The forecast shows the average PC age of global installed base between 2005 and 2015. In 2012, the average age is expected at about 5.1 years.

The forecast shows the average desktop PC age of global installed base between 2005 and 2015. In 2012, the average PC age is expected at about 6.4 years.

The average age across all municipalities in Denmark saw no significant changes in 2024 in comparison to the previous year 2023 and remained at around 42.4. Still, the average age reached its highest value in the observed period in 2024.

This statistic shows the average age of freight rail cars in the United States from 2005 to 2011. In 2010, the average age of all U.S. freight rail cars was 24.5 years.

Average age of women at first child deliveryData Source: Lao Population and Housing Census 2005Contact: Ministry of Planning and Investment, Lao Statistics Bureau, Dongnasokneua Village, Sikhottabong District, Vientiane Capital Email: lstats@lsb.gov.la ; Tel: (+85621) 214740, Fax: (+86521) 242022ອາຍຸສະເລ່ຍຂອງແມ່ຍິງໃນເວລາເກີດລູກ ທຳອິດການສຳຫລວດສຳມະໂນປະຊາກອນ 2005ກະຊວງແຜນການ ແລະ ການລົງທຶນ ສູນສະຖິຕິແຫ່ງຊາດ ບ້ານດົງນາໂຊກເໜືອ, ເມືອງສີໂຄດຕະບອງ, ແຂວງນະຄອນຫລວງວຽງຈັນ. ໂທ: (+856 21)214740, ແຟັກ: (+856 21)242022. ອີເມລວ: lstats@lsb.gov.la

Average age by first name normally used and year

Average of actual hours worked for persons aged 15-74 (LFS) with children living at home by marital status, sex, Age of the youngest child, observations and year

Since 1946, the Central Bureau of Statistics has held regularly research on regional income distribution. These studies are mainly based on registers from the Ministry of Finance (the tax registers) and the Dutch municipalities (de population registers = GBA). The final results from the Regional Income research (RIO) is based on a sample of more than 1.9 million households.

Income distributions of persons or households, by country, province, COROP area, metropolitan agglomeration, urban region and municipality.

Data available from: 2005 These renewed figures from the 2005 RIO relate to 'provisional figures. For RIO 2005, a new production run of the income production system took place with improved input data from the tax registers of 2005. With this improved input data, the number of data to be imputed on micro level from previous research years (2004 and 2003) substantially less this improves the quality of output. It is now apparent from the plausibility contoles that in the numbers and amounts small differences are found in relation to the previous production run from the beginning of this year, we are forced to have the existing RIO 2005 output to be revised. The reference date is 1 January 2006; the data relate to the research year 2005.

Frequency: one-off Because the municipal division changes annually, the results are published from the RIO for each individual research year; merging or division of municipalities will result in all information related to income in a newly formed or split municipality can change so that comparability over time is not possible.

Changes between 2005 and 2015 in the average age of women at first child deliveryData Source: Lao Population and Housing Census 2005-2015Contact: Ministry of Planning and Investment, Lao Statistics Bureau, Dongnasokneua Village, Sikhottabong District, Vientiane Capital Email: lstats@lsb.gov.la ; Tel: (+85621) 214740, Fax: (+86521) 242022ການປ່ຽນແປງລະຫວ່າງປີ 2005 ແລະ 2015 ໃນອາຍຸສະເລ່ຍຂອງແມ່ຍິງໃນເວລາເກີດລູກ ທຳ ອິດການສຳຫລວດສຳມະໂນປະຊາກອນ 2005-2015ກະຊວງແຜນການ ແລະ ການລົງທຶນ, ສູນສະຖິຕິແຫ່ງຊາດ ບ້ານດົງນາໂຊກເໜືອ, ເມືອງສີໂຄດຕະບອງ, ແຂວງນະຄອນຫລວງວຽງຈັນ. ໂທ: (+856 21)214740, ແຟັກ: (+856 21)242022. ອີເມລວ: lstats@lsb.gov.la

The information on public sector contractual salaries is published as part of the Ministry of Internal Affairs' publication key figures on public sector employees. This publication annually describes the composition and the number of persons employed in eleven public sectors. Statistics Netherlands provides data on six public sectors, i.e. municipalities, provinces, district water boards, intermunicipal corporations, university hospitals and the police force. The Ministry of Internal Affairs provide from 2002 the public sector police force itself.

Data available from: 1997 Frequency: yearly

Status of the figures: The figures from 1997 until 2005 are final.

When will new figures be published? The table is canceled because the information on public sector contractual salaries is now published by the 'Ministry of Internal Affairs'.

Edat mitjana de les persones empadronades a domicilis de Barcelona agrupades per estructura del domicili segons el Padró Municipal d'Habitants a data 1 de gener de cada any

Abstract

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates (for consumer units or CUs) of average expenditures in news releases, reports, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (see Section XVI. Appendix 5). These microdata files present detailed expenditure and income data for the Diary component of the CE for 2005. They include weekly expenditure (EXPD), annual income (DTBD) files, and imputed income files (DTID). The data in EXPD, DTBD, and DTID files are categorized by a Universal Classification Code (UCC). The advantage of the EXPD and DTBD files is that with the data classified in a standardized format, the user may perform comparative expenditure (income) analysis with relative ease. The FMLD and MEMD files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLD files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files. Estimates of average expenditures in 2005 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2005. A list of recent publications containing data from the CE appears at the end of this documentation.

The microdata files are in the public domain and, with appropriate credit, may be reproduced without permission. A suggested citation is: “U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Diary Survey, 2005”.

State Identifier Since the CE is not designed to produce state-level estimates, summing the consumer unit weights by state will not yield state population totals. A CU's basic weight reflects its probability of selection among a group of primary sampling units of similar characteristics. For example, sample units in an urban nonmetropolitan area in California may represent similar areas in Wyoming and Nevada. Among other adjustments, CUs are post-stratified nationally by sex-age-race. For example, the weights of consumer units containing a black male, age 16-24 in Alabama, Colorado, or New York, are all adjusted equivalently. Therefore, weighted population state totals will not match population totals calculated from other surveys that are designed to represent state data.

To summarize, the CE sample was not designed to produce precise estimates for individual states. Although state-level estimates that are unbiased in a repeated sampling sense can be calculated for various statistical measures, such as means and aggregates, their estimates will generally be subject to large variances. Additionally, a particular state-population estimate from the CE sample may be far from the true state-population estimate.

Interpreting the data Several factors should be considered when interpreting the expenditure data. The average expenditure for an item may be considerably lower than the expenditure by those CUs that purchased the item. The less frequently an item is purchased, the greater the difference between the average for all consumer units and the average of those purchasing. (See Section V.B. for ESTIMATION OF TOTAL AND MEAN EXPENDITURES). Also, an individual CU may spend more or less than the average, depending on its particular characteristics. Factors such as income, age of family Members, geographic location, taste and personal preference also influence expenditures. Furthermore, even within groups with similar characteristics, the distribution of expenditures varies substantially.

Expenditures reported are the direct out-of-pocket expenditures. Indirect expenditures, which may be significant, may be reflected elsewhere. For example, rental contracts often include utilities. Renters with such contracts would record no direct expense for utilities, and therefore, appear to have no utility expenses. Employers or insurance companies frequently pay other costs.CUs with Members whose employers pay for all or part of their health insurance or life insurance would have lower direct expenses for these items than those who pay the entire amount themselves. These points should be considered when relating reported averages to individual circumstances.

The Diary survey PUMD are organized into five major data files for each quarter: 1. FMLD - a file with characteristics, income, and summary level expenditures for the household 2. MEMD - a file with characteristics and income for each member in the household
3. EXPD - a detailed weekly expenditure file categorized by UCC 4. DTBD - a detailed annual income file categorized by UCC
5. DTID - a household imputed income file categorized by UCC

Analysis unit

Consumer Unit

Kind of data

Sample survey data [ssd]

Sampling procedure

A. SURVEY SAMPLE DESIGN

Samples for the CE are national probability samples of households designed to be representative of the total U. S. civilian population. Eligible population includes all civilian noninstitutional persons.

The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2005 sample is composed of 102 areas. The design classifies the PSUs into four categories:

• 28 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 42 "B" PSUs, are medium-sized MSAs. • 16 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 16 "D" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI.

The sampling frame (that is, the list from which housing units were chosen) for the 2005 survey is generated from the 2000 Population Census file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (EDs) from the Census that fail to meet the criterion for good addresses for new construction, and all EDs in nonpermit-issuing areas are grouped into the area segment frame.

To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance.

Each selected sample unit is requested to keep two 1-week diaries of expenditures over consecutive weeks. The earliest possible day for placing a diary with a household is predesignated with each day of the week having an equal chance to be the first of the reference week. The diaries are evenly spaced throughout the year.

B. COOPERATION LEVELS

The annual target sample size at the United States level for the Diary Survey is 7,800 participating sample units. To achieve this target the total estimated work load is 11,275 sample units. This allows for refusals, vacancies, or nonexistent sample unit addresses.

Each participating sample unit selected is asked to keep two 1-week diaries. Each diary is treated independently, so response rates are based on twice the number of housing units sampled.

Mode of data collection

Computer Assisted Personal Interview [capi]

Response rate

The response rate for the 2005 Diary Survey is 68.9%. This response rate refers to all diaries in the year.

Estonia EE: Age Dependency Ratio: % of Working-Age Population data was reported at 55.811 % in 2017. This records an increase from the previous number of 54.671 % for 2016. Estonia EE: Age Dependency Ratio: % of Working-Age Population data is updated yearly, averaging 51.070 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 55.811 % in 2017 and a record low of 46.868 % in 2005. Estonia EE: Age Dependency Ratio: % of Working-Age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Estonia – Table EE.World Bank.WDI: Population and Urbanization Statistics. Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: this indicator implies the dependency burden that the working-age population bears in relation to children and the elderly. Many times single or widowed women who are the sole caregiver of a household have a high dependency ratio.

Average duration of unemployment and number of unemployed persons aged 15-74 (LFS) by sex, age, observations and year

This census is the seventh enumeration of state adult correctional institutions and the fourth of federal institutions sponsored by the Bureau of Justice Statistics and conducted by the Bureau of the Census. Earlier censuses were completed in 1979 (ICPSR 7852), 1984 (ICPSR 8444), 1990 (ICPSR 9908), 1995 (ICPSR 6953), and 2000 (ICPSR 4021). For each facility, information was provided on physical security, age, functions, capacity, court orders for specific conditions, one-day counts and average populations, race/ethnicity of inmates, inmate work assignments, inmate deaths, special inmate counts, assaults, and incidents caused by inmates.

Denmark DK: Net Intake Rate in Grade 1: % of Official School-Age Population data was reported at 80.567 % in 2009. This records an increase from the previous number of 72.773 % for 2005. Denmark DK: Net Intake Rate in Grade 1: % of Official School-Age Population data is updated yearly, averaging 80.567 % from Dec 2000 (Median) to 2009, with 3 observations. The data reached an all-time high of 86.069 % in 2000 and a record low of 72.773 % in 2005. Denmark DK: Net Intake Rate in Grade 1: % of Official School-Age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Denmark – Table DK.World Bank: Education Statistics. Net intake rate in grade 1 is the number of new entrants in the first grade of primary education who are of official primary school entrance age, expressed as a percentage of the population of the corresponding age.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Abstract

The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular.

MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

Survey Objectives The 2005 Serbia Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Serbia. - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Serbia and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

Survey Implementation The survey was carried out by the Statistical Office of the Republic of Serbia and the Strategic Marketing Research Agency, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

In 2005 Serbia and Montenegro was the State Union composed of the Republic of Serbia (92.5% of population) and the Republic of Montenegro (7.5% of total population). The MICS 2005 survey was planned and implemented on the whole territory of Serbia and Montenegro, and all documents regarding survey plan and contracts with implementing agencies covered the State Union. In May, 2006 the Republic of Montenegro had a referendum of independency and the State Union broke apart. The results of MICS 2005 survey were presented separately for both countries and two separate reports were prepared.

The survey was implemented by the Statistical Office of the Republic of Serbia (in Serbia) and the Statistical Office of the Republic of Montenegro (in Montenegro) and the expert research agency - Strategic Marketing & Media Research Institute (SMMRI), which covered the survey implementation in both Serbia and Montenegro.

Special tasks performed by the Statistical Office of the Republic of Serbia: Preparation of questionnaire for the survey: Preparation of methodological guidelines for realization of the survey; Updating of lists of households in the selected census block units; Conducting the pilot ; Selection of households to be covered by sample; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Special tasks performed by the SMMRI: Sample selection; Preparation of survey tools; Organising the training; Conducting the pilot; Updating of lists of households in the selected census block units; Organising field work; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Data processing and analysis; Preparation of report.

Geographic coverage

The sample for the Serbia Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for urban and rural areas, and for six regions: Vojvodina, Belgrade, West, Central, East and South-East Serbia. Belgrade has a large population (almost one-quarter of the total) and its predominantly urban characteristics make it necessary to separate it from the rest of Central Serbia, to which it administratively belongs. In order to look more deeply into existing ethnic disparities and to provide national estimates, a separate sample was designed for Roma living in Roma settlements.

Analysis unit

Households (defined as a group of persons who usually live and eat together)

De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

Women aged 15-49

Children aged 0-4

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2005 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to prodvide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. In additon, the sample was designed to provide estimates for each of the 6 regions (Vojvodina, Belgrade, West, Central, East and South-East Serbia) for key indicators. Separate sample was designed for Roma living in Roma settlements.

Important factors which influenced the sample design of both Serb and Roma samples are the fertility rate and number of household members.

A stratified, two-stage random sampling approach was used for the selection of the survey sample.

In the case of the Serbia without the Roma settlements sample, 400 census enumeration areas within each region with probability proportional to size were selected during the first stage. Since the sample frame (Census 2002) was not up to date, household lists in all selected enumeration areas were updated prior to the selection of households. Owing to the low fertility rate and small household size, households were stratified into two categories. One category of households consists of households with under 5 children, while the other category consists of households without children under 5. The allocation of the sample in the category of households with children was significantly greater than the allocation of the sample in the category of households without children. Based on the updated information, selected units were divided into clusters of 18 households on average, plus 3 backup households. Backup households were interviewed only if some of the first 18 households were not found. In the event that a household refused to be interviewed, a backup household was not contacted. In each cluster, the number of households with children was selected with probability proportional to size.

In the case of the Roma population, the universe could be defined only for Roma who live in separate settlements. During the first stage, 106 census enumeration areas were selected. The updating of household lists was done prior to household selection, but there was no need for sample stratification of households with and without children under 5. The average number of households selected in each cluster was 18 on average, plus 3 backup households.

Secondly, after the household listing was carried out within the selected enumeration areas, a systematic sample of 7,794 households in Serbia without Roma from Roma settlements and 1,959 Roma households was drawn up, which makes a total of 9,953 sampled households.

The 2002 Serbian Population Census framework was used for the selection of clusters. Census enumeration areas (app. 100 households) were defined as primary sampling units (PSUs), and were selected from each of the sampling domains by using systematic pps (probability proportional to size) sampling procedures, based on the estimated sizes of the enumeration areas from the 2002 Population Census. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the 6 regions by urban and rural areas separately.

Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.

The Serbia Multiple Indicator Cluster Survey sample is not self-weighted. For reporting of national level results,

In 2024, average retirement age in South Korea was 49.4 years old. Since 2007, the average age has remained around 49 years old. The highest retirement age in the last 20 years was 50.3 years old in 2006.

Suriname SR: Net Intake Rate in Grade 1: % of Official School-Age Population data was reported at 64.364 % in 2016. This records a decrease from the previous number of 68.599 % for 2015. Suriname SR: Net Intake Rate in Grade 1: % of Official School-Age Population data is updated yearly, averaging 65.332 % from Dec 2005 (Median) to 2016, with 12 observations. The data reached an all-time high of 92.200 % in 2009 and a record low of 57.429 % in 2005. Suriname SR: Net Intake Rate in Grade 1: % of Official School-Age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Suriname – Table SR.World Bank: Education Statistics. Net intake rate in grade 1 is the number of new entrants in the first grade of primary education who are of official primary school entrance age, expressed as a percentage of the population of the corresponding age.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Abstract

The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular.

MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

Survey Objectives The 2005 Montenegro Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Montenegro. - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Montenegro and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

Survey Implementation The survey was carried out by the Statistical Office of the Republic of Montenegro (MONSTAT) and the Strategic Marketing Research Agency (SMMRI), with the support and assistance of UNICEF and other partners. Technical assistance and training for the survey was provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

In 2005 Serbia and Montenegro was the State Union composed of the Republic of Serbia (92.5% of population) and the Republic of Montenegro (7.5% of total population). The MICS 2005 survey was planned and implemented on the whole territory of Serbia and Montenegro, and all documents regarding survey plan and contracts with implementing agencies covered the State Union. In May, 2006 the Republic of Montenegro had a referendum of independency and the State Union broke apart. The results of MICS 2005 survey were presented separately for both countries and two separate reports were prepared.

The survey was implemented by the Statistical Office of the Republic of Serbia (in Serbia) and the Statistical Office of the Republic of Montenegro (in Montenegro) and the expert research agency - Strategic Marketing & Media Research Institute (SMMRI), which covered the survey implementation in both Serbia and Montenegro.

Special tasks performed by the Statistical Office of the Republic of Montenegro: Preparation of questionnaire for the survey: Preparation of methodological guidelines for realization of the survey; Updating of lists of households in the selected census block units; Conducting the pilot ; Selection of households to be covered by sample; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Preparation of report.

Special tasks performed by the SMMRI: Sample selection; Preparation of survey tools; Organising the training; Conducting the pilot; Updating of lists of households in the selected census block units; Organising field work; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Data processing and analysis.

Geographic coverage

The survey is nationally representative and covers the whole of Montenegro.

Analysis unit

Households (defined as a group of persons who usually live and eat together)

De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

Women aged 15-49

Children aged 0-4

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2005 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to prodvide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. In additon, the sample was designed to provide estimates for each of the 3 regions (South, Central and North) for key indicators.

Each region in Montenegro is subdivided into municipalities. Each municipality is divided into settlements and each settlement into enumeration areas. In total Montenegro includes 21 municipalities, 1256 settlements and 3201 enumeration areas. The sample frame for this survey was based on the list of enumeration areas developed from the 2003 population census.

The primary sampling unit (PSU), the cluster for the 2005 MICS, is defined on the basis of the enumeration areas from the census frame. Census enumeration areas (app. 100 households) were defined as primary sampling units (PSUs), and were selected from each of the sampling domains by using systematic pps (probability proportional to size) sampling procedures, based on the estimated sizes of the enumeration areas from the 2003 Population Census

A stratified, two-stage random sampling approach was used for the selection of the survey sample.

Regions were identified as the main sampling domains and the sample was selected in two stages. Within each region, 141 census enumeration areas were selected with probability proportional to size. Based on updated data from the last census (2003), those units were divided into clusters of 18 households on average. Important factor, which influenced on sample design, is very low fertility rate and small number of household members. For example, one generation of born children makes less than 2 percent of population, and average number of household members is 3.4. Due to these facts, we stratified the households in selected enumeration areas to two strata. One stratum contained households with children, and the other one contained households without children. Allocation of sample in the stratum of households with children was significantly bigger than allocation of sample in the stratum of households without children.

After a household listing was carried out within the selected enumeration areas, a systematic sample of 2,575 households was drawn. The sample was stratified by region and two more strata: households with children and household without children, and is not self-weighting. For reporting national level results, sample weights are used.

Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.

The Montenegro Multiple Indicator Cluster Survey sample is not self-weighted. For reporting of national level results, sample weights were used, according to MICS standard procedures.

The sampling procedures are more fully described in the sampling design document and the sampling appendix of the final report.

Sampling deviation

No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Montenegro MICS were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes household characteristics, education, child labour, water and sanitation, security of tenure and durability od housing, child discipline, and child disability.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire