TIME Use Survey (TUS) is the first of its kind ever carried out in Pakistan in collaboration with the Ministry of Finance and the Federal Bureau of Statistics (FBS) to analyse and document how people in Pakistan spend their time on socio-economic and other activities. The objective of the survey was to collect and analyse the comprehensive information about the time spent by people on market and non-market economic activities, personal care and related activities that cannot be delegated to others. TUS provides the most complete account of all human activities performed by the respondents: the time spent on each activity, the sex and family context of persons performing them, as well as the location in the day when these activities are performed. Respondents are expected to report the duration and timing of their different activities in sequence throughout the day(s) of the reference period, together with information on the context of the activities, i.e., where the activities are performed, with whom and for what purpose. The survey report has recently been finalised by the FBS in March 2009 and it would be launched very soon. FBS, the main producer of national official statistics, takes the lead for data collection and research for survey throughout Pakistan from January to December Year 2007 with a sample size of 19,600 households. The survey results are representative at national and provincial level with rural-urban breakdown. The survey was initiated by the Gender Responsive Budgeting Initiative Project and is currently being completed with support of the Strengthening Poverty Reduction Strategy (PRS). Monitoring project funded by the United Nations Development Programme (UNDP). The data collected through TUS helps in analysing how people allocate their time to various activities such as paid and unpaid work (e.g. caring children and sick people). In addition, this data can be used for drawing up of satellite accounts as proposed in the System of National Accounts (SNA) to find out economic value of unpaid work and this part would be covered in part two of the article. The findings of the TUS would be assisting the government to determine whether changes in household incomes and control over the incomes by gender results in higher social investments. It would also be serving as policy input for budgetary allocations for development spending at large and for gender budgeting in particular. The survey findings reveal that, two-third population is rural and rest is urban. More than seven-tenth (71%) is in potentially productive 10+ age groups, mostly in 20-39 bracket (27%). About one-fourth (24%) are adolescents and teens (10-19 years) while one-seventh (14%) are in forties and fifties. Elderly (sixty plus) are about one in seventeen (6%). The remaining one-third (29%) are below 10 years aged. Sex wise, all groups are evenly composed save the twenties and thirties which is more female (29%) than male (25%). The survey results show literacy trends, majority (42%) is with no formal education. Among the rest, below Matric is the leading category (38%) followed distantly by below intermediate (11%). Less than, and above degree categories fare at 5% and 4% respectively. From gender perspective, all categories are more masculine than feminine except the 1st one which is predominantly feminine. Seemingly, the right of education is more accessible to male than female child. According to survey, forty-six (46) percent of the population is in labour force comprising 43% of employed and 3.3% unemployed. About two-third (68%) of the males are employed as compared to one-fifth (18%) of females. At the outset, the differential between the male-female shares (4%, 3%) of unemployed seems insignificant. However, it is instructive to collate it with the comparative shares in the out-of-labour force (29%, 79%). The information collected through survey informs the broad socio-economic groupings of jobs in Pakistan, more than half (56%) of employed respondents were in brown collar (skilled shop and market sales, craft and related trade, agriculture workers) jobs. The rest is evenly distributed between white collar (legislators, officers and managers, professionals and clerks) and blue collar (plant and machine operators and assemblers & elementary (unskilled) occupations) jobs. About one-fourth (24%) of males are white collar workers compared to about one-eight (13%) of females. In contrast seven-tenth (69%) of females are brown collar workers compared to about half (52%) of males. The females share (18%) in blue collars stands at three-fourth of males (24%). As expected, white collar jobs, and to the lesser extent, brown collar jobs are more numerous in urban than rural areas while blue collars are on the same level in this regard. TUS and Gender Trends One half (50%) of the females, compared to one-seventh (14%) of males, are unpaid family workers. A semblance of relative equivalence of female-male shares is observed in case of employees (37% Vs 44%). Own account workers, with one-eight (13%) females compared to two-fifth (39%) males, is the last category to merit collation in terms of gender specific shares. Employers with trace female shares are nearly masculine in their calculus. From rural-urban perspective, more or less, same calculus prevails though rural is more masculine as compared to that of urban According to survey, round the clock time use can be categorised into economic (SNA), para-economic (extended SNA) and socio-cultural (non-SNA) activities. Male and female participation time in SNA and extended SNA activities make opposite configuration of different skew ness. Males time in SNA is five fold of his extended SNA time while females time in extended SNA is one and half fold of her SNA time. Area wise figures make similar pattern. However, rural female spends more time in SNA related activities as compared to her urban counterpart while opposite holds for males. Quantum of SNA related activities in urban areas is higher as compared to that of rural areas. Driven by the relative availability of civic amenities, the Non-SNA activities are comparatively more abundant in urban than in rural areas. The survey findings present mean time spent on housekeeping activities including fetching fuel and water from sources outside dwelling unit. On the average, males time fares at one third of the females both in rural and urban areas. This uniformity across the area is indicative of the female provenance of the housekeeping activities. Thus, its instructive to arrange the groups in term of femininity. Youths (20-39) is the most feminine group to share most of the time burden followed by middle aged (40-59), adolescents & teens (10-19) and elderly (60+). It is a bit disconcerting to notice that most of the females productive life time is spent in housekeeping activities which bear minimal relevance for galvanising the innate faculties of mind and body but nevertheless make an important contribution to the well-being of household members. The survey quite appropriately pointed out participation rate of females in the care of children, sick and elderly is higher than that of males in all categories of the marital status. Currently married are the most visible in this regard with female faring at more than two times of the males. More ruralites than urbanites partake in the care activities. Next most visible role is played by widows/divorced, with similar configuration across the area and gender. Never married are the top most in the case of gender differentials with females participation rate four times of the males. Similarly, ruralites fare higher than urbanites. According to the survey, the provincial configuration of the meantime in minutes, referred henceforth as meantime, spent by participants in SNA, extended SNA and Non SNA activities. Mean time in SNA activities makes a descending sequence of Punjab (401), Sindh (370), Balochistan (318) and NWFP (287). The inter-provincial gaps between the eastern (Punjab and Sindh) and western (NWFP and Balochistan) provinces are equivalent (31). The male-female differentials show SNA activities as preponderantly males preview, more in Sindh (278) followed decreasingly by Balochistan (265), Punjab (251) and NWFP (229). Areas wise, SNA tasks are more exacting for urban than rural participants in a declining order of Sindh (100), NWFP (84), Punjab (65) and Balochistan (35) as shown by the urban-rural differentials in the parenthesis. In general, implementation of the TUS however, is relatively technical and lengthy process. Respondents, especially those living in rural areas and less educated, normally did not care with time. They faced difficulty in providing information on when and how they spent time for each activity. On the other hand respondents, especially women, may conduct more than one activity at the same time. A mother for example, may do cooking and cleaning house interchangeable, and at the same time carrying her child in her neck. This might results that the total number of hours for all activities more than 24 hours a day. The overall conclusion is that the survey shows gender and rural/urban differences in time use, and characterises the life pattern of the working and non-working population and paid and unpaid work. It highlights the volume of actual working time more clearly than any other quantitative measure. Time use statistics have great value in informing the government policy development process. It would help the policy makers to devise and implement gender equitable paradigm of socio-economic development so as to realise the full productive potential of the society. Much public policy is concerned with the boundaries between paid and unpaid work, and these boundaries are different for women and men, and for different groups in the society.