Abstract

In the implementation of the Party and State policy “Doi moi”, the General Statistical Office (GSO) has conducted many household living standards survey to collect information on the living standards of all social societies to serve policy-making and socio-economic development planning.

From 2002 to 2010, VHLSS are to be conducted (in every two- year) to monitor systematically the living standard of Vietnam's societies and at the same time, to exercise the monitoring and assessment of the implementation of the Comprehensive Poverty Alleviation and Growth Strategy defined in Country Strategy Paper approved by the Government Prime Minister. In addition, these surveys also serve the evaluation of realization of the Millennium Development Goals (MDGs) and the Socio-economic Development Goals set out by Vietnamese Government.

The 2002 VHLSS included all the keynote contents reflecting the living standards of the population and the basic socio-economic condition of communes/wards that might affect the living standards of the local people. As regards households, it collected data in relation to demographic characteristics of the household members, the education background, professional/ technical level of each member, income, expenditures, use of medical facilities of all kinds, employment, housing and amenity as possession, personal effects, utilities (power and water supply), sanitation and participation in the poverty alleviation programme.

As regards communes/wards, it collected a wide rage of information related to demography, nationality, infrastructure, farming, production promotion conditions, non-farming activity and law and order.

Household questionnaires and communes/wards questionnaires of the 2002 VHLSS were designed more scientifically to ensure feasibility. They had been, in fact, piloted in Bac Ninh, Binh Dinh and Dong Nai provinces prior to the actual survey.

Survey sample were selected, based on the Population and Housing Census 1999. The sample size included 75.000 households representative of the whole country, urban and rural area and 61 provinces. Survey samples were sub-divided into 4 minor samples for the quarterly surveys in 2002 for more thorough data collection in anticipation of the harvests that might somehow get in the way. To provide information on assessment of the living standards in 2001-2002, GSO developed and released the detailed results of the 2002 VHLSS, including relevant statistics and initial analysis. Expenditure related data were synthesized from samples of 30.000 households; others, from samples of 45.000 households.

To bring out the changes in the living standards, the 2002 VHLSS results were compared with the results obtained from other living standards surveys, e.g. the 1992-1993 living standards survey (1993 VLSS), the 1993 rich-poor status survey (1993 RPSS), the 1997-1998 living standards surveys (1998 VLSS), the Multipurpose household surveys throughout 1994 to 1997 and 1999 (MHPS)

The data on demography, labor, and employment ect… were collected from the 2002 VHLSS, not replace all the data already released from the surveys conducted in this area, but to shed more light on and make more on insightful analyses of the factors affecting the living standards.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community
• Consumption expenditure item/product

Kind of data

Sample survey data [ssd]

Sampling procedure

Vietnam household living standard survey 2002 was selected, based on the Population and Housing Census 1999. The sample size included 75.000 households representative of the whole country, urban and rural area and 61 provinces. Survey samples were sub-divided into 4 minor samples for the quarterly surveys in 2002 for more thorough data collection in anticipation of the harvests that might somehow get in the way.

Survey sample were designed by 2 samples: one big sample (45,000 households) which mostly concentrated on income of households to assess living standard for national, regional and provincial levels ; one smaller sample (30,000 households) with both information about income and expenditure to evaluate intensive living standard at central and provincial levels. Following are detail contents :

• Implementing survey in 2002 with income and expenditure questionnaire of 30,000 household sample (Income and expenditure survey). This sample was divided into 4 smaller ones, with 7,500 households of each which conducted in first month of four quarters in 2002 respectively. The 30,000 household sample showed estimations at national and regional levels for 2001-2002.

• In the first six months of 2002, survey was implemented on all sections, except for expenditure section (in Income and expenditure survey) for 45,000 household sample (Income survey). This sample was divided into 2 small samples with 22,500 households of each and conducted in quarter I, II/2002 respectively. Survey of 45,000 household sample combined with 15,000 households of Income and expenditure survey (30,000 household sample) which conducted in the first month in quarter I, II/2002 to establish one 60,000 household sample that showed estimations for national, regional and provincial levels for 2001.

The detail is shown as following:

Collecting data perriod Income and expenditure survey Income survey Total Total 30,000 45,000 75,000

Divided into : QI/2002 7,500 22,500 30,000 QII/2002 7,500 22,500 30,000 QIII/2002 7,500 7,500 QIV/2002 7,500 7,500

Mode of data collection

Face-to-face [f2f]

Research instrument

VLSS 2002 used 3 questionnaires: - Short household questionnaire (excluded most of consumption expenditure information) - Long household questionnaire (including detail consumption expenditure information) - Commune questionnaire

The household questionnaire contains 9 sections each of which covered a separate aspects of household activity. Here are sections: 1. Household Roster 2. Education 3. Employment 4. Health 5. Income and Household Production 6. Expenditure (collected only for long questionnaire) 7. Durable Good and Asset 8. Housing 9. Participation in Poverty Reduction Programs

The commune questionnaire includes 9 sections and was administered by the team leader and completed with the help of village chiefs, teachers, government officials and health care workers. The questionnaire was administered in both rural and urban areas but some section was only collected in rural area such as non-farm employment opportunities and infrastructure and transportation. Here are commune questionnaire sections: 0. Survey Information 1. Main Characteristics of The Commune/ Ward 2. General Economic Conditions and Aid Programs 3. Non-Farm Employment Opportunities 4. Agriculture 5. Physical Infrastructure and Transportation 6. Education 7. Health 8. Public Disorder and Other Social Affairs

Abstract

The General Director, the General Statistics Office (GSO), issued Decision Number 308/QD-TCTK dated 5nd April 2006 on Conducting the Vietnam Household Living Standards Survey in 2006 (VHLSS 2006) in order to collect necessary information for monitoring, supervising and evaluating the implementation of the “Comprehensive Strategy for Growth and Poverty Alleviation” approved by the Government Prime Minister. The survey was conducted nation-wide, involving a sample scale of 45,945 households (36,756 households for income survey, 9,189 households for income and expenditure survey) in 3,063 communes/wards, representative for whole country, 8 regions, urban/ rural area and provinces. Organizationally, the survey was conducted to collect information in 2 rounds, 2006 and by direct interviews with headed households and key commune officials.

Geographic coverage

The VHLSS 2006 was conducted nation-wide, involving a sample scale of 45,945 households (36,756 households for income survey, 9,189 households for income and expenditure survey) in 3,063 communes/wards, representative for whole country, 8 regions, urban/ rural area and provinces.

Analysis unit

• Households
• Individuals
• Communes

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

Survey sample was selected, based on the Population and Housing Census 1999. The sample size included 45,900 households representative of the whole country, urban and rural area and 64 provinces. Survey sample was divided into 2 types: 36,720 households would be surveyed on income and 9,180 households would be surveyed on income and expenditures. The survey sample was sub-divided into 2 minor samples for data collection in 2 stages: the first in May 2006 and the second in September 2006.

Mode of data collection

Face-to-face [f2f]

Research instrument

1. Income and Expenditure questionnaire
2. Income questionnaire
3. Commune questionnaire

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of Stata data files Detailed documentation of the editing of data can be found in the "Data processing guidelines" document provided as an external resource.

Abstract

The VHLSS 2010 was conducted nationwide with a sample size of 69,360 households in 3,133 communes/wards which were representative at national, regional, urban, rural and provincial levels. The survey collected information during four periods, each period in one quarter from the second quarter to the forth quarter in 2010 and one period in the first quarter of 2011 through face-to-face interviews conducted by interviewers with household heads and key commune officials in communes containing sample enumeration areas.

The survey collected information to be a base for assessment of living standard, poverty and the gap between the rich and the poor serving for policy making, planning and national targeted programs of the party and the State in order to continuously improve the living standard of citizen across the country, in all regions and localities.

Geographic coverage

National coverage. The survey is respresentative at national, urban, rural and provincial levels.

Analysis unit

• Household
• Individual
• Consumption expenditure item/ product

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire contains 11 sections: Section 1. Some basic demographic characteristics related to living standards Section 2. Education Section 3. Labour - Employment Section 4. Health and health care Section 5. Income Section 6. Consumption expenditure Section 7. Durable goods Section 8. Housing, electricity, water, sanitation facilities and use of Internet Section 9. Participation in poverty reduction programs Section 10. Business production activities Section 11. Commune general characteristics

The average American household consisted of 2.51 people in 2023.

Households in the U.S.

As shown in the statistic, the number of people per household has decreased over the past decades.

The U.S. Census Bureau defines a household as follows: “a household includes all the persons who occupy a housing unit as their usual place of residence. A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from outside the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated persons who share living arrangements. (People not living in households are classified as living in group quarters.).”

The population of the United States has been growing steadily for decades. Since 1960, the number of households more than doubled from 53 million to over 131 million households in 2023.

Most of these households, about 34 percent, are two-person households. The distribution of U.S. households has changed over the years though. The percentage of single-person households has been on the rise since 1970 and made up the second largest proportion of households in the U.S. in 2022, at 28.88 percent.

In concordance with the rise of single-person households, the percentage of family households with own children living in the household has declined since 1970 from 56 percent to 40.26 percent in 2022.

As of 2023, approximately **** percent of households in East Kalimantan, Indonesia, lived in rented residential units, showing a decrease from the previous year. Among the other provinces in Indonesia, East Kalimantan had one of the highest proportions of households living in rental housing.

How many households are in the U.S.?

In 2023, there were 131.43 million households in the United States. This is a significant increase from 1960, when there were 52.8 million households in the U.S.

What counts as a household?

According to the U.S. Census Bureau, a household is considered to be all persons living within one housing unit. This includes apartments, houses, or single rooms, and consists of both related and unrelated people living together. For example, two roommates who share a living space but are not related would be considered a household in the eyes of the Census. It should be noted that group living quarters, such as college dorms, are not counted as households in the Census.

Household changes

While the population of the United States has been increasing, the average size of households in the U.S. has decreased since 1960. In 1960, there was an average of 3.33 people per household, but in 2023, this figure had decreased to 2.51 people per household. Additionally, two person households make up the majority of American households, followed closely by single-person households.

In 2024, approximately eight percent of Indonesian urban households lived in rented housing units, showing a significantly higher rate compared to households in rural areas. Among the other provinces in Indonesia, Jakarta had the highest proportion of households living in rental housing.

Data on census family status and presence of parent in household, age group and gender for the population aged 20 to 34 in private households, Canada, provinces and territories, census metropolitan areas and census agglomerations, 2021, 2016 and 2011 censuses.

This map compares the number of households living above the poverty line to the number of households living below. In the U.S. overall, there are 6.2 households living above the poverty line for every 1 household living below. Green areas on the map have a higher than normal number of households living above compared to below poverty. Orange areas on the map have a higher than normal number of households living below the poverty line compared to those above in that same area.In this map you see the ratio of households living above the poverty line to households living below the poverty line. For the U.S. overall, there are 6.2 households living above the poverty line for every household living below. This map is shaded to clearly show which areas have about the same ratio as the U.S. overall, and which areas have far more families living above poverty or far more families living below poverty than "normal.""The poverty rate is one of several socioeconomic indicators used by policy makers to evaluate economic conditions. It measures the percentage of people whose income fell below the poverty threshold. Federal and state governments use such estimates to allocate funds to local communities. Local communities use these estimates to identify the number of individuals or families eligible for various programs." Source: U.S. Census BureauThe map shows the ratio for states, counties, tracts and block groups, using data from the U.S. Census Bureau's American Community Survey (ACS) for 2013 for the previous 12 months. -------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.

In 2024, approximately **** percent of Indonesian households lived in rented housing units. Among the other provinces in Indonesia, Jakarta had the highest proportion of households living in rental housing.

Abstract

Niger is part of the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) program. This program has developed a household level survey with a view to enhancing our knowledge of agriculture in Sub-Saharan Africa, in particular, its role in poverty reduction and the techniques for promoting efficiency and innovation in this sector. To achieve this objective, an innovative model for agricultural data collection in this region will need to be developed and implemented. To this end, activities conducted in the future will be supported by four main pillars: a multisectoral framework, institutional integration, analytical capacity building, and active dissemination.

First, agricultural statistical data collection must be part of an expanded and multisectoral framework that goes beyond the rural area. This will facilitate generation of the data needed to formulate effective agricultural policies throughout Niger and in the broader framework of the rural economy.

Second, agricultural statistical data collection must be supported by a well-adapted institutional framework suited to fostering collaboration and the integration of data sources. By supporting a multi-pronged approach to data collection, this project seeks to foster intersectoral collaboration and overcome a number of the current institutional constraints.

Third, national capacity building needs to be strengthened in order to enhance the reliability of the data produced and strengthen the link between the producers and users of data. This entails having the capacity to analyze data and to produce appropriate public data sets in a timely manner. The lack of analytical expertise in developing countries perpetuates weak demand for statistical data.

Consequently, the foregoing has a negative impact on the quality and availability of policy-related analyses. Scant dissemination of statistics and available results has compounded this problem.

In all countries where the LSMS-ISA project will be executed, the process envisioned for data collection will be a national household survey, based on models of LSMS surveys to be conducted every three years for a panel of households. The sampling method to be adopted should ensure the quality of the data, taking into account the depth/complexity of the questionnaire and panel size, while ensuring that samples are representative.

The main objectives of the ECVMA are to:

• Gauge the progress made with achievement of the Millennium Development Goals (MDGs);
• Facilitate the updating of the social indicators used in formulating the policies aimed at improving the living conditions of the population;
• Provide data related to several areas that are important to Niger without conducting specific surveys on individual topics ;
• Provide data on several important areas for Niger that are not necessarily collected in other more specific surveys.

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The data entry was done in the field simultaneously with the data collection. Each data collection team included a data entry operator who key entered the data soon after it was collected. The data entry program was designed in CSPro, a data entry package developed by the US Census Bureau. This program allows three types of data checks: (1) range checks; (2) intra-record checks to verify inconsistencies pertinent to the particular module of the questionnaire; and (3) inter-record checks to determine inconsistencies between the different modules of the questionnaire.

The data as distributed represent the best effort to provide complete information. The data were collected and cleaned prior to the construction of the consumption aggregate. Using the same guidelines as were used in 2011, the households that are provided in the data set should have consumption data for both visits. This may not be the case. During the cleaning process, it was found that households had been misidentified which allowed more households to be included in the final consumption aggregate file (see below). The raw data that contains household/item level data that was used to calculate the consumption aggregate has been included in the distribution file.There are 3,614 households and 26,579 individuals in the data.

Abstract

The Household Living Conditions Survey 2012 provides information on poverty analysis in Ukraine. The results of the household survey are used in Ukraine for analyzing various issues, among which poverty, access to material benefits, subjective self-evaluation by households of their level of well-being are of special priority. The data obtained through this survey makes it possible to carry out methodologically comparative poverty studies using almost all above criteria.

The data can be used to analyze the following: - social-demographic characteristics of household members; - expenditures and consumption; - income and other resources, including those coming from subsidiary farming; - housing conditions; - availability of durable goods; - evaluation of health conditions and access to medical goods and services; - evaluation of well-being level and economic expectations; - access to certain goods and services; - access to information and communication technologies.

Geographic coverage

National, except some settlements within the territories suffered from the Chernobyl disaster.

Analysis unit

• Households,
• Individuals.

A household is a totality of persons who jointly live in the same residential facilities of part of those, satisfy all their essential needs, jointly keep the house, pool and spend all their money or portion of it. These persons may be relatives by blood, relatives by law or both, or have no kinship relations. A household may consist of one person (Law of Ukraine "On Ukraine National Census of Population," Article 1). As only 0.50% households have members with no kinship relations (0.65% total households if bachelors are excluded), the contemporary concepts "household" and "family" are very close.

Universe

Whole country, all private households. The survey does not cover collective households, foreigners temporarily living in Ukraine as well as the homeless.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey covers only private households. The sample does not include marginal population groups (individuals without permanent place of residence, etc.). Annual full rotation of respondents is used. Every five years survey territories are rotated. The territorial sampling excludes residential areas that are located in the exclusion and compulsory resettlement zone affected by radioactive contamination as a result of the Chernobyl nuclear power station accident. Sampling is done by stratified multistage probability sampling methods. The sampling methodology ensures that each household has a certain non-zero probability of being selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household living conditions survey includes three components and uses various survey tools to obtain information.

I. Collecting general data on a household - basic interview. Interviewing of households takes place at the survey commencement stage based on the adequate questionnaire program on general basic household features: household composition, housing facilities, availability and use of land plots, cattle and poultry, and also characteristics of household members: anthropometric data, education, employment status, etc. In addition, while interviewing, the interviewer completes a household composition check card to trace any changes during the entire survey period.

II. Observation of household expenditures and incomes over a quarter. For the observation, two survey tools are used: Weekly diary of current expenditures, which is completed directly by a household twice a quarter. In the diary respondents (households) record all daily expenditures in details (e.g. for purchased foodstuffs - product description, its weight and value, and place of purchase). In addition, a household puts into the diary information on consumption of products produced in private subsidiary farming or received as a gift.

Households are evenly distributed among rotation groups, who complete diaries in different week days of every quarter. Assuming that the two weeks data are intrinsic for the entire quarter, the single time period of data processing (quarter) is formed by means of multiplying diary data by ratio 6.5 (number of weeks in a quarter divided on the number of weeks when diary records were made). Inclusion of foodstuffs for long-time consumption is done based on quarterly interview data.

Quarterly questionnaire is used in quarterly interviewing of households in the first month following the reporting quarter. At this state, we collect data on large and irregular expenditures, in particular those relating to the purchase of foodstuffs for long-time consumption (e.g. sacks, etc.), and also data on household incomes. Since recalling all incomes and expenditures made in a quarter is uneasy, households make records during a quarter in a special 'Quarterly expenditures log'.

The major areas for quarterly observation are the following: - structure of consumer financial expenditures for goods and services; - structure of other expenditures (material aid to other households, expenditures for private subsidiary farming, purchase of real estate, construction and major repair of housing facilities and outbuildings, accumulating savings, etc); - importance of private subsidiary farming for household welfare level (receipt and use of products from private subsidiary farming for own consumption, financial income from sales of such products, etc.); - structure of income and other financial sources of a household. We separately study the income of every individual household member (remuneration of labor, pension, scholarship, welfare, etc.) and the income in form payments to a household as a whole (subsidies for children, aid of relatives and other persons, income from - sales of real estate and property, housing and utility subsidies, use of savings, etc.).

III. Single-time topical interviews Questionnaires are used for quarterly interviewing.

Quarterly topical interviews covered the following: - household expenditures for construction and repair of housing facilities and outbuilding; - availability in a household of durable goods; - assessment by households members of own health and accessibility of selected medical services; - self-assessment by a household of adequacy of its income; - a household's access to Internet.

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

As of 2022, nearly ** percent of Indonesian households owned the housing unit they lived in. The share of households living in a self-owned house in Indonesia has been relatively stable over the past years, but it saw an increase of almost ***** percent between 2021 and 2022.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_2c4e8a61d3e254ef0c672192b0731de0/view

This statistic shows the share of people living in a multigenerational household in the United States between 1950 and 2016. In 2016, one fifth of Americans were living in a multigenerational household, which rose from only 12 percent in 1980.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_c3ff583aee7ef30f01872e35c2c87b8e/view

Abstract

The purpose of the Household Income and Expenditure Survey (HIES) survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in 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

Abstract

The EICV4 survey (Enquête Intégrale sur les Conditions de Vie des ménages) was conducted over a 12-month cycle from October 2013 to October 2014. Data collection was divided into 10 cycles in order to represent seasonality in the income and consumption data. A main cross-sectional sample survey, a panel survey and a VUP sample survey were conducted simultaneously.

The EICV4 provides information on poverty and living conditions in Rwanda and measures changes over time as part of the on-going monitoring of the Poverty Reduction Strategy and other Government policies. The survey data are also very important for national accounts and updating the consumer price index (CPI).

Geographic coverage

National coverage

Analysis unit

Households

Universe

All household members (variable s1q15 identifies household membership).

Kind of data

Sample survey data [ssd]

Sampling procedure

The EICV4 cross sectional (CS) sample includes two independent subsets selected using different sampling frames: 1) a new EICV4 sample of households in enumeration areas (EAs) selected using the 2012 Rwanda Population and Housing Census frame and 2) a panel of households selected from 177 EICV3 villages. A new listing of households was conducted in both the panel and new sample clusters in order to update the frame for the CS Survey. The sample households in the new CS sample EAs were selected from the new listing.

1) The new EICV4 sample The main sampling frame for the EICV4 is based on the 2012 Rwanda Census. The primary sampling units (PSUs) are the 2012 census Enumeration Areas (EAs). In the Census, each EA was classified as urban, semi-urban, peri-urban or rural. The urban areas include Kigali-Ville and the district capitals. The semi-urban areas generally correspond to smaller towns that have service facilities and markets. The peri-urban areas currently have the characteristics of rural areas, but they are located on the periphery of urban areas and are designated for future development. For the EICV4 sampling frame, the semi-urban areas were grouped with the urban strata, and the peri-urban areas with the rural strata. This results in a final distribution of 17.2% urban households and 82.8% rural households in the sampling frame. EAs in the 177 EICV3 sample villages selected for the panel study were excluded from the sampling frame, in order to avoid any overlap between the two samples.

The new EICV4 sample of 12,312 households was selected using a stratified two-stage design. At the first stage, sample EAs were selected within each stratum (district) with probability proportional to size (PPS) from the ordered list of EAs in the sampling frame. The EAs are implicitly stratified by urban and rural strata within each district, ordered first by urban, semi-urban, peri-urban and rural areas, and then geographically by sector, cellule, village and EA codes. This first stage sampling procedure provides a proportional allocation of the sample to the urban and rural areas of each district. At the second stage, households in each sample EA are selected from the listing. For the three districts in Kigali Province, 9 households were selected in each sample EA as original households; for the remaining 27 districts, 12 households were selected in each sample EA as original households. In addition, a reserve sample of 3 replacement households were selected for each sample EA in Kigali Province and 4 replacement households for each sample EA in the remaining provinces.

This new EICV4 sample contains 12,312 households, including 12,233 original households and 79 replacement households.

2) Households from 177 EICV3 villages used for panel study The second component of the EICV4 cross sectional sample consists of all the sample households interviewed inside the 177 EICV3 villages selected for the panel study (including any replacements households and panel split households inside the clusters). Within each of the 177 villages, all households that were interviewed during EICV3 were included in the cross-sectional sample. When an EICV3 sample household moved and a new household occupied the same house in the cluster, it was interviewed for the Cross-Sectional Survey, and assigned a PID (dependency) code of 94. If an EICV3 household was empty or not found, a random replacement household was selected for the EICV4 Cross-Sectional Survey from the new listing of the sample cluster, and assigned a PID code of 95. The sample households with PID codes 94 and 95 are only used for the cross-sectional study, not the panel study.

This second component of the cross-sectional sample includes 2108 households drawn from the 177 EICV3 villages sampled for the panel study. These include 1604 original EICV3 households, 181 dependent household splitting from the original household in the same cluster, along with 243 households living in the dwelling formerly occupied by a panel household and 80 replacement households in the cluster in order to have 9/12 households per cluster.

The reason why we combine the EICV4 data from the new and panel clusters for the CS analysis is to obtain the most accurate CS estimates. In the case of the CS estimates from the combined samples, the additional data from the 177 sample panel clusters will result in a significant reduction in the variance component of the MSE. Although the bias of the CS data from the sample panel clusters may slightly increase the bias component, this bias is very small compared to the corresponding reduction in the variance component. Therefore, the CS results from the EICV4 data for the combined new and panel clusters can be considered more accurate than the corresponding results using only the EICV4 data for the new sample clusters.

In total, the final EICV4 cross-sectional sample contains 14,419 households.

3) Assignment of EAs to cycles and sub-cycles Data collection covering a period of 12 month is divided into 10 cycles to represent seasonality in consumption, income, employment and agricultural activity patterns. For rural enumeration, each cycle is further divided into two sub-cycles. For the 177 EICV3 villages, the cycle and sub-cycle were pre-determined. Households were re-interviewed in the same cycle, corresponding to the same time of the year as they were in EICV3. To assign cycles to the new EICV4 sample EAs, random cycle numbers from 1 to 10 were generated to identify the selection sequence. For the 27 districts outside Kigali, sub-cycle numbers of 1 or 2 were assigned systematically with a random start. This process ensured that the final distribution of the sample EAs to cycles and sub-cycles was geographically representative within each district.

Mode of data collection

Face-to-face [f2f]

Research instrument

The same questionnaire was used for cross-sectional, panel and VUP samples. Part A of the questionnaire contains modules on household and individual information. Part B is on agriculture and consumption. The questionnaire was developed in English, and translated into Kinyarwanda.

Questionnaire design took into account the requests raised by major data users and stakeholders, as well as consistency with the previous EICV questionnaires. In addition to methodological improvements, some simplifications were made:

-The major changes introduced in this survey were changes to Section 6, the Economic Activity. Further questioning was added on unemployment and underemployment in response to questions from users, and also to comply with international standards. The section was simplified to enable the analysis to be undertaken by local analysts.

-The Section on the VUP participation was expanded to provide more information, better classification of beneficiaries and to provide greater consistency within the questionnaire. The same questionnaire is to be used on the separate VUP sample which runs in parallel with the EICV4

-The health section was reduced to try to cut respondent burden, as health-related information is being collected by Demographic and Health Surveys (DHS).

-The expenditure section was changed in minor ways to provide better information for national accounts (housing investment) and for CPI weights (retail outlets).

Questionnaire was tested in pilot surveys and amended in time prior to the fieldwork starting in October 2013. The complete questionnaire is provided as external resources.

Cleaning operations

A day before the interview started, the enumerator, accompanied by a controller, did an introduction to household, explaining how often they will come in that household and delivering a letter indicating that the HH has been selected.

During the field work, after each cycle, the data processing team produced tables and reports of inconsistencies, which were checked by the field supervisor. The data entry system also contained consistency checks that alerted the data entry operators. In case of an alert, the questionnaire was sent back to the supervisor of data entry for correction.

Response rate

Out of the 12,312 sample households selected in the new sample clusters for EICV4, only 79 were non-interviews, for a response rate of 99.4% for this sample. All of the 79 non-interviews were replaced. There were only 12 refusals, and there were few cases of houses that were empty or not found, given that the listing was conducted very close to the interviewing period.