Introduction
Gender inequality and unpaid care work are inextricably intertwined. Despite improvements made by women in labour force participation, job advancement and remuneration, unpaid care work is limiting progress and slowing the pace of gender convergence in the economy. Anecdotal evidence abounds and data from labour force surveys further lend credence to this aspect of nonmarket activity having an impact on market outcomes. There is broad agreement on the problem statement, captured considerably in official development planning and policy documents.
However, the nature of unpaid care work taking place predominantly at home—where there is no market transaction—poses a non-trivial challenge to our ability to grapple with the intricacies of the issues and advance understanding that can lead to better and more effective policy solutions. Discourses on the economy, gender inequality and unpaid care work exist in parallel but may not intersect in a meaningful way. The lack of empirical data, or the ability to count unpaid care work, often lead to the magnitude of the problem being underestimated, shifting unpaid care work down the hierarchy of issues that warrant attention and redress.
This is where the time use survey comes in. It is a methodology that comes with a set of instruments that can be used to enumerate non-market activities. Its historical roots are inseparable from unpaid care and its gender implications, but the time use survey has since taken off into many other interesting research directions. While certainly imperfect, many countries across regions and development levels are turning to time use surveys as the tool to bridge the gap between market and non-market activities. International and regional organisations are harmonising standards, and research centres are experimenting with innovative ways to conduct time use studies using new technology.
Our report, Time to Care: Gender Inequality, Unpaid Care Work and Time Use Survey, builds on this rich and growing tradition. It is based on a pilot time use survey that we conducted in 2018 but our larger motivation stems from wanting to strengthen the empirical work linking the economy, gender inequality and unpaid care work. We want to demonstrate the usefulness and potential of time use surveys, albeit at a small scale, and the insights that can be derived alongside more representative datasets to spur policy thinking.
For a detailed explanation of the survey design, data collection process, coding framework, and data processing procedures, please refer to the KRI Time Use Survey User Guide.
Caveats and Limitations
This dataset is subject to the following caveats as described in the KRI Time Use Survey User Guide :
- This dataset is based on a small-scale pilot Time Use Survey involving 125 respondents.
- The survey covers residents aged 20 - 64 in Kuala Lumpur only.
- Time use data reflects one recalled weekday (Tuesday - Thursday) per respondent.
- Information is self-reported and collected via retrospective interviews.
- Imputation and proxy measures were applied for selected demographic and income variables.
- Activities were coded using ICATUS 2016, with documented coding rules and decisions applied.
Metadata
KRI Time Use Survey Data
Dataset Brief Description
This dataset contains data from the Khazanah Research Institute Time Use Survey, a small-scale pilot survey. The survey collected information on how respondents spent their time during the previous 24-hour weekday, recorded using a time-diary starting at 4am the previous day and ending at 4am on the interview day in 15-minute intervals. The survey was conducted through face-to-face interviews with respondents aged 20 to 64 residing in Kuala Lumpur.
This particular dataset reports the sum total minutes spent for each respondent per activity category (including main and secondary activities), per location category, per transportation type, and per social context category. It also contains each respondents' demographic, household, and employment-related information, as well as whether they perceive their time reported as being representative of their usual weekday and whether they are satifsfied with their time-use.
Activities are coded according to the International Classification of Activities for Time Use Statistics 2016 (ICATUS 2016), following the coding rules and procedures described in the User Guide. Selected variables were derived or imputed during data processing as documented in the User Guide.
Methodology
A full methodology is provided in the following document: KRI Time Use Survey User Guide
Download Dataset
Respondents Time Diary
Dataset Brief Description
This dataset contains data from the Khazanah Research Institute Time Use Survey, a small-scale pilot survey. The survey collected information on how respondents spent their time during the previous 24-hour weekday, recorded using a time-diary starting at 4am the previous day and ending at 4am on the interview day in 15-minute intervals. The survey was conducted through face-to-face interviews with respondents aged 20 to 64 residing in Kuala Lumpur.
This particular dataset, in a time-diary format, reports the main and secondary activities for each 15-minute interval, as well as the transport used (if applicable), the location, social context and further time duration in minutes (for 15-minute intervals where more than one activitity is report).
Activities are coded according to the International Classification of Activities for Time Use Statistics 2016 (ICATUS 2016), following the coding rules and procedures described in the User Guide. Selected variables were derived or imputed during data processing as documented in the User Guide.
Methodology
A full methodology is provided in the following document: KRI Time Use Survey User Guide
Download Dataset
Related Data Files
1. Respondent Profile
Respondent-level demographic, employment, income, and household information.
Each row represents one respondent and can be linked to the time-diary dataset using the ID.
2. Summary Tables on Time Use
Aggregated tables showing mean time spent on primary and secondary activities by selected demographic and contextual categories.
Credits
Author(s): Christopher Choong Weng Wai, Adam Manaf Mohamed Firouz, Alyssa Farha Jasmin,Nazihah Muhamad Noor, Dr Rachel Gong
This landing page was prepared and maintained by the Knowledge, Innovation & Data Hub (KID) team at Khazanah Research Institute. The team is responsible for the structuring, documentation, and ongoing maintenance of the dataset.
