Invisibility of women’s productive work in labour statistics – special reference to Pakistan
Gender distinction in statistics, particularly labour statistics have real impact in formulating policies and programs for steering market towards economic as well as social development. True labour statistics are supposed to reflect dynamics of each individual participant in the labour force and their work situation irrespective of its gender / sex. However, studies reveal that official labour statistics don’t provide real picture of women’s paid economic activities, particularly in third world countries. The invisibility of women’s work prevails due to perception about women’s role confined to be housewife only. This perception stemmed from patriarchal gender roles and society norms. Improper field work survey of collection labour statistics also aggravates the invisibility. Enumerator and respondent are two main actors of field work of national survey and their being male with biased perception cause invisibility. Though it is not easy to suggest remedial measures for addressing enumerator’s or respondent’s biases that shaped by culture and society norms, an attempt can be made to sensitize and address the problem. This paper suggests that Pakistan Bureau of Statistics (PBS) to have more female enumerators to seek out women respondents, can still reduce invisibility. As a result, PBS may consider labour force survey as more focused and important assignment being prime input for policy making, rather than routine official duty of collecting numbers and figures only. For the purpose, a policy measure has to be taken not only for capacity building for enumerators but also for review of questionnaire and time spent on each household. Without proper training and instructions, enumerator’s own perception can influence their performance in collecting real labour force statistics which could lead to ineffective policy formulation and implementation.
|Keywords||invisibility, labour statistics, women’s productive economic activity, statistical bias, policy measures, Pakistan|
|Thesis Advisor||Siegmann, K.A. (Karin Astrid)|
|Series||Governance and Development Policy (GDP)|
Nazir, Muhammad Adnan. (2017, December 15). Invisibility of women’s productive work in labour statistics – special reference to Pakistan. Governance and Development Policy (GDP). Retrieved from http://hdl.handle.net/2105/41810