Gender mainstreamed statistics are essential to monitor, analyse and evaluate the situation of men and women and their interrelations in the world of work. The need for such statistics was recognised in particular by the 1995 Beijing Platform for Action, which called for countries and international organisations to collect and analyse statistics that reflect issues of importance to women and men in society .
Regarding labour statistics, the Beijing Platform Strategic Objective H.3 specifically mentioned the need to produce statistics on: (a) employment, including employment in the informal sector, unemployment and underemployment, that do not underestimate the participation of women and men; (b) unremunerated work which is already included in the United Nations System of National Accounts, including agriculture, particularly subsistence agriculture; (c) unremunerated work that is outside the System of National Accounts, such as caring for dependants and preparing food, and their interrelation with remunerated activities carried out simultaneously or interchangeably; (d) poverty among women and men, including their access to resources; (e) violence, including sexual harassment and trafficking; (f) women and men with disabilities, including their access to resources. Countries were requested to produce a regular statistical publication that presented and interpreted topical data on women and men, and to disaggregate all statistics at least by sex and by socio-economic and other characteristics.
It is now widely agreed that national labour statistics that are gender mainstreamed are more complete and of higher quality than those that do not, and this should be of great importance for labour statisticians. Such statistics will be an asset not only to users interested in the analysis of gender issues but to all users of labour statistics, including labour market analysts and policy decision markers.
Most importantly, statistics enhanced in this way will avoid underestimating and misrepresenting the contribution of certain groups of workers, probably women to a larger extent than men, to the national economy. A consequence will then be that policies and programmes that impact labour markets and the economy will not be designed on the basis of statistics that only partially reflect workers’ contributions. With an incomplete statistical basis such policies and programmes can be detrimental both to women and men, but to different degrees.