This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2020 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2020. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include: City - Large (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more. City - Midsize (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000. City - Small (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000. Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more. Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000. Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000. Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area. Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area. Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area. Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster. Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster. Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

Use this application to identify locale classifications for public, private, and postsecondary schools.What are locales? Locales are general geographic indicators that reflect the type of community where a school is located. NCES creates and uses the indicators for a variety of statistical purposes, and some educational programs use them to identify schools in specific types of areas.The locale data layer used in the Locale Lookup was produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program. The data provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2016 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2016. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, and rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:City - Large (11): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population of 250,000 or more.City - Midsize (12): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.City - Small (13): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urban Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urban Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urban Area with population less than 100,000. Town - Fringe (31): Territory inside an Urban Area with a population less than 50,000 that is less than or equal to 10 miles from an Urban Area with a population of 50,000 or more.Town - Distant (32): Territory inside an Urban Area with a population less than 50,000 that is more than 10 miles and less than or equal to 35 miles from an Urban Area with a population of 50,000 or more.Town - Remote (33): Territory inside an Urban Area with a population less than 50,000 that is more than 35 miles of an Urban Area with a population of 50,000 or more.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urban Area of 50,000 or more, as well as rural territory that is less than or equal to 2.5 miles from an Urban Area with a population less than 50,000.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urban Area with a population of 50,000 or more, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Area with a population less than 50,000.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urban Area with a population of 50,000 or more and is also more than 10 miles from an Urban Area with a population less than 50,000.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2014 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2014. The NCES EDGE program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.All information contained in this file is in the public _domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

Cambodia Education: Rural: Post-Secondary Education data was reported at 2.200 % in 2021. This stayed constant from the previous number of 2.200 % for 2020. Cambodia Education: Rural: Post-Secondary Education data is updated yearly, averaging 2.200 % from Jun 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 2.200 % in 2021 and a record low of 2.200 % in 2021. Cambodia Education: Rural: Post-Secondary Education data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Cambodia – Table KH.G014: Education Statistics.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

Nationally, many school districts are facing a teacher workforce sustainability crisis, and job retention for novice teachers of color represents a key area of focus for educational leaders and policymakers. In this study, we draw on nine years of administrative data from Texas K-12 public schools to better understand how teacher-principal ethnoracial matching is associated with patterns of teacher retention and system-exit. Teacher labor markets are geographically small, so we link data from the National Center for Education Statistics containing geographic locale information to explore how the relationship between ethnoracial matching and novice teacher career outcomes varies across urban, suburban, rural, and town school contexts. We find that matching is associated with an increase in the probability of retention and a decrease in the probability of system-exit, with important variation for novice Black and Latinx teachers working in some non-urban school locales.

Cambodia Education: Rural: Primary School Not Completed data was reported at 42.400 % in 2021. This records an increase from the previous number of 40.800 % for 2020. Cambodia Education: Rural: Primary School Not Completed data is updated yearly, averaging 41.600 % from Jun 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 42.400 % in 2021 and a record low of 40.800 % in 2020. Cambodia Education: Rural: Primary School Not Completed data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Cambodia – Table KH.G014: Education Statistics.

Cambodia Education: Rural: None or Only Some Education data was reported at 19.400 % in 2021. This records a decrease from the previous number of 23.600 % for 2020. Cambodia Education: Rural: None or Only Some Education data is updated yearly, averaging 21.500 % from Jun 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 23.600 % in 2020 and a record low of 19.400 % in 2021. Cambodia Education: Rural: None or Only Some Education data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Cambodia – Table KH.G014: Education Statistics.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS - TUNISIA (INS)

The National Survey on Household Budget, Consumption, and Standard of Living, 2005 is a quinquennial survey. It is the eighth survey of its kind that was carried out by the National Institute of Statistics (INS) in Tunisia. The seven previous surveys were conducted in 1968, 1975, 1980, 1985, 1990, 1995 and 2000, concurrently with the preparatory work for the Tunisian development plans. The 2005 survey was conducted as part of the preparation work for the Tenth Development Plan (2007-2011). Its expected findings would allow assessing the progress made in the improvements of the living level & conditions of the population.

The survey aims at providing detailed information on the procurement of goods and services for consumption (food consumption as well as household access to community services of health and education). And its data was collected from direct observation of household consumption to allow for having the necessary elements to assess the situation & changes in the living standards & conditions of the households.

Thus, the 2005 survey tackles three major areas of study: 1 - Household expenditure and acquisitions during the survey period 2 - Food consumption and nutritional status of households. 3 - Household access to community services of health and education.

The objectives of the survey are: a- Identifying levels of expenditure on the household level: The survey aims to assess the levels of household expenditure .The total expenditure of the household, is not only an indicator of income, but it is also a quantitative assessment of the standard of living index.

b- Income distribution: Due to the absence of data on income distribution, the mass distribution of expenditure between the different categories of the population constitutes a first outline for the income distribution in the country.

c- Investigating the structure of expenditure: Detailed information collected on expenditures per product used to establish the structures of the household expenditure as well as the budget coefficients according to different levels of classifications of goods in the nomenclature of goods and services. These factors coefficients are particularly useful for revision and development of the weights of the Consumer Prices Index (CPI). It should also be noted that the change in expenditure structure is an indicator of the evolution of living standards.

d- Analysis of household demand: Household behavior in terms of product demand is synthesized by the coefficients of income elasticity which, according to the model of consumption retained and under the assumptions of the growth of income and population, allows predicting future household demand.

e- Resources-use balance in the national accounts: The results related to the consumption by product are necessary elements for the development of balanced resource-use of products in the frame of national accounts.

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

Geographic coverage

Covering a sample of all urban, small and medium towns and rural areas.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS - TUNISIA (INS)

Sampling method

The National Survey on Household Budget, Consumption and Standard of Living, 2005 has focused initially on a sample of 13,392 households representing 0.61% of total households in the country (61 surveyed household for every 10,000 household) . This sample is distributed across 1116 districts covering all the country governorates, cities, urban and rural areas. The sample was also equally divided on the months of the survey year to take the seasonal changes in household expenditure into account.

These households were drawn using a two stages stratified random sampling in each governorate. The sampling frame follows that of the general Census of Population and Housing in 2004.

Stratification criteria: The sampling frame is stratified by two geographical criteria: namely the governorate and the living area. The latter is stratified as follows: large municipalities, medium and small towns, major cities and the rest of the non-municipal areas. These stratification criteria (governorate, habitat and size of municipalities) represent the differentiation variable of lifestyles households. Strata used are as follows:

Stratum of large cities (stratum 1): the municipalities of the city of Tunis and its suburbs, the city of Bizerte and its suburbs, the city of Sousse and its suburbs, the city of Kairouan and its suburbs, the city Sfax and its suburbs, and the general Gabes. Thus, this stratum is formed of large urban centers corresponding to municipalities with more than 100.000 inhabitants and neighboring municipalities.

Stratum of other cities (stratum 2): This is all small and medium sized cities other than those classified in the stratum of large cities.

Stratum of the main cities (stratum 3): These are non-municipal urban areas classified as major cities during the general census of population and housing 2004 (with a population of more than 70 households).a city is considered a main city if the number of its inhabitants exceeds 400 during the census of 2004.

Stratum dispersed outside communes (stratum 4): These are areas of land located outside the main towns and cities. Households in these areas live in houses scattered or grouped in small towns.

This strata classification is closely related to the levels of household income and lifestyle.

Survey type:

The sampling frame is divided on the level of each governorate according to strata previously defined. It was set, at the level of each stratum, to make a two-stage random sampling for the selection of the household survey sample. This drawing process allows to breakdown the sample into clusters of 12 households relatively little distant from each other, thereby facilitating the conduct of the survey at the time of the information collection in the field

In the first stage: a sample of primary units is drawn in proportion to their size in number of households as they were identified. Taking into consideration that the primary units correspond to the districts that have been defined in the census of the population and these geographic areas contain on average 70 households.

In the second stage: in each sampled district, 12 households are selected according to the following method: The households in each sampled district are classified primarily according to the number of employed persons in the household. Within each category of classified households, households are also classified according to the number of persons in each household. A systematic sampling is then performed to select 12 sampled households per primary unit (sampled district). For each sampled district, another 12 households are drawn according to the same previously illustrated criteria. These households serve as a substitutive sample so that in case the interviewer failed to get in contact with the originally selected household (due to long absence- change of place of residence) , after coordinating with the supervisor, this household can be replaced by one from the substitutive sample. For this purpose, two lists of the names of head of households were developed (original list, substitutive list) that the survey is supposed to cover.

Distribution of districts and households sampled by governorates

Cambodia Education: Rural: Lower Secondary Completed data was reported at 8.600 % in 2021. This stayed constant from the previous number of 8.600 % for 2020. Cambodia Education: Rural: Lower Secondary Completed data is updated yearly, averaging 8.600 % from Jun 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 8.600 % in 2021 and a record low of 8.600 % in 2021. Cambodia Education: Rural: Lower Secondary Completed data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Cambodia – Table KH.G014: Education Statistics.

Abstract

The Tajik Living Standards Survey (TLSS) was conducted jointly by the State Statistical Agency and the Center for Strategic Studies under the Office of the President in collaboration with the sponsors, the United Nations Development Programme (UNDP) and the World Bank (WB). International technical assistance was provided by a team from the London School of Economics (LSE). The purpose of the survey is to provide quantitative data at the individual, household and community level that will facilitate purposeful policy design on issues of welfare and living standards of the population of the Republic of Tajikistan in 1999.

Geographic coverage

National coverage. The TLSS sample was designed to represent the population of the country as a whole as well as the strata. The sample was stratified by oblast and by urban and rural areas.

The country is divided into 4 oblasts, or regions; Leninabad in the northwest of the country, Khatlon in the southwest, Rayons of Republican Subordination (RRS) in the middle and to the west of the country, and Gorno-Badakhshan Autonomous Oblast (GBAO) in the east. The capital, Dushanbe, in the RRS oblast, is a separately administrated area. Oblasts are divided into rayons (districts). Rayons are further subdivided into Mahallas (committees) in urban areas, and Jamoats (villages) in rural areas.

Analysis unit

• Households
• Individuals
• Communites

Kind of data

Sample survey data [ssd]

Sampling procedure

The TLSS sample was designed to represent the population of the country as a whole as well as the strata. The sample was stratified by oblast and by urban and rural areas.

In common with standard LSMS practice a two-stage sample was used. In the first stage 125 primary sample units (PSU) were selected with the probability of selection within strata being proportional to size. At the second stage, 16 households were selected within each PSU, with each household in the area having the same probability of being chosen. [Note: In addition to the main sample, the TLSS also included a secondary sample of 15 extra PSU (containing 400 households) in Dangara and Varzob. Data in the oversampled areas were collected for the sole purpose of providing baseline data for the World Bank Health Project in these areas. The sampling for these additional units was carried out separately after the main sampling procedure in order to allow for their exclusion in nationally representative analysis.] The twostage procedure has the advantage that it provides a self-weighted sample. It also simplified the fieldwork operation as a one-field team could be assigned to cover a number of PSU.

A critical problem in the sample selection with Tajikistan was the absence of an up to date national sample frame from which to select the PSU. As a result lists of the towns, rayons and jamoats (villages) within rayons were prepared manually. Current data on population size according to village and town registers was then supplied to the regional offices of Goskomstat and conveyed to the center. This allowed the construction of a sample frame of enumeration units by sample size from which to draw the PSU.

This procedure worked well in establishing a sample frame for the rural population. However administrative units in some of the larger towns and in the cities of Dushanbe, Khojand and Kurgan-Tubbe were too large and had to be sub-divided into smaller enumeration units. Fortuitously the survey team was able to make use of information available as a result of the mapping exercise carried out earlier in the year as preparation for the 2000 Census in order to subdivide these larger areas into enumeration units of roughly similar size.

The survey team was also able to use the household listings prepared for the Census for the second stage of the sampling in urban areas. In rural areas the selection of households was made using the village registers – a complete listing of all households in the village which is (purported to be) regularly updated by the local administration. When selecting the target households a few extra households (4 in addition to the 16) were also randomly selected and were to be used if replacements were needed. In actuality non-response and refusals from households were very rare and use of replacement households was low. There was never the case that the refusal rate was so high that there were not enough households on the reserve list and this enabled a full sample of 2000 randomly selected households to be interviewed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was based on the standard LSMS for the CIS countries, and adapted and abridged for Tajikistan. In particular the health section was extended to allow for more in depth information to be collected and a section on food security was also added. The employment section was reduced and excludes information on searching for employment.

The questionnaires were translated into Tajik, Russian and Uzbek.

The TLSS consists of three parts: a household questionnaire, a community level questionnaire and a price questionnaire.

Household questionnaire: the Household questionnaire is comprised of 10 sections covering both household and individual aspects.

Community/Population point Questionnaire: the Community level or Population Point Questionnaire consists of 8 sections. The community level questionnaire provides information on differences in demographic and economic infrastructure. Open-ended questions in the questionnaire were not coded and hence information on the responses to these qualitative questions is not provided in the data sets.

Summary of Section contents

The brief descriptions below provide a summary of the information found in each section. The descriptions are by no means exhaustive of the information covered by the survey and users of the survey need to refer to each particular section of the questionnaire for a complete picture of the information gathered.

Household information/roster This includes individual level information of all individuals in the household. It establishes who belongs to the household at the time of the interview. Information on gender, age, relation to household head and marital status are included. In the question relating to family status, question 7, “Nekared” means married where nekar is the Islamic (arabic) term for marriage contract. Under Islamic law a man may marry more than once (up-to four wives at any one time). Although during the Soviet period it was illegal to be married to more than one woman this practice did go on. There may be households where the household head is not present but the wife is married or nekared, or in the same household a respondent may answer married and another nekared to the household head.

Dwelling This section includes information covering the type of dwelling, availability of utilities and water supply as well as questions pertaining to dwelling expenses, rents, and the payment of utilities and other household expenses. Information is at the household level.

Education This section includes all individuals aged 7 years and older and looks at educational attainment of individuals and reasons for not continuing education for those who are not currently studying. Questions related to educational expenditures at the household level are also covered. Schooling in Tajikistan is compulsory for grades (classes) 1-9. Primary level education refers to grades 1 - 4 for children aged 7 to 11 years old. General secondary level education refers to grades 5-9, corresponding to the age group 12-16 year olds. Post-compulsory schooling can be divided into three types of school: - Upper secondary education covers the grades 10 and 11. - Vocational and Technical schools can start after grade 9 and last around 4 years. These schools can also start after grade 11 and then last only two years. Technical institutions provide medical and technical (e.g. engineering) education as well as in the field of the arts while vocational schools provide training for employment in specialized occupation. - Tertiary or University education can be entered after completing all 11 grades. - Kindergarten schools offer pre-compulsory education for children aged 3 – 6 years old and information on this type of schooling is not covered in this section.

Health This section examines individual health status and the nature of any illness over the recent months. Additional questions relate to more detailed information on the use of health care services and hospitals, including expenses incurred due to ill health. Section 4B includes a few terms, abbreviations and acronyms that need further clarification. A feldscher is an assistant to a physician. Mediniski dom or FAPs are clinics staffed by physical assistants and/or midwifes and a SUB is a local clinic. CRH is a local hospital while an oblast hospital is a regional hospital based in the oblast administrative centre, and the Repub. Hospital is a national hospital based in the capital, Dushanbe. The latter two are both public hospitals.

Employment This section covers individuals aged 11 years and over. The first part of this section looks at the different activities in which individuals are involved in order to determine if a person is engaged in an income generating activity. Those who are engaged in such activities are required to answer questions in Part B. This part relates to the nature of the work and the organization the individual is attached to as well as questions relating to income, cash income and in-kind payments. There are also a few questions relating to additional income generating activities in addition to the main activity. Part C examines employment

Abstract

The CSES is a household survey with questions to households and the household members. In the household questionnaire there are a number of modules with questions relating to the living conditions, e.g. housing conditions, education, health, expenditure/income and labour force. It is designed to provide information on social and economic conditions of households for policy studies on poverty, household production and final consumption for the National Accounts and weights for the CPI.

The main objective of the survey is to collect statistical information about living standards of the population and the extent of poverty. Essential areas as household production and cash income, household level and structure of consumption including poverty and nutrition, education and access to schooling, health and access to medical care, transport and communication, housing and amenities and family and social relations. For recording expenditure, consumption and income the Diary Method was applied for the first time. The survey also included a Time Use Form detailing activities of household members during a 24-hour period.

Another main objective of the survey is also to collect accurate statistical information about living standards of the population and the extent of poverty as an essential instrument to assist the government in diagnosing the problems and designing effective policies for reducing poverty, and in evaluating the progress of poverty reduction which are the main priorities in the "Rectangular Strategy" of the Royal Government of Cambodia.

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

In this section the sampling design and the sample selection for CSES 2009, is described. The sampling design for the 2009 survey is the same as that used for the CSES 2004. The sampling design for the 2004 CSES is described in for instance National Institute of Statistics (2005a). The sampling frame for the 2009 survey is based on preliminary data from the General Population Census conducted in 2008. The sample is selected as a three stage cluster sample with villages in the first stage, enumeration areas in the second stage and households in the third.

The Sampling Frame Preliminary data from the General Population Census 2008 was used to construct the sampling frame for the first stage sampling, i.e. sampling of villages. All villages except 'special settlements' were included in the frame. In all, the first stage sampling frame of villages consisted of 14,073 villages, see Appendix 1. Compared to previous years the frame used for the 2009 survey based on the census 2008 was more up to date than in previous surveys which were based on the population census 1998. The following variables were used from the census; Province code, province name, district code, district name, commune code, commune name, village code, village name, urban-rural classification of villages, the number of households per village and, the number of enumeration areas in the village. In the second-stage Enumeration Areas (EA) are selected in each selected village. In most villages only one EA was selected but in some large villages more than one was selected. For the third stage, the sampling of households, a frame was constructed in field. For selected EAs the census map of the village, including EAs and residences, was given to enumerator who updated the map and listed the households in the selected EA. A sample of households was then selected from the list.

Stratification The sampling frame of villages was stratified by province and urban and rural. There are 24 provinces and each village is classified as either urban or rural which means that in total we have 48 strata, see Appendix 1. Each stratum of villages was sorted by district, commune and village code.

Sampling The sampling design in the CSES 2009 survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two. The sampling designs used in the three stages were: Stage 1. A systematic pps sample of villages, Primary Sampling Units (PSUs) was selected from each stratum, i.e. without replacement systematic sampling with probabilities proportional to size. The size measure used was the number of households in the village according to the sampling frame. Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1. As mentioned above, in a few large villages more than one EA was selected. Stage 3. In each selected EA a sample of households was selected by systematic sampling. The selection of villages and EAs were done at NIS while the selection of households in stage three was done in field. As mentioned in section 1.1 all households in selected EAs were listed by the enumerator. The sample of households was then selected from the list.

Sample sizes and allocation The sample size of PSUs, were, as in the 2004 survey, 720 villages (or EAs). In urban villages 10 households were selected and in rural 20 households. In all 12,000 households were selected. Urban and rural villages were treated separately in the allocation. The allocation was done in two steps. First the sample sizes for urban and rural villages in the frame were determined and then sample sizes for the provinces within urban and rural areas were determined, i.e. the strata sample sizes. The total sample size was divided into to two, one sample size for urban villages and the other for rural villages. The calculation of the sample sizes for urban and rural areas were done using the proportion of consumption in the two parts of the population. Data on consumption from the CSES 2007 survey was used. The resulting sample sizes for urban villages was 240 and for rural 480. (Some adjustments of the calculated sample sizes were done, resulting in the numbers 240 and 480). Allocation of the total sample size on the strata within urban and rural areas respectively, was done in the following way. The sample size, i.e. the number of PSUs, villages, selected from stratum h, is proportional to the number of households in stratum h, i.e.

n(Ih)=n1(Mh/Sum of Mh) (1.1) where, is the sample size in stratum h, i.e. the number villages selected in stratum h,

is the total sample size of villages for urban or rural villages,

H is the number of strata in urban or rural areas,

is the number of households in stratum h according to the frame.

As mentioned above, the sample size calculations are done separately for urban and rural villages, i.e. for strata with urban villages (1.1) is used with nI = 240 and is the number of households in urban villages in the frame and for rural villages (1.1) is used with nI = 480 and is the number of households in rural villages in the frame.

Monthly samples In section 1.3 the selection of the annual sample was described. The annual sample was divided into 12 monthly samples of equal sizes. The monthly samples consisted of 20 urban and 40 rural villages. The division of the annual sample into monthly samples was done so that as far as possible each province would be represented in each monthly sample. Since the sample size of villages in some provinces is smaller than 12, all provinces were not included in all monthly samples. Also, the outline of the fieldwork with teams of 4 enumerators and one supervisor puts constraints on how to divide the annual sample into monthly samples. The supervisors must travel between the villages in a team and therefore the geographical distance between the villages surveyed by a team cannot be too large.

Estimation Totals, ratios such as means or proportions were estimated for the population or for subgroups of population, i.e. domains of study. The domains were defined by e.g. region or sex. Means and proportions were estimated by first estimating totals and then calculating the ratio of two estimated totals. To estimate totals from a sample survey weights are needed.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four different questionnaires or forms were used in the survey: 1. Household listing form The Household listing and mapping were done prior to the sampling. During the household listing the enumerator recorded household information on e.g. location, number of members and principal economic activity.

1. Village questionnaire The Village questionnaire was used to gather basic common information on demographic information, economy and infrastructure, rainfall and natural disasters, education, health, retail prices, employment and wages, access to common prices of resources, sale of agricultural land, and recruitment of children for work.

2. Household questionnaire The following modules were included in the Household questionnaire:

3. Initial visit

4. Education & Literacy

5. Information on migration (includes past and current migration)

6. Housing

7. Household economic activities

8. Household liabilities

9. Household income from other sources

10. Construction activities

11. Durable goods

12. Maternal health (Last pregnancy and delivery)

13. Child health (youngest child and all children under 2)

14. Health check of children under 5

15. Health care seeking and expenditure

16. Disability

17. Current economic activities (activity status during the past seven days)

18. Usual economic activity (activity in the past 12 months)

19. Victimization

20. Summary of presence in the household

21. The Diary sheet (diary method) a. Diary for expenditure & consumption of own-production b. Diary for

Abstract

After 2002 political crisis, Madagascar President Marc Ravalomanana began many reform projects. To mitigate the effects of the aftermath of the political crisis, the new government used part of the Heavily Indebted Poor Countries Initiative (HIPC) funds to pay for the tuition fee of all students in the public primary schools.

There was no representative overview of the financing of local schools at the national level in Madagascar. Given the emphasis on good governance by the new administration and the new approach towards lending that donors were planning to implement, more information about channeling of resources to the expected beneficiaries was necessary.

Based on a representative sample of schools at the national level, the main goal of this study was to provide detailed information on expenditure allocations and leakages in the Madagascar education system.

From April to May 2003, researchers visited schools and district education offices (Cisco) to gather data about funds that should arrive and do arrive at district and local facility levels.

Overall, 185 public primary schools and 24 Cisco's were surveyed in all six Madagascar provinces.

Geographic coverage

Antananarivo, Fianarantsoa, Toamasina, Mahajanga, Toliara and Antsiranana provinces.

Analysis unit

• Cisco (Circonscription Scolaire/District Education Facility);
• Primary Schools.

Kind of data

Sample survey data [ssd]

Sampling procedure

The school survey sample included a little over half of the schools visited in the post-crisis survey, conducted by Cornell University, Madagascar's National Statistical Institute and National Agricultural Research Center in November-December 2002.

The post-crisis survey covered 150 Communes. For that survey, the stratified sampling frame was set up to be representative of the situation at the national and provincial levels. Districts (Fivondronana) were divided into six strata depending on the distance to the capital of the province (close, medium, far) and on the availability of a tarred road. In each stratum, one district was selected for every province. In each district (36 out of 111 in total), four Communes were randomly selected. In each Commune, two public primary schools were surveyed: one in the center of the Commune and one remote school that was at least 3 km away from the center. Given the size of the population in cities, these were treated differently. In Antananarivo, 12 public primary schools were surveyed. In the provincial capitals, this number was reduced to six public primary schools. 326 schools were visited in total. 15% and 85% of the schools were located in urban and rural areas respectively.

During PETS-QSDS 2003, 185 public primary schools were surveyed. 73% of schools were located in rural areas. Four districts (Fivondronana) and 13 Communes were visited in each province.

For the district survey, representatives of 24 Cisco's (more than 20% of the district offices in the country) were interviewed. Four Cisco's were visited in each province.

Mode of data collection

Face-to-face [f2f]

Abstract

Malawi Conditional Cash Transfer Program (CCT) is a randomized cash transfer intervention targeting young women in Zomba region. The program provides incentives to current schoolgirls and recent dropouts to stay in or return to school. The incentives include average payment of US$10 a month conditional on satisfactory school attendance and direct payment of secondary school fees.

The CCT program started at the beginning of the Malawian school year in January 2008 and continued until November 2009. The impact evaluation study was designed to evaluate the impact of the program on various demographic and health outcomes of its target population, such as nutritional health, sexual behavior, fertility, and subsequent HIV risk.

Baseline data collection was administered from September 2007 to January 2008. The research targeted girls and young women, between the ages of 13 and 22, who were never married. Overall, 3,810 girls and young women were surveyed in the first round. The follow-up survey was carried out from October 2008 to February 2009. The third round was conducted between March and September 2010, after Malawi Conditional Cash Transfer Program was completed. The fourth round started in April 2012 and will continue until September 2012.

Datasets from the baseline round are documented here.

Enumeration Areas (EAs) in the study district of Zomba were selected from the universe of EAs produced by the National Statistics Office of Malawi from the 1998 Census. 176 enumeration areas were randomly sampled out of a total of 550 EAs using three strata: urban areas, rural areas near Zomba Town, and rural areas far from Zomba Town.

Baseline schoolgirls in treatment enumeration areas were randomly assigned to receive either conditional or unconditional transfers, or no transfers at all. A multi-topic questionnaire was administered to the heads of households, where the selected sample respondents resided, as well as to girls and young women.

Geographic coverage

Zomba district.

Zomba district in the Southern region was chosen as the site for this study for several reasons. First, it has a large enough population within a small enough geographic area rendering field work logistics easier and keeping transport costs lower. Zomba is a highly populated district, but distances from the district capital (Zomba Town) are relatively small. Second, characteristic of Southern Malawi, Zomba has a high rate of school dropouts and low educational attainment. Third, unlike many other districts, Zomba has the advantage of having a true urban center as well as rural areas. As the study sample was stratified to get representative samples from urban areas (Zomba town), rural areas near Zomba town, and distant rural areas in the district, we can analyze the heterogeneity of the impacts by urban/rural areas. Finally, while Southern Malawi, which includes Zomba, is poorer, has lower levels of education, and higher rates of HIV than Central and Northern Malawi, these differences are relative considering that Malawi is one of the poorest countries in the world with one of the highest rates of HIV prevalence.

Analysis unit

• Households;
• Girls and young women.

Universe

The survey covers never married girls and young women between the ages of 13 and 22 in Zomba district.

Kind of data

Sample survey data [ssd]

Sampling procedure

First, 176 enumeration areas (EA) were randomly sampled out of a total of 550 EAs using three strata in the study district of Zomba. Each of these 176 EAs were then randomly assigned treatment or control status. The three strata are urban, rural areas near Zomba Town, and rural areas far from Zomba Town. Rural areas were defined as being near if they were within a 16-kilometer radius of Zomba Town. Researchers did not sample any EAs in TA Mbiza due to safety concerns (112 EAs).

Enumeration areas (EAs) in Zomba were selected from the universe of EAs produced by the National Statistics Office of Malawi from the 1998 Census. The sample of EAs was stratified by distance to the nearest township or trading centre. Of the 550 EAs in Zomba, 50 are in Zomba town and an additional 30 are classified as urban (township or trading center), while the remaining 470 are rural (population areas, or PAs). The stratified random sample of 176 EAs consisted of 29 EAs in Zomba town, eight trading centers in Zomba rural, 111 population areas within 16 kilometers of Zomba town, and 28 EAs more than 16 kilometers from Zomba town.

After selecting sample EAs, all households were listed in the 176 sample EAs using a short two-stage listing procedure. The first form, Form A, asked each household the following question: "Are there any never-married girls in this household who are between the ages of 13 and 22?" This form allowed the field teams to quickly identify households with members fitting into the sampling frame, thus significantly reducing the costs of listing. If the answer received on Form A was a "yes", then Form B was filled to list members of the household to collect data on age, marital status, current schooling status, etc.

From this researchers could categorize the target population into two main groups: those who were out of school at baseline (baseline dropouts) and those who were in school at baseline (baseline schoolgirls). These two groups comprise the basis of our sampling frame. In each EA, enumerators sampled all eligible dropouts and 75%-100% of all eligible school girls, where the percentage depended on the age of the baseline schoolgirl. This sampling procedure led to a total sample size of 3,810 (in the first round, and 3,805 in follow-up rounds) with an average of 5.1 dropouts and 16.7 schoolgirls per EA.

Mode of data collection

Face-to-face [f2f]

Research instrument

The annual household survey consists of a multi-topic questionnaire administered to the households in which the selected sample respondents reside. The survey consists of two parts: one that is administered to the head of the household and another that is administered to the core respondent - the sampled girl from the target population. The former collects information on the household roster, dwelling characteristics, household assets and durables, shocks and consumption. The core respondent survey provides information about her family background, her education and labor market participation, her health, her dating patterns, sexual behavior, marital expectations, knowledge of HIV/AIDS, her social networks, as well as her own consumption of girl-specific goods (such as soaps, mobile phone airtime, clothing, braids, sodas and alcoholic drinks, etc.).

教育：农村：小学肄业在06-01-2021达42.400%，相较于06-01-2020的40.800%有所增长。教育：农村：小学肄业数据按年更新，06-01-2020至06-01-2021期间平均值为41.600%，共2份观测结果。该数据的历史最高值出现于06-01-2021，达42.400%，而历史最低值则出现于06-01-2020，为40.800%。CEIC提供的教育：农村：小学肄业数据处于定期更新的状态，数据来源于National Institute of Statistics，数据归类于全球数据库的柬埔寨 – Table KH.G014: Education Statistics。

教育：农村：其他在06-01-2021达0.000%，相较于06-01-2020的0.000%保持不变。教育：农村：其他数据按年更新，06-01-2020至06-01-2021期间平均值为0.000%，共2份观测结果。该数据的历史最高值出现于06-01-2021，达0.000%，而历史最低值则出现于06-01-2021，为0.000%。CEIC提供的教育：农村：其他数据处于定期更新的状态，数据来源于National Institute of Statistics，数据归类于全球数据库的柬埔寨 – Table KH.G014: Education Statistics。

Abstract

The main objective of CSES 1999 was to, supplement the data base generated through CSES 1997, fill critical data gaps in a number of topics, and meet the data needs for analyzing and monitoring poverty, and support the anti-poverty programmes and interventions of the Royal Government of Cambodia. Accordingly, the scope of the survey was determined to canvass detailed information on household income and consumption, employment and earnings, labour utilization, child labour, and other current data needed to compile socio-economic indicators in several subject areas. Establishing and strengthening the capacity of NIS to conduct large scale household surveys and thereby institutionalize CSES as a national survey program was an important objective of the project.

The scope of the survey with respect to items of information collected at village level and household level are follows

I. Village Level Information

 1.Demographic Information

 2. Economy and Infrastructure

 3. Education

 4. Health and Immunization

 5. Retail Prices and wages

 6. Rain Fall and Natural Disasters

I. Household Information

 1.Demographic Characteristics

 2. Education

 3. Labour Force Characteristics based on short and long reference periods

 4. Child Activities

 5. Health

 6. Housing and Environment

 7. Household Consumption Expenditures

 8. Household Assets and Liabilities

 9. Fertility, Mortality and Child Care 

 10. Household Income

Geographic coverage

The sample was designed to provide estimates of the indicators at :

National (24 provinces) Phnom Penh, Other Urban and Other Rural Plain, Tonle Sap, Coastal, and Plateau/Mountain

Analysis unit

• Individual

• Household

Universe

Select sample households from non-institutional households (All regular residents in Cambodia) in Cambodia.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two stage stratified sampling design with the villages as the first stage units (PSU's) and households as the second stage units(SSU's) was used in the sampling strategy which was based on the method of inter-penetrating sub-samples. A truncated frame which excluded 4.5% of the villages was used because of the difficulty of conducting field work for security reasons in the excluded villages. The survey covered all non-institutional households including one person households. CSES 1999 sampled 6,000 households distributed in 600 villages in the country. The survey was conducted in two rounds to capture seasonal changes in the characteristics studied. The sampling design provided for estimates to be prepared for the urban and rural sectors and the capital city of Phnom Penh as well as for the four ecological zones of the Plain, Tonle Sap Lake, Coastal and Plateau and Mountain Regions. The design is not self-weighting and weights were used in the preparation of survey estimates.

Although CSES 1997 was successful operationally, improvements in the sampling design were considered essential while retaining the main features of the design which has been briefly outlined earlier. The inclusion of such topics as employment, child labor, per capita expenditure of households, health, and education expenditure demonstrated that the sample size should be adequate to produce statistically reliable estimates for the main stratification. The approximate computation of sampling errors of some key estimates in CSES 1997 that sampled 6,000 households showed that the relative errors were in the range of 3 % to 10% or a margin of error twice as much. It was thus necessary to reduce the sampling errors and it was evident that the sampling errors of estimates of the same variables canvassed in CSES 1999 as well as those which had similar prevalence rates would be high. Thus, it was clear that the sample size in fact should be raised above 6,000 households to produce nationally and sectorally representative and statically reliable estimates in respect of some of the key variables in the core questionnaire and in the income and employment module. Because of financial and administrative constraints, it was not feasible to increase the total number of households to be sampled. Therefore it was necessary to resort to the other options available that of improving the precision of the estimates by adopting a more efficient sampling design and attempting to lower the sampling errors.

When compared with the sampling designs that were adopted in surveys conducted earlier in Cambodia, a more efficient and improved sampling strategy was adopted in CSES 1999. The new sampling strategy has provided for estimates for the urban and rural sector, and the capital city of Phnom Penh as well as for the different ecological zones. The method of interpenetrating sub-samples has also provided for the preparation of separate estimates for ecological zones of the country from independent sub-samples enabling checks on the quality of data collected and on the precision of the estimates. Apart from these major innovations, the sampling procedures for the selection of villages which were the primary sampling units (PSU's) and households which formed the secondary sampling units (SSU's) were also improved by adopting circular systematic sampling with probability proportional to size (CSSPPS) techniques.

The sampling design of CSES 1997 followed the sampling strategy adopted in the two socio-economic surveys conducted earlier namely SESC 1993/94 and SESC 1996. The designs in these surveys were based on the division of the country into three domains Phnom Penh, other urban and rural areas so that separate estimates can be prepared for the capital city, and urban and rural sectors. These surveys used truncated frames that had excluded provinces, communes and villages in which data collection was difficult for security or other reasons. From each domain a specified number for villages were selected as first stage units (PSUs) and the second stage units (SSUs) which were households were selected after a pre-listing of households in the sample PSUs.

CSES 1999 sampled 6,000 households from 600 sample villages distributed in all 24 provinces in the country. The survey covered both urban and rural areas of Cambodia. Approximately 4% of the villages were excluded in 14 provinces because of difficulties of conducting field work for security reasons. The number of households sampled from each village was restricted to 10 to reduce the cluster effect and improve the precision of the estimates.

Estimates for round one and round two are provided separately for certain characteristics in addition to the estimates from both rounds of the survey. The estimates provided in the report are for the truncated frame used in the survey that excluded 4.2% of the villages because of the difficulty of conducting fieldwork for security reasons. In respect of a few key variables extrapolated estimates were prepared which covered the excluded areas of the country in addition to the truncated frame used in the survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

As in CSES 1997, four questionnaires were used in CSES 1999 for data collection. These include:

CSES Form 1: household listing sheet was used to record all households in the village or part thereof selected for household enumeration. The current list of households was necessary for sampling households and also as an input to derive household weights.

CSES Form 2: Village Questionnaire canvassed data on village population, physical and social infrastructure, development programmes and institutions at the village level and village level prices and unskilled wage rates

CSES Form 3: Core Questionnaire canvassed data on demographic characteristics, education, health and immunization, household and housing characteristics; and household consumption.

CSES Form 4: Income and Employment Module canvassed detail information on employment, wages and earnings; child labour; all types of household economic activities; household assets and household income.

Cleaning operations

Data processing was carried out at the NIS on a net-worked computer system with 16 microcomputers and peripherals. 35 NIS staff were trained as editors and coders, key entry and supervisory staff. Completed questionnaires were checked, edited and coded by trained editors before the data was keyed in. IMPS (Integrated Micro Processing System ) software developed and supported by the US Bureau of the Census was used for data processing. The data entry and verification system designed for the survey provided for on-line editing. A number of edit programs were prepared to eliminate duplicate records and range edits and consistency checks were used in data cleaning and validation. The tabulations presented in this report were extracted after cleaning the data files.

Response rate

Non-responding households were replaced. The need to adjust the weights for non-response did not arise as completed questionnaires from all sampled villages and households were retrieved achieving a 100% response rate.

Sampling error estimates

The approximate computation of sampling errors of some key estimates in CSES 1997 that sampled 6,000 households showed that the relative errors were in the range of 3 % to 10% or a margin of error twice as much. It was thus necessary to reduce the sampling errors and it was evident that the sampling errors of estimates of the same variables canvassed in CSES 1999 as well as those which had similar prevalence rates would be high (Please see

Abstract

The 2005/6 Household Income and Expenditure Survey is the second nationwide survey of households undertaken by Solomon Islands Statistics Office (SISO) since 1992.

The primary objectives of the HIES includes: • Re-basing of the weights of the current basket of goods and services in the Consumer Price Index (CPI). The survey also aimed to provide data on the behavior of household consumption expenditure patterns that will help form the weights that would reflect the relative importance that consumers attach to commodities and services; • Obtaining relevant data for purposes of updating the series of national accounts aggregates particularly the Gross Domestic Product.

The secondary objectives of the HIES were to: • Obtain data on housing and general demographic characteristics of households; • Obtain data on poverty measures, income and income inequality measures; • Obtain relevant data for the Millennium Development Goals (MDG), particularly health and education; and • Obtain other relevant data where necessary

The field data collecting exercise was undertaken from October 2005 to March 2006 and that seasonality effects on expenditure was not fully considered.

Geographic coverage

National. The HIES operation covered both the Urban and Rural areas focusing on Honiara, Other Urban Areas and the Rural Areas of the ten (9) provinces, and aimed to produce estimates at the country national and provincial levels only.

Analysis unit

• Households
• Individuals

Universe

The survey targeted private households whilst collective households in hospital, hotels, prison and educational institutions were excluded. A household is considered in the scope for the survey if the household have resided in the Solomon Islands for the last 12 months or more, or if not, they intend to live in Solomon Islands for the next 12 months.

Kind of data

Sample survey data [ssd]

Sampling procedure

Survey Design The survey was based on a two-stage sampling strategy using probability proportional to size (PPS) selection and random selection. The strategy for selection of each area type is slightly different depending also on enumerator workload schedule and the need to accommodate estimates at the National and Provincial level as well as Urban and Rural splits.

The Survey was designed to collect data for national and provincial level estimates and covered both urban and rural areas. The survey covered Honiara, provincial centers and rural areas within these provinces.

The sampling scheme used was a stratified two stage design with the Enumeration Areas (EA) as the Primary Sampling Unit (PSU) and the households within the sample areas as the secondary sampling unit (SSU). In the first stage the EAs were selected with probability proportional to their population size based on the 1999 population census. In the second stage households were selected using systematic sampling with a random start. The next stage was allocating the sample to each provinces proportional to the square-root of the population. This should mean that estimates of each province would roughly have the same level of accuracy. The sample was then split for each province between the provincial centers (considered to be urban) and the remaining rural population. Given the need for urban and rural estimates the sample was split between the two areas proportional to the square-root of the population based on the 1999 census. The last stage in the process involved modifying the final counts to accommodate the workloads for interviewers during the fieldwork. The interviewers were expected in the field for six months and could accommodate 10 households per month (60 household in total). It was desirable to have the total workloads for each province divisible by 60 to give each interviewer an even sized workload and have the sample spread out evenly across each month.

Since Honiara (capital of Solomon Islands) consists of a mix of areas which covers high income, middle income and low income areas, it was advisable that the EAs be grouped based on the class best suited to their situation. Thus for Honiara the EA list was sorted by the income group category for selection. The number of EAs to select from Honiara is simply the desirable sample size (480 households) divided by the number of households to be selected for each EA. It was decided that 10 households should be selected from each selected EA. Therefore the number of EAs that were selected was equivalent to (480 / 10) = 48 EAs.

Mode of data collection

Face-to-face [f2f]

Research instrument

The HIES is a relatively complex survey and the instruments to collect data was implemented through the following questionnaires and associated sections: • Household Control Form – household composition and particulars; • Household Expenditure Form – housing amenities, facilities and major household, expenditure on tenure, fixed capital, land, property etc; • Personal Income Form – Income pattern of household members and other income earning activities; • Household Dairy – Daily expenditure by type of goods and services • An additional health module was included – health facility utilization, immunization, motherhood, mortality, breast feeding & family planning, Malaria and miscellaneous

Cleaning operations

The Statistics Programme at the Secretariat of the Pacific Community (SPC) provided the assistance in data processing. A HIES data entry program was setup in CSPro version 2.6 and data entry started soon after the first workload was registered in the Statistics Office in November 2005 until May 2006. Logic procedures for data editing are prepared in Microsoft Access and data editing for all questionnaires were done in CSPro, except for the Diary where the editing is done in Microsoft Excel. Data management queries are done in Microsoft Access and the production of tables was done in Microsoft Excel. This report was prepared in Microsoft Word. Data verification of 5 per cent is done to check the accuracy of data input, though data edit checks are carried out for completeness, consistency and accuracy including the outliers. Anomalies of data were amended appropriately.

Response rate

Response Rates A sample of 4,320 households was planned for the country and about 3,822 households (88.5%) responded favorably satisfying the survey requirements.

Non-Response Despite efforts made by the enumerators and follow up attempts by the supervisors in most of the cases, there was non-response encountered during the survey.

The reasons for non response by the household were due mainly to the following: • The household was out of scope of the survey • Dwelling was vacant or not being lived in • The household could not be contacted after a number of attempts • Household excluded for other reasons like death in the family, refusals, customary reasons etc

Sampling error estimates

Error Measurements No formal measures of sample errors have been calculated for the survey results.

Non sampling errors cannot be readily measured. These included: o A response difficulty caused by misunderstanding of what was required from the survey and survey instruments by both households and interviewers. o The questionnaires were in English, which is at least a second language for interviewers and respondents. o The fact that some expenditure are seasonal and would not have been picked up in the survey period. o The exclusion of remote areas and institutions from the sampling frame.