Guide on Gender Analysis of Census Data Full Draft of 6 December 2012 Contents
Source: National Statistical Institute of Cambodia. Results of the 2008 Population Census. 480. Although about one in four countries include questions in their censuses on former members of the household who are now living abroad, identifying households where a member is an emigrant is often difficult. Among other reasons, this is because migrations that involve entire families cannot be captured this way. Another possibility is to look at those censuses that ask about the nature of household income and to consider remittances as a measure. At present, only about 10 per cent of censuses in the current census round directly ask for remittances received. In those countries whose censuses are conducted on a de iure basis, one can also use married women living without their partners as a proxy for male emigration. The best alternative, however, to measure aggregate emigration figures, is to use the censuses or registration systems of the primary destination countries of emigrants. 481. With respect to immigration, the main problem is the identification of immigrants and immigrant households. When migrants do not speak the host country language, language stands out as a reason that migrants are underrepresented in censuses. Additionally, migrants may not wish to be enumerated if they do not have legal residency documents. While there is much policy interest in households and individuals with a “migration background,” these cannot always be interpreted as foreign citizens, because citizenship legislation differs from country to country. For instance, a person of Jewish descent or related to someone of Jewish descent can claim Israeli nationality (i.e. ius sanguini), while anyone born in France is French by birth right (i.e. ius soli). Thus, migration background may be hard to identify unless specifically asked, as in the German census which asks whether the respondent’s mother or father has migrated to Germany and from where. Most other countries simply use foreign citizenship as a proxy for immigrants, thus producing a number of false positives (for example, persons born in a country under ius sanguini law but who have never relocated from one place to another) and false negatives (for example, persons who have changed their country of usual residence but hold the nationality of the census-taking country). Where international migration is analysed using the variables citizenship (or, alternatively, place of birth), extrapolating to “migration” language should be avoided or done with caution. Special cases (stateless persons, naturalised persons, people who have dual citizenship) pose additional problems. Finally, where place of birth is used as a criterion to identify “immigrants,” moves in-between birth and current residence are left unaccounted. 482. The main strength of census data is that they allow for a detailed analysis of the immigrant stock and its characteristics, which is – at least in some countries – a rare group in the overall population (United Nations, 2007). When data are available, given that censuses collect a wide range of information on each individual, they permit cross-tabulation of migration-related characteristics (such as citizenship, duration of stay and place of residence in the receiving country by sex) with a combination of demographic and socio-economic variables (including age, educational attainment, marital status, labour force participation and occupation by sex) (United Nations, 2007). This helps explain the influence of these factors on the decision to migrate as well as allowing a comparison of the female migrants’ experience with that of male migrants. 483. Population censuses yield the most comparable data on international migration at the global level. Census data offer near universal coverage, a vast amount of person-specific and geographic information, and regularity of data collection. At the same time, availability, timeliness and accuracy are limitations that should be addressed at the national level in order to maximise census data usefulness. 484. In terms of internal migration, identifying past and current residence may be difficult in the case of slum-dwellers without standard addresses and people fleeing violent conflict or natural disaster. Further, significant under-reporting can occur with students, domestic personnel, temporary or circular labour migrants and other groups that have de facto relocated their usual place of residence if they have been present for six months or longer in the new location, as well as with regards to non-residents such as visitors that may be erroneously classified as recent in-migrants. Finally, there may be confusion for persons with two or more residences and members of the armed forces. Usual residence should in any case be based on the 12-month limit. 485. There has to be mention here of the fact that migrants are likely to be undercounted because they prefer evading enumeration. Also, we need to say something about the migration of nurses, although it is not clear how we can use census data to produce information on that in the countries of origin. 4. Tabulations 486. Regarding geographical and internal migration characteristics, the Principles and Recommendations recommend that NSOs construct the following essential (*), recommended (R) and additional a) tabulations:
487. The essential, recommended and additional tabulations on international migration and immigrant stock, in turn, are the following:
All of the latter concern immigrants and even more specifically those born abroad. Some censuses also ask about members of the household who are currently living abroad. While this question misses some emigrants (e.g. those that went abroad with their entire household), it is currently the best instrument for measuring emigration at the origin. The results can be tabulated by age and sex, as in the following example from the 2000 census of Cape Verde. Table 37: Cape Verde (2000) – Emigrants by age and sex declared by the remaining household members Males Females 0-4 79 80 5-9 143 150 10-14 242 314 15-19 720 760 20-24 1,156 1,127 25-29 1,096 770 30-34 906 545 35-39 638 385 40-44 365 205 45-49 168 157 50-54 79 103 55-59 68 101 60-64 87 184 65-69 78 122 70-74 50 97 75-79 40 55 80+ 11 28 Source: INE, Cape Verde What this table shows is that, while emigration is a predominantly male phenomenon in Cape Verde, women actually are the majority of emigrants below age 20 and after age 50. 5. Indicators 488. Internal Migration: The proportion of migrants (m/f) to an area a, who migrated from an area b, and conversely. This indicator can be used to measure the intensity of migration, by sex, and their direction of migration flow across two regions, between rural and urban areas or to measure internal migration (in terms of change of place of residence) within the same administrative area (for example in the same region). 489. Immigration: a) Foreign population (m/f) as a percentage of total population (m/f) and b) Proportion of women in the foreign population. Indicator a) provides the estimated number of female and male international migrants expressed as a percentage of the total female and male population; indicator b) shows sex ratios in migration. 490. Emigration [where data are available]: a) Emigration rate (m/f) and b) emigration rate of migrants with tertiary education (m/f). Indicator a) measures the stock of female and male emigrants from a country at a particular point in time expressed as a percentage of the sum of the resident population in the country of origin and the emigrant population. Indicator b) includes only those with a university education and thus indicates brain drain. 491. Labour force participation of immigrants: Economically active foreign-born population by occupation, age, sex and urban/rural residence, and may serve as a measure of upward or downward social mobility. This indicator provides the estimated number of female and male international migrants that are participating in the labour force by age, occupation and place of residence. 6. Multivariate and further gender analyses 492. Several studies provide in-depth analyses on reasons for migration. Country example 19: Marriage Migration in Nepal and Iran Acharya and Chaudhury (2010) use census data from Nepal and Iran find that both countries list marriage as one of the causes of both internal and international migration. They find that the largest proportion of women have moved because of marriage, in both internal and international migration. They explain that traditionally, women have to move onto their household of marriage, which is the household of the husband so they move to a different village, district and even country. This migration in effect isolates women from their parental household and its support system. This can create a context of diminished social status for women in the new marital household. In contrast, men seldom incur a move after a marriage, so they do not experience this same social disruption. Because men and women migrate for different reasons, their migration and integration process in the new milieu may be different. A female migrant may experience a different trajectory of labour force participation and health outcomes compared to her male migrant counterpart due to the different reasons that one may move, which seems to be patterned by gender. A next step would be to examine many factors, such as labour force participation, health outcomes, and poverty status, to understand to what extent they are similar and different across women and men. 493. Marriage – voluntary or forced – or family reunification has traditionally played a significant role in migration, now exacerbated by increasing world globalization. Marriage may be a driving force for women to migrate within their countries or internationally – be it for constituting a new family, or for escaping abusive marriages that limited their freedom. Where “reasons for migration” are asked in the census (e.g. Cambodia, Colombia, Nepal), long form questionnaires or the combination of censuses and migration surveys can be used to produce simple tabulations such as the example from Cambodia below, or to carry out multivariate analyses such as the example from China below. 494. A first tabulation may be to examine the per cent of migrants as a result of marriage, by age, sex, ethnic group, rural/urban, educational level, and country or city of origin. From this, it may then make sense to example using a multivariate logistic model what factors – such as age, sex, ethnic group, rural or urban background, educational level, and city or country of origin – to know what proportion of the variation in the per cent of migrants as a result of marriage is associated with each of these factors, while considering the interrelations among these factors. 495. Fan and Huang (1998), for instance, based on statistical analyses of a 1 per cent sample of China’s 1990 Census, analysed interprovincial female migration as an economic strategy and, thus, for empowerment. The results indicated that women in disadvantaged positions – regarding institutional, structural, and socioeconomic factors – were more likely to pursue marriage as a strategy to achieve migration and to improve their social and economic mobility. Female migrants with agricultural hukou (household) classification, for instance, were 5.0 times more likely to be marriage migrants than those with non-agricultural hukou. Further, female migrants with college or above level of education were 77.3 per cent less likely to be marriage migrants than those without. Estimates of the economic variables also suggested that female migrants from wealthier provinces were less likely (having a 41.3 per cent lower likelihood or propensity), and female migrants to coastal provinces more likely (1.2 times), to be marriage migrants. 496. Another study may be to examine gender barriers to labour force participation. Female migrant workers are among the least protected by labour and immigration laws (cf. Beijing Platform for Action) and face additional barriers to the enjoyment of their labour rights due to language, ethnicity, culture, religion, or socio-economic status. Household composition may pose an additional difficulty. Although many female migrant workers contribute to the economies of both the sending and the receiving countries or cities – through their participation in the labour force and remittances – in many receiving countries they experience higher levels of unemployment compared with both non-migrant workers and male migrant workers. A logistic regression could be carried out with ‘status in employment’ or ‘currently working or employed’ (recoded as a binary variable: unemployed or not unemployed) as a dependent variable. The various above-cited socio-demographic variables, as well as ‘disposition to work’ and other work-related census variables (as long as no collinearity exists) could be entered as predictors to assess their relative weight. As governments are accountable for facilitating migrant’s full integration into the labour force and for assuring full access to economic opportunities, a better understanding of barriers to employment can help formulate policy-responses. As examples, are language courses or child care needed, or does one particular ethnic group need more social support? 497. A study by Stone, Purkayastha and Berdahl (2006) looking at differences in earnings of female migrants in the US according to their country of origin, found that some Asian subgroups require specific policy responses. Data from the 1 per cent 2000 Integrated Public-Use Microdata Series including Filipina, Asian Indian, and non-Hispanic white women living in New York, Chicago, and Los Angeles, revealed that earnings inequality among highly educated migrant women of the same age and occupation, proficient in English and working the same amount of hours, is associated with ethnic origin and period of arrival in the US. While Filipinas and non-Hispanic white women’s earnings are found not to differ significantly, Asian Indian women’s earnings are lower. Women who arrived in the United States in the 1990s earn significantly less compared to natives, while women who migrated before the 1980s report higher earnings compared to natives, thus defying the supposed “double burden” of being a migrant and a woman. 498. Immigration and household composition. Information on the living arrangements of migrant women and men is useful for understanding migrants’ lives and experiences, including: a) Household composition (e.g. sex, age, etc. of those who live alone, live with other migrants, live with people born in the receiving country) which can be further disaggregated by age at arrival, years of residence, place of birth, highest level of education, etc. and should, at least for internal migration, be compared with women and men who live in their previous place of residence (e.g. rural areas); b) Family size and fertility rate among immigrants; and c) The relationship between migratory status and employment as domestic personnel. 499. An example investigating household composition and living arrangements among migrants is Thomas’ (2001) study “Evolving family living arrangements of Canada’s immigrants.” Combining data from the 1986, 1991 and 1996 Canadian Population Censuses and data from the Landed Immigrant Data System (LIDS), the author finds that migrant men and women have different living arrangements at different stages in their lives in the receiving country. Regarding those who migrated in their twenties, there is a one in three chance that a woman will live with an immigrant who was already established in Canada, comparing with a one in four chance for men. Around 20 per cent of the men in this age-group will live with a person who followed them to Canada, contrasting with 11 per cent of the women. Also, 15 per cent of men who immigrate in their twenties will live alone. As the age at migration increases, the probability that an immigrant, either man and woman, will live with relatives that are already established in the receiving country increases. Nevertheless, there is a 48 per cent likelihood that those who arrived as pensioners will be living with immigrants who preceded them. Also, marriage migration from the US to Canada is found to be a frequent phenomenon, and Americans and Europeans have the highest probabilities of living with Canadian-born adults. 500. Emigration and changes in family structure. Emigration can create changes in family structure. To analyse the situation, emigrant households need to be identified; then, issues such as unmet basic needs (see poverty section), employment opportunities of the spouse staying behind and children’s education can be analysed. For example, women left behind may need to spend more time in productive activities outside the house and give more responsibilities of childcare and housework to their daughters. It is therefore interesting to analyse school enrolment rates of boys and girls in emigrant households and to compare them to the rest of the population. Other issues for analysis include: a) The household structure and headship of households that have members living abroad vis à vis the general population; b) The economic characteristics of female heads of households that have members residing abroad, such as the amount of financial support received from people living outside of the household within the country or outside, particularly anything suggestive of the way they manage the remittances received from abroad, small businesses that they may head, homes that they may have acquired, and consumer durables in the home; c) The age and sex of household members residing abroad, if these are known, cross-classified by the socioeconomic characteristics of the households, which may be indicative of the amount of resources sent by different kinds of migrants. 501. Gender and the brain drain. Highly skilled women are on the move as a result in part due to the rise of female education. Docquier et al. (2007), for instance, computed sex-disaggregated indicators of brain drain as a proportion of the total educated population born in the source country for 195 countries. Using census data (1990 and 2000) of the receiving OECD countries, the authors restricted their study to the foreign-born adult population aged 25 and over, classified into three educational level groups. The findings suggest that, between 1990 and 2000, the number of skilled women immigrants to OECD countries increased by 74 per cent, and that the share of women in the skilled immigrant population also increased. For the vast majority of source regions, the growth rates of skilled women emigrants were higher than the growth rates for unskilled women emigrants or skilled male emigrants; indeed, on average, women’s brain drain was 17 per cent above that of men. According to the authors, this feminization of the South-North brain drain mostly reflects gendered changes in the supply of education. 502. The gendered nature and consequences of remittance sending. As women are increasingly migrating independently and as income-earners, remittances are also increasingly being sent by female migrant workers. Investigating the gendered nature of remittance sending helps elucidate the contributions women and men make to their families and communities of origin, to GDP in their home countries and thus to poverty reduction and economic growth. There is evidence from Cuba showing that women are more likely to send remittances (cash, goods, or both) than male migrants (Blue, 2004), be it in small amounts or in kind. In some countries, such as Sri Lanka, the amount of remittances sent by females outweighs that sent by men (UNFPA, 2006), while in others, such as the Philippines, men send more money back home than women, even when taking into consideration earnings differentials between the sexes (Semyonov and Gorodzeisky, 2005). In many countries, remittances sent by women differ from those sent by men in amount, frequency, and orientation on how they should be spent. (Blue, 2004; Semyonov and Gorodzeisky, 2005). 503. The effect of remittances – regardless of the sender – is another research topic with gender implications. For instance, studying rural areas in Pakistan, Mansuri (2006) found a positive impact of remittances on children’s schooling. Not only are children in migrant households more likely to attend school, the effect is also more pronounced for girls than for boys. In contrast, Haveman and Wolfe (1995) studied children left behind by highly skilled female migrants and observe that these children are more likely to drop out of school than their peers. Their explanation is that these children tend to have higher levels of human capital which makes them attractive assets to the domestic labour market and able to significantly contribute to household income. Where such data is available from the census, NSOs could tabulate: a) Average shares of remittances as part of total household income, by sex of remitter; b) Educational attainment, literacy, school attendance (m/f) of children in remittance-receiving households, by sex of remitter. 7. Interpretation, Policy and Advocacy 504. If sex ratios of internal migrants and international emigrants and immigrants are significantly skewed, analysts need to ask follow-up questions, such as: a) If internal migrants are mainly males moving to the bigger cities (e.g. Ghana): What are the characteristics of male migrants (e.g. age, education, employment, marital status)? What are the implications on urban women (e.g. employment options), rural women (e.g. marriage options) and families left behind (e.g. remittances, children’s education)? b) If international emigrants are mainly female (e.g. the Philippines), what are the characteristics of the females who migrate (e.g. age, education, employment, marital status)? What are the reasons for migration (e.g. marriage, types of work)? What are the effects (e.g. remittances, education) to be felt by families, especially children, left behind? 505. Vulnerabilities associated with gender and migration can be mutually reinforcing. This is known double burden or double disadvantage. For example, migrant women are less likely to be employed in their European Union host country than are native women or migrant men. Neither being female nor being a migrant alone can explain this result. Rather, gender and migratory status reinforce vulnerability in this case. 506. Many gender issues related to migration cannot be invesigated using census data alone. At present just a few countries ask about reasons for migration – such as marriage, poverty, or military conflict – and census data are not useful to measure the circular or seasonal movement of persons, or whether the migration is regular, irregular, forced, voluntary, or possibly related to gender-based violence. Migrants’ issues can be better understood if more replete data are collected on the process of migration itself. 507. The Philippines is one of the world’s largest labour exporting countries. The number of women migrants outnumbers that of men. The National Statistical Coordination Board (NSCB) plays an important role in supporting emigrants by providing sex-disaggregated data on issues such as: 1) the distribution of overseas Filipino workers by place of work and occupation; 2) the average cash remittance of overseas Filipino workers by place of work; and 3) the distribution of overseas Filipino workers by major occupation and average cash remittance. The NSCB has regularly publishing and disseminated reports and Factsheets on Women and Men, as well as to making sex-disaggregated census data available online (www.census.gov.ph). Among the data users are NGOs, the Central Bank and the Commission on Overseas Filipinos. The latter registers emigrants, provides pre-departure orientation seminars, supports families with relatives abroad, and provides community assistance or referrals to cases involving trafficking and domestic violence. The Central Bank uses NSCB data to enhance the financial products and services available to migrants and their families, while NGOs learn more about their constituencies through census data. For instance, the United Filipinos in Hong Kong group, that monitors the working conditions of foreign domestic workers, was able to estimate the size of its target population (UNIFEM, 2008). NSCB in turn collaborates with NGOs and other stakeholders to broaden implementation of Objective A.4. of the Beijing Platform for Action, which suggests that national and international statistical organizations should devise suitable statistical means to recognize and make visible women’s participation in the unremunerated and domestic sectors, to migrant workers. Download 4.06 Mb. Share with your friends: |