3.2 Share of women in wage employment in the non-agricultural sector

Modified on 2012/11/05 09:59 by ILO Gender — Categorized as: Goal 3

Contents

GOAL AND TARGET ADDRESSED

Goal 3. Promote gender equality and empower women
Target 3.A: Eliminate gender disparity in primary and secondary education, preferably by 2005, and in all levels of education no later than 2015

DEFINITION AND METHOD OF COMPUTATION

Definition
The share of women in wage employment in the non-agricultural sector is expressed as a percentage of female workers in total wage employment in the non-agricultural sector.

Concepts
Wage employment refers only to wage earners and salaried employees, or persons in paid employment jobs. Employees are typically remunerated by wages and salaries, but may also be paid by commission from sales, piece-rates, bonuses or payments in kind such as food, housing, training, etc. Wage employment does not include self-employed (employers, own-account workers, members of producers' cooperatives and contributing family workers).

Employment refers to persons above the nationally defined working age (different in every country, but generally close to 15 years) who worked or held a job during a specified reference period. Typically, the specified age group excludes children and the elderly. Included are persons who worked for pay or profit (or pay in kind); persons who were temporarily absent from a job for such reasons as illness, maternity or parental leave, holiday, training or industrial dispute; and unpaid family workers who worked for at least one hour, although many countries use a higher hour limit in their definition. The measure of employment is intended to capture persons working in both the formal and informal sectors.

The non-agricultural sector includes industry and services.

Industry includes mining and quarrying (including oil production), manufacturing, construction, electricity, gas and water. These activities correspond to divisions 2-5 in the International Standard Industrial Classification of All Economic Activities (ISIC-Rev.2), tabulation categories C-F in ISIC-Rev. 3 and tabulation categories C in ISIC-Rev. 4.

Services include wholesale and retail trade and restaurants and hotels; transport, storage and communications; financing, insurance, real estate and business services; and community, social and personal services. These activities correspond to divisions 6-9 in ISIC-Rev. 2, tabulation categories G-Q in ISIC-Rev. 3, and tabulation categories G-U in ISIC-Rev. 4.

Method of computation
The share of women in wage employment in the non-agricultural sector is equal to the total number of women in wage employment in the industrial and service sectors divided by the total number of people in paid employment in that same sector, multiplied by 100.

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RATIONALE AND INTERPRETATION

This indicator measures the degree to which women have equal access to paid employment in the industry and service sectors. With the growing levels of development and related structural economic changes, production tends to move from the agricultural sector towards the non-agricultural sectors. At the same time, this causes a movement to paid employment jobs away from other types of jobs, with an accompanying emergence of monetized industrial and services sectors. The extent to which women have access to paid employment could thus reflect their integration into the monetary economy while benefiting from a more s more regular and largely monetary income.  This on turn would be expected to have a positive impact on women’s autonomy, self-reliance within the household and enhance personal development and decision-making power.

This indicators also indicates the degree to which labor markets are open to women in industry and services sectors, which affects not only equal employment opportunity for women, but also economic efficiency through flexibility of the labor market and the economy’s capacity to adapt to changes over time.

The indicator may vary from 0 per cent (there are only men in wage employment in the non-agricultural sectors) to 100 per cent (there are only women in wage employment in the non-agricultural sectors). Equal numbers of women and men in the sectors would result in an indicator value of 50 per cent. An increase in the indicator means that more women have obtained paid jobs, which has positive implications for poverty reduction.

Low shares, or declining shares of women in wage employment call for policies to increase employment opportunities for women, both in terms of access to jobs and the quality of such jobs. There is no optimal share for women in paid employment; this indicator should be assessed in conjunction with other labour market indicators to inform more specific labour market policies.

When interpreting the indicator, the share of women in total employment, unemployment and the economically active population should be taken into account in order to assess whether women are under- or over-represented in non-agricultural wage employment. It is also important to consider information on employment by status in employment, because it is known that women are more likely to work as unpaid family workers. Additional information on the situation of women in the labour market that should be analysed include level of education, level of remuneration, wage differentials,sectoral and occupational segregation, and women’s and men’s access to social protection.

 

SOURCES AND DATA COLLECTION

While labour force surveys constitute a primary source of information, data can also be obtained from population censuses, establishment censuses and surveys, other household surveys, administrative records of different types, and official estimates based on results from several of these sources.

The various sources differ in coverage, scope, units of measurement and methods of data collection. Each source has advantages and limitations in terms of the cost, quality and type of information yielded. The results from various sources can be combined, provided that concepts, definitions, coverage, reference period, classification, etc. agree as far as possible.





Various sources of data may be available for different or same points in time.  However, such disparate sources are seldom completely comparable in their sampling methods, coverage and definitions and the results should be considered with great care in trying to determine comparability over time. Therefore, great care should be taken when trying to compare data over time. There are a number of reasons why data obtained from different sources may not be easily combined:


DISAGGREGATION

The indicator can be disaggregated by geographical regions, urban and rural areas, age groups, income and ethnicity.

Other disaggregations will vary depending on the sample design of the data source. Countries could tabulate the data by branch of industry, number of hours worked, presence of small children and working time arrangement.

Disaggregated data assists policy makers in monitoring progress, creating an environment that promotes decent, productive work for women, and implementing specifically targeted policies and programmes.

COMMENTS AND LIMITATIONS

The main limitation of this indicator is that it does not reflect the quality of wage employment such as the level of remuneration, conditions of work, and the legal and social protection work offers.

In developing countries where non-agricultural wage employment represents only a small portion of total employment, this indicator is less effective in depicting the conditions of women. To overcome this limitation, the share of women in total employment, unemployment and the economically active population should be considered along with the MDG 3.2 to assess whether women are under- or over-represented in non-agricultural wage employment. In developing countries where most employment is in agricultural activities, and where employment is frequently unpaid, additional indicators are needed to evaluate the situation of women in the labour market. Also it is important to consider the status in employment since women are more likely than men to work as unpaid family workers.

 

Further, the indicator does not reveal any differences in the quality of the different types of non-agricultural wage employment, such as formal and informal employmnet, in terms of earning, conditions of work, or the provision of legal or social protection.

GENDER EQUALITY ISSUES

In developing regions and outside the agricultural sector, wage employment is a middle-class, urban phenomenon. Outside of urban areas, non-agricultural paid employment is limited and is more likely to go to men. Men more often hold regular and better remunerated jobs, whereas women are frequently in peripheral, insecure, less valued jobs as home workers, casual workers or part-time or temporary workers, all of which affect differences in income.

As economies develop, the share of women in non-agricultural wage employment becomes increasingly important. A higher share in paid employment can secure higher incomes for women, as well as economic security and well-being. However, this shift is not automatic, nor does it account for differentials in working conditions between men and women. Other variables need to be considered, such as levels of education, levels of remuneration and wage differentials, and the extent to which women and men benefit from labour legislation and social programmes.

 

 

DATA FOR GLOBAL AND REGIONAL MONITORING

Data for global and regional monitoring for this indicator are reported by the International Labour Organization Department of Statistics. 

Comprehensive statistics on total and wage employment disaggregated by sex, branch of economic activity, occupation and status in employment are collected annually through a specialized questionnaire sent directly to national statistical authorities. Statistics are also sourced from national statistics publications and web sites.  These statistics, together with  relevant methodological information on national practices,  are disseminated online in the ILO Database on Labour Statistics (LABORSTA), http://laborsta.ilo.org/.



Data are assessed for validation and consistency through qualitative and quantitative checks. All departures from international standards or classifications are indicated with footnotes and where necessary, countries are contacted for further clarifications.

Regional and global estimates are calculated as weighted averages of the country level indicator, where the weights correspond to each country’s share in the total economically active population in the non-agricultural sector in the region/world in the benchmark year 1990. As estimates of economically active population in the non-agricultural sector are not available for few countries and territories (mainly small islands with population of less than 30,000), their weights are estimated by assuming that about one third of the total population is active in the non-agricultural sector.

 

The formula used to estimate the indicator at the regional and global level is as follows:

Where Ii is the indicator for country i and wi is the share of country i in the total economically active population in non-agricultural sector in the world.



Treatment of missing values

Proxy series such as the share of women in total wage employment have been used when data on wage employment in non-agriculture do not exist or are not available. Underlying this approximation is the assumption that the share of women in total wage employment is not significantly different from that in wage employment in the non-agricultural sector. Sensitivity analysis conducted on a selected number of countries has shown that there is a strong correlation between the indicator and the auxiliary variable.

If a country has data for some years but not for others, it is assumed that data values in the missing years are not abnormal. Values for the missing years are estimated on the basis of changes in correlated series from another source or series. Where data from multiple sources or multiple series from the same source are available, data selection is based on a number of criteria, including: the consistency of the concepts, definitions and classifications with international standards; the quality of the data; the availability of methodological information; and the availability of data or sources over time.

 

Where country data are not available, and no auxiliary variable can be used as a proxy indicator, the values are imputed. The missing values are imputed on the assumption that the data that are available for a given country are representative of that country’s deviation from the average trend across time, which is estimated based on the whole sample in the region. The imputed values are used solely for producing regional and global estimates of the indicator. Their use for monitoring at the national level may not be appropriate.

 

SUPPLEMENTARY INFORMATION



EXAMPLES



REFERENCES

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