Abstract

The general objective of Manufacturing and Electricity Industries Survey is to collect basic quantitative information on the country's manufacturing that is essential for planning, policy making, monitoring, System of National Accounts (SNA) and evaluation of the performance and structure of the manufacturing industries, and ensure the smooth supply of inputs and production of commodities and deal with the problems that crop up in the sector.

The specific objectives of Manufacturing and Electricity Industries Survey are to gauge the total number of proprietors/manufacturing industries, employment, income obtained, and volume and value of production and inputs, value added and other variables of interest. The specific objectives also enable to reveal the distribution of manufacturing industries across the regions and major towns of the country, the sector's contribution to the economy, the investment situation, etc.

Geographic coverage

National

Analysis unit

Enterprises/ Industries

Universe

All public and private manufacturing industries/enterprises which engaged ten persons and more and used power-driven machinery.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable - the survey enumerated all manufacturing industries/ enterprises that qualified as large and medium manufacturing industry category.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questinnaire contains the following sections/ items:

Item 1.1. Adress of the establishments: This section has varibles that identify the questionnaire uniquely. The variables are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Year, ISIC, Establishmnet no, Eelephone no and P.O.Box codes or numbers.

Item 1.2. Address of Head Office if Separated From Factory: In this section information about factory head office is collected (if the factory is separated from the head office). The varibles used to collect the information are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Telephone no and P.O.Box.

Item 2. Basic Information About The Establishment: This section has questions related to basic information about the establishment.

Item 3.1. Number of Persons Engaged: This section has variables (questions) that used to collect establishment's employees number by employees occupation.

Item 3.2. Number of Persons Engaged by Educational Status: This section has varabils (questions) that used to collect establishment's employees number by their educational status.

Item 3.3. Number of Persons Engaged by Age Group: Contains variables that used to collect information about employees number by employees age group.

Item 3.4. Wages and Salaries and Other Employee Benefits Paid: This section has variables related to wages and other employees benefits by employee occupation.

Item 3.5. Number of Permanent Employees by Basic Salary Group: This section has variables related to salary groups by sex of employees

Item 4.1. Products and By-products: This section has questions related to product produced, produced quantity and sales.

Item 4.2. Service and Other Receipts: Contains questions related to income from different source other than selling the products.

Item 5. Value of Stocks: Contains questions that related to information about materials in the stock.

Item 6.1. Cost and Quantity of Raw Materials, Parts and Containers Used: This section has questions related to principal raw materials, raw material type, quantity, value and source (local or imported).

Item 6.2. Other Industrial Costs: This sections has questions related to other industrial costs including cost of energy and other expenses.

Item 6.3. Other Non-industrial Expenses: Contains questions related to non-industrial expenses like license fee, advertising, stationary, etc.

Item 6.4. Taxes Paid: This section has questions related to taxes like indirect tax and income tax.

Item 7. Fixed Assets and Investment: This section has questions related to fixed assets and investment on fixed assests and working capital.

Item 8.1. Annual Production at Full Capacity: This section has questions about quantity and value of products if the establishment uses its full capacity.

Item 8.2. Estimated Value and Quantity of Raw Materials Needed, at Full Capacity: This section has questions about the estimate of quantity and value of raw materials that needed to function at full capacity.

Item 8.3. The three major problems that prevented the establishment from operating at full capacity.

Item 8.4. The three major problems that are facing the establishment at present.

Cleaning operations

Editing, Coding and Verification Statistical data editing plays an important role in ensuring the quality of the collected survey data. It minimizes the effects of errors introduced while collecting data in the field, hence the need for data editing, coding and verification. Although coding and editing are done by the enumerators and supervisors in the field, respectively, verification of this task is also done at the Head Office comprehensively.

An editing, coding and verification instruction manual was prepared and reproduced for this purpose. Then 30 editors-coders and verifiers were trained for two days in editing, coding and verification using the aforementioned manual as a reference and teaching aid. The completed questionnaires were edited, coded and later verified on a 100 % basis before the questionnaires were passed over to the data entry unit. The editing, coding and verification exercise of all questionnaires took 30 days.

Data Entry, Cleaning and Tabulation Before data entry, the Business Statistics Directorate of the CSA prepared edit specification for the survey for use on personal computers for data consistency checking purposes. The data on the edited and coded questionnaires were then entered into personal computers and checked and cleaned for consistency purposes using the edit specification prepared earlier for this purpose. The data entry operation involved about 20 data encoders and took 30 days to finish the job. Finally, summarization of the data was done on personal computers to produce statistical tables as per the tabulation plan.

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 2006 Thailand Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Thailand; - To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals (MDG), the goals of A World Fit for Children (WFFC) and other internationally agreed upon goals, as a basis for future action at national and provincial level; and - To contribute to the improvement of data and monitoring systems on the situation of children and women in Thailand and strengthening technical expertise for 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 implemented by the National Statistical Office of Thailand, 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.

Geographic coverage

The survey was designed to produce estimates for indicators at the national level, by urban and rural disaggregation, for each of the 4 regions of Thailand (North, Northeast, Central, and South) and by individual province for 26 (out of 76 total) targeted provinces (note: additional data collections were performed for the targeted provinces during March-May 2006; separate results publications for each province are pending).

Analysis unit

• Households
• Women aged 15-49
• Children under 5 years of age

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 Thailand Multiple Indicator Cluster Survey (MICS) was carried out by a sample survey method that used a stratified two stage sampling plan. The primary sample units (PSUs) consisted of blocks (in municipal areas) or villages (in non-municipal areas). The secondary sample units consisted of collective households systematically drawn from a household listing. The plan is designed to provide estimates of situation indicators for children and women at the national level, for municipal and non-municipal areas, and for four regions: Central (including Bangkok), North, Northeast and South. The household listing is obtained from The Basic Household Information Survey conducted every two years by the National Statistical Office (NSO). In the survey, members of each household located in the block/village samples are counted.

Data on basic household information from the survey are to be used as the sample frame in various survey projects of the NSO. Data from the 2006 Basic Household Information Survey were used as the frame for household samples in the Thailand MICS. Thirty collective household samples per block/village sample were selected in both municipal and non-municipal areas. Field staff then created a Listing of Household Samples by adding together all the names of household heads and the addresses. After a household listing was carried out within the selected 30 households in each block/village, a systematic sample of households was drawn. For national-level results, sample data were weighted in accordance with sampling plan.

A block is an operational boundary in a municipal area that is made up of approximately 100 to 200 households. Blocks are established on a map so that field staff know the exact area they are to cover in the survey.

A village is an administrative unit, a community, in a non-municipal area governed by a village head (Phuyaiban) or a district head (Kamnan).

The MICS national-level report included 1,449 block/village samples. Thirty collective household samples per block/village samples were selected and a total of 43,470 household samples were obtained.

For MICS provincial-level reports, 1,032 block/village samples were selected and 30,960 household samples were included.

More detailed information on the sample design is available in Appendix A of the Survey Final Report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Thailand 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, relationship, and orphanhood status.

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 was administered to the mother or caretaker of the child.

The questionnaires were translated into Thai by the NSO MICS coordinators in September 2005.

In addition to the administration of questionnaires, fieldwork teams tested salt used for cooking in the households surveyed for presence of iodine, and measured the weight and height of children under 5 years of age.

Cleaning operations

After the fieldwork, the team supervisor checked the data collected during the interview for completeness. Then the Provincial Statistical Officer in each province and the Director of the Data Management Division of the Bangkok Metropolitan Administration randomly rechecked the data before sending all the questionnaires to the National Statistical Office (NSO) for processing.

Upon receiving the questionnaires from the 76 provinces, the collected data were entered on 30 microcomputers by data entry operators and data entry supervisors at the Thai NSO, using CSPro software. In order to ensure quality control, editing and structural checks, all questionnaires were double entered for verification and internal consistency checks were performed, followed by secondary editing. The data entry and verification used CSPro programme applications that were developed under the global Multiple Indicator Cluster Survey (MICS) project by UNICEF to be used as standard processing procedures worldwide. In Thailand, the standard CSPro programme was modified appropriately to the Thai version questionnaires. The modification was done by NSO staff that had been trained on data processing by MICS experts from UNICEF.

Data entry and data verification for the national level report began in February 2006 and was completed in April 2006. For the provincial reports, the process was completed in June 2006. Data were analysed using the Statistical Package for Social Sciences (SPSS) software programme, Version 14, and the model syntax and tabulation plans developed by UNICEF for this purpose.

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Response rate

Of the 43,440 households selected for the sample, 42,302 were found to be occupied. Of these, 40,511 were successfully interviewed, yielding a response rate of 95.8 percent. In the interviewed households, 37,187 eligible women (aged 15-49) were identified. Of these eligible women, 36,960 were successfully interviewed, yielding a response rate of 99.4 percent. In addition, 9,444 children under the age of 5 were listed as being eligible in the households. The mothers and/or caretakers of 9,409 of these children (99.6 per cent) were successfully interviewed.

Differentials in response rates by areas showed 94.9 percent of the households in municipal areas and 96.9 percent in non-municipal areas. Participant differentials in response rates were observed, with the highest in the North Region (98.8 percent), followed by the Northeast Region (98.1 percent), and the South and the Central regions' same low response rate of 93 percent.

Sampling error estimates

The sample of respondents selected in the Thailand Multiple Indicator Cluster Survey (MICS) is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey results.

The

Abstract

The 1994 Indonesia Demographic and Health Survey (IDHS) is a follow-on project to the 1987 National Indonesia Contraceptive Prevalence Survey (NICPS) and to the 1991 IDHS. The 1994 IDHS was significantly expanded from prior surveys to include two new modules in the women's questionnaire, namely maternal mortality and awareness of AIDS. The survey also investigated the availability of family planning and health services, which provides an opportunity for linking women's fertility, family planning and child health care with the availability of services. The 1994 IDHS also included a household expenditure module, which provides a means of identifying the household's economic status.

The 1994 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality and awareness of AIDS that can be used by program managers, policymakers, and researchers to evaluate and improve existing programs; - Provide data about availability of family planning and health services, thereby offering an opportunity for linking women's fertility, family planning and child-care behavior with the availability of services; - Provide data on household expenditures, which can be used to identify the household's economic status; - Provide data that can be used to analyze trends over time by examining many of the same fertility, mortality and health issues that were addressed in the earlier surveys (1987 NICPS and 1991 IDHS); - Measure changes in fertility and contraceptive prevalence rates and at the same time study factors that affect the changes, such as marriage patterns, urban/rural residence, education, breastfeeding habits, and the availability of contraception; - Measure the development and achievements of programs related to health policy, particularly those concerning the maternal and child health development program implemented through public health clinics in Indonesia.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

Indonesia is divided into 27 provinces. For the implementation of its family planning program, the National Family Planning Coordinating Board (BKKBN) has divided these provinces into three regions as follows:

• Java-Bali: DKI Jakarta, West Java, Central Java, DI Yogyakarta, East Java, and Bali
• Outer Java-Bali I: Dista Aceh, North Sumatra, West Sumatra, South Sumatra, Lampung, West Nusa Tenggara, West Kalimantan, South Kalimantan, North Sulawesi, and South Sulawesi
• Outer Java-Bali II: Riau, Jambi, Bengkulu, East Nusa Tenggara, East Timer, Central Kalimantan, East Kalimantan, Central Sulawesi, Southeast Sulawesi, Maluku, and Irian Jaya

The 1990 Population Census of Indonesia shows that Java-Bali accounts for 62 percent of the national population, Outer Java-Bali I accounts for 27 percent, and Outer Java-Bali II accounts for 11 percent. The sample for the 1994 IDHS was designed to produce reliable estimates of fertility, contraceptive prevalence and other important variables for each of the provinces and for urban and rural areas of the three regions.

In order to meet this objective, between 1,650 and 2,050 households were selected in each of the provinces in Java-Bali, 1,250 to 1,500 households in the ten provinces in Outer Java-Bali I, and 1,000 to 1,250 households in each of the provinces in Outer Java-Bali II, for a total of 35,500 households. With an average of 0.8 ever-married women 15-49 per household, the sample was expected to yield approximately 28,000 women eligible for the individual interview.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

The 1994 IDHS used four questionnaires--three at the household level and one at the community level. The three questionnaires administered at the household level are the household questionnaire, an individual questionnaire for women, and the household expenditure questionnaire. The household and individual questionnaires were based on the DHS Model "A" Questionnaire, which is designed for use in countries with high contraceptive prevalence. A deviation from the standard DHS practice is the exclusion of the anthropometric measurement of young children and their mothers. Topics covered in the 1994 IDHS that were not included in the 1991 IDHS are knowledge of AIDS and maternal mortality. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Indonesia. Except for the household expenditure module, the questionnaires were developed mainly in English and were translated into Babasa Indonesia. The household expenditure schedule was adapted from the core Susenas questionnaire model. Susenas is a national household survey carried out annually by BPS to collect data on various demographic and socioeconomic indicators of the population.

Cleaning operations

The first stage of data editing was carried out by the field editors who checked the completed questionnaires for thoroughness and accuracy. Field supervisors then further examined the questionnaires. In many instances, the teams sent the questionnaires to CBS through the regency/municipality statistics offices. In these cases, no checking was done by the PSO. At CBS, the questionnaires underwent another round of editing, primarily for completeness and coding of responses to open-ended questions.

The data were processed using 16 microcomputers and the DHS computer program, ISSA (Integrated System for Survey Analysis). Data entry and office editing were initiated immediately after fieldwork began. Simple range and skip errors were corrected at the data entry stage. Data processing was completed by November 1994, and the preliminary report of the survey was published in January 1995.

Response rate

A total of 35,510 households were selected for the survey, of which 34,060 were found. Of the encountered households, 33,738 (99.1 percent) were successfully interviewed. In these households, 28,800 eligible women were identified and complete interviews were obtained from 28,168 women, or 97.8 percent of all eligible women. Generally high response rates for both household and individual interviews were due mainly to the strict enforcement of the role to revisit the originally selected household if no one was at home initially. No substitution for the originally selected households was allowed. Interviewers were instructed to make at least three visits in an effort to contact the household or eligible woman.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during implementation of the 1994 IDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 1994 IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 1994 IDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1994 IDHS is the ISSA Sampling Error Module. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jacknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: See detailed estimate of sampling error calculation in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

Note: See detailed tables in APPENDIX C of the report which is presented in this documentation.

Abstract

The IDHS is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health.

The main objective of 2007 IDHS was to provide detailed information on population, family planning, and health for policymakers and program managers. The 2007 IDHS was conducted in all 33 provinces in Indonesia. The survey collected information on respondents’ socioeconomic background, fertility levels, marriage and sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, childhood and adult mortality including maternal mortality, maternal and child health, and awareness and behavior regarding HIV/AIDS and other sexually-transmitted infections.

The 2007 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS/STIs to program managers, policymakers, and researchers to help them evaluate and improve existing programs; - Measure trends in fertility and contraceptive prevalence rates, analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception.; - Evaluate achievement of goals previously set by the national health programs, with special focus on maternal and child health; - Assess men’s participation and utilization of health services, as well as of their families; - Assist in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the area of family planning, fertility, and health in general.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Kind of data

Sample survey data

Sampling procedure

Administratively, Indonesia is divided into 33 provinces. Each province is subdivided into districts (regency in areas mostly rural and municipality in urban areas). Districts are subdivided into subdistricts and each subdistrict is divided into villages. The entire village is classified as urban or rural.

The 2007 IDHS sample is designed to provide estimates with acceptable precision for the following domains: - Indonesia as a whole; - Each of 33 provinces covered in the survey, and - Urban and rural areas of Indonesia

The census blocks (CBs) are the primary sampling unit for the 2007 IDHS. The sample developed for the 2007 National Labor Force Survey (Sakernas) was used as a frame for the selection of the 2007 IDHS sample. Household listing was done in all CBs covered in the 2007 Sakernas. This eliminates the need to conduct a separate household listing for the 2007 IDHS.

A minimum of 40 CBs per province has been imposed in the 2007 IDHS design. Since the sample was designed to provide reliable indicators for each province, the number of CBs in each province was not allocated proportional to the population of the province nor proportional by urban-rural classification. Therefore, a final weighing adjustment procedure was done to obtain estimates for all domains.

The 2007 IDHS sample is selected using a stratified two-stage design consisting of 1,694 CBs. Once the number of households was allocated to each province by urban and rural areas, the number of CBs was calculated based on an average sample take of 25 selected households. All evermarried women age 15-49 and all unmarried persons age 15-24 in these households are eligible for individual interview. Eight households in each CB selected for the women sample were selected for male interview.

Note: See detailed description of sample design in APPENDIX B of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2007 IDHS used three questionnaires: the Household Questionnaire (HQ), the Ever-Married Women’s Questionnaire (EMWQ) and the Married Men’s Questionnaire (MMQ). In consultation with BKKBN and MOH, BPS made a decision to base the 2007 IDHS survey instruments largely on the questionnaires used in the 2002-03 IDHS to facilitate trend analysis. Input was solicited from other potential data users, and several modifications were made to optimize the draft 2007 IDHS instruments to collect the needs for population and health data. The draft IDHS questionnaires were also compared with the most recent version of the standard questionnaires used in the DHS program and minor modifications incorporated to facilitate international comparison.

The HQ was used to list all the usual members and visitors in the selected households. Basic information collected on each person listed includes: age, sex, education, and relationship to the head of the household. The main purpose of the HQ was to identify women and men who were eligible for the individual interview. Information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, construction materials used for the floor and outer walls of the house, and ownership of various durable goods were also recorded in the HQ. These items reflect the household’s socioeconomic status.

The EMWQ was used to collect information from all ever-married women age 15-49. These women were asked questions on the following topics:: - Background characteristics (marital status, education, media exposure, etc.) - Knowledge and use of family planning methods - Reproductive history and fertility preferences - Antenatal, delivery and postnatal care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Practices related to the malaria prevention - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant’s and children’s feeding practices - Childhood mortality - Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) - Sibling mortality, including maternal mortality.

The MMQ was administered to all currently married men age 15-54 living in every third household in the IDHS sample. The MMQ collected much of the same information included in the EMWQ, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition and maternal mortality. Instead, men were asked about their knowledge and participation in health-care-seeking practices for their children.

Cleaning operations

All completed questionnaires for the IDHS, accompanied by their control forms, were returned to the BPS central office in Jakarta for data processing. This consisted of office editing, coding of openended questions, data entry, verification, and editing computer-identified errors. A team of 42 data entry clerks, data editors and data entry supervisors processed the data. Data entry and editing was carried using a computer package program called CSPro, which was specifically designed to process DHS-type survey data. During the preparation of the data entry programs, a BPS staff spent several weeks at ORC Macro offices in Calverton, Maryland. Data entry and editing activities, which began in September, 2007 were completed in March 2008.

Response rate

In general, the response rates for both the household and individual interviews in the 2007 IDHS are high. A total of 42,341 households were selected in the sample, of which 41,131 were occupied. Of these households, 40,701 were successfully interviewed, yielding a household response rate of 99 percent.

In the interviewed households, 34,227 women were identified for individual interview and of these completed interviews were conducted with 32,895 women, yielding a response rate of 96 percent. In a third of the households, 9,716 eligible men were identified, of which 8,758 were successfully interviewed, yielding a response rate of 90 percent. The lower response rate for men was due to the more frequent and longer absence of men from the household.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2007 Indonesia Demographic and Health Survey (IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2007 IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall.

Abstract

The general objective of Manufacturing and Electricity Industries Survey is to collect basic quantitative information on the country's manufacturing that is essential for planning, policy making, monitoring, System of National Accounts (SNA) and evaluation of the performance and structure of the manufacturing industries, and ensure the smooth supply of inputs and production of commodities and deal with the problems that crop up in the sector.

The specific objectives of Manufacturing and Electricity Industries Survey are to gauge the total number of proprietors/manufacturing industries, employment, income obtained, and volume and value of production and inputs, value added and other variables of interest. The specific objectives also enable to reveal the distribution of manufacturing industries across the regions and major towns of the country, the sector's contribution to the economy, the investment situation, etc.

Geographic coverage

National

Analysis unit

Enterprises/ Industries

Universe

The universe of the large and medium scale manufacturing survey is confined to those establishments which engaged 10 persons and above and use power-driven machines and covers both public and private industries in all regions of the country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable - the survey enumerated all manufacturing industries/ enterprises that qualified as large and medium manufacturing industry category.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questinnaire contains the following sections/ items:

Item 1.1. Adress of the establishments: This section has varibles that identify the questionnaire uniquely. The variables are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Year, ISIC, Establishmnet no, Eelephone no and P.O.Box codes or numbers.

Item 1.2. Address of Head Office if Separated From Factory: In this section information about factory head office is collected (if the factory is separated from the head office). The varibles used to collect the information are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Telephone no and P.O.Box.

Item 2. Basic Information About The Establishment: This section has questions related to basic information about the establishment.

Item 3.1. Number of Persons Engaged: This section has variables (questions) that used to collect establishment's employees number by employees occupation.

Item 3.2. Number of Persons Engaged by Educational Status: This section has varabils (questions) that used to collect establishment's employees number by their educational status.

Item 3.3. Number of Persons Engaged by Age Group: Contains variables that used to collect information about employees number by employees age group.

Item 3.4. Wages and Salaries and Other Employee Benefits Paid: This section has variables related to wages and other employees benefits by employee occupation.

Item 3.5. Number of Permanent Employees by Basic Salary Group: This section has variables related to salary groups by sex of employees

Item 4.1. Products and By-products: This section has questions related to product produced, produced quantity and sales.

Item 4.2. Service and Other Receipts: Contains questions related to income from different source other than selling the products.

Item 5. Value of Stocks: Contains questions that related to information about materials in the stock.

Item 6.1. Cost and Quantity of Raw Materials, Parts and Containers Used: This section has questions related to principal raw materials, raw material type, quantity, value and source (local or imported).

Item 6.2. Other Industrial Costs: This sections has questions related to other industrial costs including cost of energy and other expenses.

Item 6.3. Other Non-industrial Expenses: Contains questions related to non-industrial expenses like license fee, advertising, stationary, etc.

Item 6.4. Taxes Paid: This section has questions related to taxes like indirect tax and income tax.

Item 7. Fixed Assets and Investment: This section has questions related to fixed assets and investment on fixed assests and working capital.

Item 8.1. Annual Production at Full Capacity: This section has questions about quantity and value of products if the establishment uses its full capacity.

Item 8.2. Estimated Value and Quantity of Raw Materials Needed, at Full Capacity: This section has questions about the estimate of quantity and value of raw materials that needed to function at full capacity.

Item 8.3. The three major problems that prevented the establishment from operating at full capacity.

Item 8.4. The three major problems that are facing the establishment at present.

Cleaning operations

Editing, Coding and Verification Statistical data editing plays an important role in ensuring the quality of the collected survey data. It minimizes the effects of errors introduced while collecting data in the field, hence the need for data editing, coding and verification. Although coding and editing are done by the enumerators and supervisors in the field, respectively, verification of this task is also done at the Head Office comprehensively.

An editing, coding and verification instruction manual was prepared and reproduced for this purpose. Then 30 editors-coders and verifiers were trained for two days in editing, coding and verification using the aforementioned manual as a reference and teaching aid. The completed questionnaires were edited, coded and later verified on a 100 % basis before the questionnaires were passed over to the data entry unit. The editing, coding and verification exercise of all questionnaires took 30 days.

Data Entry, Cleaning and Tabulation Before data entry, the Business Statistics Directorate of the CSA prepared edit specification for the survey for use on personal computers for data consistency checking purposes. The data on the edited and coded questionnaires were then entered into personal computers and checked and cleaned for consistency purposes using the edit specification prepared earlier for this purpose. The data entry operation involved about 20 data encoders and took 30 days to finish the job. Finally, summarization of the data was done on personal computers to produce statistical tables as per the tabulation plan.

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.

The 2006 Iraq Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Iraq; - To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals and the goals of A World Fit For Children (WFFC) as a basis for future action; - To contribute to the improvement of data and monitoring systems in Iraq 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 was customized to the needs of the 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 implemented by the Central Organization for Statistics and Information Technology (COSIT), the Kurdistan Region Statistics Office (KRSO) and Suleimaniya Statistical Directorate (SSD), in partnership with the Ministry of Health (MOH). The survey also received support and assistance of UNICEF and other partners. Technical assistance and training for the surveys 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.

Geographic coverage

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

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. The survey also includes a full birth history listing all chuldren ever born to ever-married women age 15-49 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the Iraq Multiple Indicator Cluster Survey was designed to provide estimates on a large number of indicators on the situation of children and women at the national level; for areas of residence of Iraq represented by rural and urban (metropolitan and other urban) areas; for the18 governorates of Iraq; and also for metropolitan, other urban, and rural areas for each governorate. Thus, in total, the sample consists of 56 different sampling domains, that includes 3 sampling domains in each of the 17 governorates outside the capital city Baghdad (namely, a metropolitan area domain representing the governorate city centre, an other urban area domain representing the urban area outside the governorate city centre, and a rural area domain) and 5 sampling domains in Baghdad (namely, 3 metropolitan areas representing Sadir City, Resafa side, and Kurkh side, an other urban area sampling domain representing the urban area outside the three Baghdad governorate city centres, and a sampling domain comprising the rural area of Baghdad).

The sample was selected in two stages. Within each of the 56 sampling domains, 54 PSUs were selected with linear systematic probability proportional to size (PPS).

\After mapping and listing of households were carried out within the selected PSU or segment of the PSU, linear systematic samples of six households were drawn. Cluster sizes of 6 households were selected to accommodate the current security conditions in the country to allow the surveys team to complete a full cluster in a minimal time. The total sample size for the survey is 18144 households. The sample is not self-weighting. For reporting national level results, sample weights are used.

The sampling procedures are more fully described in the sampling appendix of the final report and can also be found in the list of technical documents within this archive.

(Extracted from the final report: Central Organisation for Statistics & Information Technology and Kurdistan Statistics Office. 2007. Iraq Multiple Indicator Cluster Survey 2006, Final Report. Iraq.)

Sampling deviation

No major deviations from the original sample design were made. One cluster of the 3024 clusters selected was not completed all othe clusters were accessed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were based on the third round of the Multiple Indicator Cluster survey model questionnaires. From the MICS-3 model English version, the questionnaires were revised and customized to suit local conditions and translated into Arabic and Kurdish languages. The Arabic language version of the questionnaire was pre-tested during January 2006 while the Kurdish language version was pre-tested during March 2006. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, and measured the weights and heights of children age under-5 years.

Cleaning operations

Data were processed in clusters, with each cluster being processed as a complete unit through each stage of data processing. Each cluster goes through the following steps: 1) Questionnaire reception 2) Office editing and coding 3) Data entry 4) Structure and completeness checking 5) Verification entry 6) Comparison of verification data 7) Back up of raw data 8) Secondary editing 9) Edited data back up

After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files: 10) Export to SPSS in 5 files (hh - household, hl - household members, wm - women age 15-49, ch - children under 5 bh - women age 15-49) 11) Recoding of variables needed for analysis 12) Adding of sample weights 13) Calculation of wealth quintiles and merging into data 14) Structural checking of SPSS files 15) Data quality tabulations 16) Production of analysis tabulations

Detailed documentation of the editing of data can be found in the data processing guidelines in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)

Data entry was conducted by 12 data entry operators in tow shifts, supervised by 2 data entry supervisors, using a total of 7 computers (6 data entry computers plus one supervisors computer). All data entry was conducted at the GenCenStat head office using manual data entry. For data entry, CSPro version 2.6.007 was used with a highly structured data entry program, using system controlled approach, that controlled entry of each variable. All range checks and skips were controlled by the program and operators could not override these. A limited set of consistency checks were also included inthe data entry program. In addition, the calculation of anthropometric Z-scores was also included in the data entry programs for use during analysis. Open-ended responses ("Other" answers) were not entered or coded, except in rare circumstances where the response matched an existing code in the questionnaire.

Structure and completeness checking ensured that all questionnaires for the cluster had been entered, were structurally sound, and that women's and children's questionnaires existed for each eligible woman and child.

100% verification of all variables was performed using independent verification, i.e. double entry of data, with separate comparison of data followed by modification of one or both datasets to correct keying errors by original operators who first keyed the files.

After completion of all processing in CSPro, all individual cluster files were backed up before concatenating data together using the CSPro file concatenate utility.

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Detailed documentation of the editing of data can be found in the data processing guidelines in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)

Response rate

Of the 18144 households selected for the sample, 18123 were found to be occupied. Of these, 17873 were successfully interviewed for a household response rate of 98.6 percent. In the interviewed households, 27564 women (age 15-49 years) were identified. Of these, 27186 were successfully interviewed, yielding a

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 2006 Bosnia and Herzegovina (BiH) Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Bosnia and Herzegovina. - 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 Bosnia and Herzegovina 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.

The 2006 BiH Multiple Indicator Cluster Survey also included a module referring to household income and expenditure within the household questionnaire.

Survey Implementation The survey was carried out by Ministry of Health and Social Welfare Republika Srpska and FBiH Public Health Institute, 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.

Geographic coverage

The survey is nationally representative and covers the whole of Bosnia and Herzegovina.

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 2006 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 2006 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2006 MICS was to provide 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 addition, the sample was designed to provide estimates for each of the two entities: the Federation of Bosnia and Herzegovina (FBiH) and the Republika Srpska (RS) for key indicators (owing to the constraints in the survey budget, the Brcko District is represented in the same way as other municipalities in BiH). Each entity is subdivided into municipalities. In addition municipalities in Federation of BiH are grouped into 10 cantons. Each municipality is divided into settlements, settlements into statistical circles and each circle into enumeration areas. In total BiH includes 154 municipalities, 12 thousands circles and 18 thousands enumeration areas. The sample frame for this survey was based on list of enumeration areas developed from the 1991 population census. In 2006 the update of 1500 enumeration areas was done and this master sample frame was used for sample selection.

The primary sampling unit (PSU), the cluster for the 2006 MICS, is defined on the basis of the enumeration areas from the master sample frame. A total of 455 census enumeration areas were systematically selected from the Master Sample with equal probability. All households from 455 census enumeration areas were allocated to two household lists. The first list (type 1) consisted of all households with children under five, and the second list consisted of all other households. 3,000 households having equal selection probability were selected from each list. This meant that each household from the list had the same selection probability. As the lists were different, the households with different sizes from different lists had different selection probability. Thus, a sample was obtained, which was self-weighted at the level of each list but is not self-weighted at the national level.

The number of households within each cluster is unequal and proportional to the cluster size.

The households in each list were implicitly stratified, i.e. sorted by entity/district, by urban/rural classification, by order of census enumeration area within the municipality, and by ordinal number within the cluster.

No replacement of households was permitted in case of non-response or non-contactable households. Adjustments were made to the sampling weights to correct for non-response, 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 BiH 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, relationship, and orphanhood status. The household questionnaire includes household listing, education, water and sanitation, household characteristics,child labour, child discipline, child disability, household expenditure, and household incomes.

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 was administered to the mother or caretaker of the child.

The women's questionnaire includes women's characteristics, marriage-union, contraception and unmet need, attitude toward domestic violence, sexual behavior, and HIV/AIDS knowledge.

The children's questionnaire includes children's characteristics, birth registration and early learning, child development, breastfeeding, care of illness, immunization, and anthropometry.

The questionnaires were developed in Bosnian, Serbian and Croatian from the MICS3 Model Questionnaires. After an initial review the questionnaires were translated back into English by an independent translator with no prior knowledge of the survey. The back translation from theBosnian, Serbian and Croatian versions was independently reviewed and compared to the English original. Differences in translation were reviewed and resolved in collaboration with the original translators.

The Bosnian, Serbian and Croatian questionnaires were both piloted as part of the survey pretest.

Cleaning operations

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Detailed documentation of the editing of data can be found in the data processing guidelines

Response rate

At the BiH level (Table HH.1), 5,549 households were successfully interviewed and the response rate reached 93.4 percent. In the interviewed households, 4,977 women were identified within the sample range, out of which 4,890 were interviewed. A total of 3,209 children under five years-of-age were listed in the household questionnaire, and the questionnaire was completed for 3,188 children. The ratio of responses for children under five differed significantly between rural areas (89.0 percent) and other areas (95.2 percent).

In the Republika Srpska, 2,019, out of the 2,129

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 2006 Kyrgyz Republic Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Kyrgyz Republic - 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 Kyrgyz Republic 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 National Statistical Committee of the Kyrgyz Republic, 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.

Geographic coverage

The survey is nationally representative and covers the whole of Kyrgyz Republic.

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 sample for the Kyrgyzstan Multiple Indicator Cluster Survey was designed to provide representative estimates of MICS indicators at the national level, in urban and rural areas, as well as for eight regions: Batken, Jalalabad, Issyk Kul, Naryn, Osh, Talas, Chui regions, and Bishkek. The urban and rural areas of each region were used as strata, where the sample design was made in two stages.

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 2006 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.

Four hundred clusters, or Census-1999 Enumeration Areas (CEA), were selected with a probability proportional to the population size in the first stage. For rural areas, populated settlements were used as Primary Sampling Units (PSUs). For urban areas, internal territorial-administrative units were used as PSUs. For each enumeration area, a household listing was updated and used as a sample framework for the second selection stage. Later, households with an equal probability were selected, according to the up-dated lists of addresses.

In defining the cluster size, a high rate of intra-cluster correlation of different indicators was taken into account. This required clusters of small size, as well as consideration of the effective use of interviewers' time, requiring a minimization of movement from one settlement to another. As a compromise between data accuracy and the efficient use of limited time and funding, a cluster size was determined to consist of 13 households.

Thus, a total sample volume consisted of 5,200 households. Given that a sample is not self-weighting, and that sample size by strata is approximately equal, sample weights were used for reporting national level results.

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 Kyrgyzstan 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, relationship, and orphanhood status. The household questionnaire includes household characteristics, Household listing, Education, Water and sanitation, Household characteristics, Child labour, Child discipline, Maternal mortality, consumption of iodized salt and durability of housing.

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 was administered to the mother or caretaker of the child.

The women's questionnaire include women's characteristics, child mortality, maternal and newborn health, marriage/union, contraception, attitude toward domestic violence, sexual behavior ans HIV/AIDS knowledge.

The children's questionnaire includes children's characteristics, birth registration and early learning, child development, vitamin A, breastfeeding, immunization, treatment of illness and care and anthropometric data.

The questionnaires are based on the MICS3 model questionnaire. The English version of questionnaires was translated into Kyrgyz and Russian languages and was pre-tested in August 2005. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

All questionnaires and modules are provided as external resources.

Cleaning operations

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files Detailed documentation of the editing of data can be found in the data processing guidelines

Response rate

During the course of the survey, all 400 PSUs selected at the first sampling stage were visited. A list of household addresses was made for those PSUs. Out of 5,200 sample households, 5,199 were found to be occupied (Table ??.1). Out of these populated households, 5,179 were successfully interviewed, yielding a household response rate of 99.6%. In all regions except for Naryn, the interviewers managed to carry out interviews in all selected households.

In the interviewed households 7,043 women (aged 15-49) were identified. Of these women, 6,973 were successfully interviewed, which corresponds to a response rate of 99.0%. Additionally, the household sample accounted for 3,000children under five years of age, and 2,987 questionnaires were completed on these, for a response rate of 99.6.

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2006 MICS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors can be evaluated statistically. The sample of respondents to the 2006 MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which

Abstract

In 2001, the World Bank in co-operation with the Republika Srpska Institute of Statistics (RSIS), the Federal Institute of Statistics (FOS) and the Agency for Statistics of BiH (BHAS), carried out a Living Standards Measurement Survey (LSMS). The Living Standard Measurement Survey LSMS, in addition to collecting the information necessary to obtain a comprehensive as possible measure of the basic dimensions of household living standards, has three basic objectives, as follows:

1. To provide the public sector, government, the business community, scientific institutions, international donor organizations and social organizations with information on different indicators of the population's living conditions, as well as on available resources for satisfying basic needs.

2. To provide information for the evaluation of the results of different forms of government policy and programs developed with the aim to improve the population's living standard. The survey will enable the analysis of the relations between and among different aspects of living standards (housing, consumption, education, health, labor) at a given time, as well as within a household.

3. To provide key contributions for development of government's Poverty Reduction Strategy Paper, based on analyzed data.

The Department for International Development, UK (DFID) contributed funding to the LSMS and provided funding for a further two years of data collection for a panel survey, known as the Household Survey Panel Series (HSPS). Birks Sinclair & Associates Ltd. were responsible for the management of the HSPS with technical advice and support provided by the Institute for Social and Economic Research (ISER), University of Essex, UK. The panel survey provides longitudinal data through re-interviewing approximately half the LSMS respondents for two years following the LSMS, in the autumn of 2002 and 2003. The LSMS constitutes Wave 1 of the panel survey so there are three years of panel data available for analysis. For the purposes of this documentation we are using the following convention to describe the different rounds of the panel survey: - Wave 1 LSMS conducted in 2001 forms the baseline survey for the panel - Wave 2 Second interview of 50% of LSMS respondents in Autumn/ Winter 2002 - Wave 3 Third interview with sub-sample respondents in Autumn/ Winter 2003

The panel data allows the analysis of key transitions and events over this period such as labour market or geographical mobility and observe the consequent outcomes for the well-being of individuals and households in the survey. The panel data provides information on income and labour market dynamics within FBiH and RS. A key policy area is developing strategies for the reduction of poverty within FBiH and RS. The panel will provide information on the extent to which continuous poverty is experienced by different types of households and individuals over the three year period. And most importantly, the co-variates associated with moves into and out of poverty and the relative risks of poverty for different people can be assessed. As such, the panel aims to provide data, which will inform the policy debates within FBiH and RS at a time of social reform and rapid change. KIND OF DATA

Geographic coverage

National coverage. Domains: Urban/rural/mixed; Federation; Republic

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The Wave 3 sample consisted of 2878 households who had been interviewed at Wave 2 and a further 73 households who were interviewed at Wave 1 but were non-contact at Wave 2 were issued. A total of 2951 households (1301 in the RS and 1650 in FBiH) were issued for Wave 3. As at Wave 2, the sample could not be replaced with any other households.

Panel design

Eligibility for inclusion

The household and household membership definitions are the same standard definitions as a Wave 2. While the sample membership status and eligibility for interview are as follows: i) All members of households interviewed at Wave 2 have been designated as original sample members (OSMs). OSMs include children within households even if they are too young for interview. ii) Any new members joining a household containing at least one OSM, are eligible for inclusion and are designated as new sample members (NSMs). iii) At each wave, all OSMs and NSMs are eligible for inclusion, apart from those who move outof-scope (see discussion below). iv) All household members aged 15 or over are eligible for interview, including OSMs and NSMs.

Following rules

The panel design means that sample members who move from their previous wave address must be traced and followed to their new address for interview. In some cases the whole household will move together but in others an individual member may move away from their previous wave household and form a new split-off household of their own. All sample members, OSMs and NSMs, are followed at each wave and an interview attempted. This method has the benefit of maintaining the maximum number of respondents within the panel and being relatively straightforward to implement in the field.

Definition of 'out-of-scope'

It is important to maintain movers within the sample to maintain sample sizes and reduce attrition and also for substantive research on patterns of geographical mobility and migration. The rules for determining when a respondent is 'out-of-scope' are as follows:

i. Movers out of the country altogether i.e. outside FBiH and RS. This category of mover is clear. Sample members moving to another country outside FBiH and RS will be out-of-scope for that year of the survey and not eligible for interview.

ii. Movers between entities Respondents moving between entities are followed for interview. The personal details of the respondent are passed between the statistical institutes and a new interviewer assigned in that entity.

iii. Movers into institutions Although institutional addresses were not included in the original LSMS sample, Wave 3 individuals who have subsequently moved into some institutions are followed. The definitions for which institutions are included are found in the Supervisor Instructions.

iv. Movers into the district of Brcko are followed for interview. When coding entity Brcko is treated as the entity from which the household who moved into Brcko originated.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data entry

As at Wave 2 CSPro was the chosen data entry software. The CSPro program consists of two main features to reduce to number of keying errors and to reduce the editing required following data entry: - Data entry screens that included all skip patterns. - Range checks for each question (allowing three exceptions for inappropriate, don't know and missing codes). The Wave 3 data entry program had more checks than at Wave 2 and DE staff were instructed to get all anomalies cleared by SIG fieldwork. The program was extensively tested prior to DE. Ten computer staff were employed in each Field Office and as all had worked on Wave 2 training was not undertaken.

Editing

Editing Instructions were compiled (Annex G) and sent to Supervisors. For Wave 3 Supervisors were asked to take more time to edit every questionnaire returned by their interviewers. The FBTSA examined the work twelve of the twenty-two Supervisors. All Supervisors made occasional errors with the Control Form so a further 100% check of Control Forms and Module 1 was undertaken by the FBTSA and SIG members.

Response rate

The panel survey has enjoyed high response rates throughout the three years of data collection with the wave 3 response rates being slightly higher than those achieved at wave 2. At wave 3, 1650 households in the FBiH and 1300 households in the RS were issued for interview. Since there may be new households created from split-off movers it is possible for the number of households to increase during fieldwork. A similar number of new households were formed in each entity; 62 in the FBiH and 63 in the RS. This means that 3073 households were identified during fieldwork. Of these, 3003 were eligible for interview, 70 households having either moved out of BiH, institutionalised or deceased (34 in the RS and 36 in the FBiH).

Interviews were achieved in 96% of eligible households, an extremely high response rate by international standards for a survey of this type.

In total, 8712 individuals (including children) were enumerated within the sample households (4796 in the FBiH and 3916 in the RS). Within in the 3003 eligible households, 7781 individuals aged 15 or over were eligible for interview with 7346 (94.4%) being successfully interviewed. Within cooperating households (where there was at least one interview) the interview rate was higher (98.8%).

A very important measure in longitudinal surveys is the annual individual re-interview rate. This is because a high attrition rate, where large numbers of respondents drop out of the survey over time, can call into question the quality of the data collected. In BiH the individual re-interview rates have been high for the survey. The individual re-interview rate is the proportion of people who gave an interview at time t-1 who also give an interview at t. Of those who gave a full interview at wave 2, 6653 also gave a full interview at wave 3. This represents a re-interview rate of 97.9% - which is extremely high by international standards. When we look at those respondents who have been interviewed at all three years of the survey there are 6409 cases which are available for longitudinal analysis, 2881 in the RS and 3528 in the FBiH. This represents 82.8% of the responding wave 1 sample, a

Abstract

The practice of conducting a census of agriculture at an interval of five or ten years has now become an established national and international routine activity. The first world census of agriculture was promoted by the International Institute of Agriculture (IIA). The FAO of UN, successor of IIA, has continued espousing implementation of the census programme in various member countries. Bangladesh carried out agriculture censuses in 1960, 1977, 1983-84, 1996, and 2008. The censuses were designed to provide a broad range of statistics on both structure and flow aspects of agriculture according to defined government national policy guidelines and also FAO advocated standard formats warranting international comparability.

Objectives:

The broad objective of the census was to determine structure and operational characteristics of agriculture holdings managed by dwelling households. The specific objectives were to determine: I. number of agriculture holdings, area of holdings, average size of holding, tenure, equipment, and farming system II. number and distribution of agriculture households III. agriculture employment IV. number of agriculture wage labour by gender V. irrigated area under crops VI. stock of livestock and poultry VII. agriculture loan VIII. agriculture implements

In addition, the specific objective was also to use all census bench-mark data as basis for improving current crop and livestock statistics as well as for formulating and implementing various policies and programmes of agriculture development.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as a production unit under single management (both technical and economic) and engaged in agriculture activities. The AC 2008 covered only the agricultural holdings in the household sector. All holdings were classified according to size as:

· small - holdings with a total land area between 0.05 and 2.49 acres (1 acre = 0.4047 ha); · medium - holdings operating a total area between 2.5 and 7.49 acres; and · large - holdings operating more than 7.5 acres of land.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The census was carried out in accordance with policy recommendations of NSC and broad guidelines of FAO to maintain international comparability. The full-count of all households both in rural and urban areas was adopted for the census. For the census taking, the entire country was divided into 1,978 zones. For each zone, a zonal officer was appointed from among the manpower of BBS. On average, a zone consisted of about 78 EAs. The zonal officers carried out various functions before doing the actual data collection work. These were:

i. forming and demarcating zones and enumeration areas (EAs) ii. preparation of EA sketch maps iii. selecting and making enumerator and supervisor lists iv. selecting training centers for imparting trainings to enumerators and supervisors v. updating lists of restricted areas, special areas, and VIPs vi. contacting local administrative authorities vii. making arrangement for safe keeping of census materials viii. preparing lists of bank branches for disbursing honoraria ix. forming census committees at union, upazila/thana, and district/zila levels.

The census was conducted in two phases:

· Phase I: complete enumeration of all households, both in rural and urban areas. · Phase II: sample enumeration with a long questionnaire was adopted to obtain detailed data on agriculture.

For Phase II, 10 percent of the 155 578 EAs were selected; subsequently, 10 percent of the households involved in agricultural activities were drawn in each selected Enumeration Area, or EA (a total of about 155 000 households).

Mode of data collection

Face-to-face [f2f]

Research instrument

Data were collected by means of two questionnaires:

(i) a short questionnaire in the first phase (full count) (ii) a long questionnaire in the second phase (sample-based)

The AC 2008 questionnaires covered 13 items of the 16 core items4 recommended for the WCA 2010 round, namely;

0001 Identification and location of agricultural holding 0002+ Legal status of agricultural holder 0003 Sex of agricultural holder 0004 Age of agricultural holder 0005 Household size 0006 Main purpose of production of the holding 0007 Area of holding according to land use types 0008 Total area of holding 0009 Land tenure types on the holding 0010 Presence of irrigation on the holding 0011 Types of temporary crops on the holding 0012 Types of permanent crops on the holding and whether in compact plantation 0013 Number of animals on the holding for each livestock type 0014 Presence of aquaculture on the holding 0015+ Presence of forest and other wooded land on the holding 0016 Other economic production activities of the holding's enterprise

The following items were not covered:

(i) "Legal status of agricultural holder" (ii) "Age of agricultural holder" (iii) "Main purpose of production of the holding

Cleaning operations

(a) Data Processing The data processing of the census was originally conceived to be done with help of ICR (intelligent character reader) machine use. The aim was to cut-down substantially the usually long data- entry time of the census. But some practical limitations led the steering committee to recommend abandoning plan of ICR data entry for the census. Therefore, the manual keying of data into micro computers was adapted. Here, the following rigid measures were taken up to expedite error-free manual data entry for the census:

i. establishment of local network system ii. ensuring correctness of data right at the stage of data entry process; this included checks on completeness, possible errors, and consistency iii. incentives for data-entry operators and supervisors on the basis of volume of work done iv. constant monitoring of progress.

(b) Manual Editing As soon as the data collection phase was completed, the documents were stored systematically in order of the computer geo-code list to ensure their easy retrieval as and when needed. Systematic storage of documents was a very important step that ensured smooth processing. An elaborate list of editing checks was developed and the editors were thoroughly trained. For every 10 editors, one supervisor was engaged to ensure accuracy of editing. Also, for strict control of data-edit one supervising officer had overseen work of every two supervisors. The data entry program was developed in such a way as to reject any record with wrong or inconsistent data. In order to speed-up data entry, it was necessary that the manual edit was comprehensive and correct. However, data entry operators and their supervisors were also trained in manual edit in order to enable them to carry out necessary corrections when needed. Apart from accuracy of data sets, manual edit ensured completeness of enumeration-books and their geo-code identifications.

(c) Data Entry and Computer Edit A special data entry program was developed in FoxPro with exhaustive checks of every kind including duplication of records. These checks, although slowed down the speed of data entry operation, ensured accuracy and consistency. As a results, no further edit or imputation was necessary before embarking upon tabulation process. At the end, products of operators were merged together to make a district file. At this stage, it was ensured that the relevant number of records of all EAs were in the file and that no EA was missing. Completeness, accuracy, and consistency were the main elements of computer edit.

Data appraisal

Post Enumeration Check (PEC):

Upon completion of field work of full count census, a post enumeration check (PEC) was done in order to assess the census data quality. The PEC findings are available in a report published separately.

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. The survey has been a joint endeavor of the Government of Mongolia and UNICEF to make an in-depth analysis of Mongolia's child and women health, education, livelihood status and right exercises and to assess the progress of implementation of a National Programme for Child Development and Protection (2002-2010). The data will furnish the preparation process of the national reporting to be presented by the Government of Mongolia at the special session of UN regarding the country's implementation of Declaration of the A World Fit for Children.

Survey Objectives The primary objectives of “Multiple Indicator Cluster Survey: Child Development 2005-2006” are the following: - To update the data for assessing the situation of child and women and their right exercises - To furnish the data needed for monitoring progress towards the goals of Millennium Declaration and the WorldFit for Children as a basis for future action planning - To contribute to the improvement of data and monitoring systems in Mongolia and strengthen the expertise in the design, implementation and analytical of these systems.

Survey plans The Mongolia Multiple Indicator Cluster Survey was conducted by the National Statistical Office of Mongolia with the support of the Government of Mongolia and UNICEF. Technical assistance and training for the surveys 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.

Geographic coverage

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

Analysis unit

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

• Household members (defined as members 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 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 MICS - 3 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 MICS - 3 collected data from a nationally representative sample of households, women and children. The primary focus of the MICS - 3 was to provide estimates of key population and health, education, child protection and HIV related indicators for Mongolia as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates for each of the 5 regions for key indicators. Mongolia is divided into 5 regions. Each region is subdivided into provinces (aimags) and a capital city, and each province into soums, a capital city into districts, each soum into bags and each districts into khoroos. As bag and khoroo household and population listing is annually updated, these were taken as primary sampling units. Bags and khoroos with a large population were divided into 2-3 primary sampling units in order to keep the similar number of households for sampling units. Bag and khoroos (primary sampling unit) were selected with probability proportional to size and 25 households within each of these selected units were sampled using the systematic method. The primary sampling unit variable is the cluster (HH1).

The survey estimates the indicators on the child and women situation by national level, rural, urban areas and regions. Five regions (Western, Khangai, Central, Eastern and Ulaanbaatar) were the main sampling domains and a two stage sampling design was used. Within each region households were selected with probability proportional to size.

A total of 6325 households in 253 primary sampling units were selected to represent 21 aimags and Ulaanbaatar city. Sample weights were used for estimating the data collected from each of the sampled households. No replacement of households was permitted in case of non-response or non-contactable households. Adjustments were made to the sampling weights to correct for non-response, according to MICS standard procedures.

Sampling deviation

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

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the MICS were structured questionnaires based on the MICS - 3 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, relationship, and orphanhood status. The household questionnaire includes household's characteristics, household listing, education, water and sanitation, child labour, child discipline, child disability, and salt iodization.

To reflect the country specific characteristics, module “Salt Iodization” of household questionnaire was enlarged by the question about the vitamin enriched flour and module “child discipline” was added with sub-module child behaviour. These additions were made based on the decisions made by work group members and Steering Committee.

In the meantime, the salt used for household cooking was on site tested to measure the iodine content.

Household questionnaire was administered to an adult household member who can best represent other members, women questionnaire to women themselves and under-five questionnaire to mothers or caretakers of children under 5 years. Child weights and heights were measured during the interviews.

The women's questionnaire includes women's characteristics, women listing, child mortality, maternal and infant health, marriage, contraception, attitudes towards family violence, and HIV/AIDS knowledge.

The children's questionnaire includes children's characteristics, child listing, birth registration and pre-schooling, child development , “A” vitamin supplement, breastfeeding, care of illness, immunization, and anthropometry.

The questionnaires were developed in Mongolian from the MICS3 Model Questionnaires, and were translated into English.

In order to check the clarity and logical sequence of questions and determine the interview duration per household, the pretest of questionnaires was made in September 2005 covering the selected households in Erdene soum of Tuv aimag. Based on the findings of the pretest, wording and logical sequence of the questions were improved.

Cleaning operations

Data were processed in clusters, with each cluster being processed as a complete unit through each stage of data processing. Each cluster goes through the following steps: 1) Questionnaire reception 2) Office editing and coding 3) Data entry 4) Structure and completeness checking 5) Verification entry 6) Comparison of verification data 7) Back up of raw data 8) Secondary editing 9) Edited data back up After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files: 10) Export to SPSS in 4 files (hh - household, hl - household members, wm - women, ch - children under 5) 11) Recoding of variables needed for analysis 12) Adding of sample weights 13) Calculation of wealth quintiles and merging into data 14) Structural checking of SPSS files 15) Data quality tabulations 16) Production of analysis tabulations

Details of each of these steps can be found in the data processing documentation, data editing guidelines, data processing programs in CSPro and SPSS, and tabulation guidelines in the MICS manual http://www.childinfo.org/mics/mics3/manual.php

Data entry was conducted by 8 data entry operators in tow shifts, supervised by 1 data entry supervisors, using a total of 9 computers (8 data entry computers plus one supervisor's computer). All data entry was conducted at the NSO using manual data entry. For data entry, CSPro version 2.6.007 was used with a highly structured data entry program, using system controlled approach that controlled entry of each variable. All range checks and skips were

Abstract

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

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

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

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

Geographic coverage

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

Analysis unit

• Households
• Individuals

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

Cleaning operations

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

Response rate

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

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

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

Sampling error estimates

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

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

Abstract

The Annual Survey of Industries (ASI) is one of the large-scale sample survey conducted by Field Operation Division of National Sample Survey Office for more than three decades with the objective of collecting comprehensive information related to registered factories on annual basis. ASI is the primary source of data for facilitating systematic study of the structure of industries, analysis of various factors influencing industries in the country and creating a database for formulation of industrial policy.

The main objectives of the Annual Survey of Industries are briefly as follows: (a) Estimation of the contribution of manufacturing industries as a whole and of each unit to national income. (b) Systematic study of the structure of industry as a whole and of each type of industry and each unit. (c) Casual analysis of the various factors influencing industry in the country: and (d) Provision of comprehensive, factual and systematic basis for the formulation of policy.

The Annual Survey of Industries (ASI) is the principal source of industrial statistics in India. It provides statistical information to assess changes in the growth, composition and structure of organised manufacturing sector comprising activities related to manufacturing processes, repair services, gas and water supply and cold storage. The Survey is conducted annually under the statutory provisions of the Collection of Statistics Act 1953, and the Rules framed there-under in 1959, except in the State of Jammu & Kashmir where it is conducted under the State Collection of Statistics Act, 1961 and the rules framed there-under in 1964.

Geographic coverage

The ASI extends its coverage to the entire country upto state level.

Analysis unit

The primary unit of enumeration in the survey is a factory in the case of manufacturing industries, a workshop in the case of repair services, an undertaking or a licensee in the case of electricity, gas & water supply undertakings and an establishment in the case of bidi & cigar industries. The owner of two or more establishments located in the same State and pertaining to the same industry group and belonging to same scheme (census or sample) is, however, permitted to furnish a single consolidated return. Such consolidated returns are common feature in the case of bidi and cigar establishments, electricity and certain public sector undertakings.

Universe

The survey cover factories registered under the Factory Act 1948. Establishments under the control of the Defence Ministry,oil storage and distribution units, restaurants and cafes and technical training institutions not producing anything for sale or exchange were kept outside the coverage of the ASI.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Procedure

The sampling design followed in ASI 2000-01 is a Circular Systematic one. All the factories in the updated frame (universe) are divided into two sectors, viz., Census and Sample.

Census Sector: Census Sector is defined as follows:

a) All the complete enumeration States namely, Manipur, Meghalaya, Nagaland, Tripura and Andaman & Nicobar Islands. b) For the rest of the States/ UT's., (i) units having 100 or more workers, and (ii) all factories covered under Joint Returns.

Rest of the factories found in the frame constituted Sample sector on which sampling was done. Factories under Biri & Cigar sector were not considered uniformly under census sector. Factories under this sector were treated for inclusion in census sector as per definition above (i.e., more than 100 workers and/or joint returns). After identifying Census sector factories, rest of the factories were arranged in ascending order of States, NIC-98 (4 digit), number of workers and district and properly numbered. The Sampling fraction was taken as 12% within each stratum (State X Sector X 4-digit NIC) with a minimum of 8 samples except for the State of Gujarat where 9.5% sampling fraction was used. For the States of Jammu & Kashmir, Himachal Pradesh, Daman & Diu, Dadra & Nagar Haveli, Goa and Pondicherry, a minimum of 4 samples per stratum was selected. For the States of Bihar and Jharkhand, a minimum of 6 samples per stratum was selected. The entire sample was selected in the form of two independent sub-sample using Circular Systematic Sampling method.

Sampling deviation

There was no deviation from sample design in ASI 2000-01

Mode of data collection

Statutory return submitted by factories as well as Face to face

Research instrument

Annual Survey of Industries Questionnaire (in External Resources) is divided into different blocks:

BLOCK A.IDENTIFICATION PARTICULARS BLOCK B. PARTICULARS OF THE FACTORY (TO BE FILLED BY OWNER OF THE FACTORY) BLOCK C: FIXED ASSETS BLOCK D: WORKING CAPITAL & LOANS BLOCK E : EMPLOYMENT AND LABOUR COST BLOCK F : OTHER EXPENSES BLOCK G : OTHER INCOMES BLOCK H: INPUT ITEMS (indigenous items consumed) BLOCK H1: FUELS, ELECTRICITY AND WATER CONSUMPTION BLOCK I: INPUT ITEMS – directly imported items only (consumed) BLOCK J: PRODUCTS AND BY-PRODUCTS (manufactured by the unit)

Cleaning operations

Pre-data entry scrutiny was carried out on the schedules for inter and intra block consistency checks. Such editing was mostly manual, although some editing was automatic. But, for major inconsistencies, the schedules were referred back to NSSO (FOD) for clarifications/modifications.

Validation checks are carried out on data files. Code list, State code list, Tabulation program and ASICC code are may be refered in the External Resources which are used for editing and data processing as well..

B. Tabulation procedure

The tabulation procedure by CSO(ISW) includes both the ASI 2000-01 data and the extracted data from ASI 99-00 for all tabulation purpose. For extracted returns, status of unit (Block A, Item 12) would be in the range 17 to 20. To make results comparable, users are requested to follow the same procedure. For calculation of various parameters, users are requested to refer instruction manual/report. Please note that a separate inflation factor (Multiplier) is available for each unit against records belonging to Block-A for ASI 2000-01 data. The multiplier is calculated for each stratum (i.e. State X NIC'98(4 Digit)) after adjusting for non-response cases.

.

C. Merging of unit level data

As per existing policy to merge unit level data at ultimate digit level of NIC'98 (i.e., 5 digit) for the purpose of dissemination, the data have been merged for industries having less than three units within State, District and NIC'98(5 Digit) with the adjoining industries within district and then to adjoining districts within a state. There may be some NIC'98(5 Digit) ending with '9' which do not figure in the book of NIC '98. These may be treated as 'Others' under the corresponding 4-digit group. To suppress the identity of factories data fields corresponding to PSL number, Industry code as per Frame (4-digit level of NIC-98) and RO/SRO code have been filled with '9' in each record.

It may please be noted that, tables generated from the merged data may not tally with the published results for few industries, since the merging for published data has been done at aggregate-level to minimise loss of information.

Sampling error estimates

Relative Standard Error (RSE) is calculated in terms of worker, wages to worker and GVA using the formula (Pl ease refer to Estimation Procedure document in external resources). Programs developed in Visual Faxpro are used to compute the RSE of estimates.

Data appraisal

To check for consistency and reliability of data the same are compared with the NIC-2digit level growth rate at all India Index of Production (IIP) and the growth rates obtained from the National Accounts Statistics at current and constant prices for the registered manufacturing sector.

Abstract

The Indonesia Demographic and Health Survey (IDHS) is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health. The 2002-2003 IDHS follows a sequence of several previous surveys: the 1987 National Indonesia Contraceptive Prevalence Survey (NICPS), the 1991 IDHS, the 1994 IDHS, and the 1997 IDHS. The 2002-2003 IDHS is expanded from the 1997 IDHS by including a collection of information on the participation of currently married men and their wives and children in the health care.

The main objective of the 2002-2003 IDHS is to provide policymakers and program managers in population and health with detailed information on population, family planning, and health. In particular, the 2002-2003 IDHS collected information on the female respondents’ socioeconomic background, fertility levels, marriage and sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, childhood and adult mortality including maternal mortality, maternal and child health, and awareness and behavior regarding AIDS and other sexually transmitted infections in Indonesia.

The 2002-2003 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS/STIs to program managers, policymakers, and researchers to help them evaluate and improve existing programs - Measure trends in fertility and contraceptive prevalence rates, analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception - Evaluate achievement of goals previously set by the national health programs, with special focus on maternal and child health - Assess men’s participation and utilization of health services, as well as of their families - Assist in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the area of family planning, fertility, and health in general.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN AND IMPLEMENTATION

Administratively, Indonesia is divided into 30 provinces. Each province is subdivided into districts (regency in areas mostly rural and municipality in urban areas). Districts are subdivided into subdistricts and each subdistrict is divided into villages. The entire village is classified as urban or rural.

The primary objective of the 2002-2003 IDHS is to provide estimates with acceptable precision for the following domains: · Indonesia as a whole; · Each of 26 provinces covered in the survey. The four provinces excluded due to political instability are Nanggroe Aceh Darussalam, Maluku, North Maluku and Papua. These provinces cover 4 percent of the total population. · Urban and rural areas of Indonesia; · Each of the five districts in Central Java and the five districts in East Java covered in the Safe Motherhood Project (SMP), to provide information for the monitoring and evaluation of the project. These districts are: - in Central Java: Cilacap, Rembang, Jepara, Pemalang, and Brebes. - in East Java: Trenggalek, Jombang, Ngawi, Sampang and Pamekasan.

The census blocks (CBs) are the primary sampling unit for the 2002-2003 IDHS. CBs were formed during the preparation of the 2000 Population Census. Each CB includes approximately 80 households. In the master sample frame, the CBs are grouped by province, by regency/municipality within a province, and by subdistricts within a regency/municipality. In rural areas, the CBs in each district are listed by their geographical location. In urban areas, the CBs are distinguished by the urban classification (large, medium and small cities) in each subdistrict.

Note: See detailed description of sample design in APPENDIX B of the survey report.

Mode of data collection

Face-to-face

Research instrument

The 2002-2003 IDHS used three questionnaires: the Household Questionnaire, the Women’s Questionnaire for ever-married women 15-49 years old, and the Men’s Questionnaire for currently married men 15-54 years old. The Household Questionnaire and the Women’s Questionnaire were based on the DHS Model “A” Questionnaire, which is designed for use in countries with high contraceptive prevalence. In consultation with the NFPCB and MOH, BPS modified these questionnaires to reflect relevant issues in family planning and health in Indonesia. Inputs were also solicited from potential data users to optimize the IDHS in meeting the country’s needs for population and health data. The questionnaires were translated from English into the national language, Bahasa Indonesia.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Basic information collected for each person listed includes the following: age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, the Household Questionnaire also identifies unmarried women and men age 15-24 who are eligible for the individual interview in the Indonesia Young Adult Reproductive Health Survey (IYARHS). Information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, construction materials used for the floor and outer walls of the house, and ownership of various durable goods were also recorded in the Household Questionnaire. These items reflect the household’s socioeconomic status.

The Women’s Questionnaire was used to collect information from all ever-married women age 15-49. These women were asked questions on the following topics: • Background characteristics, such as age, marital status, education, and media exposure • Knowledge and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Woman’s work and husband’s background characteristics • Childhood mortality • Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) • Sibling mortality, including maternal mortality.

The Men’s Questionnaire was administered to all currently married men age 15-54 in every third household in the IDHS sample. The Men’s Questionnaire collected much of the same information included in the Women’s Questionnaire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, and maternal mortality. Instead, men were asked about their knowledge and participation in the health-seeking practices for their children.

Cleaning operations

All completed questionnaires for IDHS, accompanied by their control forms, were returned to the BPS central office in Jakarta for data processing. This process consisted of office editing, coding of open-ended questions, data entry, verification, and editing computer-identified errors. A team of about 40 data entry clerks, data editors, and two data entry supervisors processed the data. Data entry and editing started on November 4, 2002 using a computer package program called CSPro, which was specifically designed to process DHS-type survey data. To prepare the data entry programs, two BPS staff spent three weeks in ORC Macro offices in Calverton, Maryland in April 2002.

Response rate

A total of 34,738 households were selected for the survey, of which 33,419 were found. Of the encountered households, 33,088 (99 percent) were successfully interviewed. In these households, 29,996 ever-married women 15-49 were identified, and complete interviews were obtained from 29,483 of them (98 percent). From the households selected for interviews with men, 8,740 currently married men 15-54 were identified, and complete interviews were obtained from 8,310 men, or 95 percent of all eligible men. The generally high response rates for both household and individual interviews (for eligible women and men) were due mainly to the strict enforcement of the rule to revisit the originally selected household if no one was at home initially. No substitution for the originally selected households was allowed. Interviewers were instructed to make at least three visits in an effort to contact the household, eligible women, and eligible men.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2002-2003 Indonesia Demographic and Health Survey (IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents

Abstract

Objectives of the Survey The main objective of this survey is to provide statistical data on ICT for the enterprises in the Palestinian Territory. The specific objectives can be summarized in the following: ·Enriching ICT statistical data on the actual use and access by the economic enterprises of ICT. ·Identifying the characteristics of the tools and means of ICT used in the economic activity, the type of economic activity and size of enterprises. ·Providing opportunity for international and regional comparisons which helps in knowing the location of the Palestinian Territory among the technological world countries. ·Assisting planners and policy makers in understanding the current status of the Technology-Based Economy in the Palestinian Territory, which helps to meet the future needs of the Palestinian economy.

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip),

Analysis unit

Enterprises

Universe

The enterprises in the Palestinian Territory

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Size and Design Frame

Target Population The target population consists of all operating private establishments in the Palestinian Territ.

Sampling Frame The sampling frame is the list of all operating private establishments enumerated in the Establishments Census 2007.

Sample Size The sample size is 1,905 establishments, of which 1,591 are establishments in the West Bank and 314 establishments in Gaza Strip.

Mode of data collection

Face-to-face [f2f]

Research instrument

In light of identifying data requirements, the survey instrument was developed following a review of international recommendations and experiences of countries in this area, and the experience of the BICT survey 2007 that implemented by PCBS. In addition to identification information and data quality control, BICT survey 2009 instrument consists of one main section studied the mechanisms and characteristics of use and access for the basic tools of ICT such as telephone, mobile phone, computer, internet, intranet, extranet, and e-commerce transactions on technology by the economic establishments in the Palestinian Territory. The survey aims mainly to provide comprehensive statistical data on the availability of the means, access and use of ICT tools in the establishments by the major economic activities, employment size, places and different goals as well as main features for the use of ICT

Cleaning operations

Data Editing The project's management developed a clear mechanism for editing the data and trained the team of editors accordingly. The mechanism was as follows: · Receiving completed questionnaires on a daily basis; · Checking each questionnaire to make sure that they were completed and that the data covered all eligible enterprises. Checks also focused on the accuracy of the answers to the questions. Returning the uncompleted questionnaires as well as those with errors to the field for completion

Response rate

The survey sample consists of about 3,011 establishments; 1,905 establishments completed the interview, of which 1,591 establishments were in the West Bank and 314 establishments in Gaza Strip. The response rate was 66.0%.

Sampling error estimates

Detailed information on the sampling Error is available in the Survey Report.

Data appraisal

Detailed information on the data appraisal is available in the Survey Report.

Abstract

The aim of the survey is to collect data on the health and Accessibility to health services of the Palestinian Population in the Palestinian Territory. The main objectives of the survey was to study the availability of health facilities in the Palestinian Territory, to study the satisfaction of beneficiaries and to provide data base on accessibility to health institutions.

Geographic coverage

All Palestinian households living in the Palestinian Territory (west bank and Gaza Strip)

Analysis unit

Household

Universe

All Palestinian households living in the Palestinian Territory, excluding persons living in institutions such as prisons or shelters.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame consisted of a master sample of enumeration areas (EAs) selected from the Population Housing and Establishment Census 1997. The master sample consists of area units of relatively equal size (number of households) , these units have been used as primary sampling units (PSUs).

Sample Design The sample is a two-stage stratified cluster random sample.

Stratification Four levels of stratification were made: Stratification by Governorates. 1. Stratification by type of locality which comprises: (a) Urban (b) Rural (c) Refugee Camps
2. Stratification by classifying localities, excluding governorate centers, into three strata based on the ownership of households of durable goods within these localities. 3. Stratification by size of locality (number of households).

Sample Size The sample covered a total of 4,077 households of which 2,745 households were from the West Bank and 1,332 from Gaza Strip.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was developed by the Palestinian Central Bureau of Statistics according to the national needs of related indicators. Therefore, number of questionnaire was reviewed:

1.Access to Health Care Services Survey questionnaire in Canada. 2.Health Survey-2000 questionnaire. 3.Nutritional Survey-2002 questionnaire

Cleaning operations

The data processing stage consisted of the following operations:

Editing before data entry All questionnaires were then edited in the main office using the same instructions adopted for editing in the field.

Data Entry In this stage data were entered into the computer, using a data entry template Microsoft Access. The data entry program was prepared in order to satisfy the following requirements:

·Duplication of the questionnaire on the computer screen. ·Logical and consistency checks of data entered. ·Possibility for internal editing of questionnaire answers. ·Maintaining a minimum of errors in digital data entry and fieldwork. ·User- friendly handling.

Response rate

The response rate for the SURVEY 98.2%.

Sampling error estimates

Since the data reported here are based on a sample survey and not on complete enumeration, they are subjected to two main types of errors: sampling errors and non-Sampling errors.

Sampling errors are random outcomes of the sample design, and are, therefore, easily measurable.

Non-sampling errors can occur at the various stages of the survey implementation in data collection and data processing, and are generally difficult to be evaluated statistically. They cover a wide range of errors, including errors resulting from non-response, sample frame coverage, data processing and response (both respondent and interviewer-related). The use of effective training and supervisions and the careful design of questions as measures have direct bearing on the magnitude of non-sampling errors, and hence the quality of the resulting data are of high quality.

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 Sierra Leone Multiple Indicator Cluster Survey has the following primary objectives: - To provide up-to-date information for assessing the situation of children and women in Sierra Leone; - To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals and the goals of A World Fit For Children (WFFC) as a basis for future action; - To contribute to the improvement of data and monitoring systems in Sierra Leone and to strengthen technical expertise in the design and implementation of these systems and analysis of the information they generate.

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 conducted by Statistics Sierra Leone with financial and technical support from UNICEF Sierra Leone 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.

Geographic coverage

The survey is nationally representative and covers the whole of Sierra Leone

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 primary objective of the sample design for the Sierra Leone MICS3 was to produce statistically reliable estimates of most indicators at the national level, for urban and rural areas, and at the province level. The design of the sample allows the estimation of indicators at district level - however, such estimates are likely to be very imprecise, since the sample size was not determined to enable district-level estimates.

A multi-stage, stratified cluster sampling approach was used to select the survey sample. The 2004 census frame was used for the selection of clusters. Census enumeration areas (EAs) were defined as primary sampling units (PSUs), and were selected in each district using pps sampling procedures. The stages of the sampling approach are described below.

Description of sampling approach for Sierra Leone MICS3

Stage 1: Selection of EAs The list of all EAs in Sierra Leone was ordered using implicit stratification according to the following variables: province; district; chiefdom; and, population size. 320 EAs were then selected using stratified systematic sampling, thus yielding a self-weighting sample. Selected EAs were then classified as rural (population of the settlement were the EA is located is < 2,000) or urban (population of the settlement where the EA is located is = 2,000).

Stage 2: Selection of households A list of all households in each of the 320 selected EAs as enumerated during the 2004 census was prepared using data contained in the 2004 Population and Housing Census registers. A team of listers/verifiers visited each of the 320 EAs to update the household lists in the EA by verifying each of the households on the list and adding any new households that have been formed in order to control for out-movers, non-existent households, and/or new households. This task produced an updated listing of households in all selected EAs. The newly updated listing of households in each EA was then sequentially numbered from 1 to n (the total number of households in the enumeration area of interest) at the Statistics Sierra Leone Office. Sampling experts then selected 25 households in each EA using systematic selection procedures.

(Information extracted from final report: Statistics Sierra Leone and UNICEF-Sierra Leone 2007. Sierra Leone Multiple Indicator Cluster Survey 2005, Final Report. Freetown, Sierra Leone: Statistics Sierra Leone and UNICEF-Sierra Leone.)

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Sierra Leone MICS3 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, relationship, and orphanhood status.

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 was administered to the mother or caretaker of the child.

English is the only written language in Sierra Leone; for this reason, questionnaires were written in English and verbally translated by enumerators into the language preferred by the respondent (generally Krio, Timne, Mende or Limba), using standardized, pre-tested key words. The questionnaires were pre-tested in the Western Area in September 2005. Based on the results of the pre-test, modifications were made to the wording of the questions, the response categories, and the key words.

Information extracted from final report: Statistics Sierra Leone and UNICEF-Sierra Leone 2007. Sierra Leone Multiple Indicator Cluster Survey 2005, Final Report. Freetown, Sierra Leone: Statistics Sierra Leone and UNICEF-Sierra Leone.

Cleaning operations

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Detailed documentation of the editing of data can be found in the data processing guidelines in the MICS global manual, see www.childinfo.org

Response rate

Of the 8,000 households selected for the sample, only 7,125 were found to be occupied. Of the 7,125 occupied households, 7,078 were successfully interviewed for a household response rate of 99.3 per cent. In the interviewed households, 9,257 eligible women (aged 15-49) were identified. Of these, 7,654 were successfully interviewed, yielding a response rate of 82.7 per cent. The response rate for the Questionnaire for Children Under Five was 88.9 per cent; mothers/caretakers of 5,246 children under five were successfully interviewed, from among 5,904 children under five who were identified in the interviewed households. Overall response rates of 82.1 percent and 88.3 percent are calculated for the women's and under-5's interviews, respectively

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2005 MICS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors can be evaluated statistically. The sample of respondents to the 2005 MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which is the square root of the variance. Confidence intervals are calculated for each statistic within which the true value for the population can be assumed to fall. Plus or minus two standard errors of the statistic is used for key statistics presented in MICS, equivalent to a 95 percent confidence interval.

If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formulae for calculating sampling errors. However, the 2005 MICS sample is the result of a multi-stage stratified design, and consequently needs to use more complex

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The basic goal of the Household and Consumption Survey is to provide a necessary database for formulating national policies at various levels. This survey provides the contribution of the household sector to the Gross National Product (GNP). It determines the incidence of poverty, and provides weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Furthermore, this survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

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

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and governorates.

Analysis unit

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

Universe

All Palestinian households who are usually resident in the Palestinian Territory during 2011.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

Sample and Frame: The sampling frame consists of all enumeration areas which were enumerated in 2007, each numeration area consists of buildings and housing units with average of about 120 households in it. These enumeration areas are used as primary sampling units PSUs in the first stage of the sampling selection.

Sample Size: The calculated sample size for the Expenditure and Consumption survey 2011 is about 4,317 households, 2,834 households in West Bank and 1,483 households in Gaza Strip.

Sample Design: The sample is a stratified cluster systematic random sample with two stages: First stage: selection of a systematic random sample of 215 enumeration areas. Second stage: selection of a systematic random sample of 24 households from each enumeration area selected in the first stage.

Note: in Jerusalem Governorate (J1), 14 enumeration areas were selected. In the second stage, a group of households from each enumeration area were chosen using the 2007 census method of delineation and enumeration to obtain 24 responsive households. This ensures household response is the maximum to comply with the percentage of non-response as set in the sample design.

Enumeration areas were distributed to twelve months and the sample for each quarter covers sample strata (Governorate, locality type)

Sample strata: The population was divided by: 1- Governorate 2- Type of Locality (urban, rural, refugee camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

The PECS questionnaire consists of two main sections:

First: Survey's Questionnaire Part of the questionnaire is to be filled in during the visit at the beginning of the month, while the other part is to be filled in at the end of the month. The questionnaire includes: Control Sheet: Includes household's identification data, date of visit, data on the fieldwork and data processing team, and summary of household's members by gender. Household Roster: Includes demographic, social, and economic characteristics of household's members. Housing Characteristics: Includes data like type of housing unit, number of rooms, value of rent, and connection of housing unit to basic services like water, electricity and sewage. In addition, data in this section includes source of energy used for cooking and heating, distance of housing unit from transportation, education, and health centers, and sources of income generation like ownership of farm land or animals. Food and Non-Food Items: includes food and non-food items, and household record her expenditure for one month. Durable Goods Schedule: Includes list of main goods like washing machine, refrigerator, TV. Assistances and Poverty: Includes data about cash and in kind assistances (assistance value, assistance source), also collecting data about household situation, and the procedures to cover expenses. Monthly and Annual Income: Data pertinent to household's income from different sources is collected at the end of the registration period.

Second: List of Goods The classification of the list of goods is based on the recommendation of the United Nations for the SNA under the name Classification of Personal Consumption by purpose. The list includes 55 groups of expenditure and consumption where each is given a sequence number based on its importance to the household starting with food goods, clothing groups, housing, medical treatment, transportation and communication, and lastly durable goods. Each group consists of important goods. The total number of goods in all groups amounted to 667 items for goods and services. Groups from 1-21 includes goods pertinent to food, drinks and cigarettes. Group 22 includes goods that are home produced and consumed by the household. The groups 23-45 include all items except food, drinks and cigarettes. The groups 50-55 include durable goods. The data is collected based on different reference periods to represent expenditure during the whole year except for cars where data is collected for the last three years.

Registration Form The registration form includes instructions and examples on how to record consumption and expenditure items. The form includes columns: * Monetary: If the good is purchased, or in kind: if the item is self produced. * Title of the service of the good * Unit of measurement (kilogram, liter, number) * Quantity * Value

The pages of the registration form are colored differently for the weeks of the month. The footer for each page includes remarks that encourage households to participate in the survey. The following are instructions that illustrate the nature of the items that should be recorded: * Monetary expenditures during purchases * Purchases based on debts * Monetary gifts once presented * Interest at pay * Self produced food and goods once consumed * Food and merchandise from commercial project once consumed * Merchandises once received as a wage or part of a wage from the employer.

Cleaning operations

Raw Data

Data editing took place through a number of stages, including: 1. Office editing and coding 2. Data entry 3. Structure checking and completeness 4. Structural checking of SPSS data files

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Agency.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables.
• A post-harmonization cleaning process is then conducted on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

The survey sample consisted of 5,272 households, weights were modified to account for the non-response rate. The response rate was 88%.

Total sample size = 5,272 Households Household completed = 4317 Households Traveling households = 66 Households Unit does not exist = 48 Households No one at home = 135 Households Refused to cooperate = 347 Households Vacant housing unit = 222 Households No available information = 6 Households Other= 30 Households

Response and non-response rates formulas:

Percentage of over-coverage errors = Total cases of over-coverage*100% Number of cases in original sample = 5% Non-response rate = Total cases of non-response*100% Net sample size = 12% Net sample = Original sample - cases of over-coverage Response rate = 100% - non-response rate= 88%

Sampling error estimates

The impact of errors on data quality was reduced to a minimum due to the high efficiency and outstanding selection, training, and performance of the fieldworkers.

Procedures adopted during the fieldwork of the survey were considered a necessity to ensure the collection of accurate data, notably: 1- Develop schedules to conduct field visits to households during survey fieldwork. The objectives of the visits and the data collected on each visit were predetermined. 2- Fieldwork editing rules were applied during the data collection to ensure corrections were implemented before the end of fieldwork activities 3- Fieldworkers were instructed to provide details in cases of extreme expenditure or consumption by the household. 4- Questions on income were postponed until the final visit at the end of the month 5- Validation rules were embedded in the data processing systems, along with procedures to verify data entry and data edit.

Abstract

Within the frame of PCBS' efforts in providing official Palestinian statistics in the different life aspects of Palestinian society and because the wide spread of Computer, Internet and Mobile Phone among the Palestinian people, and the important role they may play in spreading knowledge and culture and contribution in formulating the public opinion, PCBS conducted the Household Survey on Information and Communications Technology, 2014.

The main objective of this survey is to provide statistical data on Information and Communication Technology in the Palestine in addition to providing data on the following: -

· Prevalence of computers and access to the Internet. · Study the penetration and purpose of Technology use.

Geographic coverage

Palestine (West Bank and Gaza Strip) , type of locality (Urban, Rural, Refugee Camps) and governorate

Analysis unit

Household. Person 10 years and over .

Universe

All Palestinian households and individuals whose usual place of residence in Palestine with focus on persons aged 10 years and over in year 2014.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame The sampling frame consists of a list of enumeration areas adopted in the Population, Housing and Establishments Census of 2007. Each enumeration area has an average size of about 124 households. These were used in the first phase as Preliminary Sampling Units in the process of selecting the survey sample.

Sample Size The total sample size of the survey was 7,268 households, of which 6,000 responded.

Sample Design The sample is a stratified clustered systematic random sample. The design comprised three phases:

Phase I: Random sample of 240 enumeration areas. Phase II: Selection of 25 households from each enumeration area selected in phase one using systematic random selection. Phase III: Selection of an individual (10 years or more) in the field from the selected households; KISH TABLES were used to ensure indiscriminate selection.

Sample Strata Distribution of the sample was stratified by: 1- Governorate (16 governorates, J1). 2- Type of locality (urban, rural and camps).

Sampling deviation

-

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire consists of identification data, quality controls and three main sections: Section I: Data on household members that include identification fields, the characteristics of household members (demographic and social) such as the relationship of individuals to the head of household, sex, date of birth and age.

Section II: Household data include information regarding computer processing, access to the Internet, and possession of various media and computer equipment. This section includes information on topics related to the use of computer and Internet, as well as supervision by households of their children (5-17 years old) while using the computer and Internet, and protective measures taken by the household in the home.

Section III: Data on persons (aged 10 years and over) about computer use, access to the Internet and possession of a mobile phone.

Cleaning operations

Preparation of Data Entry Program: This stage included preparation of the data entry programs using an ACCESS package and defining data entry control rules to avoid errors, plus validation inquiries to examine the data after it had been captured electronically.

Data Entry: The data entry process started on 8 May 2014 and ended on 23 June 2014. The data entry took place at the main PCBS office and in field offices using 28 data clerks.

Editing and Cleaning procedures: Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

Response rate

Response Rates= 79%

Sampling error estimates

There are many aspects of the concept of data quality; this includes the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are three components to the quality of statistics: accuracy, comparability, and quality control procedures.

Checks on data accuracy cover many aspects of the survey and include statistical errors due to the use of a sample, non-statistical errors resulting from field workers or survey tools, and response rates and their effect on estimations. This section includes:

Statistical Errors Data of this survey may be affected by statistical errors due to the use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators.

Variance calculations revealed that there is no problem in disseminating results nationally or regionally (the West Bank, Gaza Strip), but some indicators show high variance by governorate, as noted in the tables of the main report.

Non-Statistical Errors Non-statistical errors are possible at all stages of the project, during data collection or processing. These are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous efforts were made to train the field workers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, and practical and theoretical training took place during the training course. Training manuals were provided for each section of the questionnaire, along with practical exercises in class and instructions on how to approach respondents to reduce refused cases. Data entry staff were trained on the data entry program, which was tested before starting the data entry process.

Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

The sources of non-statistical errors can be summarized as: 1. Some of the households were not at home and could not be interviewed, and some households refused to be interviewed. 2. In unique cases, errors occurred due to the way the questions were asked by interviewers and respondents misunderstood some of the questions.

Abstract

The production and utilization of food crops is a necessity to humanity. Agriculture, as a primary activity directly connected to food availability, plays a crucial role in responding to this necessity. Agriculture is presumed to be the engine for economic development in developing countries and more oriented to rural development to ensure the wellbeing of the population. Consequently the efforts of government and non - government organizations have been poured on to it besides the farmers' to realize food security. Adverse conditions emanating from natural disasters and man made problems such as the over exploitation of land generate shocks to agriculture that instigate crises related to food availability. These and other effects necessitate a priority in scrutinizing the performance of agriculture in order to combat food crises. Accurate and timely statistics are a requisite to check, appraise and gauge the agricultural situation. They are used to inform data users of the nature of agriculture and changes taking place in it and trigger policy intervention. To this end, the Central Statistical Agency (CSA) has been furnishing statistical information on the country's agriculture since 1980-1981. As part of this task the 2005-2006 (1998 E.C) Agricultural Sample Survey was conducted to provide data on crop area and production of crops within the private peasant holdings for Main (“Meher”) Season of the cited year.

The general objective of CSA's Agricultural Sample Survey (AgSS) is to collect basic quantitative information on the country's agriculture that is essential for planning, policy formulation, monitoring and evaluation of mainly food security and other agricultural activities.

The specific objectives of Main (“Meher”) Season Post Harvest Survey are: - To estimate the total cultivated area, production and yield of crops and provide estimates of land use area and quantity of agricultural inputs. - To estimate the total volume of inputs used, inputs applied area and number of holders using inputs. - To estimate the total cultivated area and other forms of land use.

Geographic coverage

The 2005-2006 annual Agricultural Sample Survey covered the entire rural parts of the country except all zones of Gambella region, and the non-sedentary population of three zones of Afar and six zones of Somali regions.

Analysis unit

Agricultural household/ Holder/ Crop

Universe

Agricultural households

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: The list containing EAs of all regions and their respective agricultural households obtained from the 2001/02 Ethiopian Agricultural Sample Enumeration (EASE) was used as the sampling frame in order to select the primary sampling units (EAs). Consequently, all sample EAs were selected from this frame based on the design proposed for the survey. Resettlement localities, on the other hand, are sub-samples of the list of all resettlements localities obtained from each region. The second stage sampling units, households, were selected from a fresh list of households that were prepared for each EA/ resettlement localities at the beginning of the survey.

Sample Design: In order to select the sample a stratified two-stage cluster sample design was implemented. Enumeration areas (EAs) /resettlement locality were taken to be the primary sampling units (PSUs) and the secondary sampling units (SSUs) were agricultural households. In 2005-2006, unlike the years before, in order to obtain a fairly representative number of extension program participant households the CSA categorized the listed agricultural households in each EAs/resettlement area into two strata, i.e. households that are and that are not participants of extension program. The stratification was done on the basis of the six major crops where by the extension program is mostly exercised in the country. The crops are maize, teff, wheat, barley, sorghum and finger millet. The sample size for the 2005-2006 agricultural sample survey was determined by taking into account of both the required level of precision for the most important estimates within each domain and the amount of resources allocated to the survey. In order to reduce non-sampling errors manageability of the survey in terms of quality and operational control was also in addition considered. Except Harari, Addis Ababa and Dire Dawa, where each region as a whole was taken to be the domain of estimation; each zone of a region / special wereda was adopted as a stratum for which major findings of the survey are reported. Moreover, values about the 2005-2006 cultivated areas of crops and the expected amount of production for Gambella region is also provided. However, it is important to note that the values are not obtained from the survey but they are projections from the results of the 2003/04 annual Crop Production Forecast Sample Survey.

Selection Scheme: Enumeration areas/resettlement localities from each stratum were selected systematically using probability proportional to size sampling technique; size being number of agricultural households. The sizes for EAs were obtained from the 1994 Population & Housing Census and adjusted for the sub-sampling effect. Sizes for resettlement localities on the other hand were obtained from the 2004 listings of resettlement localities. From the fresh list of households prepared at the beginning of the survey 30 agricultural households within each sample EA/resettlement locality were selected systematically. Twenty of the households were selected from non extension participant agricultural households while the rest 10 households were selected from extension participant agricultural households.

Note: Distribution of sampling units planned and covered EAs and resettlement localities) by stratum is presented in Appendix III of 2005-2006 Agricultural Sample Survey, Volume I report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2005-2006 annual Agricultural Sample Survey used structured questionnaires to collect agricultural information from selected sample households. List of forms in the questionnaires: - AgSS Form 98/0: It contains forms that used to list all households in the sample areas. - AgSS Form 98/1: It contains forms that used to list selected households in the sample areas. - AgSS Form 98/2A: It contains forms that used to collect information about crops, results of area measurements covered by crops and other land uses. - AgSS Form 98/2B: It contains forms that used to collect information about miscellaneous questions for the holders. - AgSS Form 98/4: It contains forms that used to collect information about list of temporary crop fields for selecting crop cutting plots. - AgSS Form 98/5: It contains forms that used to collect information about list of temporary crop cutting results.

Note: The questionnaires are presented in the Appendix III of the 2005-2006 Agricultural Sample Survey report, Volume I which is provided as external resource.

Cleaning operations

Editing, Coding and Verification: Statistical data editing plays an important role in ensuring the quality of the collected survey data. It minimizes the effects of errors introduced while collecting data in the field, hence the need for data editing, coding and verification. Although coding and editing are done by the enumerators and supervisors in the field, respectively, verification of this task is done at the Head Office. An editing, coding and verification instruction manual was prepared and reproduced for this purpose. Then 55 editors-coders and verifiers were trained for two days in editing, coding and verification using the aforementioned manual as a reference and teaching aid. The completed questionnaires were edited, coded and later verified on a 100 % basis before the questionnaires were passed over to the data entry unit. The editing, coding and verification exercise of all questionnaires took 25 days.

Data Entry, Cleaning and Tabulation: Before data entry, the Natural Resources and Agricultural Statistics Department prepared edit specification for the survey for use on personal computers for data consistency checking purposes. The data on the edited and coded questionnaires were then entered into personal computers. The data were then checked and cleaned using the edit specifications prepared earlier for this purpose. The data entry operation involved about 80 data encoders and it took 60 days to finish the job. Finally, summarization of the data was done on personal computers to produce statistical tables as per the tabulation plan.

Response rate

A total of 2,024 enumeration areas (EAs) and 250 resettlement localities were selected to be covered in the survey. However, due to various reasons that are beyond control, in 12 EAs and 1 resettlement locality the survey could not be successful and hence interrupted. Thus, all in all the survey succeeded to cover 2,012 EAs and 249 resettlement localities (99.43 %) throughout the regions.

Sampling error estimates

Estimation procedure of totals, ratios, sampling error and the measurement of precision of estimates (CV) are given in Appendix I and II of 2005-2006 Agricultural Sample Survey, Volume I report which is provided as external resource.