Guide on Gender Analysis of Census Data Full Draft of 6 December 2012 Contents


Chapter 10: Work, Economic Activities and Social Protection



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Chapter 10:
Work, Economic Activities and Social Protection


1. What is it?
413. Work refers to the participation of individuals in economic activities, both paid and unpaid production for a period longer than one-hour during the reference period, and which delineates employment from unemployment. The population census directly collects data on the economic activities and characteristics of individuals in the areas of employment status, type of work, and the sources and/or amounts of income received by individuals and/or households (United Nations, 2008 a).
414. The economically active population, or equivalently the formal labour force, is made up of all persons above the minimum age specified, generally 15 years of age or older, who report being available to furnish the supply of labour for the production of goods and services during a short reference period (e.g. one week, one day), and are usually registered as being “unemployed.” The economically active population can be categorized into two groups: employed and unemployed.


  1. Employed comprises all persons of a specified age, generally 15 and over, who work for pay, profit or family gain in cash or kind or who do nonpaid work for a family business or farm. If persons are temporarily absent during the reference period, they are considered to be employed??????.




  1. Unemployed comprises all individuals above a specified age, generally 15, who do not work, are available for work, and who did actively seek work during a reference period.

415. The group, inactive or not currently active persons or persons not in the labour force, is comprised of persons not fitting the categories of employed or unemployed during the reference period, and further, those who are outside of the specified age defined for the economically active population. A person may be economically inactive because one is in school, training or college, engaging in household duties, retired or aged out of the labour force, or sick, infirm or disabled. Women are more likely than men to fall into this category, as they typically produce services – such as preparing and serving meals or caring for children, the sick and elderly within a household – that are consumed by the household.


416. Occupation is defined as the type of work done in a job by employed persons. It is recommended that NSOs collect information on occupation in accordance with the latest revision available of the International Standard Classification of Occupations (ISCO) at the following URL: http://www.ilo.org/public/english/bureau/stat/isco/index.htm (ILO 2010).

417. Industry refers to the kind of production or economic activity where persons work. It is recommended to collect information on industry in accordance with the most recent revision of the International Standard Industrial Classification of All Economic Activities (ISIC) (United Nations, 2008). Important gender differences are observed in terms of economic sector. Women are predominantly and increasingly employed in the service sector and the relative importance of the industrial sector as a source of employment for women continued to decline in the last two decades in all regions (United Nations, 2010 b). This preponderance of women in service work may be due to the general development of service work as women have entered formal sector employment en masse after 1960, or it could also be linked to industry or employer discrimination on the one hand, or to a gender preference of women to work in the service sector. For example, this preference could be driven by social expectations for what types of work are acceptable for women, or by different childhood socialisation by sex (i.e. caretaking among girls who then are represented in caretaking professions such as nursing and social work in many societies). By nation, these factors may differ and are potential engendered analysis points.

418. Informal sector work includes persons who are employed in a reference period in the untaxed and unregulated part of an economy [not the official definition]. The informal sector economic activity is not included in the gross national product (GNP) [not true: it should be included and often is], yet it comprises more than one-half of the economically active population in low-income countries and is present in middle- and high-income countries, too (International Labour Organization, 2005).

419. Status in employment describes the type of explicit or implicit employment contract [self-employed people (and others) do not have contracts] the economically active person has. It is recommended that the economically active population be classified by employment status into the following groups: 1) Employees, 2) Employers, 3) Own-account workers, 4) Contributing family workers, 5) Members of producers' cooperatives, and 6) Persons not classifiable by status.


420. Time worked is a measure that typically asks the number of hours per week employed persons work. ‘Time worked’ data help to ensure a more accurate measurement of the relative contributions of men and women to the workforce and identify gender gaps. Time worked is the total time actually spent producing goods and services, within regular working hours and as overtime, during the reference period adopted for economic activity in the census. It is recommended that the reference period is short, for example, the week preceding the census. If the reference period is long, for example, the 12 months preceding the census, time worked should be measured in larger units such as weeks. If a person has more than one job during the reference period, it is recommended to record both total time worked from all jobs and the time worked in the main job for which occupation is being registered. In many countries, especially in Europe, women having young children may choose or may have limited options other than to work part-time. Part-time employment is much more common among women than among men globally, with the prevalence rate for women exceeding twice that for men in about three quarters of the countries (United Nations, 2010 a).
421. These higher participation rates of women in part-time work are due in part to the difficulties women experience in combining family responsibilities and work life. In those countries where child care services are very expensive (i.e. as costly as a salary earned by the woman), or poor quality and/or not widely available, it is difficult for women to work full-time in the formal labour market. It is not necessarily a “free choice” for women, but rather women’s participation in the labour market while also juggling family responsibilities and perhaps even a limited child care and support structure. Where affordable, quality, full-time child care is accessible, women typically work full-time (e.g. Sweden, Norway). For example, the Netherlands has the highest percentage of women working part-time, which is a response to an environment of limited, affordable, full-time child care. This is a gender concern.
422. Full-time and part-time are defined as follows:
a) Full-time work typically refers to working at least 35 hours in a week [is this the internationally agreed definition ? check with ILO].
b) Part-time work refers to a national-level definition of work that is less than a full-time threshold and more than one hour in a typical week. [if 35 hours is the limit, why not say that part time is less than 35 hours ?]

423. The institutional sector of employment describes the legal organization and primary functions, behaviour and objectives of the enterprise that are associated with a job as defined by the System of National Accounts (SNA) as the following categories: 1) corporation, 2) general government, 3) non-profit institutions serving households (e.g. churches, cultural and sports clubs and charitable institutions), and 4) households.


424. Place of work is the location of an employed person’s main job and typically takes the following categories: 1) work at home, 2) no fixed place of work, and 3) with a fixed place of work outside the home. However, the place of work categories may differ by nation determined by local relevancy (e.g. categories for Serbia include 1) at home, 2) on the farm, 3) no fixed place of work, 4) abroad, and 5) fixed place outside the home). In the 2011 census of Albania, 2) and 5) were merged and 4) was disaggregated to identify neighbouring countries. Mauritius (2011) distinguishes between those working at a fixed place outside the home, those without a fixed place of work, those working at home and those working outside the country. Swizerland (2010) distinguishes between those working from home, at a fixed place of work and those working at varying locations. The Costa Rican census actually tries to establish how far away the place of work is from the home.

425. The right to social protection is enshrined in Article 22 of the Universal Declaration of Human Rights (United Nations, 1948) which states that every human being has the right to social security. Article 25 protects the right to security in the event of unemployment, sickness, disability, widowhood, old age or other lack of livelihood in circumstances beyond an individual’s control. Social security has two main dimensions, specifically “income security” and the “availability of medical care.” The preface to the World Social Security Report 2010/11 (ILO, 2010 b) notes that while some level of social security protection exists in all countries, just one-third of countries and 28 per cent of the world’s population have comprehensive social protection systems covering all branches of social security defined in the Social Security (Minimum Standards) Convention (No. 102) (ILO, 1952), and about one-third have no access to any health facilities or services at all. Statutory unemployment social security protection exists in just 78 countries (or 42 per cent).

426. Of persons over age 65 in high-income countries 75 per cent receive pension benefits, compared with less than 20 per cent of those in low-income countries (ILO, 2010 b). In less developed regions, old-age pension or social insurance coverage is found in the formal and public sectors, and women are often not covered because they are less likely to be employed in these sectors than men. Informal employment is the main source of work for women outside agriculture in these regions (United Nations, 2010 a). As a result, most of the world’s elderly, a majority of whom are women, depend either on social security systems or the support of their children in order to stay out of poverty.

427. Although the social security concept is not intrinsically linked to work or employment, most social security systems in the world are organized around employment. Being or having been employed, usually only in the formal sector, is often a precondition for becoming eligible for benefits, e.g. health benefits for employees and their families, old age pensions based on pension contributions accumulated during one’s working life, or unemployment benefits based on previous income and the number of years worked prior to dismissal. Typically, employment in the formal sector is also the precondition for maternity benefits. Some countries (New Zealand, Namibia, several European countries), however, have a flat-rate minimum old age pension benefit based on the number of years of residence in the country, rather than the number of years worked.


428. The Principles and Recommendations for Population and Housing Censuses, Rev. 2 (2008 a) do not provide specific recommendations on gathering and analysing data on social security, yet many countries gather data relating to employment, receipt of social security, contributions to social security, and health insurance coverage. Of the 99 countries examined within the most recent, long form census round (2005-14) as presented in Appendix X, 55.6 per cent of countries ask whether respondents are currently working or employed, 13 per cent ask about receipt of social security, 4 per cent ask about contributions to social security, and 12.1 per cent ask whether the respondents have health insurance. Update this information.
2. Why is it important?
429. Women’s economic independence through employment and productive resources is protected within the CEDAW (United Nations, 1979). In addition, the Beijing Platform (i.e. Fourth World Conference on Women) issued a commitment for women’s full economic independence and access to work and productive resources, and the Millennium Declaration linked full and productive employment and decent work for both women and men as a necessary step to promote economic development and do away with poverty and hunger.
430. The Fourth World Conference on Women (United Nations, 1995) commits to promote women's economic independence, specifically through employment and access to productive resources and opportunities, as well as through the coordination of work and family responsibilities for women and men. Further, the Millennium Declaration commits to full and productive employment and decent work for all, both men and women, as part of Goal 1, to eradicate extreme poverty and hunger. And legally binding because most countries have ratified it, the Convention on the Elimination of Discrimination Against Women (CEDAW) (1979) protects women’s access to work.
431. Statistics on the economic characteristics of employed, unemployed and inactive persons gathered in the population census can be used in combination with other demographic and social factors (e.g. education, household and dwelling information) to construct a comprehensive picture of the socio-economic situation. Economic data gathered in the population census also provide baseline information from which survey data and administrative data can be related and evaluated.
432. There is a marked difference, 25 percentage points, in the global labour force participation rate between men and women in 2010; 77 per cent of men participate in the labour force compared with 52 per cent of women (United Nations, 2010 a). In addition to this large gap in participation, which has persisted for 20 years, there is considerable occupational segregation and a gender wage gap that continue to persist in all regions of the world. Further, women increasingly are employed in the services sector and within informal economic activities, which generally commands less in remuneration than the industrial sector (United Nations, 2010 a). In some countries, e.g. in Central America, Colombia and Venezuela, average salaries for women are the same or even higher than those for men, but non-salary incomes are substantially lower, due to the informal natural of much of the work carried out by women (ECLAC, 2011). Beyond sector differences on how women and men are engaged, there remains a need to examine the different conditions of employment for women and men. Working from home may allow women who would not otherwise have the opportunity to be employed to exercise an economic activity, but if more women work from home than men, it can reinforce the marginalization and devaluation of female work (Chant and Pedwell, 2008).
433. Adding to this, women actually work longer hours on average than men when both paid and unpaid work are considered. Women spend at least twice as much time as men in unpaid domestic work (Bianchi et al., 2000). The number of hours that women spend on housework and community and volunteer work exceeds those spent by men for the same purposes. The average number of hours per day women spend in unpaid housework and community activities ranges from around three (in Denmark) to over six (in Turkey) (United Nations, 2010 a). At the same time, men spend less than one hour on these activities in several countries such as Cambodia and Pakistan. This is important, because women’s unpaid domestic and caretaking work is considered household consumption and not counted as being employed as part of the economically active population. Because unpaid work mainly done by women is not included in the national accounting systems, it goes under-estimated. However, understanding this under-estimated household work situation through census questions (i.e. whether water is fetched from a well or wood collected for cooking compare to less labour-intensive alternatives) allows us to understand women’s roles, opportunities and constraints, and overall life chances compared with men. Finally, women who do not participate in the labour market depend on the resources provided by their spouse or partner or another relative, and therefore are more vulnerable in case of widowhood or separation (United Nations, 2010 a).
434. Social security protection mechanisms are important for women because they are more likely than men to live longer and have more interruptions in their work than men. The latter may result in lower benefits during retirement, especially in systems with a tight link between contributions and benefits (Ståhlberg et al., 2008). In such systems, women who do full-time housekeeping and child rearing work are left vulnerable. In more developed countries, women rely on survivor benefits through their husband’s work, but in less developed countries there is often no benefit. Even in developed countries, women often earn less than men and spend more time out of the work force due to caregiving responsibilities, which results in “gaps” in their earnings histories referred to as “the cost of caring.” At the birth of a child, maternity leave is an important social protection for the mother as well as the child and others living in the household. When women take time off from formal employment to care for children and the elderly, it is again a situation when women are more likely than men not to earn income or save for the future. Retired women generally have less access to other sources of income, such as pensions, assets and earnings, and hence rely on social security more than men to avoid poverty in older age (Hayes, Hartmann and Lee, 2010). As a result of women marrying older spouses and living longer than men, they are more likely to be widowed and then must rely on old-age pensions and social security payments for longer periods than men. Women are also more likely to deplete their financial resources caring for a spouse. In all, these demographic patterns may place women in a vulnerable economic situation (Hayes, Hartmann and Lee, 2010).

435. Systems based on years of residence rather than work, which generally imply substantial transfers from contributors to non-contributors, are particularly beneficial to women who do not have a long employment history. For example, in Japan the national pension scheme implemented in the 1960s succeeded in expanding pension insurance to more than 18 million previously uninsured workers, the majority of whom were women (Chen, Jhabvala and Lund, 2002). ILO (2010) maintains that a big challenge of social protection is extending maternity benefits. At present, cash benefits before and after birth are limited to formal sector employees, and there are huge differences in the amount of benefit across rich and poor countries, and across rural and urban areas. Adding to this, while less than 35 per cent of women in rural areas are estimated to have access to professional health services in low-income countries, about 70 per cent of urban women have access. However, this higher rate is still substantially less, over 20 per cent lower, than health services access in high-income countries (ILO, 2010 b).


436. Access to social security is considered requisite for gender equality. The Plan of Action of the first World Conference on Women (1975), for instance, explicitly referred to the need of ensuring women the provision of social security protection, equal in all aspects to that of men. Other human rights treaties, such as the ICPD Programme of Action, have also expressed concern with the increasing numbers and proportions of elderly people in the world and emphasized the need of developing and ensuring quality systems of economic and social security in old age.

3. Data issues
437. The way work is defined and measured is crucial to measuring how employment and income opportunities may be different by sex. Men are more often employed outside the house with a paid job, while women do most of the unpaid domestic work and are more likely to be misclassified as homemakers when only basic questions are asked. Because women are generally engaged in homemaking duties, or cultural perceptions relating to sex roles on the part of the respondent or the enumerator, women’s economic activity status may be misclassified and therefore under-counted. Indeed, there remains a need to collect data on time-use to capture time spent by men and women on paid and unpaid work, both in the home and the labour market.
Kim raised the issue of village work as a category of work.
438. Occupational data should be coded at the lowest possible level of the classification in order to identify gender differences in occupation. For example, the ISCO 08 (ILO, 2010 a) classifies "Health professionals" under item 22, but differentiate at the level of three digits “Medical doctors” (item 221), “Nursing and midwifery professionals” (222), “Traditional and complementary medicine professionals” (223), “Paramedical practitioners” (224), “Veterinarians” (225), and “other health professionals” (226). While all of these categories are health professionals, a significantly greater number of women are employed as nurses compared with men. Failure to collect specific categories may result in categories that are too broad to capture the differences in prevalence of men and women within a particular occupational category, and further risks conflating two categories which may command vastly different incomes and statuses. 1. You can go up to the fourth digit; 2. How feasible is it to do that in censuses ? 3. We are not really trying to give advice to countries on how they should design their census forms.
439. Comparisons between the wages of men and women are often made in weekly or monthly terms, without considering that part-time work is more common among women. In order to make meaningful comparisons, wages have to be computed on the basis of the number of hours worked. Additionally, income data such as self-employment, property income and non-cash or in kind income can be difficult to collect in population censuses. Because income is typically more easily gathered in a sample survey of households, depending on the national requirements countries may ask limited information on cash income. This paragraph is out of place
440. Because the census data for institutional sector of employment are captured with pre-coded alternatives, borderline classifications may be categorized according to the subjective understanding of the respondent rather than the intended distinctions. Any analysis and resulting statistics should keep this in mind as a possible limitation of the data.
441. Even though the Principles and Recommendations do not make specific recommendations on the analysis of data relating to social security as defined by the ILO, many countries gather these data (e.g. currently working or employed, receipt of social security, contributions to social security, and health insurance coverage). A question to capture maternity benefit or loss of work after the birth of a child may provide a useful measure of women’s status within a country. If this question is repeated longitudinally, cohorts can be followed over time. Alternatively, cohorts of women by age and by number of children including the last birth could be constructed with data from one census administration to examine loss of work due to the birth of a child or a critical number of children.
4. Tabulations
442. The Principles and Recommendations for Population and Housing Censuses Rev 2 (United Nations, 2008 a) recommend several tabulations to describe how persons’ work and economic lives may be shaped differently by gender. The usual or current activity status is the basis for these tabulations, yet the activity rates used to monitor labour force participation exclude unpaid work, such as own-account production or caring for children and the elderly [careful: own-account production is employment, caring for children is not]. Hence, women’s labour force participation is lower and likely to be underestimated compared with that of men at all stages of the life cycle.
P7.1-R Population ... years of age and over, by usual (or current) activity status,

educational attainment, age and sex*

P7.2-R Usually (or currently) active population by activity status, main occupation, age and sex*

P7.3-R Usually (or currently) active population by activity status, main industry, age and sex*

P7.4-R Usually (or currently) active population by activity status, main status in

employment, age and sex*

P7.5-R Usually (or currently) active population by activity status, main status in

employment, main industry and sex

P7.6-R Usually (or currently) active population by activity status, main status in

employment, main occupation and sex

P7.7-R Usually (or currently) active population by activity status, main industry, main occupation and sex*

P7.8-R Population not usually (or currently) active, by functional categories, age and sex*


443. As discussed above, the interpretation of these tables is likely to show a lower labour market participation of women compared with men. Additional tabs might explore whether the gender gap in labour market participation is explained by educational attainment. An engendered perspective would ask: ‘Do women and men at similar levels of educational attainment have similar labour market participation rates?’ Are women and men at similar levels of educational attainment represented in the same occupations or industries at similar rates? Are women and men at similar levels of educational attainment represented in the same functional categories (e.g. management, factory line) within work organisations. Some gaps in labour market participation may be the result of women being less educated compared with men, or alternatively, there may be cultural reasons (e.g. discrimination, social norms, laws limiting women’s work) that limit women’s participation at the same rate as of men. For many women, it is not a choice.
444. As mentioned above, some censuses, such as the Australian and Canadian censuses of 2006 and the Korean censuses of 2005 and 2010, have specific questions on care-giving activities, including child care. The 2005 census of the Republic of Korea established, for instance, that 5.4 per cent of children between ages 0 and 12 are cared for by their grandparents during the daytime. Australia asked questions on unpaid domestic work carried out and care given to family members or others because of disability, a long term illness or problems related to age. With respect to child care, it asked: “In the last two weeks did the person spend time looking after a child, without pay? The data results, which were computed at the national level and excluding cases where the information was not stated or not applicable, were as follows:

Table 33: Australia (2006) - Percentage of men and women who spent time providing unpaid child care



Type of unpaid child care provided

Men


Women


Own child(ren)

19.7

22.9

Other child(ren)

5.3

10.0

Both own and other

0.6

1.6

Source: Australian Bureau of Statistics CDATA Online (2006 Census)

In those rare cases where this kind of information is available from the census, it can be used to fine-tune either of the two methods outlined above.

445. Some potential tabulations with a gendered perspective regarding social security include:

a) Participation in the labour market of persons 65 years and over, by sex and age (in five-year increments);

b) Social security or old-age pension receipt of persons 65 years and over, by sex and age (in five-year increments);

c) Health insurance receipt of persons 65 years and over, by sex and age (in five-year increments);

d) Contributions to social security or an old-age pension of persons 15 years and over, by sex and five-year increments of age; and

e) Health insurance status of persons 15 years and over, by sex and five-year increments of age.

446. Additional factors, such as race, ethnicity, marital status or rural/urban status, may also be relevant dependent on the composition of the national population and should be added to the above tabulations when relevant.

5. Indicators
447. Minimum Set of Gender Indicators
Computable with census data
Labour force participation rates for persons aged 15-24 and 15+, by sex

Proportion of employed who are own-account workers, by sex

Proportion of employed who are working as contributing family workers, by sex

Proportion of employed who are employers, by sex

Percentage distribution of employed population by sector, each sex

Informal employment as a percentage of total non-agricultural employment, by sex (??)

Youth unemployment, by sex

Proportion of employed working part-time, by sex (??)

Employment rate of persons aged 25-49 with a child under 3 living in a household and with no children living in the household, by sex
448. Not computable with census data
Average number of hours spent on unpaid domestic work, by sex (separate housework and child care if possible)

Average number of hours spent on paid and unpaid work combined (total work burden), by sex

Percentage of firms owned by women

Proportion of children under age 3 in formal care;

Women’s share of managerial positions;

Percentage of female police officers;



Percentage of female judges.
449. A gendered analysis of the factors related to paid and unpaid work begins with the core topic areas that describe persons’ economic situations, and then considers how these may vary in a systematic manner across men and women in the population. This section outlines several indicators that may be useful to measure and describe persons’ economic situations.


  1. Unemployment rate for women and men. To calculate the unemployment rate, the economically active population is divided into employed and unemployed population, and the unemployment rate is the percentage among the economically active who are not employed (i.e. among those who are registered as such with the government. Promoting gender equality in employment is widely recognized as an essential component of economic and social development. Women’s participation in employment increases their contribution to household income and their control over the allocation of those resources. This leads to greater economic independence and self-determination, which are both important for women’s empowerment. In the vast majority of countries, adult unemployment is higher among women compared to men, with important regional differences [the bigger problem is that many unemployed women are classified as not economically active]. Unemployment is also prevalent among the youth population, especially young women. Northern Africa had the highest gap – seven points – between women’s and men’s employment rate overall in 2007, and had a gap of 12 points across young men and women (United Nations, 2010 a). Finland, on the other hand, reported that its register-based census of 2010 had found that in 2009, for the first time, the employment rate of women exceeded that of men. The economic downturn of 2009 mainly affected export industries and brought men’s employment down more than women’s. The occupational structures among women and men differ from each other, so that the majority of women work in the public or services sector, which are less vulnerable to economic trends (UNECE, 2012 c). Larger numbers of unemployed men compared to women were also found in the 2010 censuses of Belarus, the Republic of Moldova, Russian Federation, Tajikistan, and Ukraine (UNECE, 2012 c).


b) Occupation and industry for women and men. The complete analysis of the distributions of women and men by status in employment, occupation and economic sector of activity reveal gender differences and economic segregation. Cross-tabulations, for example, of sector of activity and status in employment are necessary to answer questions such as how men and women are distributed across employment status and whether they differ in any way from one branch of activity to another. But beyond mere sex-disaggregation, the analysis of the causes and consequences of gender differences should be analysed in depth. Women are usually found in specific (i.e. female) occupations and sectors that also have lower status and lower pay. This is part of the existing occupational segregation and discrimination in employment.


  1. Informal sector work. Two indicators on informal sector work can be obtained from population census data. The first is the percentage of economically active women and men employed in the informal sector by branch of activity; it shows the differences in how women and men are engaged in the informal sector. The second is the sex composition of informal sector workers by branch of activity, and illustrates the relative importance of women and men within the informal sector. In many countries, the informal sector provides women with the only opportunity for work in a situation of limited access to formal sector employment. However, those working in the informal sector lack protection, rights and representation, and represent a vulnerable population.

d) Average hours worked for women and men. One way in which the work of men and women may be different is that women tend to work part-time more often than men. The average number of hours worked, when asked in the census, can be compared between women and men, and even analysed by occupation, branch of activity or urban and rural areas. This provides a measure of intensity of work involvement. The main utility of this indicator is that it is one of the elements by which income differentials between men and women need to be qualified.

Average hours worked by women in occupation or branch i x 100

Average hours worked by men in occupation or branch i




  1. Average number of hours spent on unpaid domestic work for women and men. This measure can be computed similarly to the average hours worked indicator above to examine the branch of activity, whether unpaid domestic work, across women and men.




  1. Percentage of women and men in part-time work. Part-time work is one way employed women balance paid work with family responsibilities. In many countries, employed women typically assume most of the responsibility for domestic work.




  1. Average income by occupation for women and men. The gender pay gap reflects inequalities that affect mainly women. A simple indicator is the ratio of women’s average earnings to men’s average earnings, expressed per 100 and for the same period of time (monthly, yearly…). From the information collected on income, when included in the census questions and identified by category (salary and other), it is possible to estimate the ratio by occupation and branch of activity using the following method.

Average income of women in occupation i x 100

Average income of men in occupation i


Additionally, it is important to investigate whether the gender wage gap is due to discrimination or not. An engendered perspective would ask: for a similar position with the same education and experience, do men earn more than women? Some gender wage gaps may be the result of women being less educated, occupying lower positions, and spending more time out of the labour market long term. Considering women who are equal to men in the areas of education, occupational rank and experience, what is the average wage by sex? The above calculation for income should therefore be computed with these “educational,” “occupational rank” and “experience” qualifications. Income information should not be here but in chapter 8

h) Average household income by female and male household head. If income data are not gathered at the individual level within households, examining the average household income by female or male household head may be another useful indicator of economic well being. It can be computed similarly to average income of women and men by occupation above. If valid individual income data are available within households, women’s income could be presented as a per cent of men’s income similarly to average income of women to men in an occupation discussed just above.
450. Some useful indicators for gender analyses of social security are:
a) Percentage of female and male beneficiaries, by age appropriate to retired population

In the US, women comprise 57 per cent of all Social Security beneficiaries age 62 and older, and 68 per cent of beneficiaries age 85 and older.

b) Average monthly social security income received by women and men, by appropriate age range

c) Percentage of economically active women and men protected by social security, by age range

d) Average years of contribution and average years of benefits, by sex

6. Multivariate and further gender analyses
451. Occupational Feminization and Pay in the US. A longitudinal study (Levanon, England, and Allison, 2009) using US decennial census data found that occupations with a greater share of females pay less than those with a lower share, even when controlling for education and skill. Therefore, at each level of education and skill level within an occupation where there were more women than men working, the women were paid less than their male counterparts of the same education and skill level. The authors used census data to test two theories about why women’s work is paid less. The first theory, a gendered labour queue for certain occupations reasons that employers’ preference for men creates the greater propensity of women to be represented in lower paid occupations, while the second theory reasons that it is the proportion of women in the occupation that drives down wages or devalues women’s work. They used fixed-effects regression models, which allow the researcher to control for the stable characteristics of occupations over 50 years. Their findings largely support the devaluation view over the queuing view. Similarly, Blackwell and Glover (2008) use linked census and longitudinal study data to examine women’s participation in science, engineering and technology fields. They find that 80 per cent of women in health-related occupations (e.g. nursing) were mothers, compared with only 40 per cent in science, engineering and technology. These results show a connection between occupation and family life choices for women.

452. Labour Force Participation of Married Women in China. Research (Maurer-Fazio, Connelly, Chen and Tang, 2011) using longitudinal population census data from 1982-2000 in China examined married, urban women’s labour force participation. They find that while having a parent, parent-in-law, or person above 75 years old in the household increases women’s likelihood of being employed, while having a preschool-age child in the household decreases women’s propensity to be employed. These older people in the household may take on some of the unpaid household work that women generally do in China, thus freeing these women of working age up to take paid employment outside the home. When rural-to-urban migrant status is included in the analysis, the negative effect on women’s labour force participation of having young children in the household is substantially larger for married, rural-urban migrants than for their non-migrant urban counterparts. These rural-urban migrant women may not have other supports for child care if they are new to the urban area, so they stay at home with their preschool-aged children. Indeed, the study finds that the positive effect of co-residence with elders is greater for the rural-urban migrant women than for the non-migrants. These rural-urban migrant women are in a position where the kin-based help is likely to live in the same household, whereas non-migrant urban women with elder family members established in the urban area may receive kin-based help from kin who do not live with them.


453. Agricultural holdings in households, fertility patterns and women’s labour force participation as unpaid family workers. In the 2010 census round, several countries, following FAO recommendations, have included a question on whether households serve as agricultural production units, with their own plot of land and/or livestock. This opens up some gender-relevant opportunities for analysis as rural households with their own agricultural holdings are expected to be different from those that do not have such holdings. Women belonging to such households are expected to have higher labour force participation rates, although almost exclusively as unpaid family workers, almost all male heads of households are expected to have a wife to help them in the production, fertility is expected to be higher, and children are expected to have lower school attendance rates: boys because they need to help on the family holding, girls because they must replace their mothers in household duties. However, in order to bear out such relationships, certain statistical controls have to be included. It may be appropriate to control for the socio-economic level of households, for example, by introducing some sort of wealth index based on the quality of the dwelling and the ownership of consumer durables. Moreover, it is probably advisable to control for the presence of other adults, such as grandparents, in the household as these may take over some of the household tasks of spouses.
454. On the basis of the 2010 Aruba Population and Housing Census, two separate analyses were done to look into the occupational status of women and men: a) the type of organization of work and b) the status of employment. For both analyses multinomial logistic regressions were set up. The multinomial logistic regression is the extension of the simple logistic model with a dichotomous dependent variable. The multinomial model allows for a categorical dependent outcome with more than two levels. In the analysis, one of these categories has to be chosen as a residual (or reference) category. In the analysis, all other categories of the dependent variable are then compared to this category. The regression coefficients and odds ratios of the predictors in the multinomial regression are equivalent to those of the simple logistic model, i.e. each category of a given predictor is compared to the residual category of that predictor in terms of their probability of occurring.
455. In the Aruban census the following categories of type of work were used: 1) Limited corporation, 2) One-person business, 3) Foundation, 4) General partnership, 5) Association, 6) Government institution, 7) Government company and 8) Other. In the analysis, categories ‘General partnership’ and ‘Association’ were placed in the category’ others’, as they had very few cases. The reference category for type of work was ‘Limited Corporation’.
456. Table 34 presents the results of the multinomial logistic regression for type of organization worked for. The results show that, after controling for age, education, marital status and country of birth, large differences remain between male and females in terms of the type of organization for which they work. Compared to employment in a limited corporation, women are less likely than men to be economically active in a one-person business (odds ratio = 0.728) or in a government company (odds ratio = 0.391). Their chances are almost equal to those of men to find work in government department (odds ratio = 0.986), but they are much more likely to work for a foundation (odds ratio = 3.441) or the ‘other type’ (odds ratio = 1.306). Differences between males and females are highest for ‘Government Company’ and ‘Foundation’. On Aruba, utilities (water, gas, electricity…) are placed in government companies. More men than women work here. On the other hand, many of the organizations in public service (elderly homes, health organizations) and education are foundations. On Aruba, jobs in these sectors are clearly dominated by women.
457. Table 35 sheds some light on the gender differences in status of employment. Categories for status employment in the analysis are: 1) Employer (3 or more employees), 2) Small independent, 3) Small independent, without employees, 4) Temporary employee deployed by a job agency and 5) Temporary employee, volunteer, non-paid family member. The last category actually consists of three response categories in the census questionnaire. As there were only a small number of cases in these categories, they were brought together.
458. Again the same predictors were chosen. The reference category for status of employment is ‘salary earner’. Compared to this reference category, women are less likely than men to be found in any of the other categories of employment status. The differences between men and women are biggest in those categories that involve independent entrepreneurship, i.e. employer (3 or more employees), small independent, small independent without employees. The odds of being an employer with 3 or more employees are about 2.5 times bigger for males than for females (odds ratio = 0.403). Also, men are about three times more likely than women of being a small independent without employees (odds ratio = 0.339) and twice more likely to be a small independent with one or two employees (odds ratio = 0.512).
Table 34: Aruba (2010) - Multinomial logistic regression of type of organization that women work for, compared to men, by various explanatory variables


 

Reference category =

One-p. business

Foundation

Govt.dept.

Govt. company

Other

 

Limited corporation

B

exp(B)

B

exp(B)

B

exp(B)

B

exp(B)

B

exp(B)

Intercept




-2.124

 

-4.308

 

-2.065

 

-2.779

 

-3.636

 

Age




0.008

1.008

0.026

1.027

0.007

1.007

-0.005

0.995

0.028

1.029

Sex

Male

0.000

.

0.000

.

0.000

.

0.000

.

0.000

.

 

Female

-0.318

0.728

1.236

3.441

-0.014

0.986

-0.940

0.391

0.181

1.306

Marital status

Never married

0.000

.

0.000

.

0.000

.

0.000

.

0.000

.

 

Married

0.152

1.164

0.046

1.047

0.166

1.180

0.332

1.393

-0.871

0.460

 

Divorced/Legally sep.

0.074

1.077

-0.161

0.851

0.145

1.156

-0.013

0.987

-0.637

0.604

 

Widowed

0.432

1.540

-0.338

0.713

0.034

1.035

0.351

1.421

-0.513

0.777

Educ. attainment

None

0.000

.

0.000

.

0.000

.

0.000

.

0.000

.

 

Primary

0.038

1.039

-0.204

0.816

-0.104

0.901

0.126

1.135

-0.151

1.001

 

Lower vocational

-0.100

0.905

0.219

1.245

0.276

1.318

0.770

2.160

-0.397

0.813

 

High school (4 - 6 yrs)

-0.169

0.845

-0.079

0.924

0.437

1.548

0.501

1.650

-0.546

0.682

 

Higher vocational

-0.256

0.774

1.150

3.157

0.904

2.469

1.373

3.949

-0.612

0.665

 

Higher (BA - MA - PhD)

-0.354

0.702

2.289

9.862

1.468

4.339

1.076

2.934

-0.540

0.714

Country of birth

Aruba

0.000

.

0.000

.

0.000

.

0.000

.

0.000

.

 

Colombia

0.458

1.580

-2.169

0.114

-2.845

0.058

-3.225

0.040

1.633

5.738

 

USA

0.415

1.515

-1.474

0.229

-1.646

0.193

-1.576

0.207

0.919

4.479

 

Dominican Republic

0.282

1.326

-1.505

0.222

-2.482

0.084

-2.123

0.120

0.967

3.102

 

Venezuela

0.390

1.478

-1.824

0.161

-2.569

0.077

-3.302

0.037

1.095

3.629

 

Curaçao

-0.169

0.844

-0.461

0.631

-0.752

0.471

-0.859

0.424

0.221

1.750

 

Netherlands

-0.014

0.986

-0.181

0.835

-0.561

0.571

-1.709

0.181

0.354

1.868

 

Other

0.124

1.132

-1.172

0.310

-2.240

0.106

-2.272

0.103

1.118

3.452



Table 35: Aruba (2010) - Multinomial logistic regression of women’s status in employment, compared to men, by various explanatory variables



 

Reference category =

Employer (3 or more employees)

Small independent

Small independent, without employees

Temporary employee deployed by a job agency

Temporary employee, volunteer, unpaid family member

 

Salary earner

B

exp(B)

B

exp(B)

B

exp(B)

B

exp(B)

B

exp(B)

Intercept




-5.982

 

-5.148

 

-4.143

 

-2.080

 

-1.008

 

Age




0.032

1.033

0.025

1.025

0.029

1.030

-0.021

0.980

-0.019

0.981

Sex

Male

0.000

.

0.000

.

0.000

.

0.000

.

0.000

.

 

Female

-0.908

0.403

-0.670

0.512

-1.080

0.339

-0.117

0.890

-0.137

0.872

Marital status

Never married

0.000

.

0.000

.

0.000

.

0.000

.

0.000

.

 

Married

0.720

2.054

0.776

2.172

0.177

1.194

-0.256

0.774

-0.341

0.711

 

Divorced/Legally sep.

0.386

1.471

0.596

1.815

0.230

1.259

-0.132

0.877

-0.167

0.846

 

Widowed

0.863

2.370

0.867

2.379

0.447

1.564

-0.085

0.918

0.190

1.209

Educ. attainment

None

0.000

.

0.000

.

0.000

.

0.000

.

0.000

.

 

Primary

0.179

1.196

0.377

1.458

0.056

1.057

-0.392

0.676

-0.262

0.769

 

Lower vocational

-0.075

0.928

0.221

1.248

0.045

1.046

-0.711

0.491

-0.531

0.588

 

High school (4 - 6 yrs.)

0.729

2.073

0.466

1.594

-0.049

0.952

-0.538

0.584

-0.503

0.605

 

Higher vocational

0.619

1.858

0.378

1.460

-0.128

0.880

-0.801

0.449

-0.905

0.404

 

Higher (BA - MA - PhD)

1.243

3.466

0.581

1.787

-0.281

0.755

-1.174

0.309

-0.792

0.453

Country of birth

Aruba

0.000

.

0.000

.

0.000

.

0.000

.

0.000

.

 

Colombia

-0.024

0.976

0.208

1.232

0.493

1.638

0.393

1.481

0.512

1.668

 

USA

1.291

3.638

1.055

2.873

0.670

1.954

0.157

1.170

1.059

2.885

 

Dominican Republic

0.217

1.242

0.080

1.083

0.426

1.531

0.488

1.629

0.625

1.869

 

Venezuela

0.568

1.764

0.743

2.102

0.512

1.669

0.320

1.377

0.733

2.082

 

Curaçao

0.367

1.444

0.382

1.465

0.099

1.104

-0.394

0.674

0.212

1.237

 

Netherlands

0.892

2.440

0.624

1.865

0.333

1.396

0.203

1.225

0.448

1.565

 

Other

0.812

2.253

0.508

1.663

0.268

1.308

0.125

1.134

0.412

1.510

Source: Population and Housing Census Aruba, 2010



7. Interpretation, Policy and Advocacy
459. Compared to their male counterparts, women participate in the labour market at a lower rate and are represented in higher numbers in less lucrative occupations and sectors of the economy. This is not a coincidence, but a pattern all over the world, which reflects discriminatory practices in the labour force (i.e. education, selection, promotion, etc.). And, women still earn less than men even after controlling for hours worked, education and skills over 15 years after the Beijing Declaration (United Nations, 1995 b) affirming women’s right to employment and productive resources, and the Millennium Declaration’s further commitment to full, productive employment for both women and men.
460. Unpaid work mainly carried out by women need to measured, valued and accounted in the national accounting systems. In this regard, data should be collecetd in such a way that household and caretaking work, predominantly done by women across countries, is not misclassified and underestimated. Related to this, policies should be enacted that pay women for doing domestic work (e.g. Canada pays an allowance for unpaid and caretaking work) and provide access to daycare to help families manage work and household responsibilities.

461. Advocates should inform policymakers and the general public about the importance of this unpaid work done by women, when in turn allows men to do paid work. Also, advocates can alleviate women’s domestic burden by sensitising the general public to inequalities in the amount of domestic work by sex among those couples where both women and men work in the labour market. Finally, the women’s domestic burden may be lightened by providing basic infrastructure (e.g. clean, running water) and labour-saving equipment and technologies (e.g. cooking, grinding and cleaning appliances) accessible to all.

462. The Institute for Women’s Policy Research (IWPR, 2011) has used US Census Bureau data to examine women’s disadvantaged economic position with respect to social security benefits and retirement. The institute finds that older American women are more likely to face poverty than older men, especially unmarried or widowed women. Women’s median annual social security benefits reach just 70 per cent of that of men. Further, these social security benefits mean the difference between living in poverty or not for over two-thirds of unmarried women living alone. With Medicare health insurance covering individuals at age 65, few women or men lack health insurance. The IWPR combines analysis with policy activism in order to represent the interests of women. Their research on social security pensions and Medicare health insurance raises awareness of the income inequalities within the US pension system.
463. The World’s Women report (United Nations, 2010 a) found that one-half of the countries worldwide meet the new international standard for minimum duration of maternity leave and that 40 per cent meet the minimum standard for cash benefits, but there remains a gap between statutory law and what is practiced. Many women, in particular those who do not work in the formal or public sectors, are not covered by the legislation. Oun and Trujillo (2005) make the case that where the maternity benefit funds come from is the reason for this inequality towards women. They suggest that payment with public funds or social insurance could reduce this inequality and gap between law and practice. Employers no longer bear the direct costs of maternity. Currently, about one in four countries, especially in Africa, Asia and the Arab States, continue to provide payment during maternity leave through the employer with no public or social security assistance.



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