Abstract

The Statistical Service Law 135 of 1985 established the Ghana Statistical Service (GSS) as part of the Ghana Public Service. GSS by mandate conducts censuses and surveys and publishes socio-economic data critical for the development of the country. The GSS Microdata Catalog holds GSS micro-datasets from 1960 to the current year, disseminated as public use or research use data.

Analysis unit

Households, individuals, and establishments

Kind of data

Administrative records and survey data

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This article investigates: What groups were most affected by COVID-19? How did mental health diagnosis and substance use disorder patterns change? Most importantly, what can these data show us about what was done immediately after COVID-19 to alleviate mental health and substance use diagnoses and how might we better address future public health challenges? This analysis utilized data from multiple national surveys to examine trends in mental health and substance use and the availability of treatment facilities. The analysis focused on both before and after the COVID-19 pandemic specifically in 2018 and 2022. The primary data sources were the General Social Survey (GSS), the Mental Health Client-Level Data (MH-CLD) data set, and the National Substance Use and Mental Health Services Survey (N-SUMHSS). This analysis reveals significant shifts in both mental health and substance use trends following the COVID-19 pandemic.

The China GSS is an annual or biannual questionnaire survey of China's urban and rural households aiming to monitor systematically the changing relationship between social structure and quality of life in urban and rural China. The objectives of the China GSS are: (1) to gather longitudinal data on social trends; (2) to address issues of theoretical and practical significance; and (3) to serve as a global resource for the international scholarly community. Includes: labour force activity, demographic variables, household size and composition, ethnicity of R and parents, mobility, dwelling, income, expenditures and facilities, education, military service, etc. 1 data file (1,000 logical records) & accompanying documentation (5 pdf files) in both English and Chinese characters.

Ghana GSS Projection: Population: Female data was reported at 15,231.056 Person th in 2020. This records a decrease from the previous number of 15,392.003 Person th for 2019. Ghana GSS Projection: Population: Female data is updated yearly, averaging 14,264.824 Person th from Dec 2011 (Median) to 2020, with 10 observations. The data reached an all-time high of 15,392.003 Person th in 2019 and a record low of 12,929.830 Person th in 2011. Ghana GSS Projection: Population: Female data remains active status in CEIC and is reported by Ghana Statistical Service. The data is categorized under Global Database’s Ghana – Table GH.G002: Population Projection: by Sex: Ghana Statistical Service.

Abstract

The Ghana Statistical Service (GSS) and the World Bank Development Economics Research Group (DECRG) partnered to implement the survey. The purpose was to find out household's access to and use of available financial services.This was a follow-up to an earlier test of survey designs regarding household access to financial services. The underlying premise is that the identity of a respondent can affect the quality and completeness of the information provided, especially when that respondent is providing information about other household members.

The survey will examine whether questions about specific products (e.g. credit cards, life insurance policies, savings clubs) elicit more complete information than questions asking whether a respondent uses services from a type of provider (e.g. commercial bank, credit union).

To derive the data necessary for these tests, the Financial Service Survey incorporated an experimental design in which one of three versions of the survey instrument (questionnaire) was randomly administered to each household. Individual household members were also randomly selected to respond to some sections of the questionnaire.

Geographic coverage

National Regional District, Municipal, Metropolitan

Analysis unit

Individuals

Universe

The survey covered all adult household members (usual residents) aged 15 years and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The most recently visited enumeration areas (EAs) for the Ghana Living Standards Survey Round 5 (GLSS5) were targeted for the survey. This is because the characteristics of these households may not have changed much, and they were more likely to recollect information they had already provided. All the 120 EAs visited in the 10th and 11th cycles of the GLSS5 were included in the survey, with an additional 34 EAs selected from the 60 EAs visited in the 9th cycle. Households within the 154 EAs were listed and 15 selected randomly from each EA yielding a total of 2,310 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used in the survey:

1. Group 1 Questionnaire - All questions in the three (3) sections were administered to all household members aged 15 years and older. It collected information on background characteristics, the use of financial services and products and actions and attitudes towards accessing and using financial services and products.

2. Group 2 Questionnaire - Sections 1 and 2 of this questionnaire were administered to all household members aged 15 years and older. Sections 3 and 4 were administered to household members randomly selected using the Kish Grid based on given criteria.

3. Group 3 Questionnaire - All questions in section (1) were administered to heads of household and one randomly selected household member and covered background characteristics. Section two (2) was administered to heads of household and covered the use of financial services. Sections 3 and 4 were administered to a randomly selected household member and covered the use of financial services and products and actions and attitudes towards access and use of financial services and products.

All the questionnaires were in English and whenever necessary, the interview was conducted in a language of the respondent's choice. An interpreter was also used where the interviewer was not proficient in the respondent's choice of language.

Cleaning operations

The GSS data editing occurs at three levels:

1. Field editing by interviewers and supervisors
2. Office editing
3. Data cleaning and imputation

Response rate

Out of the 2,310 households selected for the survey, 2,292 were identified and successfully enumerated. This yielded a response rate of 99.2 percent.

Abstract

The 2022 Ghana Demographic and Health Survey (2022 GDHS) is the seventh in the series of DHS surveys conducted by the Ghana Statistical Service (GSS) in collaboration with the Ministry of Health/Ghana Health Service (MoH/GHS) and other stakeholders, with funding from the United States Agency for International Development (USAID) and other partners.

The primary objective of the 2022 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the GDHS collected information on: - Fertility levels and preferences, contraceptive use, antenatal and delivery care, maternal and child health, childhood mortality, childhood immunisation, breastfeeding and young child feeding practices, women’s dietary diversity, violence against women, gender, nutritional status of adults and children, awareness regarding HIV/AIDS and other sexually transmitted infections, tobacco use, and other indicators relevant for the Sustainable Development Goals - Haemoglobin levels of women and children - Prevalence of malaria parasitaemia (rapid diagnostic testing and thick slides for malaria parasitaemia in the field and microscopy in the lab) among children age 6–59 months - Use of treated mosquito nets - Use of antimalarial drugs for treatment of fever among children under age 5

The information collected through the 2022 GDHS is intended to assist policymakers and programme managers in designing and evaluating programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, men aged 15-59, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

To achieve the objectives of the 2022 GDHS, a stratified representative sample of 18,450 households was selected in 618 clusters, which resulted in 15,014 interviewed women age 15–49 and 7,044 interviewed men age 15–59 (in one of every two households selected).

The sampling frame used for the 2022 GDHS is the updated frame prepared by the GSS based on the 2021 Population and Housing Census.1 The sampling procedure used in the 2022 GDHS was stratified two-stage cluster sampling, designed to yield representative results at the national level, for urban and rural areas, and for each of the country’s 16 regions for most DHS indicators. In the first stage, 618 target clusters were selected from the sampling frame using a probability proportional to size strategy for urban and rural areas in each region. Then the number of targeted clusters were selected with equal probability systematic random sampling of the clusters selected in the first phase for urban and rural areas. In the second stage, after selection of the clusters, a household listing and map updating operation was carried out in all of the selected clusters to develop a list of households for each cluster. This list served as a sampling frame for selection of the household sample. The GSS organized a 5-day training course on listing procedures for listers and mappers with support from ICF. The listers and mappers were organized into 25 teams consisting of one lister and one mapper per team. The teams spent 2 months completing the listing operation. In addition to listing the households, the listers collected the geographical coordinates of each household using GPS dongles provided by ICF and in accordance with the instructions in the DHS listing manual. The household listing was carried out using tablet computers, with software provided by The DHS Program. A fixed number of 30 households in each cluster were randomly selected from the list for interviews.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Face-to-face computer-assisted interviews [capi]

Research instrument

Four questionnaires were used in the 2022 GDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Ghana. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

The GSS organized a questionnaire design workshop with support from ICF and obtained input from government and development partners expected to use the resulting data. The DHS Program optional modules on domestic violence, malaria, and social and behavior change communication were incorporated into the Woman’s Questionnaire. ICF provided technical assistance in adapting the modules to the questionnaires.

Cleaning operations

DHS staff installed all central office programmes, data structure checks, secondary editing, and field check tables from 17–20 October 2022. Central office training was implemented using the practice data to test the central office system and field check tables. Seven GSS staff members (four male and three female) were trained on the functionality of the central office menu, including accepting clusters from the field, data editing procedures, and producing reports to monitor fieldwork.

From 27 February to 17 March, DHS staff visited the Ghana Statistical Service office in Accra to work with the GSS central office staff on finishing the secondary editing and to clean and finalize all data received from the 618 clusters.

Response rate

A total of 18,540 households were selected for the GDHS sample, of which 18,065 were found to be occupied. Of the occupied households, 17,933 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 15,317 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 15,014 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 7,263 men age 15–59 were identified as eligible for individual interviews and 7,044 were successfully interviewed.

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 2022 Ghana Demographic and Health Survey (2022 GDHS) 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 2022 GDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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. 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% 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 2022 GDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the GDHS 2022 is an SAS program. This program used the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Standardisation exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women and men
• Heaping in anthropometric measurements for children (digit preference)
• Observation of mosquito nets
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Number of

Macau GSS: Receipts: Gaming Services data was reported at 228,832,000.000 MOP th in 2016. This records a decrease from the previous number of 232,951,000.000 MOP th for 2015. Macau GSS: Receipts: Gaming Services data is updated yearly, averaging 190,621,000.000 MOP th from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 362,745,000.000 MOP th in 2013 and a record low of 44,043,000.000 MOP th in 2004. Macau GSS: Receipts: Gaming Services data remains active status in CEIC and is reported by Statistics and Census Service. The data is categorized under Global Database’s Macau – Table MO.S003: Annual Gaming Sector Survey.

Abstract

The Job Tracking Survey was conducted to provide credible data for effective monitoring and evaluation of job creation programmes being implemented by the Government. These data were to be used to monitor the progress of the Poverty Reduction Strategies (PRS) and the Millennium Development Goals (MDGs). The Growth and Poverty Reduction Prgramme (GPRP) in Ghana provides a coordinated programme for achieving sectoral, national and international development outcomes including the MDGs. Unemployment reaims a critical challenge in efforts at reducing poverty. Policy orientation in 2006 was therefore towards providing various incentives for firms to invest productively, create jobs and expand. Thus the theme: Investing in People, Investing in Jobs.

The survey targeted firms which are the main source of information on the creation of jobs. The study collected information background of the firms, including the type of operation and ownership. It also collected information on the knowledge and access to various tax incentives granted to the different sectors of the economy and how these have helped the firms in their expansion prograames towards the creation of jobs.

Several indicators including jobs created, job losses, training (both on the job and formal) and level of skills were also collected. Finally, the survey evaluates the impact of the National Youth Employment Programme (NYEP), labour market demand and job vacancies, job quality and related labour market issues.

Geographic coverage

National

Analysis unit

Establishments

Universe

Firms within the private and public sector in Ghana.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling for the survey was purposive, and was designed to provide sufficient level of precision for survey estimates for each 3-digit ISIC (International Standard Industrial Classicfication of economic avtivities) domain.

A total of 2,015 establishments in both the private and public sector were covered in the survey. These were made up of 784 from the public sector, made up of 701 public sector institutions in the Ministries, Departments and Agencies, and other public insitutions in the 138 Metropolitan, Municipal and District Assemblies. All establishments operating under the President's Special Initiatives (PSIs) were also covered. In addition, 83 public limited companies were covered.

For the private sector, all members of the Association of Ghana Industries (AGI), members of the Ghana Club 100, and establishments listed on the Ghana Stock Exchange were covered in the survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

One questionnaire, the Job Tracking Survey Questionnaire was used. The questionnaire was organized in 11 parts (A - K) and the questions were in English.

Part A was used to collect information on the background of the establishments including Name, Address, Type of Ownership, Organization and Goods and Services produced.

Part B looked at the establishment's connection with any Policy Objectives and Outcomes within the various sectors.

Part C looked the creation of jobs and hiring of personnel.

Part D was devoted to awareness and access to Tax Incentives.

Part E dealt with On-The -Job-Training, Internship and Industrial attachment, while Part F sought for information on Micro-finance, Loans and Grants.

Part G was devoted to outcomes under the National Youth Employment Programme.

Part H collected information on the creation of jobs within the Construction sector.

Parts I and J were used to solicit information on Labour Market Demand and Job Vacancies, Job Quality and other labour market indicators.

PArt K sought for comments and suggestions for the preparation of the 2007 national budget.

Cleaning operations

The GSS data editing occurs at three levels:

1. Field editing by interviewers and supervisors
2. Office editing
3. Data cleaning and imputation

Response rate

All the 2,015 establishments selected in both the private and public sector were covered in the survey.

This dataset represents the outreach for solicitations conducted by Government Support Services (GSS) within identified segments of the marketplace that businesses have identified themselves as performing in. The data includes a breakdown by Outreach Type of DE, Small, MWBE and Veteran and SDV owned businesses who were invited to consider responding to the solicitation. This data does not include outreach data from Cooperatives or Government Services Administration Contracts that GSS has executed contracts with.

Abstract

The Integrated Business Establishment Survey was an establishment census conducted by the Ghana Statistical Service (GSS) in 2014. IBES 2014 phase 1 collected data on 638 000 establishments in Ghana across all sectors. Phase 2 was a roughly 5% stratified sample of the phase 1 firms undertaken in 2015 (GSS, 2017). Phase 2 contained many more questions to the firms sampled, for example their costs, revenues and assets. GSS allowed DataFirst to release a 40% sample of the phase 2 data, through a project funded by the Project for Enterprise Development in Low Income Countries (PEDL). Thus the observations we have represent aronud 2% of the total census.

Geographic coverage

The survey was designed to be representative at the regional level.

Analysis unit

Establishments

Universe

All non-household establishments with a fixed site and any household-based business with a sign indicating its presence within a household.

Kind of data

Census/enumeration data

Sampling procedure

IBES 2014 consisted of two phases. Phase 1 was a census of non-household establishments with a fixed site and any household-based business with a sign indicating its presence within a household. Phase 2 was a stratified roughly 5% sample of the phase I firms.

Mode of data collection

Face-to-face [f2f]

Research instrument

For Phase II there were nine different questionnaires (or "forms") used, depending on the sector that the firms main business activity was in. Manufacturing was split further, with small firms (<30 persons engaged) getting form 3A and larger firms getting 3B.

Cleaning operations

The data are released with a detailed description of the how the final dataset was prepared - please see the documentation.

Response rate

78% of the firms selected for re-interview in phase II were successfully interviewed.

Data appraisal

The data are released with a detailed description of the how the final dataset was prepared and the data quality issues - please see the documentation.

Abstract

The purpose was to find out household's access to and use of available financial services.This was a follow-up to an earlier test of survey designs regarding household access to financial services. The underlying premise is that the identity of a respondent can affect the quality and completeness of the information provided, especially when that respondent is providing information about other household members. The survey will examine whether questions about specific products (e.g. credit cards, life insurance policies, savings clubs) elicit more complete information than questions asking whether a respondent uses services from a type of provider (e.g. commercial bank, credit union). To derive the data necessary for these tests, the Financial Service Survey incorporated an experimental design in which one of three versions of the survey instrument (questionnaire) was randomly administered to each household. Individual household members were also randomly selected to respond to some sections of the questionnaire.

Geographic coverage

National coverage

Analysis unit

Household, individual

Universe

The survey covered all adult household members (usual residents) aged 15 years and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The most recently visited enumeration areas (EAs) for the Ghana Living Standards Survey Round 5 (GLSS5) were targeted for the survey. This is because the characteristics of these households may not have changed much, and they were more likely to recollect information they had already provided. All the 120 EAs visited in the 10th and 11th cycles of the GLSS5 were included in the survey, with an additional 34 EAs selected from the 60 EAs visited in the 9th cycle. Households within the 154 EAs were listed and 15 selected randomly from each EA yielding a total of 2,310 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used in the survey:

1. Group 1 Questionnaire - All questions in the three (3) sections were administered to all household members aged 15 years and older. It collected information on background characteristics, the use of financial services and products and actions and attitudes towards accessing and using financial services and products.
2. Group 2 Questionnaire - Sections 1 and 2 of this questionnaire were administered to all household members aged 15 years and older. Sections 3 and 4 were administered to household members randomly selected using the Kish Grid based on given criteria.
3. Group 3 Questionnaire - All questions in section (1) were administered to heads of household and one randomly selected household member and covered background characteristics. Section two (2) was administered to heads of household and covered the use of financial services. Sections 3 and 4 were administered to a randomly selected household member and covered the use of financial services and products and actions and attitudes towards access and use of financial services and products. All the questionnaires were in English and whenever necessary, the interview was conducted in a language of the respondent's choice. An interpreter was also used where the interviewer was not proficient in the respondent's choice of language.

Cleaning operations

The GSS data editing occurs at three levels: 1. Field editing by interviewers and supervisors 2. Office editing 3. Data cleaning and imputation

Response rate

Out of the 2,310 households selected for the survey, 2,292 were identified and successfully enumerated. This yielded a response rate of 99.2 percent.

A cloud based service for creating a single system of record for all types of technology business services managed by M/CIO. ServiceNow ITSM applications are built on a single platform as a service, offering a consistent and intuitive user experience through the entire IT Infrastructure Library (ITIL) service lifecycle. This is not classified as GSS. This is a client-facing IT system where M/CIO is the client.

Wimmera Southern Mallee GIS Shared Services default mapping styles. Although all due care has been taken to ensure that this data is correct, no warranty is expressed or implied by Wimmera CMA in …Show full descriptionWimmera Southern Mallee GIS Shared Services default mapping styles. Although all due care has been taken to ensure that this data is correct, no warranty is expressed or implied by Wimmera CMA in its use.

Abstract

The 2017 Ghana Maternal Health Survey (2017 GMHS) was designed to produce representative estimates for maternal mortality indicators for the country as a whole, and for each of the three geographical zones, namely Coastal (Western, Central, Greater Accra and Volta), Middle (Eastern, Ashanti and Brong Ahafo) and Northern (Northern, Upper East and Upper West). For other indicators such as maternal care, fertility and child mortality, the survey was designed to produce representative results for the country as whole, for the urban and rural areas, and for each of the country’s 10 administrative regions.

The primary objectives of the 2017 GMHS were as follows: • To collect data at the national level that will allow an assessment of the level of maternal mortality in Ghana for the country as a whole and for three zones: Coastal (Western, Central, Greater Accra, and Volta regions), Middle (Eastern, Ashanti, and Brong Ahafo regions), and Northern (Northern, Upper East, and Upper West regions) • To identify specific causes of maternal and non-maternal deaths, in particular deaths due to abortionrelated causes, among adult women • To collect data on women’s perceptions of and experiences with antenatal, maternity, and emergency obstetrical care, especially with regard to care received before, during, and following the termination or abortion of a pregnancy • To measure indicators of the utilisation of maternal health services, especially post-abortion care services • To allow follow-on studies and surveys that will be used to observe possible reductions in maternal mortality as well as abortion-related mortality

The information collected through the 2017 GMHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Woman age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2017 GMHS was designed to provide estimates of key reproductive health indicators for the country as a whole, for urban and rural areas separately, for three zonal levels (Coastal, Middle, and Northern), and for each of the 10 administrative regions in Ghana (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West).

The sampling frame used for the 2017 GMHS is the frame of the 2010 Population and Housing Census (PHC) conducted in Ghana. The 2010 PHC frame is maintained by GSS and updated periodically as new information is received from various surveys. The frame is a complete list of all census enumeration areas (EAs) created for the PHC.

The 2017 GMHS sample was stratified and selected from the sampling frame in two stages. Each region was separated into urban and rural areas; this yielded 20 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before the sample selection, according to administrative units at different levels, and by using a probability proportional to size selection at the first stage of sampling.

In the first stage, 900 EAs (466 EAs in urban areas and 434 EAs in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum. A household listing operation was implemented from 25 January to 9 April 2017 in all of the selected EAs. The resulting lists of households then served as a sampling frame for the selection of households in the second stage. The household listing operation included inquiring of each household if there had been any deaths in that household since January 2012 and, if so, the name, sex, and age at time of death of the deceased person(s).

Some of the selected EAs were very large. To minimise the task of household listing, each large EA selected for the 2017 GMHS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment. Thus, in the GMHS, a cluster is either an EA or a segment of an EA. As part of the listing, the field teams updated the necessary maps and recorded the geographic coordinates of each cluster. The listing was conducted by 20 teams that included a supervisor, three listers/mappers, and a driver.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the 2017 GMHS: the Household Questionnaire, the Woman’s Questionnaire, and the Verbal Autopsy Questionnaire.

Cleaning operations

All electronic data files for the 2017 GMHS were transferred via the IFSS to the GSS central office in Accra, where they were stored on a password-protected computer. The data processing operation included registering and checking for any inconsistencies and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of openended questions. The data were processed by five GSS staff members. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in June and completed in November 2017.

Response rate

A total of 27,001 households were selected for the sample, of which 26,500 were occupied at the time of fieldwork. Of the occupied households, 26,324 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 25,304 eligible women were identified for individual interviews; interviews were completed with 25,062 women, yielding a response rate of 99%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and 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 2017 Ghana Maternal Health Survey (2017 GMHS) 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 2017 GMHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 among 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 in. For example, for any given statistic calculated from a sample survey, the true value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017 GMHS sample is the result of a multi-stage stratified sampling, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed by SAS programs developed by ICF International. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final 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 - Completeness of information on siblings - Sibship size and sex ratio of siblings - Pregnancy-related mortality trends

See details of the data quality tables in Appendix C of the survey final report.

This dataset highlights the General Salary Schedule (GSS), Police Leadership Service (PLS) and Management Leadership Services (MLS) salary adjustments from Fiscal Year 2015 to current. The additional Salary Schedule information can be viewed at https://www.montgomerycountymd.gov/HR/compensation/Compensation.html

Abstract

The survey was conducted in Ghana between December 2012 and July 2014 as part of the Africa Enterprise Survey 2013 roll-out, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

Data from 720 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Ghana was selected using stratified random sampling. Three levels of stratification were used in this country: firm sector, firm size, and geographic region.

Industry stratification was designed in the way that follows: the universe was stratified into four manufacturing industries (food, textiles and garments, chemicals and plastics, other manufacturing) and two service sectors (retail and other services).

Size stratification was defined following the standardized definition for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees).

Regional stratification for the Ghana ES was defined in four regions: Accra, North (Kumasi and Tamale), Takoradi, and Tema.

For the Ghana ES, several sample frames were used. The first was supplied by the World Bank and consists of enterprises interviewed in Ghana 2007. The World Bank required that attempts should be made to re-interview establishments responding to the Ghana 2007 survey where they were within the selected geographical regions and met eligibility criteria. Due to the fact that the previous round of surveys seemed to have utilized different stratification criteria (or no stratification at all) and due to the prevalence of small firms and firms located in the capital city in the 2007 sample the following convention was used. The presence of panel firms was limited to a maximum of 50% of the achieved interviews in each cell. That sample is referred to as the Panel.

The second frame was constructed using different lists acquired from relevant institutions in Ghana. The main lists used were obtained from the Ghana Statistical Service (GSS). These include: 1) The 2012 Firm Registry. The registry lacked information on firm employee size. 2) The list of firms paying VAT. The VAT dataset included a variable on firms; turnover. The VAT dataset and Firm Registry were merged by using the firms' identification number (TIN). VAT information was not available for all firms in the Firm Registry. 3) The list of Large Tax Payers. The Large Tax Payers file also lacked information on firm employee size.

Since firm size was missing from all lists mentioned above, after having discussed with GSS and with the local contractor the following methods were used to predict firm size. - All firms who were in the Firm Registry but not in the VAT dataset were considered to be micro firms and therefore not use in the current survey. - Firms who were in the Firm Registry and in the VAT dataset were considered to be small firms. - Firms in the Large Tax Payers dataset were considered medium or large firms. The original design was divided into two size groups: small firms and medium and large firms.

During fieldwork the GSS lists proved to be very inaccurate and not sufficient to reach the target sample design, As such they were complemented with additional lists of firms from the Ghana Chamber of Commerce and Industry and Business Associations. The list from the Ghana Chamber of Commerce lacked information on firm employee size or firm turnover. Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 1.3% (26 out of 1,990 establishments).

Finally, a block enumeration was also undertaken in order to build an additional list. The block enumeration allowed to physically creating a list of establishments from which to sample from. A total of 41 blocks were enumerated in the four locations included in the project out of the total 804 blocks identified. The enumeration was conducted without major problems in the time planned. The list of enumerated firms contained 958 records eligible for main Enterprise Survey.

Note: Unlike the standard ES, the universe for the Ghana ES is characterized by the presence of 5 size categories. The category medium&large was added as stratum in order to sample from the GSS large payers list, while the category "unknow size" was included in order to sample the firms in the Chamber of Commerce and Industry list.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Module Questionnaire - Services Module Questionnaire

The survey is fielded via manufacturing or services questionnaires in order not to ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve

Abstract

Amongst the many objectives of the survey were the following: · Measure the extent to which the supply and quality of official statistics satisfy the needs of users. · Examine the strengths and weaknesses of official statistics and identify the areas that need improvement. · Determine how relevant statistical products from the NSS are for informed decision-making by government and business communities, by the education sector; and for informed discussions and debates by the media. · Help GSS formulate actions for the NSS and increase quality of statistical products; help improve packaging of statistical products to be user friendly, and enhance use of statistical information in the country. · Make known the perception of users of statistics on the supply and quality of statistics in terms of reliability, credibility, timeliness and packaging. · Monitor the use of statistics and for examining the perceptions of users of statistics. · Identify misconceptions and help to determine the corrective actions that need to be taken to improve the NSS.

Geographic coverage

National coverage

Analysis unit

Institution, individual

Universe

Several types of institutions or organizations constituted the broad sector, as explained below: · Metropolitan, Municipal and District Assemblies (MMDAs)/Ministries, Department and Agencies (MDAs): includes government ministries; the legislative assembly of the country (parliamentarians) and associated entities, such as public agencies; the central bank (Bank of Ghana) and other government bodies; and district assemblies. · Business community: includes business organizations such as the chamber of commerce, industries and other business entities, association of employers, labour unions, banks and other financial corporations. · Education sector: includes universities and other tertiary institutions, educational institutions at the intermediate levels, such as teacher training colleges, nursing training schools etc. · Media: includes the main media houses in the country such as newspaper, radio and television stations and other media publishing houses writing on economic, societal and political affairs. · International agencies: includes development partners and other international bodies operating within Ghana and dealing with economic and social development issues, providing technical assistance, and donating or administering funds for development. · Civil society: includes key non-governmental organizations, professional associations, religious institutions and political parties. · Individual researchers: These are individuals who collect data from the Ghana Statistical Service for research and other activities.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame of the GUSS was prepared by compiling the names of organizations and individuals who had ever used official statistics or statistical product from all the producers of official statistics from January 2007 to December 2011 across the 10 regions of Ghana. This resulted in master sampling frame of 934 local users of statistics. This included: 1. Ministries, Department and Agencies (MDAs) and Metropolitan, Municipal and District Assemblies (MMDAs) 2. Financial Institutions 3. International Organizations 4. Media Houses 5. Educational/Research Organizations 6. Other Private Enterprises 7. Civil Society and 8. Individual researchers.

By assuming a Z-value of 1.96, an absolute precision of 10 percent and an expected rate of satisfaction of 50 percent, each sector required at least 87 institutions/individuals. This represents about 10 percent of the sample size required nationally to be able to have enough data for detailed analysis for each sector. In determining the total sample size of the survey, it was ensured that each sector had enough representation of statistical users to allow detail analysis per sector.

A one-stage stratified sample design with proportional allocation to size was adopted in selecting the number of users for each sector. The selection procedure of each sector involved the following steps: · arranging Institutions/individuals in each sector in alphabetical order, and · systematically selecting Users in each sector using the systematic sampling method.

Sampling deviation

No deviation from the original sample design was made.

Mode of data collection

Face-to-face [f2f]

Research instrument

A GUSS questionnaire was developed based on a standard template used by other statistics authorities elsewhere. The standard templates were customized to ensure that it was appropriate for Ghana. All the questionnaires were in English and whenever necessary, the interview was conducted in a language of the respondent's choice. The questionnaire was in four sections:

• Section A asked about the respondents' use of official statistics - which statistics they use regularly, the main sources from which they obtain those statistics, what they normally use them for, how long and how often they have been using official statistics.
• Section B looked at the respondents' views on the quality of official statistics in terms of relevance and accuracy, reliability, timeliness of release, frequency of release and accessibility; their overall assessment of the quality of, and level of satisfaction with, official statistics in the country.
• Section C asked the respondents about the quality of service delivery by the GSS including the frequency with which they seek their products and services, methods that they use when seeking those products and services, their views on the official websites.
• Section D gathered information on the respondents, including the organizations for which they worked age, sex, education and contact information.

Cleaning operations

Two office editors checked and prepared the questionnaires for data entry as they arrive from the field.

Response rate

A total of 610 institutions/individuals were selected in the sample, of which 566 completed the interview yielding a response rate of 92.8 percent. The difference between selected and completed interview occurred mainly because some of the selected institutions refused and some could not be traced. In some cases the officer to answer the questions had travelled out of the country and some also stopped the interview midway. Business community recorded the least response rate (71.2%) whiles MDAs and the Media recorded 96.6 percent and 95.9 percent respectively.

Macau GSS: EP: OE: Other Contract Services data was reported at 1,573,000.000 MOP th in 2017. This records an increase from the previous number of 1,459,000.000 MOP th for 2016. Macau GSS: EP: OE: Other Contract Services data is updated yearly, averaging 900,067.500 MOP th from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 1,673,000.000 MOP th in 2013 and a record low of 153,321.000 MOP th in 2004. Macau GSS: EP: OE: Other Contract Services data remains active status in CEIC and is reported by Statistics and Census Service. The data is categorized under Global Database’s Macau SAR – Table MO.S003: Annual Gaming Sector Survey.