Labour force surveys (LFS) or household-based surveys that collect work-related statistics are expected to be the main source of collecting information on workforce and labour force. Over the years, however, several limitations of LFS are coming to the fore. These limitations have emerged from several relatively recent developments, namely: (a) changes in the production boundary of the UN System of National Accounts (SNA) that have made it difficult to capture workforce statistics adequately, (b) changes in the labour market structures and in the characteristics of workforce and labour force over the years that call for some innovative approaches to estimate and understand the flexibilities of work, and (c) the new classification of SNA work under the resolution (unpaid trainee work and voluntary work of certain kinds) that calls for modification in the workforce/labour force classifications. In addition, there is also an acceptance that the causes of the inferior status of women, as compared to men, in the labour market lie in the unequal sharing of unpaid work by men and women.
Time-use surveys (TUS) have the potential to address the limitations of the LFS, and they need to complement and supplement LFS. The main strength of TUS is that they provide comprehensive information on how individuals spend their time, daily or weekly, on SNA activities, non-SNA activities that fall within the general production boundary, and personal activities that are non-delegable activities. There are three major components of a TUS: (a) information on major socio-economic characteristics of households and individuals (for whom time-use data is collected) through a background schedule or through the main schedule in case TUS is a module in a major survey, (b) data on the time spent by individuals on different activities, and (c) the context in which activities are carried out. Additionally, time-use statistics can also be used with other data (such as LFS) to enhance the value of the data.
Time-use data provide improved understanding of gender gaps in the status of workers in the labour market. This is because this data provides information on the burden of unpaid domestic services and unpaid care work on men and women. The burden of unpaid work on women is observed to be one of the major constraints which do not allow women a level playing field with men in the labour market. The highly unequal distribution of unpaid domestic work between men and women in the household, along with the socio-cultural norms emanating from it, tends to restrict human capital formation among women and reduce their participation, their mobility, as well as their choice of work in the labour market. Therefore, TUS have considerable potential to get over some of the problems and limitations of LFS in terms of estimating and understanding informal and subsistence work of men and women in an economy.
The National Sample Survey Office (NSSO) in India conducts an all-India employment and unemployment survey (EUS) every five years. Since the year of the TUS that was conducted in 1998–99 matched with the EUS in 1999–2000, we decided to compare the results of the two surveys. As both the years are close to each other and are ‘normal years’, the data can be treated as comparable. The comparison was made for the six states covered under the TUS as well as all-India estimates of the EUS and the ‘combined state’ estimates of the time-use statistics.
India’s first national TUS was conducted on a pilot basis in 1998–9. The survey covered six major states: Haryana from north, Madhya Pradesh from centre, Tamil Nadu from south, Gujarat from west, Orissa (now Odisha) from east, and Meghalaya from north-east. The survey covered both rural and urban areas, and was conducted in four rounds to capture seasonal changes in the time use. In all, 18,591 households and 77,593 individuals (all members above six years of age from the selected households) were selected for the survey (Government of India 2000).
TUS usually collect data for two days—a weekday and another weekly variant day (a few countries collect data on one day or three days). In the case of the NSSO, on the other hand, there are three reference periods, namely, one year, one week, and each day of the week, and workforce estimates are made for each of the reference periods.
Workforce participation rates under NSSO and TUS table presents weekly workforce participation rates (WPRs) of men and women for rural and urban areas from NSSO (1999–2000) and from the TUS (1998–9).
Some of the striking observations from the table are as follows:
- The TUS-based estimates of WPRs are higher than the NSSO-based WPRs for men and women in both rural and urban areas. The WPRs of women under the TUS are double or more than the corresponding WPRs under the NSSO.
- The gap between the NSSO-based rates and TUS-based rates is much higher for women than for men. This indicates greater under-reporting of women’s work than of men’s work under the NSSO. The highest gap between the NSSO-based WPRs and TUS-based WPRs is observed in the case of urban women. This indicates that the most underestimated WPRs under the NSSO are WPRs of urban women.
- Although there are interstate differences, the above two observations are applicable to all the states.
Another interesting finding is, gender gaps as well as variations across the states, are much lower for the WPRs based on the TUS data. For example, in the case of Haryana, the gender gaps in the WPRs are 31.39 points as per the NSSO data, but it is 0.39 for the TUS-based WPRs. This is because Haryana has well-developed agriculture and animal husbandry (dairy industry) where women’s participation as unpaid family workers is predominant. However, the gender gap is the highest in Gujarat among the six states, perhaps because there are several social constraints against women’s participation in workforce in certain castes in Saurashtra and Kachchh—the two major regions in the state.
Scholars in India have frequently observed that women’s labour market participation is very low, and have tried to explain this through various theories. But the TUS data shows that the gaps are not very large. For the combined states, the gender gap in WPR is 11.41 points under the TUS estimates, and 28.88 in the cases of NSSO. This clearly indicates that the large gender gaps discussed by scholars are not really so large in reality, and the gaps are mainly due to the inability of the conventional sources to capture SNA work of women.
The workforce is less diversified for NSSO-based WPRs. While the time-use-based male WPR in the primary sector is 56.13 per cent, the NSSO-based WPR in the primary sector is 47 per cent. Again, the time-use-based male WPR in the non-primary sector is 43.86 per cent, the corresponding rate for NSSO is 53.00 per cent. Both estimates show predominance of the tertiary sector over the secondary sector, with the TUS-based estimates showing much lower values. Overall, it appears that the TUS has been able to capture the primary sector work of men and women more effectively. This could be because the share of organized/formal employment is relatively low in the sector.
As expected, men’s work is more diversified than that of women. As against 56.13 per cent male workers in the primary sector, 77.45 per cent female workers are working in the primary sector. The percentage of workers in the secondary and tertiary sectors is much less: 15.11 per cent and 28.75 per cent for men and 9.97 per cent and 12.59 per cent for women respectively.
Within the primary sector, women are predominant in collection of free goods, animal husbandry, and crop farming, while men are mainly in crop farming and animal husbandry. In the secondary sector, women are mainly in the manufacturing activities, while in the tertiary sector they are mainly in services. Men’s work is also significant in construction and trade. In short, men have better opportunities in the non-primary sectors as compared to women.
It is important to note that women are predominantly involved in collection of free goods (which includes water, fuel wood, vegetables, fruits, and leaves) for meeting basic needs of the household, fodder, wood, and raw material for family business, etc. from common lands, common forests, and other common property resources. These activities are time-consuming, and more so with the increasing depletion and degradation of common property resources in most developing countries. For rural and urban areas combined, 35.56 per cent of women, which is more than one-third of total women, participate in these activities, as against only 5 per cent of men. The total time spent on these activities also is much longer (3.11 hours per week) for participant women than for participant men (0.97 hours per week).
The most time-consuming activities for women are collection of water (WPR 12.87), followed by collection of vegetables, fruits, etc. (WPR 11.61), and collection of fodder and raw material for crafts, etc. (WPR 5.74). Women’s participation in these activities is seven times more than that of men. On an average, women spend 3.11 hours per week on collection of free goods, which is more than three times the time spent by men.
7.23 per cent of men and 9.27 per cent of women participate in some additional activities of the same type, namely, animal grazing; making cow dung; collecting, storing, and stocking of fruits; woodcutting; and stocking of firewood. These activities, like the activities listed in Table 5.7 have low productivity and they are time-consuming drudgery. Men (mainly young boys) participate in animal grazing, while women participate in making dung cakes, grazing animals, and chopping and storing firewood. Once again, participant women spend more time per day (70.43 minutes) on these activities than the time spent by participating men (66.40 minutes per day). Similarly, men and women spend significant time on making dung cakes, grazing animals, and cutting and chopping wood for fuel. These time-consuming activities do not do not leave much time for women to participate in the productive activities in the labour market.
An important characteristic of workforce in developing countries is that a significant percentage of the workforce is employed in multiple activities. For example, a man may work on his farm for some time or during a crop season, and then may work as hired labour on other farms, may migrate to an urban area and work on construction of roads, or may work in a brick kiln or in a small factory. Similarly, a woman may tend animals at home, work on the family farm, work as hired labour on other farms, or may work as domestic servant at a rich man’s house. These multiple jobs are taken up because: (a) one job does not provide enough employment (for example, a small field does not need more than one full-time worker, or a cow or two do not need full-time work); (b) one job does not earn enough income for survival; (c) there are not enough skills or education to access a full-time job; or (d) there are not enough funds or access to funds to expand the present activity into a full-time activity.
The percentage of workers performing one SNA activity is small—15.17 per cent for men workers and 28.85 per cent for women workers. Performing two activities is, however, very common with half of men workers and 30 per cent of women workers. However, women’s share is much higher in performing three, four, and more activities. 5.37 per cent women workers perform more than five SNA activities against 2.94 per cent of men workers. The different activities are perhaps performed at different times and at different locations.
The burden of unpaid non-SNA work is shared highly unequally between men and women. Women, on an average, spend 28.96 hours per week on household management, that is, taking care of the household. The maximum time is spent on cooking (14.59 hours), followed by cleaning and washing (7.89 hours), care of textiles (2.31 hours), and household maintenance, shopping, etc. (2.14 hours). Men, on an average, spend less than one hour per week on each of these activities. As regards childcare and care of the old, sick, or disabled in the household, women spend 4.47 hours per week against 0.88 hours per week by men. Women spend maximum time on physical care of children (3.09 hours), followed by non-physical care of children (that is, teaching and training children, accompanying them to places, etc.). Women also spend more time on other care activities than men. On an average, men spend 2.17 per cent of their total time on non-SNA work as against 20.61 per cent by women. Clearly, this is a major constraint for women who want to participate in the labour market.
The time-use data indicates a highly unequal sharing of total work, including SNA and non-SNA work, by men and women. While men spend more time in SNA work, women spend more time on non-SNA work. However, the gender gap is much more in non-SNA work, with the result that women carry much higher burden of total work. Women spend an average 69.03 hours on total work, while men spend about 62.71 hours. As a result, women get much less time for personal activities, such as rest, sleep, recreation, etc., as compared to men. Women also get less time for studying, skill formation, etc.
If we include all men and women, and not just participants, men spend about 27 per cent of their time on SNA and non-SNA work put together, while women spend about 38 per cent of their time on this total work. As regards sharing of the SNA work, men share 67.89 per cent of work (in total person hours of SNA work), while women share 32.11 per cent of SNA work. It appears that though the gender gap in WPR is not very high, the gap in work intensity is significant.
In the Indian context, the data underlines the fact that women’s participation in SNA work is not as low as is seen from the conventional surveys, though it is commonly observed that the WPR of women in the country is very low due to socio-cultural. The Indian time-use data shows that the gap between the WPRs of men and women is not as big as revealed by LFS. The major difference between men and women’s WPR is that women participate, on an average, for four hours a day or less, as compared to men who participate full-time, in SNA work, which is mostly because of their domestic responsibilities. They are constrained heavily by the high burden of unpaid work, which leaves them with less time and energy to participate in productive work in the labour market. This burden is also reflected in women’s low capabilities and low human capital formation as well as low mobility in the labour market.
Another major constraint of women is their high participation in collection of free goods for meeting basic needs of the household. The lack of basic infrastructure like water, fuel wood/energy, etc., keeps women busy in acquiring these needs, which takes away a lot of time and energy of women. Free collection of raw material for family business (that is, fodder, wood, and raw material for craft) is another form of drudgery for women. The preoccupation of women in unpaid SNA and non-SNA work leaves little scope for women to move into productive activities in the labour market. Poor diversification and crowding in low-productivity, stereotypical activities is a consequence of the overall pattern of use of women’s labour in SNA and non-SNA work.
It will not be out of place here to mention that the working group for the 68th round on employment and unemployment in India has recognized the advantages of TUS and accepted its role in enriching the household survey (NSSO 2013).
*Professor of economics and director, Centre for Development Alternatives, Ahmedabad. These are excerpts from the research paper “Challenges to Measuring Workforce (SNA)/Labour Force in Global South” in the book “Mainstreaming Unpaid Work”, edited Prof Hirway. The book contains research articles by scholars from different countries on how Times Use Surveys (TUS) help identify unpaid work and help address gender issues