Analysis unit

Persons and households

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: The dwelling is a separate and independent place of residence. Regular dwellings (accommodations) are defined as housing units typical of the Republic (detached houses, flats, hostels) intended for private households to live in. - Households: The household is defined as a person, family or a group of families or persons permanently living in a given dwelling and having a common budget, with blood relationship between them not being compulsory. - Group quarters: Institutions (collective quarters) are places of residence intended for collective households, i.e. for groups of people cohabiting in the same housing unit (specialized institution), sharing common meals, but not having individual budgets or common consumer espenses, observing common rules and usualy not being related.

Universe

All inhabitants permanently residing in each housing unit, including persons who were temporarily absent at the census moment. Temporarily present citizens of the Republic of Belarus who reside in other places are to be only listed in the check census list. Children born after and persons who died before the census moment are not to be included in the census documents. Homeless (persons without a specific place of residence)

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Ministry of Statistics and Analysis of the Republic of Belarus

SAMPLE SIZE (person records): 990706.

SAMPLE DESIGN: Systematic sample of every 10th household after a random start, drawn by the National Statistical Office. Homeless (persons without a specific place of residence)

Mode of data collection

Face-to-face [f2f]

Research instrument

There are three documents. Form 2P contains directions for completing the list of those usually (permanently) living in the dwelling and their housing conditions. Form 3N III. Directions for recording answers to questions of the enumeration questionnaire. Form 4E directions for recording answers to questions of the enumeration questionnaire for those temporarily present on the territory of the Republic of Belarus.

A dataset of Government schools average Secondary School English Class Size, showing average for Year 12 and overall secondary classes, from census year 2001 to 2023.\r \r The size of secondary English classes is collected from government schools as part of the February School Census conducted on the last school day of February each year.\r The data is based on the number of English classes in secondary year levels. English class size is an indication of the size of classes in secondary schools, as almost all students study English. This includes each compulsory and elective English class for secondary students held during the week of the census. Secondary students not studying English are NOT counted in the class size return. Also included are classes (such as Remedial English or ESL / English as a Second Language) that a student attends instead of compulsory English. Excluded are classes such as English Literature, Remedial English or ESL that a student attends as well as “compulsory” English. Please note that extra teaching support is NOT included when calculating the average class size. Average class size is NOT the same as the student/teacher ratio.

Abstract

The 2001 Croatia Population and Housing Census was carried out on the basis of the Law on the Census of Population, Households and Dwellings 2001 (Narodne novine, official gazette of the Republic of Croatia, No. 64/2000) and the Act on Amendments to the Law on the Census of Population, Households and Dwellings 2001 (Narodne novine, official gazette of the Republic of Croatia, No. 22/2001).

The "Recommendations for the 2000 Censuses of Population and Housing in the ECE Region" jointly prepared by the United Nations Economic Commission for Europe and the Statistical Office of the European Communities (New York and Geneva, 1998) were relevant for the Census 2001. Their aim is to "facilitate and improve the international comparability of data through the harmonization of data, definitions and classification of topics".

The Recommendations offer detailed definitions of census units, characteristics and modalities, prescribing them as either obligatory or optional. In line with the Recommendations, the Croatian Bureau of Statistics took over the entire obligatory contents (core topics) as well as over 50% unobligatory or optional contents (non-core topics).

Geographic coverage

National

Analysis unit

• Household;
• Indivudual.

Universe

On the basis of article 2 of the Law on Census 2001, the following census units are covered by the Census: residents (persons), households and conventional dwellings as well as other inhabited premises and objects that are not conventional dwellings by definition.

Kind of data

Census/enumeration data [cen]

Sampling procedure

No sampling - whole universe covered

Mode of data collection

Face-to-face [f2f]

The 2001 Census: Special Licence Household Sample of Anonymised Records (SL-HSAR) dataset comprises Sample of Anonymised Records (SARs) data that relate to 29 April 2001. They were created by the Office for National Statistics (ONS) as part of the 2001 Census of Population. All households were asked to complete a form giving information about the household and all individuals living in the household. Completion of the form was compulsory for the entire population. The Census schedule includes questions on housing and tenure, and demographic and socio-economic information for all household members.

The dataset comprises SARs data for 1% of households in England and Wales, including imputed values for households which were not enumerated during the Census. Individual data for households larger than 11 residents have been suppressed. To protect confidentiality, age data have been grouped into 2-year bands and there is no geographical breakdown available. A small amount of perturbation has been applied to the data to protect confidentiality. As with the Individual Licensed SAR (see under SNs 7210 and 7211), separate variables indicate whether or not imputation or perturbation has been applied to any given variable for each case in the sample. Documentation, training and user support for these data is undertaken by the SARs team at the Cathie Marsh Centre for Census and Survey Research (CCSR). A further release of data, which contains additional derived variables, will be made available at a later date.

The Secure Access version replaces the previous Special Licence version that was held under SN 5278, which is no longer available. Prospective users of the Secure Access data will need to fulfil additional requirements, including completion of face-to-face training and agreement to Secure Access' User Agreement and Breaches Penalties Policy, in order to obtain permission to use that version (see 'Access' section below).

Detailed SARs data:
A more detailed version of these data, containing geographical information at the level of Local Authority, is available as a Controlled Access Microdata Sample (CAMS). These can be accessed at all ONS sites. Applications to use these data should be made to ONS; further details can be found on their CAMS web page. The CAMS file includes data for Scotland and Northern Ireland as well as England and Wales.

Attitude of the German population to the census before census day, 31 May 1987. Political attitudes. Topics: political interest; satisfaction with democracy in the Federal Republic; difficulties in taking care of official matters; sympathy scale for political parties; attitude to the census and intent to participate; knowledge about the compulsory participation requirement; personal consequences of non-participation; willingness to participate given threat of fine; response or boycott behavior during the survey; time of last noticed media reports about the census and tendency of the content of these articles; conversations about the census in social surroundings and time of last conversation; living together with a partner and his attitude to the census; assumed participation of partner in the census; attitude to the census in circle of friends and acquaintances as well as their assumed willingness to participate; perceived attitude of the population as well as parties, churches and trade unions to the census; knowledge about the survey procedure; attitude to government statistics; personal concerns regarding misuse of personal census data; trust in observance of data protection; attitude to the census in 1983; willingness to participate in a microcensus survey; attitude to technology; self-assessment on a left-right continuum; knowledge about the office for data protection and the data protection official; earlier participation in a survey and type of survey; attitude to opinion polls (scale). Demography: month of birth of respondent; sex; marital status; number of children; ages of children (classified); religious denomination; frequency of church attendance; school education; vocational training; occupation; occupational position; employment; monthly gross 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 this 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; identification of interviewer; sex of interviewer; age of interviewer test. Einstellung der bundesdeutschen Bevölkerung zur Volkszählung vor dem Stichtag am 31. Mai 1987. Politische Einstellungen. Themen: Politisches Interesse; Zufriedenheit mit der Demokratie in der Bundesrepublik; Schwierigkeiten bei der Erledigung von Behördenangelegenheiten; Sympathie-Skalometer für die politischen Parteien; Einstellung zur Volkszählung und Beteiligungsabsicht; Kenntnis der gesetzlichen Teilnahmeverpflichtung; persönliche Folgen einer Nicht-Teilnahme; Beteiligungsbereitschaft bei Bußgeldandrohung; Antwort- bzw. Boykottverhalten bei der Erhebung; Zeitpunkt der zuletzt wahrgenommenen Medienberichte über die Volkszählung und inhaltliche Tendenz dieser Beiträge; Gespräche über die Volkszählung im sozialen Umfeld und Zeitpunkt des letzten Gesprächs; Zusammenleben mit einem Partner und dessen Einstellung zur Volkszählung; vermutete Teilnahme des Partners an der Volkszählung; Einstellung zur Volkszählung im Freundes- und Bekanntenkreis sowie deren vermutete Teilnahmebereitschaft; perzipierte Einstellung der Bevölkerung sowie der Parteien, der Kirchen und der Gewerkschaften zur Volkszählung; Kenntnis des Erhebungsverfahrens; Einstellung zu staatlichen Statistiken; eigene Befürchtungen hinsichtlich einer Zweckentfremdung der persönlichen Volkszählungsdaten; Vertrauen in die Einhaltung des Datenschutzes; Einstellung zur Volkszählung im Jahre 1983; Teilnahmebereitschaft an einer Mikrozensus-Erhebung; Einstellung zur Technik; Selbsteinschätzung auf einem Links-Rechts-Kontinuum; Kenntnis des Amtes für Datenschutz und des Datenschutzbeauftragten; frühere Teilnahme an einer Befragung und Befragungsart; Einstellung zu Meinungsumfragen (Skala). Demographie: Geburtsmonat des Befragten; Geschlecht; Familienstand; Kinderzahl; Alter der Kinder (klassiert); Konfession; Kirchgangshäufigkeit; Schulbildung; Berufsausbildung; Beruf; Berufliche Position; Berufstätigkeit; monatliches Netto-Einkommen des Befragten und des Haushalts insgesamt; Anzahl Personen, die zum Haushaltseinkommen beitragen; Haushaltsgröße; Stellung des Befragten im Haushalt; Charakteristika des Haushaltsvorstands; Anzahl wahlberechtigter Personen im Haushalt; Personen im Haushalt, die nicht die deutsche Staatsangehörigkeit besitzen; Selbsteinschätzung der Schichtzugehörigkeit; Gewerkschaftsmitgliedschaft des Befragten und anderer Haushaltsmitglieder; Telefonbesitz. Interviewerrating: Anwesenheit Dritter beim Interview und Person, die die Anwesenheit erwünschte; Eingriffe Dritter in das Interview und Person, die die Intervention herbeiführte; Einstellung der beim Interview zusätzlich anwesenden Person zur Volkszählung; Anwesenheit weiterer Personen in anderen Räumen; Kooperationsbereitschaft und Zuverlässigkeit des Befragten. Zusätzlich verkodet wurden: Interviewdauer; Interviewdatum; Intervieweridentifikation; Interviewergeschlecht; Intervieweralter Test.

Abstract copyright UK Data Service and data collection copyright owner. The 2001 Census: Special Licence Household Sample of Anonymised Records (SL-HSAR) dataset comprises Sample of Anonymised Records (SARs) data that relate to 29 April 2001. They were created by the Office for National Statistics (ONS) as part of the 2001 Census of Population. All households were asked to complete a form giving information about the household and all individuals living in the household. Completion of the form was compulsory for the entire population. The Census schedule includes questions on housing and tenure, and demographic and socio-economic information for all household members. The dataset comprises SARs data for 1% of households in England and Wales, including imputed values for households which were not enumerated during the Census. Individual data for households larger than 11 residents have been suppressed. To protect confidentiality, age data have been grouped into 2-year bands and there is no geographical breakdown available. A small amount of perturbation has been applied to the data to protect confidentiality. As with the Individual Licensed SAR (see under SNs 7210 and 7211), separate variables indicate whether or not imputation or perturbation has been applied to any given variable for each case in the sample. Documentation, training and user support for these data is undertaken by the SARs team at the Cathie Marsh Centre for Census and Survey Research (CCSR). A further release of data, which contains additional derived variables, will be made available at a later date. The Secure Access version replaces the previous Special Licence version that was held under SN 5278, which is no longer available. Prospective users of the Secure Access data will need to fulfil additional requirements, including completion of face-to-face training and agreement to Secure Access' User Agreement and Breaches Penalties Policy, in order to obtain permission to use that version (see 'Access' section below). Detailed SARs data: A more detailed version of these data, containing geographical information at the level of Local Authority, is available as a Controlled Access Microdata Sample (CAMS). These can be accessed at all ONS sites. Applications to use these data should be made to ONS; further details can be found on their CAMS web page. The CAMS file includes data for Scotland and Northern Ireland as well as England and Wales.

Abstract

The HIES gathers information related to demographic characteristics of the members of the surveyed households, expenditure on food and non-food items and income received by each household member from all the different sources in a compulsory manner. Starting from the HIES 2006/07, the survey questionnaire was further expanded beyond the collection of demographic, income and expenditure information. It has been introduced 7 new sections to collect almost all the other household information that helps to understand the correct living standards of the households. Those newly introduced areas covered by the HIES starting from the HIES 2006/07 are as follows. 1. School education (aged 5-19 years) 2. Health information 3. Inventory of durable goods 4. Access to infrastructure facilities 5. Household debts and borrowings 6. Housing, sanitary and disasters 7. Land and agriculture holdings

Geographic coverage

National - excluding Mannar, Kilinochchi and Mullaithivu districts in the Northern province

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample design of the survey is two stage stratified and the Urban, Rural and the Estate sectors in each district of the country are the selection domains thus the district is the main domain used for the stratification. The sampling frame is the list of housing units prepared for the Census of Population and Housing (CPH) 2001 and the HIES 2009/10 will be the last HIES sampled from this sampling frame as the DCS is all set to conduct the CPH in 2011 based on whole newly prepared set of census blocks, which has been almost completed by now.

Selection of Primary Sampling Units Primary sampling units (PSUs) are the census blocks selected for the survey and the sampling frame, which is the collection of all the census blocks prepared in 2001 in Sri Lanka, is used for the selection of the PSUs at the first stage of the selection.

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

The selected PSUs are updated to include newly built housing units and to exclude demolished or vacated housing units, which are no longer considered as housing units according to the survey definitions, to capture variation of natural growth and to make necessary adjustments for the same. The PSU updating operation in field is generally done less than one month prior to the survey and it was carried out for the 12 months starting from June 2009 to May 2010 to support the scheduled 12 survey months started from July 2009 to June 2010 for the HIES 2009/10.

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire consists of nine parts. i. Demographic Characteristics ii. School education (aged 5 to 20 years) iii. Health vi. Household expenditure v. Household income vi. part a : Inventory of durable goods vi. part b : Debts of the household vii. Access to facilities in the area viii. Information about housing ix. Agriculture holdings and livestock

Sampling error estimates

Estimation, Standard error, and coefficient of variation table is available in the final survey report.

Abstract

In an effort to make adequate and reliable data and information available for scientific policy formulation, planning and implementation of various programs and projects in education in Ghana, the Ministry of Education (MoE) launched the Education Management Information System (EMIS) Project in January, 1997 with technical support during the first and second Phases from the Harvard University and funds from the World Bank and the Government of Ghana. As an integral part of the Free, Compulsory and Universal Basic Education (FCUBE) Program, the EMIS Project was planned to build on the already existing EMIS established in 1988 in the Ministry as part of the Education Reforms. Currently, technical support is being given by UNESCO Institute for Statistics (UIS). Through the EMIS, a strong database has been established within the Ministry of Education. Twenty four basic school censuses have so far been conducted since 1988 and the reports on them are available in the Ministry. This is the Twelfth senior high school census in recent times. This report is presented to provide and upgrade basic data and planning parameters on enrolment, teaching staff, school facilities and examination results. This year's information on Senior High Schools has been produced at national and regional levels. The survey is presented in four sections as follows.

• Section One gives a brief introduction of the report highlighting briefly the EMIS Project.
• Section Two gives a brief summary of the analysis of the data. An attempt has been made in the analysis to compare the previous census (2011-2012) results with those of the current census. An effort has also been made to analyze the data by type of education, region and gender.
• Section Three gives a summary of tables, charts and maps for basic Schools. The arrangement of tables followed immediately by maps and charts has been used to facilitate visualization of the concepts being presented. Section Four provides detailed statistics at the national and regional levels by type of education.

Geographic coverage

National level Region District

Analysis unit

Questionnaire administered to all basic schools in Ghana to collect data on type of school (Public or Private), Location, locality type (Rural or Urban), details of teachers, textbooks, enrolment, facilities, rooms condition etc.

Universe

Basic schools level

Kind of data

Census/enumeration data [cen]

Sampling procedure

14,800 Basic Schools were selected for the census of Ghana Annual Schools

Mode of data collection

Other [oth]

Research instrument

The questionnaire consists of the following;

1. School identification
2. School profile and organization
3. School infrastructure
4. School management
5. School building
6. Characteristics of school's materials and equipment
7. Pupils and teacher textbooks
8. Non-teaching staff information
9. Enrolment by grade, by sex and by age
10. Pupil attendance and movement
11. Teacher profiles
12. Teacher periods and subjects taught
13. Pupil and teacher information
14. Staff movement
15. Income and expenditures of the school in 2012-2013

Cleaning operations

1. Question to question vetting by CS and stats officers.
2. In built consistency checks in applications.
3. Checks from programmers.

Response rate

100% coverage for public schools 85% coverage for private schools

Sampling error estimates

No sampling error

Data appraisal

No other forms of appraisal reported.

Abstract

Toward EC2011, the pilot survey aims to:

(1) gain statistical data on the current Cambodian economy which are comparable with the results of EC2011;

(2) gain the updated list of large-scaled establishments;

(3) test the form and other documents; and

(4) test the work procedures of every stage of the enumerators, supervisors, local government offices and NIS.

An establishment is an enterprise or part of enterprise which is situated in a single location and in which only a single (non-ancillary) productive activity is carried out or in which the principal productive activity accounts for most of the value added. This conforms to the International Standard Industrial Classifications (ISIC) Rev.4 of the United Nations. Generally speaking, there are three kinds of establishments: fixed, movable, and I-8 mobile. “Fixed” means an establishment running some economic activity always in the fixed place and building. “Movable” means an establishment running some economic activity always in the fixed place, but it is possible to move the place easily. And “mobile” means an establishment running some economic activity on the run. Since the PS2010 covered “fixed” and “movable” only, unfixed “mobile" was not included in these final results.

Geographic coverage

National Province

Analysis unit

Establishment

Universe

The pilot survey covers all establishments which exist at the reference date in the territory of the Kingdom of Cambodia.

The following establishments, however, are excluded:

(1) establishments classified into "Section A, Agriculture, forestry, and fishing" specified in the United Nations International Standard Industrial Classification of Economic Activities, Revision 4 (hereinafter, quoted as ISIC);

(2) establishments classified into "Section O, Public administration and defense; compulsory social security" specified in ISIC;

(3) establishments classified into "Section U, Activities of extraterritorial organizations and bodies" specified in ISIC; and

(4) establishments classified into "Section T Activities of households as employers; undifferentiated goods-and services-producing activities of households for own use" specified in ISIC.

Kind of data

Sample survey data [ssd]

Sampling procedure

(1) All the villages were stratified into 72 strata by 24 provinces and 3 characteristics of villages (dominant industry in each village: B-F, G-I and J-U except T of ISIC),and 1-5 villages were sampled randomly from each stratum to select 199 villages/Enumeration Areas in total.

(2) Establishments with 99 persons engaged or less existing in the 199 selected villages were enumerated, and appropriate multipliers were used to estimate national total figures from the data thus collected.

(3) In addition, all the large-scaled establishments with 100 persons engaged andmore (estimated to be around 600 establishments) were enumerated throughout the country.

Mode of data collection

Face-to-face [f2f]

Research instrument

Listed below are the forms that used during the field enumeration:

Listing Form: This is a Form where in establishment within a certain village area. The establishment can be defined as an economic unit that engages, under a single ownership or control - that is, under a single legal entity - in one, or predominantly one, kind of economic activity at a single physical location.

Form Questionaire:

1.Area information

2.Establishment Information

Section for Enumerator

3.Characteristics of representative of the establishment

4.Registration to administrative agencies

5.Ownership of Establishment

6.Single unit, Head or Branch office

7.Tenure, Kind and Area

8.Opening Time

9.Year of starting business

10.Number of persons engaged actually in this establishment one week before 1 March 2010

11.Kind of main business activities

12.Number of Branch offices that this head office supervises

13.Total number of entire regular employees at the end of December 2009

14.Kind of business activities of the entire enterprise that include not only those of this head offices but also those of branch offices.

15.Does this Establishment or this Enterprise keep documents of the Balance Sheet and the Income Statements

16.Amount of sales and operating expense per day in a recent month and number of working days

17.Total amounts of assets at the end of December 2009

18.Total amount of equity held at the end of December 2009

19.Total amount of Non-current liabilities at the end of December 2009

20.Total amount of Current liabilities at the end of December 2009

21.Amount of revenue and expense in a year 2009 under “Accrual basis accounting”, which records revenues and related expenses in same period.

Cleaning operations

Coding is a part of the manual editing process that quantifies the descriptive answers to questions that are not pre-coded. The questionnaires used for the Pilot Survey 2010 of economic census have a number of questions for which descriptive answers should be recorded. Descriptive information collected in the survey that should be coded before entering the data into computer are listed below.

Questionnaire Form

• Registration to the Ministry of Commerce or Provincial Department of Commerce Q4.1 to Q4.

• Kind of Main Business Activities which this establishment only is engaged in Q11

• Kind of business activities of the entire enterprise that include not only those of this Head Q14.1 to Q14.2

Sampling error estimates

Not available

Saudi Arabia Average Weekly Hours Worked: Public Administration & Defence, Compulsory Social Security data was reported at 40.846 Hour in Mar 2024. This records an increase from the previous number of 40.838 Hour for Dec 2023. Saudi Arabia Average Weekly Hours Worked: Public Administration & Defence, Compulsory Social Security data is updated quarterly, averaging 41.043 Hour from Mar 2023 (Median) to Mar 2024, with 5 observations. The data reached an all-time high of 41.300 Hour in Jun 2023 and a record low of 40.838 Hour in Dec 2023. Saudi Arabia Average Weekly Hours Worked: Public Administration & Defence, Compulsory Social Security data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.G027: Average Weekly Hours Worked: Based on 2022 Census.

This dataset presents the location of Queensland state schools with full-time enrolments by year level for the years 2013-2017.

The data was collected from the School Census which is conducted on the first Friday of August each year. The Census collects information on students and staff from all non-government establishments that have, as their major activity, the administration or provision of full-time primary, secondary and/or special education.

For further information about this dataset, please visit the Queensland Department of Education - Downloadable Data Files.

Please note:

• AURIN has spatially enabled this data using the Queensland Department of Education - State and Non State School Listings 2012-2018.

• Data is made available through a AURIN-QCIF-RIDL collaboration.

• From 2015, students enrolled at state schools are recorded against their age or ability appropriate year level as determined by their school.

• From 2015, Year 7 became the first year of secondary school in Queensland.

• A half cohort of Prep Year was introduced in 2007 to align with the shift in the compulsory school starting age from 2008. In 2017 the half cohort is in Year 10.

• The school structure in this data is as at August 2017; historical data has been combined for schools which have been amalgamated. For this reason, schools which were created by an amalgamation may have enrolments for years prior to opening.

• The number of schools in this data may differ from the school count cube because there are a small number of schools which do not have enrolments of their own; rather students from other schools attend these schools on an as needs basis. The Lady Cilento Children's Hospital School does not have enrolments of their own.

Abstract

The Census of Public and Semi-Government Sector employment conducted by the Department of Census and Statistics in 1994 is the fourth in the series. Previous censuses in this series were conducted by the Department of Census and Statistics in 1980, 1985 and 1990 respectively. Three censuses administered before 1980 were limited only to Public Sector employment. Those censuses were conducted by the Ministry of Public Administration in 1968, 1972 and 1976. The information collected at the four censuses conducted since 1980 were obtained through the postal medium by an individual questionnaire filled personally by the employees.

A section of Public Sector employees who were previously under the Central Government was absorbed in to the provincial public service in 1990. Since then the information on public sector employees collected at the censuses were collected under the two sectors State and Provincial Public Sectors separately. Information on employees under corporations, statutory boards and public-private companies are collected under the Semi-Government Sector.

With a view in achieving a maximum coverage, a listing of all the institutions under these three sectors was done in 1993. A list of all institutions coming under each ministry of the Central Government was prepared along with the estimated number of employees in each of the institution. This list included; Ministry offices, Departments, Corporations, Authorities, Statutory Boards and Public-Private Companies. Similar lists were also prepared for each of the Provincial Council.

Finally the Census was conducted according to the lists so prepared which included 32 Ministries and 131 Departments under the State Sector and 197 Corporations, Statutory Boards and Public-Private Companies under the Semi-Government Sector. Provincial Public sector employees working under 41 Provincial Ministries under· 8 Provincial councils were enumerated under the Provincial Public Sector.

Geographic coverage

National coverage including institutions in the Nothern and Eastern Provinces.

Total number of employees covered in this census in all three sectors was 739,517 persons.

The sectors being (i) State Sector. (ii) Provincial Public Sector. and (iii) Semi-Government Sector.

(i) The State Sector includes the Ministries and Departments under the Central Government. (ii) The Provincial Public Sector includes the Ministries and institutions under the provincial councils. (iii)The Semi-Government Sector includes the Corporations, Statutory Boards, Authorities and State Banks under the Central Government and Public-Private Companies. (Note:-Public-Private company is a company in which some percentage of shares is owned by the State.)

The employees in the following categories are included in the census. (i) Permanent. (ii) Temporary/Casual. (iii) Employees who work on Contract Basis.

The employees in the following categories are not included in the Census. (i) The personnel attached to armed forces(Army, Navy and Air force). However the civilian staff was not excluded from the census. (ii) The field labourers in the state owned estates.

Much reliance should not be placed on the estimated number of employees as reported by the individual institution. Most of the institutions provided the figure given in budget estimates, instead of the actual number of employees, as the estimated numbers of employees in the institution. Also the estimates provided by the ,institutions which employ temporary/casual workers on a seasonal basis were always seen to be over estimated. Further the estimates provided on the number of employees attached to Provincial Councils could not be considered reliable as the estimates had been prepared mainly based on the cadre position rather than the actual numbers. It is likely that some conceptual problems also may arise in the interpretation of questions for which data is collected, especially because the data is collected through the postal medium. Further it has been reported in the census that there are some employees belonging to lower occupational groups under the State Sector drawing salaries which could be considered fairly high for such occupational categories. It is to be noted here that these are the salaries of the employees who are working in Sri Lanka Foreign Missions. It is important to notice here that the information in this report are provided according to the structure that was in existence at the time of conducting census in 1994.

Total Coverage Rates:

Estimated No of Employees = 812,472 Enumerated No of employees = 739,517 Coverage Rate = 91.0

State sector Response Rates:

Estimated No of Employees = 245,175 Enumerated No of employees = 221,229 Coverage Rate = 90.2

Prov. Pub Sector:

Estimated No of Employees = 326,375 Enumerated No of employees = 291,265 Coverage Rate = 89.2

Semi-Govt:

Estimated No of Employees = 240,922 Enumerated No of employees = 227,023 Coverage Rate = 94.2

Analysis unit

Employees in the Central Government Public Sector/ Corporations/Statutory Boards and 'Public-Private' companies, Provincial public sector and in Local Authorities.

Universe

All employees in the Central Government Public Sector/ Corporations/Statutory Boards and 'Public-Private' companies in Sri Lanka as well as all the persons employed under the Provincial Public sector and in L:ocal Authorities.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was printed in all three languages Sinhala, Tamil and English. The format of the questionnaire used to fill the details of the employees in the Central Government is the same as the one used for Provincial Public Sector and Local Authorities with one exception where a box has been provided to record the Ministry an employee is attached to in the former and the same box is used in the latter to record the Provincial Ministry.

Abstract

Under World Bank contracts (two separate contracts), the Data Analysis and Technical Assistance (DATA) have conducted a three-round survey “Addressing Extreme Poverty in Bangladesh: The Case of monga” in the Northwestern region of Bangladesh to have a better understanding of the causes of the occurrence and persistence of Monga. This survey is specifically designed to permit a scientific and rigorous assessment, of impacts of the Monga which would have implications for policy to mitigate Monga, through follow-up surveys.

The South Asia PREM Sector Unit (SASPR) of the World Bank have undertaken this aforesaid survey. This region experiences seasonal deprivation and a famine-like situation, locally known as Monga, with alarming regularity, along with high incidence of chronic poverty. The primary objective of the task is to provide a better understanding of the causes of the occurrence and persistence of Monga, which would also have implications for broader understanding of extreme poverty in Bangladesh; implications for policy, including proposals for pilot interventions, to help relevant actors such as the government, the NGOs, and the donors to mitigate Monga. The funds for this work have come from the UK Department for International Development (DFID) trust fund (TF091124).

Geographic coverage

The survey covered the following ares, Monga-prone greater Rangpur districts (Kurigram, Gaibandha, Lalmonirhat, Nilphamari, Rangpur) and Bogra district, in the northwestern.

Analysis unit

• Households
• Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

Survey Areas and Survey Population

The survey has both a household level and a community level questionnaire. The survey has households belonging to the Monga-prone greater Rangpur districts (Kurigram, Gaibandha, Lalmonirhat, Nilphamari, Rangpur) with the sampling frame being representative of the diversity of the region. For example, the survey covered the various agro-ecological zones of the region, include households on river banks and away from it, include mainland households as well as char-land households. In addition to Monga area households, the survey has sample from non-Monga area households in the northwestern Bogra district. It is determined by the World Bank that the total sample size is 2,375 rural households selected from about 125 villages/PSUs. There are 95 PSUs in 5 districts of greater Rangpur (Lalmonirhat, Kurigram, Nilphamari, Gaibandha and Rangpur) and 30 PSUs in Bogra districts.

Survey Design and Sampling Strategy

It was decided by the World Bank that the sample size for the study is 2,375 households. Out of these 2,375 households, 1,805 households from 95 PSUs/villages were from Monga-prone greater Rangpur districts (Kurigram, Gaibandha, Lalmonirhat, Nilphamari, Rangpur) and rest 570 households were from non-Monga area, Bogra district, in the northwestern. Sample list of the villages/PSUs from each of the districts were provided by the World Bank.

In the first round of survey, it entailed two sub-surveys: a) Household listing operation: census of households in selected 125 villages with average size of 250 households, if a village size was more than 250 households, village was split using natural/constructed demarcation line such as by using river/canal or village road; and b) the detailed household survey and community component. For the later one it required on-site sampling of required number of households using random sampling technique from the census list and then conducted the household survey on sampled households. For the household sampling from census list a simple random sample selection protocol was developed and used for on-site sample selection. For follow-up 2 rounds of surveys same sample households were tracked and surveyed, only exception is there was no census hence no on-site sampling procedure was adopted for later rounds.

Sampling Protocol

Since village census was compulsory to list all household in the PSUs to sample required 19 households for detailed household survey, it was decided to do the census on the first day of survey in each of the PSUs and in the evening once the census is completed an on-site sampling technique was used to sample 19 households per PSU.

Below is a practical example on sample selection procedure adopted in field after the census is completed. Simple Random Selection of households was performed as follows:

a) Total number of household in the sample village/PSU; in this case it was 300. b) Total number of sample to be selected. In this case the sample size is 19 per PSU. c) So an "Interval" (steps) is estimate by dividing: Total Population/Sample size. In this case 300/19 = 15.79 d) A random number was generated for each of the PSU by using excel worksheet function "rand()". In this case it was 0.164 e) Then the "Interval (step)" was multiplied by random number "Interval X Random number", it gave the value for first sampling number (a non-integer number) = 2.594689447.

Now for the second sampling number the "Interval" value added with first sampling number, for third sampling number again the "Interval value" with second sampling number, and so on until we get all 19 sampling number.

The census was listed per PSU from 1 to Nth number as long as it required to number all the listed households in a PSU. As the sampling numbers are non-integer number, to get an integer that corresponds to the listing number of all households the sampling numbers were converted into integer and added "1" to get the household sample number.

Mode of data collection

Face-to-face [f2f]

Research instrument

Development of Questionnaires

The draft questionnaires for the study have been provided by the World Bank. Later Refinement and adaptation of the questionnaires has been done. Revisions of the questionnaires took place mainly at two instances: 1) initial revision by Consultant upon receipt of the questionnaires; and 2) following the practice session/pretest (testing stage), where the need for further revisions and adaptation has transpired.

After the first draft of questionnaires are received from the World Bank the questionnaires have been revised, modified and reformatted to make it more survey friendly. Then a formative research trip to North-western region (mainly Rangpur and Kurigram) of Bangladesh was arranged to understand living condition and how the people in the monga prone area response in crises. Dr. Umar Serajuddin from the World Bank and Md. Zobair from DATA participated in the formative research trip. After the formative research trip, first draft of the questionnaire has further been revised according to the understanding from formative research.

In follow-up rounds modification of questionnaires mainly due to addition of some questions to or deletion of modules from the survey instrument already fielded in the first round of the survey.

The Census questionnaire collected general information such as, household location, religion, electrification, housing characteristics, land owned by the household, ever migrated for work, participation in 100 days EGP program membership in MFI, asset listing. Furthermore the census survey collected demographic information of the household that includes member specific sex, age, marital status literacy, education in terms of highest class passed, attending school, main occupation. Census questionnaire has been administered to each of the household in the selected villages. For a village the survey considered maximum of 250 household as village size; if a village size was more than 250 households, village has been split using natural/constructed demarcation line such as river/canal or village road. Once the census has been completed, 19 households from each of the villages sampled using random sampling technique for detailed household survey.

Household questionnaire has been administered to each household selected for the survey. The household head, main respondent, was interviewed to complete the household questionnaire. In specific module there are multiple respondent. For an example while interviewing food consumption module, the quantity consumed is answered by the main female while the price of the item was answered by the main male member of the household.

Community questionnaire has been administered to various community leaders such as the large farmer, the principal of a school, local elites. A community questionnaire has been completed in each village in which a household is selected for the survey.

Abstract

In an effort to make adequate and reliable data and information available for scientific policy formulation, planning and implementation of various programmes and projects in education in Ghana, the Ministry of Education launched the Education Management Information System (EMIS) Project in January 1997, with technical support during the first and second Phases from the Harvard University and funds from the World Bank and the Government of Ghana. As an integral part of the Free, Compulsory and Universal Basic Education (FCUBE) Programme, the EMIS Project was planned to build on the already existing EMIS established in 1988 in the Ministry as part of the Education Reforms.

Currently, technical support is being given by UNESCO Institute for Statistics (UIS). Through the EMIS, a strong database has been established within the Ministry of Education. Twenty four basic school censuses have so far been conducted since 1988 and the reports on them are available in the Ministry. This is the seventh senior high school census in recent times. This report is presented to provide and upgrade basic data and planning parameters on enrolment, teaching staff, school facilities and examination results. This year's information on Senior High Schools has been produced at national and regional levels.

Geographic coverage

National level.

Analysis unit

Senior High Schools level with following units of analysis: enrolment, classrooms, facilities, teachers, textbooks, finance, etc

Universe

Senior High School level.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Other [oth]

Research instrument

The questionnaire consists of the following;

• School Identification
• School Profile and Organisation
• School Management and Finance
• Institution's Building and Vehicles
• Characterisitics of School Materials and Equipment
• Enrolment by Subject
• Summary of Enrolment by Programme
• Enrolment by Age
• Students Attendance and Movement
• Teacher Profiles
• Teacher Periods and Subjects Taught
• Students and Teacher Information
• Staff Movement
• Income and Expenditure of the School
• Academic Qualifications
• Professional Qualification
• Management Units
• Ranks

Cleaning operations

1. District Office editing
2. In-built Controls in the application to check for inconsistencies
3. Computer Programs are also run to correct errors

Response rate

Public Schools - 100%

Private Schools - 98%

Data appraisal

No other forms of appraisal reported

The Annual Respondents Database (ARD) is constructed from a compulsory business survey. Until 1997 it was created out of the Annual Censuses of Production and Construction (ACOP and ACOC); these were combined into the Annual Business Inquiry (ABI) in 1998. The ARD is a census of large businesses, and a sample of smaller ones. Smaller firms may receive a "short form". These do not require detailed breakdowns of totals. Hence for certain variables the values may be imputed from third party sources or estimated rather than returned by respondents.

This dataset is created for the Economic Analysis and Satellite Accounts Division for research purposes. To create the ARD, the other surveys are converted into a single consistent format linked by the Inter-Departmental Business Register references over time. Northern Ireland data is held up to 2001. From 2002, the ABI is collected and stored separately in Northern Ireland. Special permission is required to use new NI ABI data.

ABI background
The ABI is the financial information survey conducted by the Office for National Statistics (ONS). This is a statutory survey conducted under the Statistics of Trade Act 1947. Organisations are obliged under this legislation to provide a response. Businesses are sampled from the ONS business register current at the time of drawing the sample: first the CSO Business Register, which ran until 1993; then the Inter-Departmental Business Register, which has run from 1994 onwards. The ONS holds firms' responses to the ABI in the Annual Respondents Database (ARD).

The ABI replaced the following annual survey systems in 1998:

• Annual Employment Survey (AES)
• Annual Censuses of Production and Construction (ACOP/ACOC), which include the Purchases Inquiry (PI)
• The six annual Distribution and Services (DSI) inquiries (Annual Wholesale Inquiry; Annual Retail Inquiry; Annual Motor Trades Inquiry; Annual Catering Inquiry; Annual Property Inquiry; and Annual Service Trades Inquiry

Until 1997 the data were limited to the production and construction industries surveyed by the ACOP and ACOC (construction from 1993 only). The incorporation of the DSI inquiries for six additional sectors is reflected in the number of individual business contributors rising from approximately 15,000 for 1980 to 1996 to approximately 50,000 for 1997/98 and to over 70,000 for 1999.

The ABI is one of the most comprehensive surveys undertaken of business organisations in the UK, covering over 100 key economic variables, and approximately two-thirds of the UK economy. Detailed variables for turnover, employment, costs, capital and the derivation of sales and profits are included. A firm-level measure of Gross Value Added (GVA) is also generated so that the productivity of organisations can be evaluated.

The ABI samples UK businesses and other such establishments according to their employment size and industry sector. It is a census of large businesses, and a stratified sample of small and medium sized enterprises. The stratified sampling framework means that smaller firms move in and out of the survey. The forms are customised for industry sectors and sub-sectors. The statistics produced from the sample data are used primarily to assist in the generation of the National Accounts and the measurement of Gross Domestic Product (GDP).

A number of different form-types are used in the survey. Long form-types are sent to all businesses with an employment of 250 or more and also to a proportion of selected businesses with lower employment. Short form-types are sent to the remaining selected businesses. The forms differ in that long form-types ask for a detailed breakdown of purchases; employment costs; taxes, duties and levies etc, whereas short form-types just ask for the totals of these variables.

The data are collected in two parts: Part 1 is an employment record, collected as soon as possible after 12th December. Part 2 is for financial information, which may be submitted up to twelve months after the financial year end.

Geographical references: postcodes
The postcodes available in these data are pseudo-anonymised postcodes. The real postcodes are not available due to the potential risk of identification of the observations. However, these replacement postcodes retain the inherent nested characteristics of real postcodes, and will allow researchers to aggregate observations to other geographic units, e.g. wards, super output areas, etc. In the dataset, the variable of the replacement postcode is 'new_PC'.

Linking to other business studies
These data contain Inter-Departmental Business Register reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

ARD, the Annual Business Survey (ABS) and the Business Register and Employment Survey (BRES)
The ABI, Part 2 (ABI/2) was replaced by the ABS in 2009. The ABI, Part 1 (ABI/1) was replaced by the BRES in 2009. The BRES data for 2009 onwards are held separately under UK Data Archive SN 7463. ABS data for 2008 onwards are held under UK Data Archive SN 7451. Researchers who are applying for access to the ARD and who require data for 2009 onwards are recommended to also apply for the ABS data under SN 7451.

Definition of chronic health conditions.

Panama Unemployment: Public Administration, Defense & Compulsory Social Security Plans data was reported at 2,822.000 Person in 2017. This records a decrease from the previous number of 3,213.000 Person for 2016. Panama Unemployment: Public Administration, Defense & Compulsory Social Security Plans data is updated yearly, averaging 3,713.000 Person from Aug 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 6,916.000 Person in 2005 and a record low of 1,967.000 Person in 2013. Panama Unemployment: Public Administration, Defense & Compulsory Social Security Plans data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Panama – Table PA.G007: Unemployment.

Panama Unemployment: Female: Public Administration, Defense & Compulsory Social Security Plans data was reported at 1,956.000 Person in 2017. This records an increase from the previous number of 1,669.000 Person for 2016. Panama Unemployment: Female: Public Administration, Defense & Compulsory Social Security Plans data is updated yearly, averaging 2,370.000 Person from Aug 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 4,165.000 Person in 2005 and a record low of 1,119.000 Person in 2013. Panama Unemployment: Female: Public Administration, Defense & Compulsory Social Security Plans data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Panama – Table PA.G007: Unemployment.

Panama Employment: Male: Public Administration, Defense & Compulsory Social Security Plans data was reported at 65,105.000 Person in 2017. This records an increase from the previous number of 63,224.000 Person for 2016. Panama Employment: Male: Public Administration, Defense & Compulsory Social Security Plans data is updated yearly, averaging 48,219.000 Person from Aug 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 65,105.000 Person in 2017 and a record low of 40,892.000 Person in 2005. Panama Employment: Male: Public Administration, Defense & Compulsory Social Security Plans data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Panama – Table PA.G006: Employment and Underemployment.