Ghana Time Use Survey 2009
Ghana, 2009
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Reference ID
GHA-GSS-GTUS-2009-v02.
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Ghana Statistical Service
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Feb 14, 2013
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Identification
Survey ID Number
GHA-GSS-GTUS-2009-v02.
Title
Ghana Time Use Survey 2009
Country
| Name | Country code |
|---|---|
| Ghana | GHA |
Study type
Other Household Survey [hh/oth]
Series Information
This is the first time thisTime Use Survey has been implemented in Ghana
Abstract
EXECUTIVE SUMMARY
In 2006 and 2007, the United Nations Economic Commission for Africa (UNECA), in collaboration with its stakeholders, developed a manual on collecting sex-disaggregated time use data. Using this manual the Ghana Statistical Service, with the financial and technical assistance of UNECA, conducted the fieldwork for the very first Time Use Survey in the country. The main objective of the GTUS was to measure and analyze the time spent in a 24-hour period by different individuals aged 10 years and over - women, men, girls, and boys - on all activities including paid and unpaid work and leisure activities.
A representative sample of 4,800 households was drawn randomly from the list of Enumeration Areas (EAs) of the 2008 Ghana Demographic and Health Survey (GDHS). In the selected households all individuals aged 10 years and older were interviewed on the basis of a questionnaire containing questions common to standard household surveys. The study also used a 24-hour diary, divided into one hour slots, as the core instrument to record activities. Data was collected from June to July, 2009. This report presents the main results of the survey.
Main findings
The results demonstrate a distinct gender dimension with respect to the type of activities men and women were involved in. Men reported being more involved in SNA and remunerated activities (74%) than in extended SNA and unpaid activities (66%), while for women the opposite is true, in that 69% of women were involved in SNA activities and 95% in extended SNA activities. There is also the same noticeable gender difference in respect of learning with 31% of men engaged in this activity against 22% for women.
The gender dimensions of the participation rate also appear within the disaggregated categories of activities. The most noticeable differences can be seen for the SNA activities. For example, men (17%) are more likely than women (11%) to work for formal establishments, which usually offer the best conditions in terms of remuneration and social protection. On the other hand, women (29%) are more likely than men (19%) to be involved in paid domestic work.
Broad activities
Participation rates with regard to the different attributes analyzed e.g. age, marital status, educational attainment, household composition, day of week, etc. have a strong gender dimension. There are also clear gender differences in average time spent on different activities and patterns of engagement in SNA and extended SNA activities (especially unpaid care work). The most noticeable gender difference is on extended SNA, where women spend an average of 3 hours and 29 minutes, which is more than 3 times the average time spent by men (69 minutes) on the same activities. The time spent on different activities when there is further disaggregation again has a clear gender dimension. Men reported spending far more time on work for formal establishments such as corporations and government (65 minutes) than women (23 minutes). In contrast, women reported spending more time on unpaid household work (2 hours and 35 minutes) than men (40 minutes).
SNA activities
The participation rates in SNA activities with regard to the various attributes analyzed have a gender dimension. Both women and men have their highest participation rates (38% and 47% respectively) in subsistence activities, which include subsistence agriculture as well as fetching water and collecting wood for cooking. Nearly one-third of women (29%) were involved in work for households providing services for income, as against one-fifth of men (19%) in the same category of activities. Gender differences persist with regard to average time spent on SNA activities even when other factors e.g. age, marital status, residential area are taken into account. Across nearly all demographic characteristics, men generally dedicate more time to SNA activities than women. The most important gender difference between men and women above 18 years old is with the work for household in construction activities, which seems to be a predominantly male activity.
Extended or non SNA-production
In terms of participation rates, child care is the most important sub-category of unpaid care work for both men and women, with adult care coming far behind as the second most important sub-category. There are distinct gender differences in the average time spent on extended SNA activities. When mean time spent by actors on extended SNA activities is further examined across demographic and other factors, the overall pattern is that women spend more time than men on childcare and unpaid household services, while men generally dedicate more time to adult care. The most significant gender differences with regard to adult care are observed among younger, single/never married or married males, males in informal/loose unions, residing in rural areas and with pre and primary level of schooling. Additional gender differences with respect to adult care are found in the time spent by men on certain weekdays.
Non-productive activities
The overall participation rate in general education is high which shows that Ghana has a relatively good enrollment rate for schooling. Similarly, the difference in enrolment rates between urban and rural areas is not very large. The widest difference between the two living areas, in favour of urban areas is found in the category of additional study, non-formal education and courses during free time. The average time spent in general education is slightly higher in urban areas (320 minutes) than in rural area (314 minutes). But there are no remarkable gender differences between urban and rural dwellers. The location difference in terms of all learning activities combined is largest, and in favour of urban areas (383 minutes against 129 minutes for rural area) when it comes to study related to career and professional development. On average, men in urban areas spend significantly more time on this activity than women, while in rural areas the opposite is the case.
Similarly, the gender dimension appears clearly when it comes to leisure and personal activities. Men participate more to recreation, cultural and sport activities. The participation rate for cultural activities is 6% for men while for women it is 2%, for hobbies and other pastime activities as games it is 14% for men and 5% for women, for sport activities it is 20% for men and 5% for women. More than two-thirds (67%) of men reported having activities related to mass media, while 51% of women reported having the same activities.
Conclusion
The survey revealed how different individuals - women, men, girls, and boys in Ghana spend their time in relation to all types of work and work-related activities, both in terms of paid and unpaid labour. The results from the survey will be used as input in the development of a gender-awareness macroeconomic model for Ghana. The results have also highlighted gender imbalances in average time spent on productive and non-productive activities and on paid and unpaid work. This could well feed into the government's policy decisions in an effort to finding solutions that address gender issues in macroeconomics and poverty reduction
In 2006 and 2007, the United Nations Economic Commission for Africa (UNECA), in collaboration with its stakeholders, developed a manual on collecting sex-disaggregated time use data. Using this manual the Ghana Statistical Service, with the financial and technical assistance of UNECA, conducted the fieldwork for the very first Time Use Survey in the country. The main objective of the GTUS was to measure and analyze the time spent in a 24-hour period by different individuals aged 10 years and over - women, men, girls, and boys - on all activities including paid and unpaid work and leisure activities.
A representative sample of 4,800 households was drawn randomly from the list of Enumeration Areas (EAs) of the 2008 Ghana Demographic and Health Survey (GDHS). In the selected households all individuals aged 10 years and older were interviewed on the basis of a questionnaire containing questions common to standard household surveys. The study also used a 24-hour diary, divided into one hour slots, as the core instrument to record activities. Data was collected from June to July, 2009. This report presents the main results of the survey.
Main findings
The results demonstrate a distinct gender dimension with respect to the type of activities men and women were involved in. Men reported being more involved in SNA and remunerated activities (74%) than in extended SNA and unpaid activities (66%), while for women the opposite is true, in that 69% of women were involved in SNA activities and 95% in extended SNA activities. There is also the same noticeable gender difference in respect of learning with 31% of men engaged in this activity against 22% for women.
The gender dimensions of the participation rate also appear within the disaggregated categories of activities. The most noticeable differences can be seen for the SNA activities. For example, men (17%) are more likely than women (11%) to work for formal establishments, which usually offer the best conditions in terms of remuneration and social protection. On the other hand, women (29%) are more likely than men (19%) to be involved in paid domestic work.
Broad activities
Participation rates with regard to the different attributes analyzed e.g. age, marital status, educational attainment, household composition, day of week, etc. have a strong gender dimension. There are also clear gender differences in average time spent on different activities and patterns of engagement in SNA and extended SNA activities (especially unpaid care work). The most noticeable gender difference is on extended SNA, where women spend an average of 3 hours and 29 minutes, which is more than 3 times the average time spent by men (69 minutes) on the same activities. The time spent on different activities when there is further disaggregation again has a clear gender dimension. Men reported spending far more time on work for formal establishments such as corporations and government (65 minutes) than women (23 minutes). In contrast, women reported spending more time on unpaid household work (2 hours and 35 minutes) than men (40 minutes).
SNA activities
The participation rates in SNA activities with regard to the various attributes analyzed have a gender dimension. Both women and men have their highest participation rates (38% and 47% respectively) in subsistence activities, which include subsistence agriculture as well as fetching water and collecting wood for cooking. Nearly one-third of women (29%) were involved in work for households providing services for income, as against one-fifth of men (19%) in the same category of activities. Gender differences persist with regard to average time spent on SNA activities even when other factors e.g. age, marital status, residential area are taken into account. Across nearly all demographic characteristics, men generally dedicate more time to SNA activities than women. The most important gender difference between men and women above 18 years old is with the work for household in construction activities, which seems to be a predominantly male activity.
Extended or non SNA-production
In terms of participation rates, child care is the most important sub-category of unpaid care work for both men and women, with adult care coming far behind as the second most important sub-category. There are distinct gender differences in the average time spent on extended SNA activities. When mean time spent by actors on extended SNA activities is further examined across demographic and other factors, the overall pattern is that women spend more time than men on childcare and unpaid household services, while men generally dedicate more time to adult care. The most significant gender differences with regard to adult care are observed among younger, single/never married or married males, males in informal/loose unions, residing in rural areas and with pre and primary level of schooling. Additional gender differences with respect to adult care are found in the time spent by men on certain weekdays.
Non-productive activities
The overall participation rate in general education is high which shows that Ghana has a relatively good enrollment rate for schooling. Similarly, the difference in enrolment rates between urban and rural areas is not very large. The widest difference between the two living areas, in favour of urban areas is found in the category of additional study, non-formal education and courses during free time. The average time spent in general education is slightly higher in urban areas (320 minutes) than in rural area (314 minutes). But there are no remarkable gender differences between urban and rural dwellers. The location difference in terms of all learning activities combined is largest, and in favour of urban areas (383 minutes against 129 minutes for rural area) when it comes to study related to career and professional development. On average, men in urban areas spend significantly more time on this activity than women, while in rural areas the opposite is the case.
Similarly, the gender dimension appears clearly when it comes to leisure and personal activities. Men participate more to recreation, cultural and sport activities. The participation rate for cultural activities is 6% for men while for women it is 2%, for hobbies and other pastime activities as games it is 14% for men and 5% for women, for sport activities it is 20% for men and 5% for women. More than two-thirds (67%) of men reported having activities related to mass media, while 51% of women reported having the same activities.
Conclusion
The survey revealed how different individuals - women, men, girls, and boys in Ghana spend their time in relation to all types of work and work-related activities, both in terms of paid and unpaid labour. The results from the survey will be used as input in the development of a gender-awareness macroeconomic model for Ghana. The results have also highlighted gender imbalances in average time spent on productive and non-productive activities and on paid and unpaid work. This could well feed into the government's policy decisions in an effort to finding solutions that address gender issues in macroeconomics and poverty reduction
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Individuals
Version
Version Description
-v1.2: edited data, second version, for internal use only.
Version Date
2009-07-09
Version Notes
This is the first time thisTime Use Survey has been implemented in Ghana
Scope
Notes
Time use surveys record the activities done by different individuals from a representative selection of households, and the time spent on each activity. The time spent on an activity is measured in terms of the number of minutes or hours in a specified period, such as a 24-hour day.
Eating, travelling (walking, driving or riding in a motor vehicle), unpaid child care (for example, supervising, feeding), working in a formal sector job (whether as employee or employer, in the public or private sector), doing unpaid 'economic' work (such as fetching water or collecting firewood, or working unpaid in the family business), and housework are typical examples of activities on which a person may spend time during the course of a day.
A household questionnaire that collects demographic and other basic information on households and a diary that solicits detailed information on individuals (10 years and older) activities administered in each of the selected households.
Eating, travelling (walking, driving or riding in a motor vehicle), unpaid child care (for example, supervising, feeding), working in a formal sector job (whether as employee or employer, in the public or private sector), doing unpaid 'economic' work (such as fetching water or collecting firewood, or working unpaid in the family business), and housework are typical examples of activities on which a person may spend time during the course of a day.
A household questionnaire that collects demographic and other basic information on households and a diary that solicits detailed information on individuals (10 years and older) activities administered in each of the selected households.
Topics
| Topic |
|---|
| Household characteristics |
| Demographic characteristics |
| Socio Economic characteristics |
| Expenditure |
| Household assest |
| Use of socia services |
| Time Use |
| Education |
| Employment |
| Type of dwelling |
| Occupation |
Coverage
Geographic Coverage
National
Regional
District, Municipal, Metropolitan
Regional
District, Municipal, Metropolitan
Universe
The survey covered all adult household members (usual residents) aged15 years and olde, and all chilrdren aged 3 years and above (usual resident) in the household.
Producers and sponsors
Primary investigators
| Name |
|---|
| Ghana Statistical Service |
Producers
| Name | Affiliation | Role |
|---|---|---|
| UNITED NATIONS ECONOMIC COMMISSIOM | UNITED NATION | -[technical assistance in] manual specific |
| UNITED NATIONS ECONOMIC COMMISSION | UNITED NATION | -[Techical assistance in] financial |
| AFRICA DEVELOPMENT BANK | -[Technical assistance in] Financial |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Ghana Statistical Service | GSS | GSS was responsible for overseeing the day-to-day technical operations including recruitment and supervision of field and data processing staff as well as the supervision of the office and field operations |
| Government of Ghana | GoG | Financial and technical assistance |
| United Nations Economic Commissiom | UNECA | Financial |
| Africa Development Bank | AfDB | Financial |
Other Identifications/Acknowledgments
| Name | Role |
|---|---|
| The late Nkansah Marfo Yentumi | Project Coordinator |
| Sampled households | Providing Information during Interview |
| Field Staff and Data Entry Personnel | Discharged their duties |
| All regional and district administrators, community leaders and traditional rulers | Diverse assistance |
Sampling
Sampling Procedure
Sample design
The sample for the 2009 GTUS was designed to provide estimates of key indicators at the national and regional levels as well as for urban and rural areas in Ghana. A representative sample of 4,800 households was drawn randomly from the list of Enumeration Areas (EAs) of the 2008 Ghana Demographic and Health Survey (GDHS), which served as a frame for the GTUS sample. In the selected households all individuals aged 10 years and older were interviewed.
The sample frame was first stratified into the 10 administrative regions in the country, then into urban and rural EAs. GTUS used a two-stage stratified sample design. At the first stage of sampling, 300 EAs were selected. These are a sub-sample of the 412 EAs selected from the 2008 GDHS. The second stage involved selection of 16 households from the 2008 GDHS listing in each selected EA.
The Primary Sampling Unit (PSU) was the EA, while the Secondary Sampling Unit (SSU) was the household. In the selected households all individuals aged 10 years and older were interviewed for the 24-hour activity diary. The following factors were considered in the selection of EAs and households:
a) The regional population and average household size in the 2000 Population and Housing Census. The larger the average household size, the smaller the proportion of sampled households in the EA.
b) A confidence interval of 95% with an error margin of 0.025.
c) The number of EAs for each region in the 2008 GDHS.
d) Allowance for a non-response rate of 20 percent for households. The rationale here was to eliminate the need for substitution of unfound or non-responding households during the fieldwork. Giving the option of substituting households to supervisors would have led to a biased sample and therefore field officers were not allowed to substitute. Furthermore, the selection of households considered the average household size of the regions and hence aimed at achieving an adequate sample of individual respondents who were the observation units.
e) Increasing the number of selected households to compensate for the exclusion of the population under 10 years old in the households.
f) As variations in the variables to be studied in the GTUS are expected to be higher in rural areas, it was decided to draw a larger sample (77% of EAs in GDHS 2008) for these areas than for urban areas (67% of EAs in GDHS).
Sample Selection
The regional samples of EAs selected from the 2008 GDHS EAs were done using SPSS syntax that applies a systematic simple random sampling procedure. However, the sampling weights were calculated on the basis of the population size of the EAs and their totals in the region.
The households were also selected using a systematic simple random sampling procedure in Microsoft Excel© using the 2008 DHS listing information. A sampling interval and a random starting number were determined. The random starting number served as the first household to be selected. The remaining 15 households were selected by adding multiples of the sampling interval to the random starting number until the desired number was achieved.
The sample for the 2009 GTUS was designed to provide estimates of key indicators at the national and regional levels as well as for urban and rural areas in Ghana. A representative sample of 4,800 households was drawn randomly from the list of Enumeration Areas (EAs) of the 2008 Ghana Demographic and Health Survey (GDHS), which served as a frame for the GTUS sample. In the selected households all individuals aged 10 years and older were interviewed.
The sample frame was first stratified into the 10 administrative regions in the country, then into urban and rural EAs. GTUS used a two-stage stratified sample design. At the first stage of sampling, 300 EAs were selected. These are a sub-sample of the 412 EAs selected from the 2008 GDHS. The second stage involved selection of 16 households from the 2008 GDHS listing in each selected EA.
The Primary Sampling Unit (PSU) was the EA, while the Secondary Sampling Unit (SSU) was the household. In the selected households all individuals aged 10 years and older were interviewed for the 24-hour activity diary. The following factors were considered in the selection of EAs and households:
a) The regional population and average household size in the 2000 Population and Housing Census. The larger the average household size, the smaller the proportion of sampled households in the EA.
b) A confidence interval of 95% with an error margin of 0.025.
c) The number of EAs for each region in the 2008 GDHS.
d) Allowance for a non-response rate of 20 percent for households. The rationale here was to eliminate the need for substitution of unfound or non-responding households during the fieldwork. Giving the option of substituting households to supervisors would have led to a biased sample and therefore field officers were not allowed to substitute. Furthermore, the selection of households considered the average household size of the regions and hence aimed at achieving an adequate sample of individual respondents who were the observation units.
e) Increasing the number of selected households to compensate for the exclusion of the population under 10 years old in the households.
f) As variations in the variables to be studied in the GTUS are expected to be higher in rural areas, it was decided to draw a larger sample (77% of EAs in GDHS 2008) for these areas than for urban areas (67% of EAs in GDHS).
Sample Selection
The regional samples of EAs selected from the 2008 GDHS EAs were done using SPSS syntax that applies a systematic simple random sampling procedure. However, the sampling weights were calculated on the basis of the population size of the EAs and their totals in the region.
The households were also selected using a systematic simple random sampling procedure in Microsoft Excel© using the 2008 DHS listing information. A sampling interval and a random starting number were determined. The random starting number served as the first household to be selected. The remaining 15 households were selected by adding multiples of the sampling interval to the random starting number until the desired number was achieved.
Response Rate
Response rates at the household and individual levels. The response rate for the 2009 GTUS was 99.5 percent at the household level and 86.5 percent at the individual level. As can be seen, the response rate at the individual level was higher in rural areas (87.2%) compared with urban areas (85.5%). It was also higher overall for females compared with males (88.1% against 84.8%). This can be explained by the fact that individuals are more likely to be absent from home in urban areas than in rural areas and females are more likely than males to be present in the household premises at the time of the interviewer's visit. It should also be noted that diary questionnaires that could not be linked to a fully completed household questionnaire have not been maintained in the sample for analyses.
Weighting
Sample Weights
The 2009 GTUS sample was weighted to the 2009 national population of Ghana. The overall sampling weight was adjusted to suit the variation between the selected and responding sampling units as well as the 2000 census population projections for 2009.
The calculation of sampling weights takes into account the level of representation of sampling units. The survey observations are then adjusted accordingly.
The sampling weight Wij for jth EA in ith region is calculated as follows:
Wij = WGDHS * (1/si) * (Mi / mij)
where:
WGDHS is the weight of the EA in the 2008 GDHS.
si is the number of EAs selected from the ith region.
Mi is the total population of 2008 GDHS EAs in ith region.
mij is the population of jth EA in ith region during the 2008 GDHS.
The sampling weight Wjk for kth household in jth EA is calculated as follows:
Wjk = (Nij / 16)
where:
Nij is the number of listed households in jth EA of ith region during the 2008 GDHS.
The overall sampling weight Wijk for household k in EA j in Region i is the product of EA and household weight and is calculated as follows:
Wijk = (Wij * Wjk)
The overall sampling weight was adjusted due to the variation between the selected and responded sampling units as well as between the 2000 census population, the 2008 GDHS population and the 2009 GTUS population. The household adjustment factor was calculated by dividing the actual listed EA population by the estimated EA population from the survey.
The EA adjustment factor was calculated by dividing the estimated 2009 GTUS regional population by the 2008 GDHS regional population.
The 2009 GTUS sample was weighted to the 2009 national population of Ghana. The overall sampling weight was adjusted to suit the variation between the selected and responding sampling units as well as the 2000 census population projections for 2009.
The calculation of sampling weights takes into account the level of representation of sampling units. The survey observations are then adjusted accordingly.
The sampling weight Wij for jth EA in ith region is calculated as follows:
Wij = WGDHS * (1/si) * (Mi / mij)
where:
WGDHS is the weight of the EA in the 2008 GDHS.
si is the number of EAs selected from the ith region.
Mi is the total population of 2008 GDHS EAs in ith region.
mij is the population of jth EA in ith region during the 2008 GDHS.
The sampling weight Wjk for kth household in jth EA is calculated as follows:
Wjk = (Nij / 16)
where:
Nij is the number of listed households in jth EA of ith region during the 2008 GDHS.
The overall sampling weight Wijk for household k in EA j in Region i is the product of EA and household weight and is calculated as follows:
Wijk = (Wij * Wjk)
The overall sampling weight was adjusted due to the variation between the selected and responded sampling units as well as between the 2000 census population, the 2008 GDHS population and the 2009 GTUS population. The household adjustment factor was calculated by dividing the actual listed EA population by the estimated EA population from the survey.
The EA adjustment factor was calculated by dividing the estimated 2009 GTUS regional population by the 2008 GDHS regional population.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2009-06-01 | 2009-08-03 | Main Survey data collection |
| 2009-05-24 | 2009-05-29 | Main survey-Training |
| 2009-04-19 | 2009-04-25 | Pilot Survey Fieldwork |
| 2009-04-14 | 2009-04-17 | Pilot Survey Training |
Data Collection Mode
Face-to-face [f2f]
Supervision
Interviewing was conducted by teams of interviewers. Each interviewing team comprised of 4 interviwers, a field supervisor, and a driver.
SUPERVISOR'S ROLE: Training is a continuous process. Observation and supervision throughout the fieldwork are a part of the training and data collection process. The team supervisor will play a very important role in continuing the training of his interviewers and has the primary responsibility in ensuring that quality data are collected for the GTUS. As a team leader the specific tasks include the following:-
-Spot check some of the addresses to be interviewed to ensure that interviewers interview correct households and correct respondents.
-Review each questionnaire to be sure it is complete and consistent.
-Observe some interviews to ensure that interviewers are asking the questions in the right manner and recording the answers correctly.
-Meet with interviewers on daily basis to discuss performance and give out future work assignments.-
-Help resolve any problems that the interviewer must have including finding the assigned households, understanding the questionnaire and dealing with difficult respondents
-Responsible for coding of the occupations and activities.
-The supervisor will assign an interviewer to make the first contact with each of the households selected for the GTUS. Any capable adult member of the household is a suitable respondent for the household interview. If at least one eligible person is identified in the Household Questionnaire, the interviewer will go on to complete an Individual Diary Questionnaire.
INTERVIEWER'S ROLE: Interviewers are supposed to carry out the following tasks:
-Read all survey materials and understand the contents.
-Ensure that all fieldwork materials are brought to field for interviews.
-Visit each of the selected households: if you do not get a response at the first visit for any part of the questionnaire, visit the household at least three times at different times and try again. Report all failures to locate respondents to your supervisor. No substitution is allowed.
-Carefully complete all relevant parts of the cover page of the questionnaire for each visit.
-At the first visit, complete the household part of the questionnaire with the head of household or another knowledgeable adult.
-Use the information from the household questionnaire to identify all members aged 7 years and above.
-Administer the time use diaries immediately if any of these members are present at the household. If any are absent, ask what will be the best time to find them. Go back at that time to complete the diaries.
-Check all the completed questionnaires the same evening after the interview. Write notes about any difficulties you may have had with administering the questionnaires on the back of the questionnaires.
-Submit all completed questionnaires to your field supervisor.
-Ensure that all questionnaires and other survey materials are kept safe and confidential at all times.
SUPERVISOR'S ROLE: Training is a continuous process. Observation and supervision throughout the fieldwork are a part of the training and data collection process. The team supervisor will play a very important role in continuing the training of his interviewers and has the primary responsibility in ensuring that quality data are collected for the GTUS. As a team leader the specific tasks include the following:-
-Spot check some of the addresses to be interviewed to ensure that interviewers interview correct households and correct respondents.
-Review each questionnaire to be sure it is complete and consistent.
-Observe some interviews to ensure that interviewers are asking the questions in the right manner and recording the answers correctly.
-Meet with interviewers on daily basis to discuss performance and give out future work assignments.-
-Help resolve any problems that the interviewer must have including finding the assigned households, understanding the questionnaire and dealing with difficult respondents
-Responsible for coding of the occupations and activities.
-The supervisor will assign an interviewer to make the first contact with each of the households selected for the GTUS. Any capable adult member of the household is a suitable respondent for the household interview. If at least one eligible person is identified in the Household Questionnaire, the interviewer will go on to complete an Individual Diary Questionnaire.
INTERVIEWER'S ROLE: Interviewers are supposed to carry out the following tasks:
-Read all survey materials and understand the contents.
-Ensure that all fieldwork materials are brought to field for interviews.
-Visit each of the selected households: if you do not get a response at the first visit for any part of the questionnaire, visit the household at least three times at different times and try again. Report all failures to locate respondents to your supervisor. No substitution is allowed.
-Carefully complete all relevant parts of the cover page of the questionnaire for each visit.
-At the first visit, complete the household part of the questionnaire with the head of household or another knowledgeable adult.
-Use the information from the household questionnaire to identify all members aged 7 years and above.
-Administer the time use diaries immediately if any of these members are present at the household. If any are absent, ask what will be the best time to find them. Go back at that time to complete the diaries.
-Check all the completed questionnaires the same evening after the interview. Write notes about any difficulties you may have had with administering the questionnaires on the back of the questionnaires.
-Submit all completed questionnaires to your field supervisor.
-Ensure that all questionnaires and other survey materials are kept safe and confidential at all times.
Data Collection Notes
Data collection method: The study used a 24-hour diary, divided into one hour slots, as the core instrument to record activities. In each slot, provision was made for a maximum of five activities to be recorded. The diary was administered face-to-face to the respondent by means of an interview. In addition to the diary, the questionnaire contained many questions common to standard household surveys. For analysis of the diary, the GTUS used the revised International Classification of Activities for Time Use Statistics (new ICATUS) developed by the United Nations Statistics Division, which has 15 main groups of activities.
60 days including travel, weekends and callbacks were allocated for fieldwork. 13 mobile teams, each made up of 4 interviewers and a supervisor, were expected to complete interviews within the time frame. Each interviewer completed an average of two households per day.
60 days including travel, weekends and callbacks were allocated for fieldwork. 13 mobile teams, each made up of 4 interviewers and a supervisor, were expected to complete interviews within the time frame. Each interviewer completed an average of two households per day.
Data Collectors
| Name | Abbreviation |
|---|---|
| Ghana Statistical Service | GSS |
Questionnaires
Questionnaires
Questionnaires: There were two types of questionnaires that were used in the GTUS: Household Questionnaire and individual Questionnaire
-The household questionnaire collected information about demographic and socio-economic characteristics of the members of the household such as age, sex, level of education, household expenditures, housing and living conditions of the households. The household questionnaire permitted the interviewer to identify the eligible household members (10 years and older) for the individual interviews.
-The individual diary was used to record information on the individual's (10 years and older) activities, and the duration and the location of these activities within one-hour slots for a day (24 hours). All eligible household members were asked about their activities in the 24 hours beginning at 4am on the previous day. Each individual questionnaire was linked to a household questionnaire.
-The Teleform automated data capturing software was used to design the questionnaires. They were then printed and tested to ensure that all the variables in the questionnaires were in the database.
-English language was used in published the questionnaires
-The household questionnaire collected information about demographic and socio-economic characteristics of the members of the household such as age, sex, level of education, household expenditures, housing and living conditions of the households. The household questionnaire permitted the interviewer to identify the eligible household members (10 years and older) for the individual interviews.
-The individual diary was used to record information on the individual's (10 years and older) activities, and the duration and the location of these activities within one-hour slots for a day (24 hours). All eligible household members were asked about their activities in the 24 hours beginning at 4am on the previous day. Each individual questionnaire was linked to a household questionnaire.
-The Teleform automated data capturing software was used to design the questionnaires. They were then printed and tested to ensure that all the variables in the questionnaires were in the database.
-English language was used in published the questionnaires
Data Processing
Data Editing
-Office editing
Data processing: Capturing of the data was automated through scanning to speed up data processing. A scanning technology called the Automated Teleform System was used to capture the data collected. This system combined Optical Mark Reader (OMR), Optical Character Reader (OCR) and Intelligent Character Recognition (ICR) for the processing. Before scanning, manual edits were performed on the questionnaires received from the field to check for completeness and accuracy of the questionnaires. After the scanning exercise, structural edits were done followed by consistency checks to further reduce errors.
Data were captured, cleaned and edited in Microsoft Access© format and transferred to SPSS. Further cleaning and imputations were done during analysis where the information was found to be inconsistent or incomplete.
On the whole, scanning of the questionnaires, data cleaning and data validation were carried out from June 29 to July 31, 2009.
Data processing: Capturing of the data was automated through scanning to speed up data processing. A scanning technology called the Automated Teleform System was used to capture the data collected. This system combined Optical Mark Reader (OMR), Optical Character Reader (OCR) and Intelligent Character Recognition (ICR) for the processing. Before scanning, manual edits were performed on the questionnaires received from the field to check for completeness and accuracy of the questionnaires. After the scanning exercise, structural edits were done followed by consistency checks to further reduce errors.
Data were captured, cleaned and edited in Microsoft Access© format and transferred to SPSS. Further cleaning and imputations were done during analysis where the information was found to be inconsistent or incomplete.
On the whole, scanning of the questionnaires, data cleaning and data validation were carried out from June 29 to July 31, 2009.
Other Processing
The activity coding system: The GTUS used the International Classification of Activities for Time Use Statistics (ICATUS) developed by the United Nations Statistics Division and published in the guide to producing statistics on time use (United Nations Statistics Division. 2005. Guide to producing statistics on time use: Measuring paid and unpaid work). ICATUS defines 15 main groups of activities, which include: SNA productive, non-SNA productive and non-productive activities (see annex). Coding of activities was done in the field by the supervisors.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| AG. Government Statistician | Ghana Statistical Service | info@statsghana.gov.gh | Link |
Confidentiality
Ghana Statistical Service (GSS) requires all users to keep information and microdata strictly confidential. In this regard, before being granted access to microdatasets, all users have to formally agree to observe the following:
1. Not to make copies of any files or portions of files to which access has been granted except with the authorization by GSS
2. Not to willfully identify any individual or household or establishment in the microdataset
3. To hold in strictest confidence, the identity of any individual or household or establishment that may be inadvertently revealed in any documents or discussion, or analysis. Such unintended identification revealed should be immediately brought to the attention of GSS.
4. Microdata obtained from GSS are protected by copyright law and therefore not for re-distribution or sale
5. Prospective clients or data users may be required to submit and sign an affidavit of confidentiality of microdata they access
Access conditions
The Ghana Statistical Service as a public institution has the obligation to promote data dissemination to facilitate national development. Making mcrodata available will enable students and the academia to conduct research works, assist investors to take business decision, help the individual to evaluate and take appropriate decisions. It will also assist the government to formulate appropriate policies and programmes to facilitate national development. GSS' policy framework provides access to data through:
1. Public use files. These categories of data sets are accessible by all without any payment. They are available on-line to all interested users, for research and statistical purposes only.
2. Licensed datasets. These categories of data sets are accessible under certain conditions. Thus, prospective clients/data users may access any data based on certain conditions set by the GSS
3. Datasets only accessible on location. We consider this category as a data enclave where some data sets are only accessible at GSS offices and prospective data users and researches have to physically be available at GSS offices for further discussions before data are released. Thus, data enclave would not be linked to the outside world through our web site or other medium.
The following terms and conditions apply:
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files for which access has been granted, except those authorized by GSS.
2. Not to use any technique in an attempt to identify any person, establishment, or sampling unit.
3. To hold in strictest confidence, the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the GSS.
4. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of GSS.
5. The data will be used for statistical and scientific research purposes only.
6. The data will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
7. No attempt will be made to identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the GSS.
8. No attempt will be made to produce links among datasets provided by the GSS with other datasets that could identify individuals or organizations.
9. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the GSS would cite the source of data in accordance with the citation statement provided with the dataset
10. An electronic copy of all reports and publications based on the requested data will be sent to the GSS.
1. Public use files. These categories of data sets are accessible by all without any payment. They are available on-line to all interested users, for research and statistical purposes only.
2. Licensed datasets. These categories of data sets are accessible under certain conditions. Thus, prospective clients/data users may access any data based on certain conditions set by the GSS
3. Datasets only accessible on location. We consider this category as a data enclave where some data sets are only accessible at GSS offices and prospective data users and researches have to physically be available at GSS offices for further discussions before data are released. Thus, data enclave would not be linked to the outside world through our web site or other medium.
The following terms and conditions apply:
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files for which access has been granted, except those authorized by GSS.
2. Not to use any technique in an attempt to identify any person, establishment, or sampling unit.
3. To hold in strictest confidence, the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the GSS.
4. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of GSS.
5. The data will be used for statistical and scientific research purposes only.
6. The data will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
7. No attempt will be made to identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the GSS.
8. No attempt will be made to produce links among datasets provided by the GSS with other datasets that could identify individuals or organizations.
9. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the GSS would cite the source of data in accordance with the citation statement provided with the dataset
10. An electronic copy of all reports and publications based on the requested data will be sent to the GSS.
Citation requirements
"Ghana Statistical Service of Ghana,Ghana Time Use Survey 2009 (GTUS 2009), Version 1.0 of public use dataset (Dec,2012),
provided Ghana Statistical Service.www.statghana.gov.gh/NADA"
provided Ghana Statistical Service.www.statghana.gov.gh/NADA"
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Govenment Statistician | Government of Ghana | info@statsghana.gov.gh | Link |
Disclaimer and copyrights
Disclaimer
The original collector of the data, GSS and any producers or sponsors cited in this document bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(c) 2012, Ghana Statistical Service
Metadata production
DDI Document ID
DDI-GHA-GSS-GTUS-2009-v01
Producers
| Name | Abbreviation | Role |
|---|---|---|
| Ghana Statistical Service | GSS | Lead documetning institution |
Date of Metadata Production
2012-07-09
DDI Document version
version 1.0 (January 2013)