This study contains economic and employment data for governmental units in states, cities, towns, counties, school districts, and special districts in the United States in 1972. The employment data provide information on the number and functions of full-time and part-time government employees, retirement and insurance coverage extended to full-time employees, membership of employees in employee organizations, and governmental labor policies for the counties and states (Part 1), cities and towns (Part 2), special districts (Part 3), and school districts (Part 4). The finance data provide information on revenues from and expenditures on education, public buildings, highways, health, hospitals, libraries, natural resources, police, sanitation, public welfare, water transportation, and gas and electricity for counties and states (Part 5), cities and towns (Part 6), special districts (Part 7), and school districts (Part 8). Other items include revenues from taxes, and government debts. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR00069.v1. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

This file provides data for October 1982 drawn from the 1982 Census of Governments on full- and part-time employment, full-time equivalent employment, and payroll statistics by type of government (State, county, township, special district, and school district) and by function (elementary and secondary education, police protection, higher education, fire protection, financial administration, central administration, judicial and legal, highways, public welfare, sanitation other than sewerage, sewerage, parks and recreation, health, hospitals, water supply, electric power, gas supply, transit systems, natural resources, corrections, libraries, airports, water transportation, other education, State liquor stores, Employment Security Administration, and housing and urban renewal). Also shown are data on policies for labor-management relations, number of organized employees by function, number of bargaining units, number of employees in bargaining units, number of contractual agreements, and number of employees covered by contractual agreements. State and local data are provided for the 50 States and the Distrcit of Columbia.

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08286.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The Current Population Survey Tobacco Use Supplement data collection from May 2015 is comprised of responses from two sets of survey questionnaires, the basic Current Population Survey (CPS) and a Tobacco Use Supplement (TUS) survey. The TUS 2014-2015 Wave consists of three collections: July 2014, January 2015, and May 2015. The CPS, administered monthly, is the source of the official government statistics on employment and unemployment. From time to time, additional questions are included on health, education, and previous work experience. The Tobacco Use Supplement to the CPS is a National Cancer Institute sponsored survey of tobacco use that has been administered as part of the US Census Bureau's CPS approximately every 3-4 years since 1992-1993. Similar to other CPS supplements, the Tobacco Use Supplement was designed for both proxy and self-respondents. All CPS household members age 18 and older who had completed CPS core items were eligible for the supplement items. A new feature for the 2014-2015 cycle included random selection of self-interviewed respondents in larger households to reduce respondent burden. If the household had only 1 supplement eligible member then that person was selected for self-interview. If the household had only 2 supplement eligible members, then both of them were selected for self-interview. If the household had 3 or 4 supplement eligible members, then 2 of them were randomly selected for self-interview and the remaining were interviewed by proxy. If the household had more than 4 supplement eligible members, then 3 of them were randomly selected for self-interview and the rest of the eligible respondents were interviewed by proxy. Those selected for self-interview were eligible for the entire supplement, whereas proxy respondents were only eligible for an abbreviated interview. Occasionally, those persons to be interviewed by proxy, if available for self- interview, were interviewed directly but asked the abbreviated proxy path questions. Both proxy and self-respondents were asked about their smoking status and the use of other tobacco products. For self-respondents only, different questions were asked depending on their tobacco use status: for former/current smokers, questions were asked about type of cigarettes smoked, measures of addiction, attempts to quit smoking, methods and treatments used to quit smoking, and if they were planning to quit in the future. All self-respondents were asked about smoking policy at their work place and their attitudes towards smoking in different locations. Demographic information within this collection includes age, sex, race, Hispanic origin, marital status, veteran status, immigration status, educational background, employment status, occupation, and income.

Graph and download economic data for Employed full time: Wage and salary workers: Insurance claims and policy processing clerks occupations: 16 years and over: Men (LEU0254610100A) from 2000 to 2024 about clerical workers, occupation, processed, full-time, males, insurance, salaries, workers, 16 years +, wages, employment, and USA.

As of 2024, more than **** of all female employees in Japan were working in non-regular employment, compared to approximately ** percent of men. The share of men in non-permanent employment increased by nearly ***** percentage points in the last two decades. Non-regular employment When compared among age groups, the percentage of those in non-regular employment was lower among younger age cohorts, while the share among those aged 65 years and older was about ** percent in 2024. There are several forms of non-permanent employment in Japan: part-time workers, temporary full-time and part-time workers, and dispatched full-time and part-time workers from temporary labor agencies, among others. In 2024, the majority of the non-regular employees in the nation were working on a part-time basis. Regulations Depending on the qualifications and the contract, the employment falls under different regulations such as Labor Contract Act, Part-time Employment Act, and Act for Securing the Proper Operation of Worker Dispatching Undertakings and Improved Working Conditions for Dispatched Workers. These regulations have been amended several times following the diversification of work contracts in the past decades. The wage gap between permanent and non-permanent workers, for example, has been addressed as one of the main issues in recent years. From 2020 onwards, employers are required to pay the equivalent amount to non-permanent workers when they engage in the same tasks as permanent workers.

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Insurance claims and policy processing clerks occupations: 16 years and over: Women (LEU0254770300A) from 2000 to 2024 about clerical workers, second quartile, occupation, processed, females, full-time, insurance, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

This Hierarchical File, 2016 Census Public Use Microdata File (PUMF) product provides access to non-aggregated data covering a sample of 1% of the Canadian households. It is a comprehensive social, demographic and economic database about Canada and its people, and contains a wealth of characteristics on the population. The file enables the study of individuals in relation to their census families, economic families and households. Geographic identifiers have been restricted to the provinces, the three territories grouped into a region called Northern Canada and selected metropolitan areas (Toronto, Montréal, Vancouver, Edmonton and Calgary) to ensure respondents’ anonymity. This comprehensive file is excellent tool for policy analysts, pollsters, social researchers and anyone interested in modeling and performing statistical regression analysis using 2016 Census microdata.

The Bureau of Justice Statistics' (BJS) 2007 Census of Public Defender Offices (CPDO) collected data from public defender offices located across 49 states and the District of Columbia. Public defender offices are one of three methods through which states and localities ensure that indigent defendants are granted the Sixth and Fourteenth Amendment right to counsel. (In addition to defender offices, indigent defense services may also be provided by court-assigned private counsel or by a contract system in which private attorneys contractually agree to take on a specified number of indigent defendants or indigent defense cases.) Public defender offices have a salaried staff of full- or part-time attorneys who represent indigent defendants and are employed as direct government employees or through a public, nonprofit organization. Public defenders play an important role in the United States criminal justice system. Data from prior BJS surveys on indigent defense representation indicate that most criminal defendants rely on some form of publicly provided defense counsel, primarily public defenders. Although the United States Supreme Court has mandated that the states provide counsel for indigent persons accused of crime, documentation on the nature and provision of these services has not been readily available. States have devised various systems, rules of organization, and funding mechanisms for indigent defense programs. While the operation and funding of public defender offices varies across states, public defender offices can be generally classified as being part of either a state program or a county-based system. The 22 state public defender programs functioned entirely under the direction of a central administrative office that funded and administered all the public defender offices in the state. For the 28 states with county-based offices, indigent defense services were administered at the county or local jurisdictional level and funded principally by the county or through a combination of county and state funds. The CPDO collected data from both state- and county-based offices. All public defender offices that were principally funded by state or local governments and provided general criminal defense services, conflict services, or capital case representation were within the scope of the study. Federal public defender offices and offices that provided primarily contract or assigned counsel services with private attorneys were excluded from the data collection. In addition, public defender offices that were principally funded by a tribal government, or provided primarily appellate or juvenile services were outside the scope of the project and were also excluded. The CPDO gathered information on public defender office staffing, expenditures, attorney training, standards and guidelines, and caseloads, including the number and type of cases received by the offices. The data collected by the CPDO can be compared to and analyzed against many of the existing national standards for the provision of indigent defense services.

Abstract

The Census is the official count of population and dwellings in Tonga, providing a ‘snapshot’ of the society and its most precious resource, its people, at a point in time. The official reference period of the census was midnight, the 30th of November, 2006.

The census provides a unique source of detailed demographic, social and economic data relating the entire population at a single point in time. Census information is used for policy setting and implementation, research, planning and other decision-making. The census is often the primary source of information used for the allocation of public funding, especially in areas such as health, education and social policy. The main users of this information are the government, local authorities, education facilities (such as schools and tertiary organizations), businesses, community organizations and the public in general.

The 2006 Census was taken under the authority of Section 8 of Statistical Act Chap. 53 of 1978 which empowers the Minister of Finance to make regulations necessary to conduct the population Census. This regulation was approved by the Cabinet and cited as Census Regulation 2006. The Census regulations also indicate that the Government Statistician would be responsible for the administration and completion of the Census. In addition, the regulations enabled the Statistics Department to carry out the necessary activities required to plan, manage and implement all the necessary Census activities.

Census planning and management

From a planning and management perspective, the Census had two main objectives. Firstly, it was to ensure that the process of collecting, compiling, evaluating, analyzing and disseminating of demographic, economic and social data was conducted in a timely and accurate manner. The development of procedures and processes for the 2006 Census of Population and Housing made use of the lessons learned in previous censuses, and built upon recommendations for improvements.

Secondly, it was a valuable opportunity for building the capacities of employees of the Statistics Department (SD), thus resulting in enhancing the image, credibility and reputation of the Department and at the same time, strengthening its infrastructure. Emphasis was placed on having a senior staff with a wide perspective and leadership qualities. Through the use of vision, planning, coordination, delegation of responsibility and a strong team spirit, the census work was conducted in an effective and efficient manner. Staffs at all levels were encouraged to have an innovative mindset in addressing issues. Incentives for other parties to participate, both within Statistics Department Tonga Tonga 2006 Census of Population and Housing viii and outside the government, were encouraged. As a result, the wider community including donors such as AusAID, the Secretariat of the Pacific Community (SPC) in Noumea, that provided the technical assistance and the general public, were able to support the census project.

Extensive and detailed planning is needed to conduct a successful census. Areas that required planning include: enumeration procedures and fieldwork, public communication, data processing and output systems, mapping and the design of census block boundaries, dissemination procedures, content determination and questionnaire development and training. These aspects, and how they interacted with each other, played a crucial role in determining the quality of all of the census outputs. Each phase therefore required careful, methodical planning and testing. The details of such activities, and their implementation and responsibilities were assigned to 5 subcommittees composed of staff members of the SD.

Organizational structure of the Census

A census organizational structure is designed to implement a number of interrelated activities. Each of these activities was assigned to a specific sub-committee. The census manuals provided guidelines on processes, organizational structures, controls for quality assurance and problem solving. The challenge for managers was developing a work environment that enabled census personnel to perform all these tasks with a common goal in mind. Each sub-committee was responsible for its own outputs, and specific decisions for specific situations were delegated to the lowest level possible. Problem situations beyond the scope of the sub-committee were escalated to the next higher level.

The organizational structure of the census was as follows: a) The Steering Committee (consisting of the Head of both Government and nongovernment organizations), chaired by Secretary for Finance with the Government Statistician (GS) as secretary. b) The Census Committee (consisted of all sub-committee leaders plus the GS, and chaired by the Assistant Government Statistician (AGS) who was the officer in charge of all management and planning of the Census 2006 operations. c) There were five Sub-committees (each sub-committee consisted of about 5 members and were chaired by their Sub-committee leader). These committees included: Mapping, Publicity, Fieldwork, Training and Data Processing. In this way, every staff member of the SD was involved with the census operation through their participation on these committees.

The census steering committee was a high level committee that approved and endorsed the plans and activities of the census. Policy issues that needed to be addressed were submitted to the steering committee for approval prior to the census team and sub-committees designation of the activities necessary to address the tasks.

Part of the initial planning of the 2006 Census involved the establishment of a work-plan with specific time frames. This charted all activities that were to be undertaken and, their impact and dependencies on other activities. These time frames were an essential part of the overall exercise, as they provided specific guides to the progress of each area, and alerted subcommittees’ team leaders (TL) to areas where problems existed and needed to be addressed. These also provided the SD staff with a clear indication of where and how their roles impacted the overall Census process.

Monitoring of the timeframe was an essential part of the management of the Census program. Initially, weekly meetings were held which involved the GS, AGS and team leaders (TL) of the Census committee. As the Census projects progressed, the AGS and TL’s met regularly with their sub-committees to report on the progress of each area. Decisions were made on necessary actions in order to meet the designated dates. Potential risks that could negatively affect the deadlines and actions were also considered at these meetings.

For the 5 sub-committees, one of their first tasks was to verify and amend their terms of reference using the “Strengths, Weaknesses, Opportunities and Threats” (SWOT) analysis methodology, as it applied to past censuses. Each committee then prepared a work-plan and listed all activities for which that particular sub-committee was responsible. This listing included the assignment of a responsible person, together with the timeline indicating the start and end dates required to complete that particular activity. These work-plans, set up by all the 5 sub-committees, were then used by the AGS to develop a detailed operational plan for all phases of the census, the activities required to complete these phases, start and end dates, the person responsible and the dependencies, - all in a Ghant chart format. These combined work-plans were further discussed and amended in the Census team and reported to the Steering committee on regular basis as required.

Geographic coverage

National coverage, which includes the 5 Divisions and both Urban and Rural Areas of Tonga.

Analysis unit

Individual and Households.

Universe

All individuals in private and institutional households.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The National Population Census was a complete enumeration census, hence no sampling procedure was employed. A Mapping Sub-committee was formed to ensure complete coverage of the country.

The Mapping Sub-committee

Led by Mr. Winston Fainga'anuku, this committee's mandate was to ensure that good quality maps were produced. The objective was to ensure that the maps provided complete coverage of the country, were designed to accommodate a reasonable workload of one census enumerator and, that geographic identifiers could be used for dissemination purposes by the PopGIS system. Collaborations with the Ministry of Land, Survey and Natural Resources (MLSNR) began in 2004 to ensure that digitized maps for Tonga could be used for 2006 Census. Mr. Fainga'anuku was attached to the MLSNR in April 2005 to assist 'Atelea Kautoke, Samuela Mailau, Lilika and others to complete the task of digitizing the maps for Tonga. In addition, frequent visits by Mr. Scott Pontifex from the Secretariat of the Pacific Community (SPC) in Noumea, assisted to ensure that quality digitized maps were prepared. SPC also assisted by lending its digitizer which was used in this mapping project. The staff of the Statistics Department (SD) visited household sites throughout Tongatapu and the main outer islands. This exercise was to redesign the Census Block boundaries by amalgamating or splitting existing census blocks to achieve an average of 50 households per census block. Various updates within the census block maps were made. These included the names of the head of household; roads and other landmarks to ensure that current and accurate information was provided to the enumerators. Reliable maps, both for enumerators and supervisors are necessary ingredients to assist in avoiding any under or over - counting during

Abstract

The census date was midnight, the 23rd of July 2018.

The Census is the official count of population, household and dwellings in Wallis & Futuna and it gives a general overview of the country at one specific point in time: 23rd of July 2018. Since 1969 until 2003, Census has been taken once in every 7 or 6 years and every 5 years from 2003.

The census can be the source of information for allocation of public funding, more particularly in areas such as health, education and social policy. The main users of the information provided by the Census are the government, education facilities (such as schools and tertiary organizations), local authorities, businesses, community organizations and the public in general.

The objectives of Census changed over time shifting from earlier years where they were essentially household registrations and counts, to now where a national population census stands supreme as the most valuable single source of statistical data for Wallis & Futuna. This Census allowed to determine the legal population of Wallis and Futuna in all geographical aspects: Wallis island, Futuna island, the 3 "circonsriptions" (Alo, Sigave, Uvea) and 5 districts (Alo, Sigave, Hahake, Hihifo, Mua).

Census data is now widely used to evaluate: - The availability of basic household needs in key sectors, to identify disadvantaged areas and help set priorities for action plans; - Benefits of development programmes in particular areas, such as literacy, employment and family planning;

In addition, census data is useful to asses manpower resources, identify areas of social concern and for the improvement in the social and economic status of women by giving more information about this part of the population and formulating housing policies and programmes and investment of development funds.

Geographic coverage

National coverage.

Analysis unit

Households and Individuals.

Universe

The Census is covering all people alive on the reference date (23rd of July 2018), that are usually living in Wallis and Futuna - whichever nationality they are, for at least 12 months. The Census covered all household and communitiy members. Communities are considered to be: boarding schools, gendarmerie, retirement homes, religious communities, but also people living in mobile dwelling (e.g. boats) and homeless people.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable as it is a full coverage.

Mode of data collection

Face-to-face [f2f]

Research instrument

There are two types of questionnaire for this Census:

Individual sheet (Feuille de Logement or "FL"): describing the dwelling characteristics and enlisting all the individuals living in it; Individual form (Bulletin Individuel or "BI"): information on each individual that are usually living in the household.

The questionnaires were distributed in French and are available in the "External Resources" section.

Cleaning operations

Data editing was done by SPC in collaboration with Wallis and Futuna NSO.

Sampling error estimates

Not applicable.

To ensure an accurate sampling frame for its Law Enforcement Management and Administrative Statistics (LEMAS) survey, the Bureau of Justice Statistics periodically sponsors a census of the nation's state and local law enforcement agencies. This census, known as the Directory Survey, gathers data on 49 primary state law enforcement agencies and all sheriffs' departments, local police departments, and special police agencies (state or local) that are publicly funded and employ at least one sworn officer with general arrest powers. The 1996 Directory Survey collected data on the number of sworn and nonsworn personnel employed by each agency, including both full-time and part-time employees. Within the full-time sworn category, data were collected from all agencies on the number who were uniformed officers with regularly assigned duties that included responding to calls for service. For agencies with at least 10 full-time sworn officers, the number whose primary duties were related to investigations, court operations, or jail operations was also obtained. This data collection, compiled in June 1996, represents the third such census, with the first occurring in 1986 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1986: [UNITED STATES] [ICPSR 8696]) and the second in 1992 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1992: [UNITED STATES] [ICPSR 2266]). Variables include personnel totals, type of government, type of agency, and whether the agency had the legal authority to hold a person beyond arraignment for 48 or more hours.

The Individuals File, 2021 Census Public Use Microdata Files (PUMF) provides data on the characteristics of the Canadian population. The file contains a 2.7% sample of anonymous responses to the 2021 Census questionnaire. The files have been carefully scrutinized to ensure the complete confidentiality of the individual responses and geographic identifiers have been restricted to provinces/territories and metropolitan areas. With 144 variables, this comprehensive tool is excellent for policy analysts, pollsters, social researchers and anyone interested in modelling and performing statistical regression analysis using the Census.

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Second Homes (Module 4): ownership of a second home by any member of the household and reasons for having the second home. Elderly - use of Services (Module 17): use of health and social services by people aged 65 or over (similar to questions asked in the General Household Survey). Pension Schemes (Module 20): membership of employer's pension schemes (for use as a sift for the GAD survey of pension schemes as on the 1983 and 1987 General Household Survey). Stepchildren (Module 5): existence of step-children of informant/partner in household, receipt of child support payments from parent outside the household and existence of dependent children of informant/partner outside household Armed Forces (Module 23): opinion on whether the armed forces are essential and what advantages/disadvantages a career in the armed forces has for a young man. Census Publicity (Module 24): awareness of different forms of publicity preceding the 1991 Census and recall of the information contained in it. Additional question to form fillers on how long it took to complete the form. Multi-stage stratified random sample Face-to-face interview 1991 AGE AIDS FOR THE DISABLED AIDS FOR THE HEARIN... AIDS FOR THE VISUAL... ARMED FORCES ATTITUDES CARE OF DEPENDANTS CARE OF THE ELDERLY CAREER DEVELOPMENT CENSUS DATA CHILD BENEFITS CHILDREN CHIROPODY CONDITIONS OF EMPLO... DAY CARE DISABILITIES DISABLED FACILITIES DISEASES DOMESTIC EQUIPMENT ... DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND ELDERLY EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ETHNIC GROUPS EXPECTATION Elderly FAMILY MEMBERS FINANCIAL SUPPORT FULL TIME EMPLOYMENT Family life and mar... GENDER GENERAL PRACTITIONERS HEADS OF HOUSEHOLD HEALTH CONSULTATIONS HEALTH SERVICES HEALTH VISITORS HOME HELP HOME OWNERSHIP HOME VISITS HOUSEHOLDS HOUSING HOUSING TENURE Housing INCOME INCONTINENCE AIDS INDUSTRIES INFORMATION SOURCES INTEREST FINANCE INVESTMENT RETURN Income JOB HUNTING JOB SATISFACTION KNOWLEDGE AWARENESS LEAVE LOCAL GOVERNMENT MANAGERS MARITAL STATUS MARRIED MEN MASS MEDIA USE MEN MOTOR VEHICLES Media NURSES OCCUPATIONAL PENSIONS OCCUPATIONS OLD PEOPLE S CLUBS ONE PARENT FAMILIES PARENT RESPONSIBILITY PART TIME EMPLOYMENT PHYSIOTHERAPY PRIVATE SECTOR PUBLIC INFORMATION PUBLIC SECTOR RENTED ACCOMMODATION RESIDENTIAL MOBILITY RETIREMENT RIGHT TO PRIVACY SECOND HOMES SELF EMPLOYED SHARED HOME OWNERSHIP SOCIAL HOUSING SOCIAL SECURITY BEN... STEPCHILDREN STUDENTS SUPERVISORS SURGICAL AIDS Social behaviour an... Specific social ser... UNEMPLOYED WAGES WALKING AIDS property and invest...

The Census is the official count of population and dwellings in Tonga, providing a ‘snapshot’ of the society and its most precious resource, its people, at a point in time. The official reference period of the census was midnight, the 30th of November, 2006.

The census provides a unique source of detailed demographic, social and economic data relating the entire population at a single point in time. Census information is used for policy setting and implementation, research, planning and other decision-making. The census is often the primary source of information used for the allocation of public funding, especially in areas such as health, education and social policy. The main users of this information are the government, local authorities, education facilities (such as schools and tertiary organizations), businesses, community organizations and the public in general.

The 2006 Census was taken under the authority of Section 8 of Statistical Act Chap. 53 of 1978 which empowers the Minister of Finance to make regulations necessary to conduct the population Census. This regulation was approved by the Cabinet and cited as Census Regulation 2006. The Census regulations also indicate that the Government Statistician would be responsible for the administration and completion of the Census. In addition, the regulations enabled the Statistics Department to carry out the necessary activities required to plan, manage and implement all the necessary Census activities.

Census planning and management

From a planning and management perspective, the Census had two main objectives. Firstly, it was to ensure that the process of collecting, compiling, evaluating, analyzing and disseminating of demographic, economic and social data was conducted in a timely and accurate manner. The development of procedures and processes for the 2006 Census of Population and Housing made use of the lessons learned in previous censuses, and built upon recommendations for improvements.

Secondly, it was a valuable opportunity for building the capacities of employees of the Statistics Department (SD), thus resulting in enhancing the image, credibility and reputation of the Department and at the same time, strengthening its infrastructure. Emphasis was placed on having a senior staff with a wide perspective and leadership qualities. Through the use of vision, planning, coordination, delegation of responsibility and a strong team spirit, the census work was conducted in an effective and efficient manner. Staffs at all levels were encouraged to have an innovative mindset in addressing issues. Incentives for other parties to participate, both within Statistics Department Tonga Tonga 2006 Census of Population and Housing viii and outside the government, were encouraged. As a result, the wider community including donors such as AusAID, the Secretariat of the Pacific Community (SPC) in Noumea, that provided the technical assistance and the general public, were able to support the census project.

Extensive and detailed planning is needed to conduct a successful census. Areas that required planning include: enumeration procedures and fieldwork, public communication, data processing and output systems, mapping and the design of census block boundaries, dissemination procedures, content determination and questionnaire development and training. These aspects, and how they interacted with each other, played a crucial role in determining the quality of all of the census outputs. Each phase therefore required careful, methodical planning and testing. The details of such activities, and their implementation and responsibilities were assigned to 5 subcommittees composed of staff members of the SD.

Organizational structure of the Census

A census organizational structure is designed to implement a number of interrelated activities. Each of these activities was assigned to a specific sub-committee. The census manuals provided guidelines on processes, organizational structures, controls for quality assurance and problem solving. The challenge for managers was developing a work environment that enabled census personnel to perform all these tasks with a common goal in mind. Each sub-committee was responsible for its own outputs, and specific decisions for specific situations were delegated to the lowest level possible. Problem situations beyond the scope of the sub-committee were escalated to the next higher level.

The organizational structure of the census was as follows: a) The Steering Committee (consisting of the Head of both Government and nongovernment organizations), chaired by Secretary for Finance with the Government Statistician (GS) as secretary. b) The Census Committee (consisted of all sub-committee leaders plus the GS, and chaired by the Assistant Government Statistician (AGS) who was the officer in charge of all management and planning of the Census 2006 operations. c) There were five Sub-committees (each sub-committee consisted of about 5 members and were chaired by their Sub-committee leader). These committees included: Mapping, Publicity, Fieldwork, Training and Data Processing. In this way, every staff member of the SD was involved with the census operation through their participation on these committees.

The census steering committee was a high level committee that approved and endorsed the plans and activities of the census. Policy issues that needed to be addressed were submitted to the steering committee for approval prior to the census team and sub-committees designation of the activities necessary to address the tasks.

Part of the initial planning of the 2006 Census involved the establishment of a work-plan with specific time frames. This charted all activities that were to be undertaken and, their impact and dependencies on other activities. These time frames were an essential part of the overall exercise, as they provided specific guides to the progress of each area, and alerted subcommittees’ team leaders (TL) to areas where problems existed and needed to be addressed. These also provided the SD staff with a clear indication of where and how their roles impacted the overall Census process.

Monitoring of the timeframe was an essential part of the management of the Census program. Initially, weekly meetings were held which involved the GS, AGS and team leaders (TL) of the Census committee. As the Census projects progressed, the AGS and TL’s met regularly with their sub-committees to report on the progress of each area. Decisions were made on necessary actions in order to meet the designated dates. Potential risks that could negatively affect the deadlines and actions were also considered at these meetings.

For the 5 sub-committees, one of their first tasks was to verify and amend their terms of reference using the “Strengths, Weaknesses, Opportunities and Threats” (SWOT) analysis methodology, as it applied to past censuses. Each committee then prepared a work-plan and listed all activities for which that particular sub-committee was responsible. This listing included the assignment of a responsible person, together with the timeline indicating the start and end dates required to complete that particular activity. These work-plans, set up by all the 5 sub-committees, were then used by the AGS to develop a detailed operational plan for all phases of the census, the activities required to complete these phases, start and end dates, the person responsible and the dependencies, - all in a Ghant chart format. These combined work-plans were further discussed and amended in the Census team and reported to the Steering committee on regular basis as required.

Version 01 - Edited, cleaned, de-identified and labelled version of the Master file.

The scope of the National Population Census includes personal information on individual characteristics, health, education, literacy, labor market and reproduction.

The scope of the Household module includes information on dwelling style, energy, goods present in the HH, technology, waste, tenure, income, remittances and mortality.

• Collection start: 2006
• Collection end: 2006

Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 1.

​

The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification.

​

The variables for part 2 of the dataset are:

• Individual home ownership for the census usually resident population count aged 15 years and over
• Usual residence 1 year ago indicator
• Usual residence 5 years ago indicator
• Years at usual residence
• Average years at usual residence
• Years since arrival in New Zealand for the overseas-born census usually resident population count
• Average years since arrival in New Zealand for the overseas-born census usually resident population count
• Study participation
• Main means of travel to education, by usual residence address for the census usually resident population who are studying
• Main means of travel to education, by education address for the census usually resident population who are studying
• Highest qualification for the census usually resident population count aged 15 years and over
• Post-school qualification in New Zealand indicator for the census usually resident population count aged 15 years and over
• Highest secondary school qualification for the census usually resident population count aged 15 years and over
• Post-school qualification level of attainment for the census usually resident population count aged 15 years and over
• Sources of personal income (total responses) for the census usually resident population count aged 15 years and over
• Total personal income for the census usually resident population count aged 15 years and over
• Median ($) total personal income for the census usually resident population count aged 15 years and over
• Work and labour force status for the census usually resident population count aged 15 years and over
• Job search methods (total responses) for the unemployed census usually resident population count aged 15 years and over
• Status in employment for the employed census usually resident population count aged 15 years and over
• Unpaid activities (total responses) for the census usually resident population count aged 15 years and over
• Hours worked in employment per week for the employed census usually resident population count aged 15 years and over
• Average hours worked in employment per week for the employed census usually resident population count aged 15 years and over
• Industry, by usual residence address for the employed census usually resident population count aged 15 years and over
• Industry, by workplace address for the employed census usually resident population count aged 15 years and over
• Occupation, by usual residence address for the employed census usually resident population count aged 15 years and over
• Occupation, by workplace address for the employed census usually resident population count aged 15 years and over
• Main means of travel to work, by usual residence address for the employed census usually resident population count aged 15 years and over
• Main means of travel to work, by workplace address for the employed census usually resident population count aged 15 years and over
• Sector of ownership for the employed census usually resident population count aged 15 years and over
• Individual unit data source.

​

Download lookup file for part 2 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

​

Footnotes

Te Whata

Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.

​

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

​

Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

​

​

Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.

​

Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

​

Study participation time series

In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.

​

About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

​

Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

​

Concept descriptions and quality ratings

Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.

​

Disability indicator

This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.

Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.

​

Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

​

Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

​

Measures

Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value

Abstract

The main objectives of LFS are to collect information, mainly on the supply side of the labour market, i.e., information on those who are working or who are actively looking for work. The LFS collects social and economic information for use in the following areas:

• Macro-economic monitoring: The change in the number of people employed is an indicator of changes in economic activity. It is necessary to track these changes, specifically the types of jobs and the industries in which people work.
• Human resource development policies: The economy is changing all the time. In order to meet the needs of the changing economy, people need to be vocationally trained. LFS enables the identification of areas of training.
• Employment policies: For an economy to work at its maximum potential, all those wanting to have work should have jobs. Some people may wish to have full-time jobs and can only find part-time work. Knowing how many of these people there are can enable the Government to design policies that encourage full-employment.
• Income support and social programmes: For the majority of people, employment income is their main means of support. People not only need jobs but also productive jobs in order to receive reasonable incomes. Government needs to know what levels of income are being earned by different groups of persons.

Geographic coverage

National coverage

Analysis unit

Household member age 15-64 years old.

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified two-stage sample design was used for the 2014 Kosovo LFS. The sampling frame was based on the data and cartography from the 2011 Kosovo Census. For the purposes of the census enumeration, Kosovo was subdivided into enumeration areas (EAs), which are relatively small operational segments defined for the census enumeration. A total of 4,626 EAs were defined for Kosovo, and these were used as the primary sampling units (PSUs) selected at the first sampling stage for the LFS. The overall average number of households per EA in the sampling frame was 67; the average size of the urban EAs (103 households) was almost twice that for the rural EAs (53 households). One census enumerator was responsible for enumerating the households and population in each EA. KAS used the 2011 Census data to compile a sampling frame of EAs that was used for selecting the LFS sample.

Kosovo is divided geographically into seven regions. KAS uses these seven regions for stratifying the sampling frame and for reporting the results from their household surveys. Each region is divided into municipalities, which are further subdivided into towns or localities. The EAs were defined within the smallest administrative units. Each EA was classified as urban or rural, and this classification was used for defining sampling strata within each region.

Mode of data collection

Face-to-face [f2f]

Abstract copyright UK Data Service and data collection copyright owner.The General Household Survey (GHS), ran from 1971-2011 (the UKDS holds data from 1972-2011). It was a continuous annual national survey of people living in private households, conducted by the Office for National Statistics (ONS). The main aim of the survey was to collect data on a range of core topics, covering household, family and individual information. This information was used by government departments and other organisations for planning, policy and monitoring purposes, and to present a picture of households, families and people in Great Britain. In 2008, the GHS became a module of the Integrated Household Survey (IHS). In recognition, the survey was renamed the General Lifestyle Survey (GLF). The GLF closed in January 2012. The 2011 GLF is therefore the last in the series. A limited number of questions previously run on the GLF were subsequently included in the Opinions and Lifestyle Survey (OPN). Secure Access GHS/GLF The UKDS holds standard access End User Licence (EUL) data for 1972-2006. A Secure Access version is available, covering the years 2000-2011 - see SN 6716 General Lifestyle Survey, 2000-2011: Secure Access. History The GHS was conducted annually until 2011, except for breaks in 1997-1998 when the survey was reviewed, and 1999-2000 when the survey was redeveloped. Further information may be found in the ONS document An overview of 40 years of data (General Lifestyle Survey Overview - a report on the 2011 General Lifestyle Survey) (PDF). Details of changes each year may be found in the individual study documentation. EU-SILC In 2005, the European Union (EU) made a legal obligation (EU-SILC) for member states to collect additional statistics on income and living conditions. In addition, the EU-SILC data cover poverty and social exclusion. These statistics are used to help plan and monitor European social policy by comparing poverty indicators and changes over time across the EU. The EU-SILC requirement was integrated into the GHS/GLF in 2005. After the closure of the GLF, EU-SILC was collected via the Family Resources Survey (FRS) until the UK left the EU in 2020.Reformatted GHS data 1973-1982 - Surrey SPSS Files SPSS files were created by the University of Surrey for all GHS years from 1973 to 1982 inclusive. The early files were restructured and the case changed from the household to the individual with all of the household information duplicated for each individual. The Surrey SPSS files contain all the original variables as well as some extra derived variables (a few variables were omitted from the data files for 1973-76). In 1973 only, the section on leisure was not included in the Surrey SPSS files. This has subsequently been made available, however, and is now held in a separate study, General Household Survey, 1973: Leisure Questions (SN 3982). Records for the original GHS 1973-1982 ASCII files have been removed from the UK Data Archive catalogue, but the data are still preserved and available upon request. Main Topics:The main GHS consisted of a household questionnaire, completed by the Household Reference Person (HRP), and an individual questionnaire, completed by all adults aged 16 and over resident in the household. A number of different trailers each year covering extra topics were included in later (post-review) surveys in the series from 2000.The household questionnaire covered the following topics: household information, accommodation type, housing tenure/costs, and consumer durables including vehicle ownership.The individual questionnaire included data from the household dataset, and additional sections on migration/citizenship/national identity/ethnicity, employment, pensions, education, health, child care, smoking, drinking, family information, financial situation, and income. Multi-stage stratified random sample Face-to-face interview 2004 2005 ACADEMIC ACHIEVEMENT ADOLESCENTS ADOPTED CHILDREN ADULTS AGE ALCOHOL USE ALCOHOLIC DRINKS APARTMENTS APPRENTICESHIP ATTITUDES BATHROOMS BEDROOMS BINGE DRINKING BONUS PAYMENTS BUILDING MAINTENANCE BUSINESSES CAR PARKING AREAS CARE OF DEPENDANTS CENTRAL HEATING CHILD BENEFITS CHILDREN CHRONIC ILLNESS COHABITATION COLOUR TELEVISION R... COMMUNITIES COMPACT DISC PLAYERS COMPUTERS CONSUMER GOODS COOKING COUNCIL TAX CRIME VICTIMS CRIMINAL DAMAGE CULTURAL GOODS DEBILITATIVE ILLNESS DENTAL CARE DENTAL EXAMINATIONS DENTAL HEALTH DENTAL TREATMENT DIGITAL TELEVISION DISABILITIES DISABLED PERSONS DISEASES DIVORCE DOGS DOMESTIC APPLIANCES DRUG ABUSE ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EDUCATIONAL INSTITU... ELDERLY EMPLOYEES EMPLOYERS EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ETHNIC GROUPS EXPOSURE TO NOISE Education FAMILIES FAMILY MEMBERS FAMILY PLANNING FATHER S PLACE OF B... FINANCIAL RESOURCES FINANCIAL SUPPORT FOSSIL FUELS FOSTER CHILDREN FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION GENDER GENERAL PRACTITIONERS General health and ... HEADS OF HOUSEHOLD HEALTH HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEALTH SERVICES HIGHER EDUCATION HOME OWNERSHIP HOME SHARING HOSPITAL OUTPATIENT... HOSPITAL SERVICES HOSPITALIZATION HOSPITALIZED CHILDREN HOURS OF WORK HOUSEHOLD INCOME HOUSEHOLDS HOUSES HOUSING HOUSING AGE HOUSING FACILITIES HOUSING TENURE Health care service... Housing IMMIGRATION INCOME INDUSTRIES INFANTS INTEREST FINANCE INTERNET INTERNET ACCESS INTERPERSONAL RELAT... INVESTMENT INVESTMENT RETURN JOB HUNTING JOB SEEKER S ALLOWANCE KITCHENS LANDLORDS LOCAL COMMUNITY FAC... Labour and employment MARITAL HISTORY MARITAL STATUS MARRIAGE MARRIAGE DISSOLUTION MEDICAL CARE MEDICAL PRESCRIPTIONS MOBILE HOMES MORTGAGES MOTHER S PLACE OF B... MOTOR VEHICLES NEIGHBOURHOODS NURSES OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONAL TRAINING OCCUPATIONS ONE PARENT FAMILIES PARENTS PART TIME EMPLOYMENT PATIENTS PENSION CONTRIBUTIONS PENSIONS PHYSICIANS PLACE OF BIRTH POLICE SERVICES PREGNANCY PRIVATE HEALTH SERV... PRIVATE PERSONAL PE... PUBLIC TRANSPORT QUALIFICATIONS REFUSE RENTED ACCOMMODATION RENTS RESIDENTIAL MOBILITY ROAD TRAFFIC ROOM SHARING ROOMS SATELLITE RECEIVERS SAVINGS SCHOOLS SELF EMPLOYED SHARED HOME OWNERSHIP SHARES SHELTERED HOUSING SMOKING SMOKING CESSATION SOCIAL CAPITAL SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIO ECONOMIC STATUS SPOUSE S ECONOMIC A... SPOUSE S EMPLOYMENT SPOUSES STAKEHOLDER PENSIONS STATE HEALTH SERVICES STATE RETIREMENT PE... STEPCHILDREN STUDENTS SUBSIDIARY EMPLOYMENT SUPERVISORY STATUS Social conditions a... Specific social ser... TAX RELIEF TEACHER QUALIFICATIONS TELEPHONES TELEVISION CHANNELS TELEVISION RECEIVERS TIED HOUSING TOBACCO TRAINING COURSES UNEARNED INCOME UNEMPLOYED UNFURNISHED ACCOMMO... UNWAGED WORKERS VIDEO RECORDERS VOCATIONAL EDUCATIO... WAGES WIDOWED YOUTH

Abstract

The Namibia Labour Force Survey 2008 provides basic data required for policy making at national and regional levels as well as for different sectors.

The two main objectives for the survey were: • To measure the extent of available and unused labour time and human resources for the purpose of macro-economic monitoring and human resources development planning. • To measure the relationship between employment and other socio-economic characteristics for purposes of formulating and monitoring employment policies and programmes, income generating and monitoring schemes, vocational training and other similar programmes.

More specifi cally, the survey was designed to provide: a) Basic information on the size and structure of the country’s work force. b) Basic elements for measuring the labour supply as well as its input and the extent to which the available human resources are utilized in the production process of the economy. c) A prospective basis for projections of the economically active population and its components for socio-economic planning. d) A basis for research in many areas ranging from testing labour market segmentation theories to formulating demographic models. e) To the public, information on the employment situation of the country. When properly disaggregated by geographic area, the data may provide information on the situation in local markets especially on the number of persons available in specifi c occupational categories. f) To the business community, useful indicators on the future course of the economy. g) Basic information on the size of the informal economy.

Geographic coverage

National

Analysis unit

• Household
• Individual

Universe

Whole population excluding the following groups: Persons living in institutions such as hospitals, hostels, barracks and prisons.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample design The sample design for the survey was a stratified two-stage probability sample where the first stage units were geographical areas designated as the Primary Sampling Units (PSUs) and the second stage units were the households. The first stage units were selected from the sampling frame of PSUs and the second stage units were selected from a current list of households within the PSU, which was compiled just before the interviews for the survey.

The Master Sample Frame and stratification The national sampling frame, which is maintained by the Central Bureau of Statistics (CBS), is based on the enumeration areas (EAs) of the 2001 Population and Housing Census and the households within the EAs. One PSU could be an EA, Part of an EA or more than one EA. The frame was stratifi ed first by regions and then by urban/rural areas within each region. PSUs in the urban areas were further stratified into the high, middle or low levels of living according to the geographical location and the level of housing. In the regions where these levels contain large number of PSUs separate strata were made, while in the other regions a combined list of PSUs ordered by the levels was made. In the rural areas large proclaimed settlements and villages were stratifi ed separately while the others were combined with the communal area PSUs. Communal and commercial area PSUs were grouped separately and combined to form one list for the rural strata. After all the above groupings the PSUs were geographically ordered within the strata.

Sample size and the master sample Sample size was determined in order to make reliable estimates at the National urban/ rural and region level. This requirement was satisfied by the Master Sample, which is designed by the CBS to be used for number of surveys and hence was used for this survey also. This is actually the first stage sample, which consists of 239 PSUs. The number of households per PSU was fixed at 25. Additions to the number of sample households within the PSU would not add much to the improvement of the precision but would only increase the cost. The final sample consisted of 5,975 households in 239 PSUs.

Sample allocation The PSUs were first allocated to the major domains of estimation (regions) proportional to their population sizes (Number of households). Then further allocation was carried out for separate strata within the major domains.

Note: See Chapter 2 (in final survey report) for the details of the sample design.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the Technical Committee of the Ministry of Labour and Social Welfare in consultation with various users and producers of labour statistics. The questionnaire consists of the following sections: Section A: Identification particulars of the household, including its geographical location Section B: Information on all persons who were members of the household during the survey collection Section C: Information on the education for those aged 6 years and above Section D: Information on the current activities of the adult population 10 years and above Section E: Information on employed household members (who have worked the last 7 days or who had a job but did not work) Section F: Information on hours worked (who have worked the last 7 days or who had a job but did not work) Section G: Information on unemployment (who have not worked during the last 7 days, had no job and were ready to work) Section H: Employees Section I: Employers, own account workers Section J: Housing conditions Section K: Control information

Cleaning operations

Manual processing was done in the field. Therefore the information from the field was ready for data capture. Around 20 data entry operators were recruited and worked in different shifts for about two months. The data entry operators were temporary staff. The Census and Survey Processing System (CSPro) software, a US Census Bureau product, was used for data capture. SPSS software was used for data cleaning, tabulation and analysis together with other packages such as the Microsoft Excel.

The editing and coding of the questionnaires were handled in the regional centers. This arrangement, proved to be efficient as many of the errors made by the interviewers were detected and corrected by them before the questionnaires left the regional centers. A further benefit was the improvement of the processing speed since this process ran parallel to the fieldwork.

Substantial coding inconsistencies were nevertheless detected in the analysis stage. Since these mainly concerned the occupation and industry of employed persons, it was possible to correct them using the answers provided to related questions. The inconsistencies were primarily due to the insufficient time allocated for the training of coders, and perhaps also to inadequate time for coding itself.