Woman, training and work

Gender! A Partnership of Equals
Geneve: International Labour Office, 2000. 115 p.

Labour Statistics
Keeping the data honest

What they should do

How well do labour statistics address gender concerns? Sound policy decisions are based on statistics of good quality. Good labour statistics reflect reality as closely as possible. They cover all persons who participate in the labour market, without distinctions of sex, age or social status. They describe their different types of work situations, including multiple activities, seasonal and occasional work, and work done at home, at sufficiently detailed levels to make these distinctions apparent. They cover those topics which are relevant to describing distinctions and similarities between the various types of workers. And they are disaggregated (i.e., broken down) in such a way - by sex, for example - that they portray the underlying factors which cause such differences to occur.

In particular, good labour statistics enable users to understand and analyze the position and constraints of women workers as compared to men workers, and thus provide a more solid basis for promoting equality between women and men in the labour market.

What they should not do

On the other hand, partial labour statistics under-report and misrepresent the contribution of certain groups of workers to the economy. They contribute to inappropriate policies and programmes, and to maintaining a distorted perception of the nature of a country's economy and its human resources. This, in turn, perpetuates a vicious circle of inequality.

What's wrong?

While labour statistics have improved substantially over the years, and are certainly useful to identify differences and similarities between men and women in the labour market, they remain incomplete and have limitations in fully addressing gender concerns. This is because the quality of labour statistics depends mainly on the existing methods of data collection which can be used and on the priorities and objectives established before the data are collected.

The different methods of data collection have various limitations, and measurement priorities depend to a large extent on a society's perception of how the labour market functions, which can never be complete. As a result, national labour statistics have generally been successful in identifying and characterizing "core" employment and unemployment situations, which reflect the conventional view of what "work" (workers in full-time regular employment in formal sector enterprises) and "joblessness" (persons who are looking for such jobs) are all about. They have been less successful in identifying and describing other work situations.

Women are often found in these "other" work situations, and may go unnoticed or be inadequately described in labour statistics. Thus, labour statistics tend to under-enumerate and misrepresent women more than men. For example, the defined scope of labour statistics excludes unpaid services for consumption in one's own household. By so doing, the contribution of a vast number of workers to the economy is excluded, most of whom are women. In addition, by virtue of the criteria used in the definitions and characteristics of employed and unemployed populations, as well as the coverage limitations of the data collection methods which can be used, certain groups of workers tend to be excluded from the scope of the statistics. Because the sex composition of these groups generally is not even, where those excluded tend to be women more than men, the usefulness of the resulting statistics for reflecting gender issues is reduced. To improve this situation, international guidelines may be necessary on how to better identify and describe those groups of workers, generally women, who tend to be excluded from statistics.

What's missing?

There are certain topics which are not presently covered in national labour statistics, and for which no international definitions exist, but which are relevant to increasing the understanding of men's and women's positions and interrelationships in the labour market. What are some of these missing statistics?

• Working time arrangements would indicate the degree to which men and women work on what is known as "regular full-time" working schedules or on more irregular schedules, such as part-year, part-time employment, annualized working hours and other variable time schedules
• Overtime work would be useful to evaluate whether establishments' responses to market demands affect men and women differently
• Absences from work would help to indicate any differences in the types of absences experienced by men and women, in particular in view of family responsibilities
• Occupational diseases would be relevant, given men's tendency to be more exposed to injuries and women's tendency to be more exposed to diseases
• Home work, contingent (or non-permanent) employment, poverty, union participation, access to productive resources and the allocation of benefits among household members, etc., are other pertinent topics which would be helpful in the context of gender issues

Finally, relevant disaggregation is also generally wanting in national labour statistics. In order to adequately portray the factors which cause differences between men and women at work, it is important to separate the information by disaggregating it, as a minimum, by sex. But that alone is not enough. To address gender concerns, data on the person's work situation need to be presented; in particular, in the context of their personal and family situation. For example, information on the presence of young children and other household members requiring care would be of interest. In this area also, international guidelines would be most useful.

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