Ghana Time Use Survey 2009 - Ghana

Abstract
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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

Geographic coverage
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National
Regional
District, Municipal, Metropolitan

Analysis unit
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Individuals

Universe
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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.

Kind of data
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Sample survey data [ssd]

Sampling procedure
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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.

Mode of data collection
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Face-to-face [f2f]

Research instrument
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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

Cleaning operations
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-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.

Response rate
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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.

摘要
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执行摘要

2006年和2007年，联合国非洲经济委员会（UNECA）与利益相关者合作，编制了一本关于收集按性别分列的时间使用数据的手册。利用这本手册，加纳统计局在UNECA的财政和技术援助下，对该国首次时间使用调查进行了实地调查。GTUS的主要目标是衡量和分析10岁及以上不同个体在24小时内的所有活动花费的时间，包括有偿和无偿工作和休闲活动。

从2008年加纳人口与健康调查（GDHS）的枚举区域（EAs）名单中随机抽取了4800户家庭的代表性样本。在选定的家庭中，所有10岁及以上的个体都根据包含标准家庭调查常见问题的问卷进行了访谈。该研究还使用了一份24小时日记作为核心工具，将活动分为一小时时段进行记录。数据收集时间为2009年6月至7月。本报告介绍了调查的主要结果。

主要发现

结果显示，在男性和女性参与的活动类型方面存在明显的性别维度。男性报告称，他们参与SNA和有偿活动（74%）的比例高于参与扩展SNA和无偿活动（66%），而女性则相反，其中69%的女性参与SNA活动，95%的女性参与扩展SNA活动。在学习方面也存在相同的明显性别差异，31%的男性参与该活动，而女性为22%。

参与率的性别维度也体现在活动的细分类别中。最明显的差异体现在SNA活动中。例如，男性（17%）比女性（11%）更有可能为正规机构工作，这些机构通常在薪酬和社会保护方面提供最佳条件。另一方面，女性（29%）比男性（19%）更有可能参与有偿家务工作。

广泛活动

分析不同属性（例如年龄、婚姻状况、教育程度、家庭构成、星期几等）的参与率时，都存在明显的性别维度。在平均花费在不同活动上的时间和参与SNA和扩展SNA活动的模式（尤其是无偿护理工作）方面，也存在明显的性别差异。最明显的性别差异出现在扩展SNA上，女性平均花费3小时29分钟，是男性（69分钟）花费时间的3倍以上。当进一步细分不同活动时，花费时间也存在明显的性别维度。男性报告称，他们花费更多时间在为正规机构（如公司和国有企业）工作（65分钟），而女性（23分钟）则较少。相反，女性报告称，她们在无偿家务工作（2小时35分钟）上花费的时间比男性（40分钟）更多。

SNA活动

分析各种属性时，SNA活动的参与率也存在性别维度。男性和女性的最高参与率（分别为38%和47%）都在自给自足活动中，包括自给自足农业以及为烹饪取水和收集木材。近三分之一的女性（29%）参与为家庭提供服务的有偿工作，而同类别活动中男性的比例为五分之一（19%）。即使考虑其他因素（例如年龄、婚姻状况、居住区域），在SNA活动上花费的平均时间也存在性别差异。在几乎所有的人口统计特征中，男性在SNA活动上花费的时间通常比女性多。男性和女性18岁以上最重要的性别差异似乎在于家庭在建筑活动中的工作，这似乎是一种主要针对男性的活动。

扩展或非SNA生产

在参与率方面，儿童保育是男性和女性最重要的无偿护理工作子类别，成年护理则远远落后，成为第二重要的子类别。在扩展SNA活动上花费的平均时间存在明显的性别差异。当进一步分析参与者在扩展SNA活动上花费的平均时间，并考虑人口统计和其他因素时，整体模式是女性在儿童保育和无偿家务服务上花费的时间比男性多，而男性通常在成年护理上花费更多时间。在成年护理方面，最显著的性别差异出现在年轻、未婚或已婚男性、非正式/松散联合的男性、居住在农村地区以及接受学前和小学教育的男性中。在男性在某些工作日花费的时间上，也发现了关于成年护理的更多性别差异。

非生产性活动

总体而言，普通教育的参与率很高，这表明加纳的学校入学率相对较高。同样，城市和农村地区入学率之间的差异并不很大。在城市地区，附加学习、非正规教育和空闲时间课程类别的差异最大，有利于城市地区。在城市地区，平均花费在普通教育上的时间（320分钟）略高于农村地区（314分钟）。但城市居民和农村居民之间没有明显的性别差异。当将所有学习活动结合起来时，城市地区在职业和专业发展相关学习上的时间差异最大，有利于城市地区（383分钟对农村地区的129分钟）。平均而言，城市地区的男性在这项活动上花费的时间比女性多得多，而在农村地区则相反。

休闲和个人活动

当涉及休闲和个人活动时，性别维度也非常明显。男性更多地参与娱乐、文化和体育活动。文化活动的参与率为男性6%，女性为2%；爱好和其他消遣活动（如游戏）的参与率为男性14%，女性为5%；体育活动的参与率为男性20%，女性为5%。超过三分之二（67%）的男性报告称有与大众媒体相关的活动，而51%的女性报告称有相同的活动。

结论

调查揭示了不同个体——加纳的女性、男性、女孩和男孩——如何在各种工作和与工作相关的活动中分配时间，无论是有偿劳动还是无偿劳动。调查结果将被用作开发针对加纳的性别意识宏观经济模型的基础。调查结果还突出了在生产和非生产活动以及有偿和无偿工作中存在的性别不平衡。这可能会为政府政策决策提供参考，以寻找解决宏观经济和减贫中的性别问题的解决方案。

地理覆盖范围
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全国性
地区性
区、市、大都市

分析单元
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个人

总体
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调查涵盖了所有15岁及以上的成年家庭成员（常住居民）和所有3岁及以上的儿童（常住居民）。

数据类型
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样本调查数据 [ssd]

抽样程序
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抽样设计

2009年GTUS的样本设计旨在为国家、地区以及加纳的城市和农村地区提供关键指标的估计值。从2008年GDHS的EAs名单中随机抽取了4800户家庭的代表性样本，该名单作为GTUS样本的框架。在选定的家庭中，所有10岁及以上的个体都根据包含标准家庭调查常见问题的问卷进行了访谈。

样本框架首先被分层为国家10个行政区域，然后分为城市和农村EAs。GTUS采用了两阶段分层抽样设计。在抽样第一阶段，选择了300个EAs。这些是2008年GDHS中从412个EAs中选择的子样本。第二阶段涉及从每个选定的EAs的2008年GDHS名单中选择16户家庭。

主要抽样单位（PSU）是EAs，而次级抽样单位（SSU）是家庭。在选定的家庭中，所有10岁及以上的个体都进行了24小时活动日记的访谈。在选择EAs和家庭时考虑了以下因素：
a) 2000年人口和住房普查中的区域人口和平均家庭规模。平均家庭规模越大，EAs中抽样家庭的比例越小。
b) 95%的置信区间，误差范围为0.025。
c) 2008年GDHS中每个区域的EAs数量。
d) 允许20%的非响应率。这里的理由是消除在实地调查期间替换找不到或未响应的家庭的需要。如果允许主管替换家庭，可能会导致样本偏差，因此实地调查人员不允许替换。此外，家庭的选取考虑了地区的平均家庭规模，因此旨在实现足够的个体受访者样本，这些受访者是观察单位。
e) 增加选定家庭的数量，以补偿排除10岁以下的家庭人口。
f) 由于预计GTUS中要研究的变量的变化在农村地区更高，因此决定为这些地区抽取更大的样本（GDHS 2008年中的77%的EAs），比城市地区（GDHS中的67%的EAs）多。

样本选择

从2008年GDHS EAs中选择的地区样本使用SPSS语法执行系统简单随机抽样程序。然而，抽样权重是根据EAs的人口规模及其在地区中的总和计算的。

家庭也是使用Microsoft Excel©中基于2008年DHS名单信息的系统简单随机抽样程序选择的。确定了抽样间隔和随机起始数字。随机起始数字作为第一个要选定的家庭。通过将抽样间隔的倍数加到随机起始数字上，直到达到所需的数量，选择剩余的15户家庭。

数据收集方式
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面对面 [f2f]

研究工具
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问卷：GTUS中使用了两种类型的问卷：家庭问卷和个人问卷
-家庭问卷收集有关家庭成员人口和社会经济特征的信息，例如年龄、性别、教育水平、家庭支出、家庭的住房和居住条件。家庭问卷允许调查员识别适合个人访谈的合格家庭成员（10岁及以上）。
-The individual diary用于记录个人的（10岁及以上）活动，以及这些活动在一天（24小时）内一小时内的时间段和地点。所有合格的家庭成员都被要求就他们前一天上午4点开始的前24小时的活动进行说明。每个个人问卷都与一个家庭问卷相链接。
-The Teleform自动化数据采集软件用于设计问卷。然后打印并测试以确保问卷中的所有变量都包含在数据库中。
-使用英语发布问卷

清理操作
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-办公室编辑
数据处理：通过扫描自动化数据捕获以加快数据处理速度。使用名为自动化Teleform系统的扫描技术来捕获收集到的数据。该系统结合了光学标记阅读器（OMR）、光学字符阅读器（OCR）和智能字符识别（ICR）进行加工。在扫描之前，对从现场收到的问卷进行了手动编辑，以检查问卷的完整性和准确性。扫描作业完成后，进行了结构编辑，然后进行了一致性检查，以进一步减少错误。
数据在Microsoft Access©格式中捕获、清理和编辑，然后转移到SPSS。在分析期间，对信息不一致或不完整的情况进行了进一步的清理和插补。
总的来说，从2009年6月29日至7月31日，对问卷的扫描、数据清理和数据验证工作完成。

响应率
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家庭和个人的响应率。2009年GTUS的家庭响应率为99.5%，个人响应率为86.5%。如所见，个人层面的响应率在农村地区（87.2%）高于城市地区（85.5%）。总体而言，女性的响应率也高于男性（88.1%对84.8%）。这可以解释为，个人在城市的出现率比在农村地区更高，而女性在调查员访问时出现在家庭内部的概率比男性更高。还应注意的是，无法与完全填写好的家庭问卷相链接的日记问卷没有被保留在样本中进行分析。