000.000 PHP in 2015 and a record low of 27,972.000 PHP in 1988. Philippines Average Family Income: Region VII, Central Visayas data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H020: Family Income and Expenditure Survey: Average Annual Income, Expenditure and Saving: By Region.

Abstract

The Household Income and Expenditure Survey (HIES) was conducted by the Department of Census and Statistics (DCS) of Sri Lanka. The survey provides information on household socio demographic characteristics, access to basic services, housing, income and consumption expenditure to measure the levels and to observe the changes of living conditions of people in the country. The HIES information is also used to estimate consumption needs of the country and to compute various other important indicators related to poverty and price indices.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample design of the survey is two stages stratified and the Urban, Rural and the Estate sectors in each district of the country are the selection domains thus the district is the main domain used for the stratification. The sampling frame is the list of housing units prepared for the Census of Population and Housing (CPH) 2011.

Selection of Primary Sampling Units Primary sampling units (PSUs) are the census blocks selected for the survey. The sampling frame, which is the collection of all the census blocks prepared in CPH 2011 in Sri Lanka, is used for the selection of the PSUs at the first stage of the selection.

The PSU selection is done within all the independent-selection domains that are assigned different sample size allocations to total the targeted sample size of 2,500 PSUs. The method of selection of the PSUs at the first stage is systematic with a selection probability given to each census block proportionate to the number of housing units available in the census blocks within the selection domains (PPS).

The selected PSUs are updated to include newly built housing units and to exclude demolished or vacated housing units, which are no longer considered as housing units according to the survey definitions, to capture variation of natural growth and to make necessary adjustments for the same. The PSU updating operation in field is generally done less than one month prior to the survey and it was carried out for the 12 months starting from October 2018 to September 2019 to support the scheduled 12 survey months started from January to December in 2019 for the HIES 2019.

Selection of Secondary Sampling Units Secondary Sampling Units (SSUs) or Final sampling units (FSUs) are the housing units selected at the second stage from the 2,500 PSUs selected at the first stage. From each PSU, 10 SSUs (housing units) are systematically selected giving each housing unit in the PSU an equal probability to be selected for the survey. The total sample of size 25,000 housing units is resulted at the end of the sampling process and this sample represents the whole country in different probabilities depend on the different sample sizes allocated for the selection domains.

Sample Allocation Allocation of the number of PSUs or determining the sample sizes for the districts is made proportionate to the number of housing units and the standard deviations of the mean household expenditure values reported in the respective districts in previous surveys (Neymann Allocation). Sector allocation of the district sample is made proportionate to the square root of the sizes of the respective selection domains (Urban, Rural and Estate sectors in the district). The sample of PSUs within the selection domain is equally distributed among the 12 survey months and the monthly sample too is equally dispersed among all the weeks in the month assigning a specific week for each PSU for the survey activities.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2019 HIES survey questionnaire consists of nine sections. - Section 1: Demographic Characteristics - Section 2: School Education (For people aged 5 - 20 years) - Section 3: Health - Section 4: Expenditure - Section 5: Income - Section 6: Inventory of Durable Goods & Indebtedness - Section 7: Access to Primary facilities - Section 8: Housing Information - Section 9: Land Ownership and Livestock

Abstract

The Statistics Division of the Department of National Planning (DNP/SD) conducts Household Income and Expenditure Surveys (HIES) in the Maldives. HIES 2009-2010 is the second such nationwide survey conducted in the country. 39 islands were randomly selected from all 20 Atolls and the capital Male' with a sample of 2,060 households.

The main objective of HIES is to produce reliable statistics on different components of income and expenditure of households in Male' and the Atolls to assess the economic well-being of the population. Specifically, the results will be used to bring about improvements in the national accounts, consumer price index and the vulnerability and poverty statistics of the country.

HIES results will be particularly essential and used for following purposes: • To show the most recent composition of consumption expenditure of households which will be used to update the CPI weights • To improve GDP estimates particularly for the components of final consumption expen diture of households, income and outlay and savings. • To measure living standard and indicate the gap between different social strata • To analyze distribution of households in terms of income groups and proper statistical measure of income inequality such as Gini coefficient. • To measure the poverty situation of households and update the existing poverty esti mates and indicators.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Consumption expenditure commodities/ services

Kind of data

Sample survey data [ssd]

Sampling procedure

Required data for sampling were obtained from the population and housing census 2006. The country consists of 20 administrative atolls comprising of 194 inhabited islands. For political purpose these 20 administrative atolls are grouped as 7 regions. The capital Male' has separate administrative status. The frame for Male' consists of 6 wards and 324 enumeration blocks. HIES uses the area frame as a basis, to make the sample representative for the administrative and geographic structure of the country. All the inhabited islands have clearly marked census enumeration blocks, which were used in the sampling. Major characteristics of the HIES sampling frame are given below. A total of 880 blocks and 45,993 households were in the 194 inhabited islands of the country.

Note: Detailed sampling information is presented in APPENDIX ONE in the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were 8 different questionnaires. This includes: • Listing form (Form 1) is used to enumerate all the structures and households in the se lected Enumeration block in preparation for the actual household survey. One set of forms to be completed for each selected enumeration block. • Household form, (Form 2) consists of information on housing, household composition, household durables, and travel by members of the household, investment and financial status of household. One form has to be completed for each household. • Household member form (Individual form), (Form 3) consists of basic demographic char acteristics on all household members, education for those aged 6 years and above and identifies the labour force. One column on the form needs to be completed for each member of the household. • Employment and income form (Form 4) consists of information on employment and in come, one form to be completed for each member of the household who is aged fif teen years and over and who is working or is an income recipient. • Expenditure forms (Form 5) and, (Form 6), For Male' and the Atoll Islands, Form 5 is used to record the household expenditures and Form 6 to record the personal expendi tures of individual household members over the age of 15. Thus, a Form 5 will be filled for each household, while every individual member 15 years of age and above, who earns, fills a Form 6 to record his/her personal expenditure diary. • Summary form (Form 7) consist the summary information of the household. After all the information for the household and its members were received, this form was used to calculate the household income and expenditure and to calculate the expenditure per day and expenditure per person for a household. • ICT form (Form 8) consists of information related to the information communication technology (ICT). Accessibility, usage and expenditures on ICT by the household's mem bers aged 4 years and above were recorded in this form.

Sampling error estimates

Sampling Errors Sampling errors refers to the difference between the estimate based on a sample and its 'true' population value that would result if the whole population has been surveyed. The extent of sampling error of an estimate under a particular sample design is assessed by the variability of the estimate across all possible samples under the design. One common measure of this variability is given by the standard error (SE), which is the standard deviation of the sampling distribution of the estimate. Another measure is the relative standard error (RSE), which is obtained by expressing the standard error as a percentage to the estimate. The smaller the RSE, the more precise is the estimate.

The difference between standard error (SE) and relative standard error (RES) are that the standard error (SE) measure indicates the extent to which a survey estimate is likely to deviate from the true population and is expressed as a number. The relative standard error (RSE) is the standard error expressed as a fraction of the estimate and is usually displayed as a percentage. Estimates with a RSE of 25% or greater are subject to high sampling error and should be used with caution.

The reliability of estimates can also be assessed in terms of a confidence interval. Confidence intervals represent the range in which the population value is likely to lie. They are constructed using the estimate of the population value and its associated standard error. For example, there is approximately a 95% chance (i.e. 19 chances in 20) that the population value lies within two standard errors of the estimates, so the 95% confidence interval is equal to the estimate plus or minus two standard errors.

Note: Estimated sampling errors of some selected estimates in the HIES 2009/10 report are in Table 1.7.1.

Data appraisal

Sample surveys are limited in that they are assumed to represent the part of the population that was not included in the sample. Surveys have various sampling and non sampling errors, such an assumption may not always be correct. In the HIES 2009/2010 an important limitation is that no conclusions can be drawn from the information on the situation in any particular atoll; as the survey was designed to represent for Male' and at the 7 regions at the most disaggregated level. Also the regions in HIES 2009/2010 is different from previous HIES, hence the two HIESs is not comparable at regional level.

The survey design of HIES does not include resorts and industrial islands. Hence the direct incomes and expenditures of this particular population will not be accounted. If a person was not living in the household during the survey period the income the income of that person was recorded as transfer income. This limitation resulted in the employment in tourism industry lower compared to census 2006.

Abstract

The purpose of the HIES survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in FSM. 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. The 2005 FSM HIES asked income of all persons 15 years and over. It referred to income received during the calendar year 2004, and includes both cash and in-kind income. The survey has five primary objectives, namely to:

1) Rebase the FSM Consumer Price Index (CPI); 2) Provide data on the distribution of income and expenditures throughout the FSM; 3) Provide data for national accounts, particularly regarding income from home production activities and the consumption of goods and services derived form home production activities; 4) Provide nutritional information and food consumption patterns for the FSM families; and 5) Provide data for hardship study.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Expenditure items

Universe

The survey universe covered all persons living in their place of usual residence at the time of the survey. Income data were collected from persons aged 15 years and over while expenditure data were obtained from all household members at a household level. Persons living in institutions, such as school dormitories, hospital wards, hostels, prisons, as well as those whose usual residence were somewhere else were excluded from the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2005 FSM Household Income and Expenditure Survey (HIES) used a sampling frame based on updated information on Enumeration Districts (ED) and household listing from the 2000 FSM Census. Based on this sampling frame, the four states of FSM were then classified as the domains of the survey. Each of the states was further divided into 3 strata, except for Kosrae which was not divided at all because it doesn't possess any outer islands and it has relatively good access to goods and services. The entire island was therefore classified under stratum 1. Each stratum was defined as follows:

1) State center and immediate surrounding areas:
- High 'living standard' and has immediate access to goods and services.

2) Areas surrounding state center (rest of main island):
- Medium 'living standard' and sometime limited access to goods and services

3) Outer islands:
- Low 'living standard' and rare access to goods and services.

Within each stratum, the HIES used a two-stage stratified sampling approach from which the sample was selected independently. First, enumeration districts (EDs) were drawn from each stratum using Proportion Probability to Size (PPS) sampling. Thus, the larger the ED size, the higher its probability of selection. About 69 EDs out of a total of 373 EDs were selected nationwide for the survey. Generally, one enumerator is assigned to each ED. Second, 20 households were systematically selected from an updated household listing for each of the selected EDs using a random start to come up with a total sample size of 1,380 households, or roughly 8.4 percent of all households in the state. Although it offered a fairly good representation of the total households in the nation, the final sample size showed a reduction of nearly 180 households from the 1,560 households, or 10 percent, initially selected for the survey.

Detailed information on the changes made to the sample size can be found in the next section under "Deviations from Sample Design."

Sampling deviation

The original plan to sample 1,560 households, or about 9.5 percent of all households in the nation was eventually reduced to 1,380 households, or about 8.4 percent of all households. The reduction of the sample size was due to fuel unavailability for transportation and uncertainty of field trip schedules to some of the selected outer islands. Dropping some of these islands from the sample was not expected to impact significantly on the accuracy of the survey results because independent weighting took place within each stratum, where islands were considered to be sufficiently homogenous.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires and forms used for the 2005 FSM HIES consisted of 1) HIES Questionnaire and 2) Weekly Diaries. The HIES Questionnaire were provided to enumerators and should be filled out during the first visit to the household. Its main objective was to collect housing information, basic demographic information about members of the household and general household expenditures over the previous year. On the other hand, the weekly diaries, was an attempt to record household expenditure on a daily basis over the course of a 2 week period. Both the HIES questionnaire and the weekly diary were developed and modeled after similar forms from the 1998 FSM HIES Survey and the 2004 Palau HIES Survey. Dr. Micheal Levin from the US Census Bureau, International Program Center (IPC), Ms. Brihmer Johnson of the FSM Division of Statistics and Mr. Glenn McKinlay, statistics advisor to FSM Division of Statistics, provided crucial inputs to the overall design of these forms. All questionnaires and diaries used during the HIES were printed in English so it was extremely important that field interviewers understand the instuctions and questions contained within. Testing of the questionnaire were carried out by FSM Division of Statistics staffs who conducted "real" interviews with certain households in their neighborhood as well as having their own household be interviewed by a different office staff. Specific sections for both the HIES questionnaire and the weekly diaries are outlined below:

I. HIES Questionnaire

1) General Household characteristics 2 ) Individual Person Characteristics 3) General Expenditure Listings - 12 Months Recall Period

II. 2 Week Daily Diaries

1) Daily Expenditure Diary - Day1 (Mon) thru Day7 (Sun) 2) Home Produced Items 3) Gifts Given Away 4) Gifts Received 5) Unusual Expenses for Special Events

Cleaning operations

Data editing of the 2005 FSM HIES data occurred over several instances during the data processing phase of the project and afterwards prior to putting together the final report. After a two weeks office review and call backs right after the enumeration phase, the initial phase of data editing took place on July 18, 2005 when the data processing phase of the survey commenced. Training for editing and coding took place on the same day along with the signing of contracts for 10 office clerks recruited to carry out this phase of the survey. As part of their contract, these individuals were also hired to key in the data at a later time. One of their primary responsibily was to match geographic ids for questionnaire with corresponding diaries and ensure consistencies and valid entries accordingly. No computer consistency edit checks were run against the data during the keying/verification process since the programs for these processes were not available at the time. All data quality checks and edits were done at the US Bureau of Census. Further edits were applied to the data during the data analysis and report writing process.

There were five types of checks performed: Structural check, Verification check, Consistency check, Macro Editing check, Data Quality assessment. Edit lists were also produced for health module, income and expenditure questionnaire which needed to be checked against the questionnaires. On the edit list, corrections of errors were made by crossing out incorrect or missing values and entering the correct values in red. Missing amounts that were also missing on the questionnaire will need to be estimated using estimates from questionnaires in the same Enumeration District (ED) batch. For the diaries, the batch files were concatenated for each state and exported to tab delimited files. These files were imported into Excel and the unit price for each item was calculated using quantities and weights where possible. Records for each item were then filtered out and check for outlier unit price values (both large and small values as well as missing values). Values for missing amounts were imputed from estimated using average prices from the items within the same ED.

The office operations manual used for editing and coding the questionnaires and diaries is provided under "Technical Documents/Data Processing Documents/Office Editing & Coding."

Response rate

Original Sample Size: 1,560 Households Original Sampling fraction 9.5%

Final Sample Size: 1,380 Households Final Sampling fraction 8.4%

The response rate for the final sample size of 1,380 households is 100 percent. The majority of households originally selected for the survey did respond to the survey. Households which have moved to other unselected areas or elsewhere and those who refused to respond were replaced with nearby households that were willing to participate in the survey.

Sampling error estimates

No sampling error analysis of the survey was calculated.

Data appraisal

The questionnaire design of the 2005 HIES vary from that of the 1998 HIES rendering comparison of the data to the 2005 HIES limited. However, when the data permits, comparisons were made.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size: