Residential area, current housing and residential status. Mobility. Employment.

Topics: 1. Residential area, current housing and residential status: type of residential house; city size (degree of urbanisation); residential area; duration of residence; satisfaction with the place of residence; duration of residence in the current apartment; number of rooms; residential status; satisfaction with the apartment, the immediate residential environment and the environmental conditions in the residential environment; expected change in environmental problems in the residential environment; frequency of environmental pollution in the immediate residential environment (railway noise, traffic noise, aircraft noise, industrial and commercial noise, odours, fumes and dust formation).

1. Mobility: intention to move; preference of moving (target area); assessment of the current and future personal economic situation as well as the economic situation in the FRG and in the municipality of residence; expected change in unemployment figures.

2. Employment: employment status; assessment of job security; opinion on new technologies (lead to more unemployment vs. create new job opportunities and new jobs in the long term); experience with new technologies; desire for flexibility of working hours or for suspension of employment; maximum acceptable everyday commute in minutes; willingness to adapt to an external job; everyday commute in minutes; means of transport used for the everyday commute.

Unemployed people: opinion on new technologies (lead to more unemployment vs. create new job opportunities and new jobs in the long term); previous employment; year of termination of previous employment; reasons for giving up employment; intention to (re-)take up employment; intended full-time or part-time employment; maximum acceptable everyday commute in minutes; willingness to adapt to an external job; possible to take up work within two weeks; reasons for not taking up work within two weeks.

Demography: sex: age (month of birth and year of birth); highest school leaving certificate or targeted school leaving certificate; age at school leaving certificate; vocational education and training certificate; employment; employment status; full-time or part-time employment; previous employment; former or current employment position; marital status; cohabitation with a partner; self-assessment of class affiliation; denomination; closeness to the church; frequency of attending church; eligibility to vote in the last federal election 1987; voter participation in the last federal election and voting decision (second vote); eligibility to vote in the last election to the Berlin House of Representatives in 1985; participation in the last election to the Berlin House of Representatives and voting decision (second vote); net income of the respondent; household size; number of children in the household and age of these children; number of persons in the household over 18 years of German citizenship; number of persons in the household who contribute to the household income; household net income; telephone connection in the household.

Interviewer rating: presence of other persons during the interview; intervention of persons present at the interview; willingness of the respondent to cooperate; reliability of the data.

Additionally coded was: BBSR ID; respondent ID; state; government district; political community size (Boustedt); interview date; interview duration; interviewer ID; sex and age of interviewer; weighting factor.

Abstract

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

Some more specific outputs from the survey are listed below: a) To obtain expenditure weights and other useful data for the revision of the consumer price index; b) To supplement the data available for use in compiling official estimates of household accounts in the systems of national accounts; c) To supply basic data needed for policy making in connection with social and economic planning; d) To provide data for assessing the impact on household living conditions of existing or proposed economic and social measures, particularly changes in the structure of household expenditures and in household consumption; e) To gather information on poverty lines and incidence of poverty throughout Kiribati.

Geographic coverage

National coverage and Regional Island Groups (Northern Gilberts, South Tarawa, Central Giberts, Southern Gilberts, Linix). There are five main populations of interest for which estimates are required for the 2006 Kiribati HIES: South Tarawa, Northern, Central and Southern Gilbert Islands, and the Line Islands.

Analysis unit

• Household
• Individual
• Consumption expenditure item

Universe

The survey coverage included only persons living in private households during the month of October 2006. Persons living in institutions, such as school dormitories, hospital wards, hostels, prisons, as well as those households which had temporarily vacated their dwellings to attend cultural events were excluded from the survey. Also excluded from the survey were ex-patriot temporary residents and permanent residents who were not residing (and intending to reside) in Kiribati for at least 12 months. Income data were collected from persons aged 15 years and over and expenditure data from obtained from all household members at a household level.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Size In determining an appropriate sample size for a survey of this nature, numerous factors come into the equation. These include: a) The degree of accuracy required for key estimates b) The population size of the country c) The manner in which the sample is selected d) Cost or staffing constraints which may exist e) Whether or not estimates are required for sub-populations f) The level of variability in the data being collected

Each of these factors have different magnitudes of importance, but the major priority should always be on selecting a sample big enough to produce results of suitable accuracy. Many of these issues are generally known as well - for instance: · A user group may pre-specify what level of accuracy they may wish to achieve for the survey · The population of a country can normally be estimated to a reasonable level of accuracy · The sample selection technique adopted is known · Cost and staff constraints are generally known, and · A user group can once again provide information on whether estimates for sub-populations are required.

The one thing that normally isn't known is the degree of variability in the data being collected - this information comes after the survey. This factor is important because if there is not much variability in the data for key estimates, then the sample size does not need to be as large, and vice versa.

Without this sort of information, determining the appropriate sample size for a survey can often involve a bit of guess work. For that reason, based on previous survey experience in other Pacific Island countries, a sample of 10 per cent was considered more than sufficient for Kiribati. An additional 10 per cent of sample was selected to allow for sample loss.

As a result, a sample size of 1,555 households (10 per cent of 13,999, with a 10 per cent top-up) was considered suitable for the survey.

Allocation to "Target Areas"

For the Kiribati HIES, five target areas were identified as sub-populations for which estimates would be desirable. These five areas were: 1) South Tarawa 2) Northern Gilbert 3) Central Gilbert 4) Southern Gilbert 5) Line/Phoenix Islands

Once the sample size of 1,555 had been determined, the next step was determining how the sample should be allocated to each of these target areas in order to produce the required level of accuracy for each area. In order to achieve this, the sample was allocated in such a manner that the expected level of accuracy for each stratum would be similar. The resulting sample allocation can be found in the table below.

Stratification To achieve better representation within each target group, each target group was further stratified by grouping "like" islands. The plan from there was to select an island from each stratum to represent it. As a result, 11 strata were formed, with each of the 23 populated island/atolls of Kiribati allocated to one of these strata. The resulting strata, and islands which make them up, can be found in the following table.

The allocation of the sample to stratum within each target group was achieved by simply allocating the sample proportional to the population for that stratum. For example, for the target group Northern Gilbert, an overall sample size of 323 was desirable. To determine how much of that sample would be allocated to the first stratum which consisted of Makin and Butaritari, the following formula was applied:

n (Makin & Butaritari)= 323 * (889)/(889+1290+867)= 94

Excluded Areas Although it would be desirable to cover all of Kiribati for this survey, due to cost and time constraints a couple of areas were excluded from the frame before the selections were made. The two areas removed from scope were: · Banaba · Kanton

The impact on final estimates is considered to be very small given the small populations on these two islands; 61 households on Banaba, and 9 households on Kanton. This accounts for about 0.5 per cent of the population of Kiribati.

Sample Selection Technique

Selection of Islands For the stratum with more than one island, an island had to be selected in order to represent that stratum. The process used for this stage of selection was probability proportional to size (pps) sampling, where the size measure was the number of households on the island.

An example of how this process worked can be found below for the Central Gilbert - Group 2. For this stratum, a random number was selected between 0 and 1,005. Given the random number (254), fell within the cumulative number of households for Abemama, then that island was selected.

Selection of Households To minimize the travel requirements of interviewers, and thus travel costs, a two stage process was adopted to selected households.

The first stage of the process involved selecting EAs using probability proportional to size (pps) sampling. The required number of EAs to select from each island was simply determined by dividing the number of households to sample on that island by roughly 15, where 15 was the cluster size chosen from each selected EA.

Having selected the EAs in sample, a systematic skip was run through the list of households for each EA to determine which households would be selected in sample. These selections were performed in the NSO, and the lists provided to interviewers in the field. The lists used for this stage of selection were based on the 2005 Population Census, and thus would be out-of-date by a year or so, but given the significant gains in simplifying field logistics, this was the preferred option.

Sampling deviation

The population estimates produced by the survey represented almost all of the islands of Kiribati with the exception of Banaba and Kanton, which due to their remoteness and small population, were considered out of scope for the survey (they only contribute 0.5% to the total household population of Kiribati).

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Control Form The Household Control Form (HCF) should be filled in during the first visit to the household. Its main objective is to collect basic demographic information about members of the household. Before completing this form however, the interviewer needs to determine if the household is in scope for the survey.

Only those households which have been residing in Kiribati for more than 1 year, or those households who intend to reside in Kiribati for a total of 12 months or more, should complete this form and partake in the survey. These households can be identified by going through section (e) in the field book for interviewers. If the household does not meet these criteria, then the survey is over. In assessing the eligibility of a household to be in the survey, use some common sense - there will be many occasions when it will be clear that the household has always lived in Kiribati, so don't bother asking these questions.

Once this issue has been addressed, the HCF can be filled in for the household. The HCF form is to record names of all the usual members of the household. Information on relationship to head of household, sex, date of birth and ethnicity are asked of all members in the household. For persons aged 15 and over, questions on marital status, educational attainment, activity status, literacy status and internet usage are also asked. Codes should be used to complete these questions, and they can be found in the interviewer's field book in section (a).

Abstract

The 2010 Household Income and Expenditure Survey (HIES) is the second survey of income and expenditure in Vanuatu to provide reliable sub-national estimates, with the 2006 HIES being the first time this was attempted. The first HIES was conducted in 1985 in the two urban centres of Luganville and Port Vila. Another was conducted in 1998 but unfortunately, for a number of reasons to do with errors of estimation and observation, the 1998 HIES did not provide reliable and accurate estimates. With the lessons learnt from past experience, the main objectives for the 2010 survey were to: - Supply monitoring data needed for the then Millennium Challenge Account, Vanuatu (MCA) infrastructure projects; - Supplement the data available for use in compiling official estimates of household accounts in the system of national accounts and subsequent estimates of Gross Domestic Product (GDP); - Obtain expenditure weights and other data for the updating of the basket of items and weights used in the Consumer Price Index (CPI); - Provide data for assessing the impact on household living conditions of existing and proposed economic and social policies and programmes, particularly those resulting in changes in the structure of household expenditure and consumption; and - Gather information on key poverty indicators and statistics for poverty analysis.

Geographic coverage

National coverage.

There are eight main populations of interest for which estimates are required for the 2010 Household Income and Expenditure Survey (HIES): the provincial rural areas of Torba, Sanma, Penama, Malampa, Shefa, Tafea and the urban areas of Luganville and Port Vila. For this reason, the detailed analysis focuses on households from each of the eight sub-populations.

Analysis unit

Households (private) and individuals.

Universe

The survey coverage included only persons living in private households during the survey period (September to November 2006). Persons living in institutions, such as school dormitories, hospital wards, hostels, prisons, as well as those households which had temporarily vacated their dwellings were excluded from the survey. Also excluded from the survey were ex-patriot temporary residents and permanent residents who were not residing (and intending to reside) in Vanuatu for at least 12 months.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling method adopted for the survey was a two-stage approach. The first stage involved the selection of Enumeration Areas (EA) using probability proportional to size (PPS) sampling. The size measure was the number of expected households in the EA, based on 2010 population census estimates. Although it would be desirable to cover all of Vanuatu for this survey, due to cost and time constraints some EAs were excluded from the frame before the selections were made. The impact on sub-population estimates will differ, as some areas have had larger scope reductions.

The second stage of sampling adopted systematic sampling from a list of all households contained in the EA. These lists were produced in the field by enumerators during the first visit to the EA. Once the sample had been selected, a review of where the selections were made was conducted to see how well they covered the projects of interest to the MCA. Approximately 18 enumeration areas (EA) were selected on Efate and 21 between Port Olry and Luganville in Santo, providing good representation of each of the areas. A final sample size of 4,737 households was selected for the survey representing around 10% of the households in Vanuatu.

In order to achieve the required level of accuracy for estimates for the target areas of the six provinces and two urban centres different sample allocations were tested to determine which allocation would produce estimates of similar levels of accuracy for each target area. This sample allocation resulted in the selection of approximately 600 in each province, with the exceptions of Luganville and Torba where less than 600 households were selected. Each of the eight target areas was then further stratified to improve the representation within each of the different area types. Strata were determined by allocating Area Councils to area types based on the Area Council’s accessibility. As a result, 21 strata were used the final sample selection. Sample allocation to each stratum was derived by the proportionate allocation of the population within each “target area”.

Sampling deviation

Owing to cost and time constraints, some remote areas were not considered eligible for selection for the survey. Therefore the scope of the survey was reduced to 82.5 percent of all households in the population. Substantial reductions in scope occurred in Torba (62% in scope) and Malampa (68%) provinces. No enumeration areas were excluded in urban areas. While this may introduce some systematic bias, especially for the areas affected, the reduction of scope is not expected to affect the overall representativeness of the sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was developped both in English and Bislama. It is made of 4 forms that are listed below: - Household Control Form (HCF)- was designed to list all the members of households, their date of birth, sex, maritial status relationship to the head of the household; - Household Questionnaire Form - Part 1: Dwelling Characteristics, Access to Transport, Communication, Health, Sanitation and Market Centres, Part II: Household Expenditure, Part III: Income and Production; - Person Questionnaire Form - captures information regarding Demographic, health, education and economic activity for household members; - Household two weeks diaries to collect daily consumption and expenditure.

Cleaning operations

-DATA EDITING: Some initial editing was carried when the forms were coded and prepared for data entry. There were then several strands of editing carried out after the data entry was completed. A set of tables designed to identify missing, illegal or potentially incompatible values in the classificatory data was specified.

The development of the "Generate new records" program, described above, required extensive examination of the data. First, it was sometimes necessary to examine original questionnaires to obtain a better understanding of how households responded to certain questions, especially when the recorded responses were unexpected. Second, the development of some of the imputation functions implemented in the program required analysis of detailed data. Third, testing of the program required examination of data before and after transformation to ensure that the program was carrying out its intended functions. These and other more minor reasons for examining the data collectively also played an important editing function, even though it was unstructured from an editing point of view. Most of the editing actions flowing from this work are recorded in Queries.xls.

Outlier analysis is an important part of the editing process for household surveys. For the Household Income and Expenditure Survey (HIES), formal outlier analysis has largely been confined to examining households with very high income or expenditure. However, outliers were also detected during the processes described in the previous paragraphs.

-IMPUTATIONS: Some obvious errors were fixed and missing data supplied manually at the time of the initial coding and checking of the questionnaires prior to the data entry stage. Similarly changes were made as a result of editing queries described in the previous section. A more automated form of imputation was implemented for certain instances of missing data.

For those transactions recorded in diaries where a quantity was supplied without a value, a value was imputed on the basis of transactions in the same commodity in the same province/urban area. Consideration was given to imputing separately for each transaction type (purchases, own account production, gifts given, gifts received) but there is not sufficient data to use a cross classification of province/urban and transaction type. Examination of differences in unit values between provinces/urban areas and between transaction types showed greater differences between provinces/urban areas than between transaction types. Where there was no required data for a commodity in a particular province/urban area, the unit value from a similar province/urban area was used. Calculations are included in value and quantity by prov city 2.xls. Transaction values imputed in this way are flagged on the file by means of the "data source" variable.

For employees who did not report their gross wages and salaries, a value was imputed on the basis of the average wage/salary of other employees with the same industry and occupation codes and who reported their value. Where there were no other employees in the same category reporting wages/salary, the value for a similar industry and occupation code was used. Calculations are included in supporting file W&S 5.xls. Any imputed values were included in the transaction record for wage and salaries for the household concerned (there is only one aggregate record per household, which combines the wages and salaries of all members of the household). If any component is imputed, the whole transaction is flagged as imputed. However, the imputed value is not included in the PERSON record.

For households that own their own dwelling (including those with a loan or mortgage) but who did not estimate the potential rental value of their dwelling in the household

This dataset contains yearly certified enrollment for all public school districts (with physical boundaries) in Wisconsin for the 2023-2024 school year. This data is also available in the WISEdash Public Portal. This dataset is derived from publicly available files on the WISEdash Download Page. Enrollment Count is the number of students enrolled on specific dates as determined by school enrollment/exit dates that cover those dates. Percent Enrollment by Student Group is a percent of the enrollment count for all student groups combined. Reporting Disability is indicated in the pupil’s individualized education program (IEP) or individualized service plan (ISP). A person's race or ethnicity is the racial and/or ethnic group to which the person belongs or with which he or she most identifies. Ethnicity is self-reported as either Hispanic/Not Hispanic. Race is self-reported as any of the following 5 categories: Asian, American Indian or Alaskan Native, Black or African American, Native Hawaiian or other Pacific Islander, or White. The data displayed reflects the race/ethnicity that is reported by school districts to DPI.An economically disadvantaged student is one who is identified by Direct Certification (only if participating in the National School Lunch Program) OR a member of a household that meets the income eligibility guidelines for free or reduced-price meals (less than or equal to 185 percent of Federal Poverty Guidelines) under the National School Lunch Program (NSLP) OR identified by an alternate mechanism, such as the alternate household income form.English Learner status is any student whose first language, or whose parents' or guardians' first language, is not English and whose level of English proficiency requires specially designed instruction, either in English or in the first language or both, in order for the student to fully benefit from classroom instruction and to be successful in attaining the state's high academic standards expected of all students at their grade level.

Attitude of the Federal German population and census critics to the census on 31. May 1987.

Summary of three data sets archived and described under ZA Study Nos. 1588 to 1590.

Topics: 1. From the first wave of 1987: political interest; satisfaction with democracy in the Federal Republic; feeling of political effectiveness and degree of representation by politicians and parties; orientation of government policies on special interests or public welfare; attitude to the census; intent of members of household and respondent to participate; willingness to participate after notice of threat of fine; filling out the survey form oneself or by another person in household; conversations about the census in social surroundings and time of last conversation; attitude to the census in circle of friends and acquaintances as well as their willingness to participate; importance of political attitudes in social surroundings and visibility of one´s own views; knowledge about contents of the census survey (scale); assumed difficulty in filling out survey form; preference for filling out the form in the presence of the canvasser or alone; misgivings about canvasser in residence; difficulties in carrying out official matters; frequency of contact and ability to establish contacts; trust in institutions and organizations; self-assessment on a left-right continuum; assumed position of the majority of the population on a left-right continuum; postmaterialism; sympathy scale for political parties; frequency of use of television news broadcasts as well as the local part and political part of a daily newspaper; time of last noticed media reports about the census and content tendency of these programs; assumed attitude of the population to the census; living together with a partner and his attitude to the census; assumed participation of partner in the census; response or boycott conduct in the census survey; attitude to government statistics; attitude to punishment of census boycotters and preferred governmental behavior regarding refusal; personal fears regarding misuse of personal census data; trust in observance of data protection; sympathies regarding social movements as well as personal membership; party preference; perceived fears and their causes; attitude to technology; attitude to computers and scientific innovations; attitude to government dealing with data; assessment of census refusers as system opponents; attitude to storage of personal data; importance of data protection and trust in observance of the data protection regulation; judgement on quality of data protection; earlier participation in a survey and type of survey; attitude to selected infringements and crimes as well as other illegal actions (scale); religiousness; union membership; self-assessment of social class; possession of a telephone; willingness to participate in a re-interview.

The following additional questions were posed to persons with strong or very strong political interest: demographic information on circle of close friends (ego-centered network); agreement with respondent regarding party preference and attitude to the census; willingness of friends to participate in the census; familiarity of friends among each other; personal willingness to participate in selected political forms of protest (scale); personal fears regarding misuse of personal data by selected institutions and public offices.

Demography: month of birth; year of birth; sex; marital status; number of children; ages of children (classified); frequency of church attendance; school education; vocational training; occupation; occupational position; employment; monthly net income of respondent and household altogether; number of persons contributing to household income; size of household; position of respondent in household; characteristics of head of household; number of persons eligible to vote in household; persons in household who do not have German citizenship; self-assessment of social class; union membership of respondent and other members of household; possession of a telephone.

Interviewer rating: presence of third persons during interview and person desiring this presence; intervention of others in interview and person introducing the intervention; attitude to the census of persons additionally present during interview; presence of further persons in other rooms; willingness to cooperate and reliability of respondent.

Also encoded was: length of interview; date of interview; ident...

Abstract

The 2006-2007 Household Budget Survey (HBS) was conducted between May 2006 to July 2007 and its primary purpose was to update the information on the expenditure pattern of households. The data would then be used to compile a new consumer’s ‘basket of goods’ and revise the weights used in the compilation of the monthly Consumer Price Index and the measurement of inflation. The data have also been used in the estimation of household consumption contribution in the GDP, the average monthly household expenditure and income and also in the compilation of new poverty indicators.

Around 1200 households on Mahe, Praslin and La Digue (the 3 main islands in Seychelles) participated in the survey, each of them providing data over a period of 1 week. In the final analysis, data from 1164 households and 4323 individuals have been included.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Consumption expenditure item/ service

Universe

The survey excluded households headed by expatriates as well as institutional populations (i.e. individuals living in hospitals, military barracks and prisons) and households on outer islands.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Design A list of households from the earlier mapping exercise provided the most up-to-date sampling frame for the survey. The frame comprised of 22,831 households listed by district and enumeration area. The households served as direct sampling units.

Stratified, systematic random sampling was adopted for the selection of households with the electoral districts serving as strata. The number of households to be selected from each district was determined by proportional allocation based on size (number of households). The target sample was 1200 households which would represent a little over 5% of all households, but an initial 1511 households were selected to account for non-response and households deemed non-eligible to participate in the survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire comprised of four main parts. Form HBS 1 was the household schedule and contained questions relating to household members’ demographic details, economic status as well as household facilities and selected major expenditure.

Form HBS 2 contained questions addressed to individual members of the household aged 15 years or more. This section covered questions related to personal and business income. The third section of the questionnaire (HBS 3) was the diary or account book in which households were asked to record details on daily expenditure and Form HBS 4 was completed in circumstances of nonresponse.

Cleaning operations

The data were captured on personal computers using a programme written in DELPHI. The various software used to analyse the data at different stages included FoxPro, MS EXCEL and SPSS.

Response rate

The selected sample listed a total of 1511 households, of which some 1300 were interviewed. The survey design over-sampled households by 25% to take into consideration non-response. 222 of the selected households (18.5% of the desired sample) either refused to participate in the survey or were not available. The 100 or so additional households were interviewed to replace the households that had completed only part of the survey. Those included households that agreed to be interviewed but refused to complete the account book.

Data appraisal

A total of 4790 persons from 1300 households were interviewed. However, in the analysis of expenditure, data for 1164 households and 4323 individuals were included and the remaining was not considered on account of incompleteness of significant parts of the questionnaire.