Materials developed for this section are based on concepts and definitions laid out in the resolution adopted by the Thirteenth International Conference of Labour Statisticians in 1982. In 2013, new standards for measuring work, employment and labour underutilization were adopted by the 19th International Conference of Labour Statisticians. Activities to revise and update national data collection practices to be in line with the new standards are under way in a number of countries and regions around the world. The likely impact of the new standards on how statistics on women’s and men’s participation in the labour market are collected and how gender should be integrated fully into labour force surveys will require careful evaluation. For any further development, please contact the Department of Statistics, International Labour Office.
- + Introduction
- Uses of labour force surveys for gender statistics
The labour force survey is a household sample survey designed to collect data on the labour force and its characteristics (Hussmanns, Mehran and Verma, 1990). It is conducted in many countries and is particularly important when administrative records are non-existent or incomplete and where establishment surveys are expensive and difficult to conduct.
Household sample surveys are the most flexible of all data collection instruments on the labour force and its characteristics and are the most valuable from a gender perspective (Hussmanns, Mehran and Verma, 1990; Mata-Greenwood 2003). They can cover a wide range of topics. Information on employment, unemployment, occupation or status in employment can be collected at the same time as information on education and training, income or household and family. This combined information is useful for understanding the participation of women and men in the labour force. Furthermore, the surveys can accommodate more questions for each topic, enabling a more precise measurement of economic characteristics, based on international standards for concepts, definitions and classifications. In fact, some of the criteria specified in the international standards that are crucial for correct reporting of women’s and men’s economic activity can only be implemented through household surveys (Hussmanns, Mehran and Verma, 1990; Mata-Greenwood, 2003).
Labour force statistics disaggregated by sex, age group, activity status, status in employment, occupation, branch of economic activity and income from employment provide essential information for the design and evaluation of overall government policies aimed at (a) the promotion and creation of employment; (b) the alleviation of poverty and the redistribution of income; and (c) equal opportunity and treatment in employment (Hussmanns, Mehran and Verma, 1990). Trend data in employment and unemployment for particular subgroups of population (such as women and men, or young persons and older workers) are also crucial to the assessment of the social effects of government employment policies or structural adjustment policies. Furthermore, statistics on economic characteristics disaggregated by sex, age, education and other social individual and family characteristics can show gender-specific contributions to the economy, gender differences in employment conditions, gender segregation in the labour market and gender-specific family-related obstacles in labour force participation.
Labour force surveys may be conducted on a recurring basis at short intervals to provide data for current purposes, or they may be conducted at longer intervals and provide benchmark data and data necessary for structural in-depth analysis (Hussmanns, Mehran and Verma, 1990). It is important that a gender perspective be taken into account in both approaches, although more gender-related comprehensive information may be obtained in the second approach. In the recurring programme, the focus is on adequately monitoring the trends and seasonal variations of the currently active population, both employed and unemployed. In developed countries, a continuous survey may provide monthly or quarterly statistics on the labour force. In developing countries, however, such surveys may be collected less often. Still, it is important that countries collect statistics for both agricultural peak and slack seasons, as the seasonal variations in labour force participation are different for women and men.
In the non-current statistics programme, more-comprehensive surveys may be conducted once every few years. These surveys should provide comprehensive information on the economically active population by industry, occupation and status in employment, and on activity patterns over the year, work experience, multiple job-holding, education and training, hours worked and income from employment (Hussmanns, Mehran and Verma, 1990). Other topics, such as time use or informal employment, may also be included, along with demographic and household and family characteristics. The benchmark statistics obtained, as well as the possibility of in-depth analysis, are particularly valuable for understanding gender issues.
Avoiding gender bias in data collection
Questionnaire design, the development of manuals and the training of the interviewers are key elements in avoiding gender bias in data collection. These elements should be reviewed from a gender perspective before implementing the survey. For each topic covered by the labour force survey, there are strategies for reducing the underreporting of economic activity and the misreporting of categories of labour force or employment conditions, as presented in detail in the following subsections. Box III.5 and box III.6 present a summary of those measurement strategies.
- +Box III. 5 Designing the questionnaires for labour force surveys for better gender statistics: a checklist
Ensure that members of the team designing the questionnaires are trained in gender issues and gender-specific measurement issues related to work
Use a set of questions rather than one direct question for each of the topics
Include additional probing questions for selected groups of employed or status-in-employment categories
Use lists of economic activities that are usually underreported (for example, those considered an extension of domestic activities, and/or carried out in the home)
Avoid using keywords such as “economic activity”, “occupation” or “looking for work” that may induce underreporting of non-market economic activities
Avoid using keywords that apply exclusively to one of the sexes, such as “housewife” or “fisherman”
Include short explanatory notes in the questionnaire and detailed instructions, including explanations of concepts, in the interviewers’ manual
Use specific questions on reasons for not seeking work to identify particular subcategories of unemployed or non-active persons, such as discouraged workers or seasonal workers
Use additional questions with gender-specific reasons for: being absent from work; not being available for work; steps taken to seek work; reasons for not seeking work; and reasons for choosing certain non-regular jobs or non-standard working arrangements.
Source: Hussmanns, Mehran and Verma, 1990; Mata-Greenwood, 1999, 2003.
- +Box III. 6 Integration of gender in the preparation of manuals and training of interviewers in labour force surveys: a checklist
Key gender issues related to work are identified and integrated in the general training of staff involved in the survey
The language and all the examples given in the manual or during training exercises are free of gender-based biases or other stereotypes related to the characteristics measured
Training examples are reviewed so as not to foster gender-based or other stereotypes related to the characteristics measured
Explanation of work-related concepts is followed by a warning that the respondents’ or the interviewers’ understanding of the concepts may be different from the concept intended to be measured; stereotypes of women as housewives are discussed
Interviewers are trained to use probing questions and lists of activities and lists of economic activity that may be underreported and lists of housework activities that are not considered economic are compared and the differences between those activities are made clear
In-depth training based on examples and explanations is required for those items in the questionnaire where the interviewer has to categorize the replies given by the respondents, such as in the case of recording information on status in employment
Clear guidelines in selecting the appropriate respondent are given
Both women and men are selected as training instructors and as trainers presented in audiovisual materials
Both women and men are trained to interview persons of the same sex and of the opposite sex.
Source: Hussmann, Mehran and Verma, 1990; Mata-Greenwood, 1999.
- + Topics covered
- Labour force surveys usually cover the following topics: the economically active population; employment; unemployment; hours of work; industry (branch of economic activity); occupation; and status in employment. A wider range of information relevant to gender can also be generated by attaching additional modules on income, informal employment, time use or work-family balance to labour force surveys.
- + Economically active population
- The measurement of the economically active population involves two basic considerations: (a) the distinction between economic activities and non-economic activities; and (b) the use of a short reference period or a long reference period in applying that distinction. Both considerations are relevant from a gender perspective, as shown in the paragraphs that follow.
According to international standards, the distinction between economic activities and non-economic activities should be based on the general production boundary of the System of National Accounts. Economic activities cover market work and non-market work involved in producing goods for own consumption, as specified in the System of National Accounts. Respondents’ and interviewers’ understanding of the notion of “work” and “economic activity”, however, may not be as encompassing as the definition envisaged by international standards (Hussmanns, Mehran and Verma, 1990). The forms of work that are more likely to be underreported are those performed for own consumption and those carried out at home. As these forms of work are commonly performed by women, their participation in economic activity is often underestimated. Cultural perceptions of women as housewives and the failure of the proxy respondents or the interviewers to take into account the multiple activities of women also contribute to the underreporting of women’s economic activity.
Underreporting of economic activity may be reduced by avoiding keywords such as “economic activity” and by supplementing the general leading question on work performed with probing questions referring to specific activities. Where non-standard work situations are widespread and varied, probing questions may be formulated in terms of activity lists. Those activity lists should cover activities commonly carried out in the country by women and men and suspected as going unreported without probing (Hussmanns, Mehran and Verma, 1990). Training of the interviewers and clear explanations of the scope of economic activity in the instruction manual are also needed.
The economically active population is measured based on the current activity status or usual activity status. The most widely used is the “current activity” measurement. It is based on a short reference period, such as one week or one day, and it provides a snapshot of the economically active population at a given point in time (Hussmanns, Mehran and Verma, 1990). In this approach, currently active population is the labour force. The “usual activity” measurement is based on a longer reference period, such as one year, and is particularly useful in developing countries with significant seasonal variation of the labour force (Hussmanns, Mehran and Verma, 1990). For certain groups of population involved in seasonal activities, the employment pattern obtained on the basis of a current activity approach will be different from the employment pattern obtained by employing a usual activity approach. In particular, women are more likely than men to be involved in seasonal activities such as those in agriculture, and their dominant pattern of activities over the year may differ from the current situation at given points of time during the year. The distinction becomes clearer when the measurement of usual activity is combined with the measurement of current activity in the same survey. Retrospective measurement over a long reference period, such as a year, has limitations; however, a month by month recall with probing questions and memory cues may be used to reduce the recall errors (Hussmanns, Mehran and Verma, 1990).
- + Employment and hours of work
- Employment and unemployment are the two categories of the currently active population (labour force). Employment includes persons at work for at least one hour in a short reference period of one week or one day, including persons temporarily absent from work. The measurement of employment has to ensure that (a) all economic activities as defined by the System of National Accounts production boundary are reported, by using probing questions and activity lists, as explained previously; and (b) persons temporarily absent from work are included, by using a question or list of reasons of absence. The question on reasons of absence is particularly useful in preventing the underreporting of employment for women temporarily absent from work owing to pregnancy and birth delivery.
Additional data may be collected on hours of work (actual or usual), in order to identify, within the employed population, subgroups with different degrees of labour force participation (Hussmanns, Mehran and Verma, 1990). These data are the basis for identifying the visible underemployment and for distinguishing between full-time, part-time and other working arrangements for women and men (Hussmanns, Mehran and Verma, 1990). When visible underemployment is of interest, additional questions may be asked regarding reasons for working fewer hours than normal; willingness and availability for additional work; and the kind of additional work sought or available (see Hussmanns, Mehran and Verma, 1990). The categories of answers for reasons for working fewer hours should be detailed enough to capture some of the differences in gender roles within the household (such as time needed to take care of children or of older persons).
- + Unemployment
- Unemployment is defined by three main criteria that need to be satisfied simultaneously: persons who during the reference period were (a) “without work”; (b)”currently available for work”; and (c) “seeking work”. The criterion “without work” is used to differentiate between employed on one side and unemployed or not currently active on the other side. Furthermore, the criteria “currently available for work” and “seeking work” are used to differentiate between the unemployed and not-currently-active population.
Questions regarding steps taken to seek work, reasons for not seeking work and reasons for not being available for work are necessary to properly identify unemployed women and men; certain groups such as discouraged workers or seasonal workers that may be more often associated with women or men; and gender-specific obstacles in labour force participation. These questions and detailed categories of responses are particularly important in the developing countries where the labour market is relatively unorganized or of limited scope and the conventional means of seeking employment are of limited relevance. Such countries may choose to use a relaxed criterion for seeking work. The relaxation of the seeking-work criterion may have more effect on the unemployment classification of women than of men (Hussmanns, Mehran and Verma, 1990). For example, “discouraged workers” are those persons who are available for work and want a job, but who give up searching because they believe they cannot find a job. More women than men may be found in this situation. Under a strict “seeking work” criterion, “discouraged workers” should be considered “not active”, while under the relaxed criterion they should be considered “unemployed”. Even when the standard definition of unemployment is adopted, this category of workers should be identified separately, among the population not currently active (Hussmanns, Mehran and Verma, 1990). Similar considerations should be taken into account when classifying seasonal workers. During the off-season, these persons are available for work but not seeking work while waiting for the busy season (Hussmanns, Mehran and Verma, 1990).
- + Major economic classifications: industry, occupation, status in employment
- Data on industry, occupation and status in employment disaggregated by sex provide information on the conditions of work for women and men. These data are the basis for the study of the structure of the economically active population and the development of human resources.
Industry (branch of economic activity) and occupation refer to the main job of the person, often defined as the job where the person spends the most time working, or, sometimes, the job that provides the highest income from employment. Industry is identified on the basis of a description of the characteristics of the economic unit in which the person works such as the kind of goods or services produced at the place of work and the types of activities carried out by the economic establishment. Occupation is identified on the basis of the job title and a description of the tasks and duties performed by the person in the job. The textual responses obtained from the questions on industry and occupation are coded after the field information has been gathered, and this activity constitutes a major task of data processing. The framework used for coding industries is that of the International Standard Industrial Classification of all Economic Activities. The framework used for coding occupation is that of ISCO. Coding involves classification and subject-matter specialists at the planning stage and specially trained coders at the operational stage. It is important that wrong assumptions due to gender stereotypes are avoided at the stage when rules for data coding, data editing or data imputation are formulated.
Status in employment is categorized on the basis of the type of contract of employment, economic risk and authority over the establishment or other workers (International Labour Office, 1993). A worker may have more than one job during the reference period and, as a consequence, she or he may have more than one status in employment. For example, a woman or a man may work as an employee in one job and as an own-account worker in another. While status in employment should be measured for the main job (the same main job used for industry and occupation), it may also be useful, for analytical purposes, to collect information on status in employment for more than one job (Hussmanns, Mehran and Verma, 1990).
The information on status in employment is usually obtained through one question (such as “Did you work as . . .?”; “Were you a . . .?’; or “What is your employment status in your present job?”) followed by a list of precoded answer categories (Hussmanns, Mehran and Verma, 1990). The number and types of the precoded answer categories to the question on status in employment may vary. In addition to the five broad categories recommended by the International Classification of Status in Employment, it may be necessary to include other categories, either as separate groups or as subgroups. It is important that categories of status in employment where women or men are overrepresented be considered. For example, women may be overrepresented among the “subsistence workers”, “casual workers”, “short-term workers” or “seasonal workers”; men may be overrepresented among the “owner-managers of incorporated enterprises” or “employees with stable contracts”. Additional questions may be needed to identify those categories of workers.
Training and instructions included in the interviewers’ manuals should aim to prevent misclassification of status in employment owing to gender bias. For example, when a household enterprise is operated jointly by a couple, the appropriate statistical treatment would be to consider both persons as employers or both as own-account workers rather than considering one person as employer or own-account worker and the other as contributing family worker (Hussmanns, Mehran and Verma, 1990; Mata-Greenwood, 2003).
- + Modules attached to the labour force surveys
- A wide range of information relevant to gender can also be generated by attaching topic-specific modules to the labour force surveys. Modules may refer to, for example, income from employment, informal employment, time use or work-family balance; however, countries need to consider carefully the length and complexity of the interview, the increased respondent burden and increased work on data processing and data analysis. Countries may choose, for example, to integrate a different module within each round of the ongoing labour force survey.
Income from employment
Employment-related income consists of payments in cash, in kind or in services as a result of an individual’s current or former involvement in paid or self-employment jobs (International Labour Office, 1998). Data on employment-related income provides crucial information for the analysis of the income-generating capacity of different economic activities; income access and underemployment; and the economic well-being of women and men. Depending on the objectives set, the information on employment income may need to be collected in relation to the job (when interested in the income-generating capacity of economic activity) or in relation to the individual (when interested in women and men’s access to income and their well-being). From a gender perspective, the latter approach is preferred. Different reference periods may also apply. In the latter case, the focus may be on the past-year employment experience and income from all jobs held during the period, including main activities as well as other activities. Income should be collected separately for each component of payment and, as much as possible, directly from the person concerned.
Informal employment is defined as the total number of informal jobs, whether carried out in formal sector enterprises, informal sector enterprises or households, during a given period (International Labour Office, 2003). The measurement of informal employment involves a combination of several questions leading to the identification of different types of informal employment (Hussmanns, 2004):
(a) A question on status in employment. Contributing family workers will be considered in informal employment owing to the fact that they do not have explicit written contracts of employment and are not subject to labour legislation, social security regulations or collective agreements;
(b) A set of questions about the characteristics of the enterprise where the person works, such as the size of the enterprise, legal ownership, the type of accounts and formal registration of the enterprise. Several categories of workers in informal employment are derived, including own-account workers and employers working in their own informal sector enterprises, members of informal producers’ cooperatives, and own-account workers engaged in the production of goods for own final use;
(c) A set of questions about social protection or other employment benefits addressed to all employees – specifically, the payment of social security contributions or the existence of paid leave. The category of workers in informal employment derived is employees holding informal jobs in the formal sector. (For more information on gender and informal employment, see United Nations, Economic Commission for Europe, and World Bank, 2010.)
These types of informal employment vary in terms of the vulnerability of jobs and the level of payment as well as in terms of the shares of women and men involved. Therefore it is important that they are identified and presented in dissemination products as separate categories.
A time-use module may utilize for data collection either a separate instrument, such as a light-time diary, or, more often, a set of questions on specific paid and unpaid activities integrated within the same questionnaire dedicated to labour force measurement (United Nations, 2005). The reference time period is usually the 24 hours of a day or the seven days of a week. Information on time use is crucial to understanding gender roles in productive and non-productive activities. It is the basis for the measurement of unpaid work such as household production or volunteer community work. This work, more often performed by women than by men, is not usually covered by the labour force statistics. In addition, time-use information can be used to better capture some forms of work that, although considered economic and productive by international standards, are not properly reported, especially in the case of women. Lastly, information on time spent by women and men on specific activities such as caring for children or the elderly, cooking, washing or repairing are important for understanding intrahousehold distribution of gender roles and gender-specific work-family balance.
Understanding work-family balance requires additional information about the person and other household members. First, demographic characteristics such as sex and age should be collected for all household members; in addition, basic economic characteristics should be collected for all adults in the household. That information will show whether children or older persons (groups usually in need of some care) are part of the household, and whether other adults in the household have a source of income. Second, the distribution of gender roles within the household may be captured through questions on household responsibilities in taking care of children or ill, disabled or older household members, and involvement in various types of housework. The time spent in each activity may be provided by a time-use module. Third, questions regarding the availability and quality of childcare services are particularly important in countries where such services are not easily and equally available to all population subgroups. Fourth, questions regarding the individual reasons for choosing certain non-regular jobs or non-standard working arrangements may show whether family or non-family factors are among the main reasons.
- + References
- Hussmanns, Ralf (2004). Measuring the Informal Economy: From Employment in the Informal Sector to Informal Employment. Working Paper, No.53. Geneva: International Labour Office.
__ , Farhad Mehran and Vijay Verma (1990). Surveys of economically active population, employment, unemployment and underemployment: An ILO manual on concepts and methods. Geneva: International Labour Organisation.
International Labour Office (1982). Resolution concerning statistics of the economically active population, employment, unemployment and underemployment. Adopted at the thirteenth International Conference of Labour Statisticians. Geneva, October.
_ _(1993). Resolution concerning the International Classification of Status in Employment (ICSE). Adopted at the fifteenth International Conference of Labour Statisticians. Geneva, January.
_ __(1998). Resolution concerning the measurement of employment-related income. Adopted at the sixteenth International Conference of Labour Statisticians. Geneva, October.
_ __(2003). Resolution concerning a statistical definition of informal employment. Adopted at the seventeenth International Conference of Labour Statisticians. Geneva, December.
Mata-Greenwood, Adriana (1999). Incorporating gender issues in labour statistics. Geneva: International Labour Office.
__ _ (2003). Producing labour statistics that are useful for addressing gender concerns. Room document for the Seventeenth International Conference of Labour Statisticians. Geneva, November –December. ICLS/17/2003/RD.9.
United Nations (2005). Guide to Producing Statistics on Time Use: Measuring Paid and Unpaid Work. Series F, No. 93. Sales No. E.04.XVII.7.
__ _, Economic Commission for Europe, and World Bank Institute (2010). Developing gender statistics: a practical tool. Geneva. ECE/CES/8.