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Determinants of women's employment in Chile: a life-history approach

The study
The findings

Eugenia Muchnik de Rubinstein
Department of Agricultural Economics, School of Agriculture, Catholic University or Chile
Isabel Vial de Valdés
Institute of Nutrition and Food Technology, University or Chile
Lucía Pardo
Institute of Nutrition and Food Technology, University of Chile


An analysis of national census data since 1907 and long-term labour trends in the city of Santiago provided background information for this study to improve the understanding of current generational differences in women's workforce behaviour. A life-history methodology, based on data from two age-cohorts selected from a cross-sectional sample of households, was implemented to assess the effect of demographic and socio-economic change and different patterns of family formation on women's labour-force participation.

Chile is a country with a low population density. The 1970 census gave a total population of 8.9 million, but the National Planning Office estimated under-enumeration by about 4.8 per cent, so it was probably in the order of 9.4 million. The last population census (1982) put the figure at approximately 11.3 million. Since 1970, the annual rate of population growth has been between 1.5 and 2 per cent, which is below the average both for Latin America and for countries with similar per capita incomes. This growth is almost exclusively the result of natural Increase.

Labour-force participation rates, which express the ratio between the population in the labour market and the total population of 12 years of age and over, are influenced by both demographic and socio-economic change. Three main demographic trends have shaped population growth in Chile. The first was a steady decline in mortality rates starting in 1907, which resulted in greater longevity, especially for women. The second was a proportionally greater decline in infant mortality rates, which followed much later. In 1960, Chile had one of the highest infant mortality rates in Latin America- 120.3 deaths per 1,000 live births. By 1970, the rate had dropped by 34 per cent; neonatal (less than 28 days) rates had fallen by 11 per cent and general mortality had decreased by 30 per cent. Between 1970 and 1980, infant mortality was further reduced by 60 per cent, the neonatal rate by 48 per cent, and general mortality by 23 per cent. The decline was fastest in the periods 1976-1980 and 1980-1983.

Third, there was a long-term drop in the birth-rate after the 1920s and 1930s, (with the exception of the period 1952-1960), which became particularly noticeable after 1970. These demographic characteristics have affected the structure and composition of both the working and the total population. For example, the increase in population growth in the 1950s partially explains the decline in the total labour force in the 1970s and early 1980s.

These changes have altered both the age distribution of the population and the proportion of the population in the labour force. While the total labour force declined during the second half of the 1960s, it has been increasing since 1970. The National Bureau of Statistics (INK) estimated it to be approximately 2.9 million in 1970 and 3.9 million in 1984. An examination of census data since 1907 shows that male and female labour-force participation has declined, although both series present long-term cyclical changes. Since the 1952 census, male participation has declined comparatively more than female participation, which the 1982 census shows to have increased since 1970 (Muchnik and Vial, 1987). Women's workforce participation in the period 1960 to 1982 was relatively stable, fluctuating between 20.9 and 26.5 per cent. At the end of 1984, 30.7 per cent (1,196,100) of the workforce were women. By mid-1985, their proportion had increased to 34.6 per cent, a rise of 3.9 per cent in one year. In spite of this and the widespread increase in women's labour-market participation in developing countries in recent decades, women in Latin America, including Chile, have had one of the lowest participation rates, although they have had at least as much, and often more, formal education and technical training than women in the rest of the third world.

In Chile, as in other Latin American countries, there has been a significant rural-urban migration, particularly during the 1950s and 1960s. The impact of migration on the participation of women in the urban labour market is not easy to identify because it occurred simultaneously with other changes like increased enrolment in secondary education. The number of girls coming in to look for work may have been counterbalanced by those who stayed on in school and so sought employment later, with the result that the effect on the participation rate was probably postponed until the 1970s.

Labour-force participation rates are also influenced by socio-economic factors including education, financial pressures, and modifications in role perceptions. There have been important changes in illiteracy rates, school attendance, and the average educational level in Chile. Illiteracy has decreased substantially since 1907, while secondary-school attendance has continued to increase since the educational reform in 1965. Since 1940, the literacy rates of men and women have been about the same, and no significant gender differences in terms of years of education are apparent in the 1982 census.

These trends in education affect labour-force participation as well as the age distribution of the economically active population. An important proportion of very young people (12 to 14 years of age) began to postpone their participation in the labour force by extending their schooling; after 1960, there was an even greater reduction in the proportion of working women in the 15-19 age-bracket. Increased female participation rates since 1977 could be associated with the higher wages expected to follow the rise in education levels, which is reflected in the greater number of women professionals and technicians.

A comparison between 1960 and 1982 census data shows a 25 per cent increase in the proportion of married women in the labour force. This is not so much due to a small observed increase in nuptiality rates, but rather to the higher proportion of married women who took up formal economic activity. It is also evident that the labour-force participation of married women with one to four children increased between 1961) and 1982. It is not yet clear whether this represents a long-term trend or is more a consequence of deteriorating economic conditions. Rosales (1979) suggests that in a recession the labour-force participation of low-income women increases, while that of medium- and high-income women decreases. The lower real wages and general unemployment force poorer women, including those with children, to work in order to maintain family income. Better-off women, on the other hand, are deterred from entering the workforce by the lower real wages and the higher opportunity cost of their time.

This is borne out by data which show that the workforce participation rates of poorer women increased from 18 to 22.4 per cent during 1975, a year of crisis characterized by rising and falling real incomes. The participation of middle- and high-income women decreased significantly at this time.

Another indicator of their increasing involvement in formal economic activity and of their need to work in difficult times - was their participation in government programmes like the Programa de Empleo Mínimo (PEM) (Minimum Employment Programme) and, later, in a special programme for heads of households, Programa de Ocupación para Jefes de Hogar (POJH). Women's high participation rates in these programmes was remarkable, especially as many of them had to cope simultaneously with child care. A survey of 10,000 PEM participants in June 1982 showed that 52.3 per cent of them were women (Cheyre and Ogrodnic, 1982). Seventy per cent were aged between 18 and 40, and so likely to be raising children, and 22 per cent were invalids and sick women who worked up to eight hours a day in the programme. While there are as yet no comparable studies of the POJH program, a newspaper survey of eight communities showed that a somewhat lower proportion of women also took part in this programme, in which they worked seven hours a day, frequently performing the same heavy duties as men (Buvinic, 1983).

According to consumer demand theories, individuals and families seek to maximize the relative benefits that they perceive that they derive from the consumption of goods, some of which have to be purchased and some of which are produced at home, and from leisure time. In order to obtain the market goods, members of the household must devote part of their time to work in order to generate income. This in turn implies less time for either leisure or the production of other goods or services in the home. This dilemma is particularly relevant in the case of housewives, as the production of domestic goods and services is very time-consuming and therefore competes with the allocation of time to market work. Cultural norms in countries like Chile usually assign household responsibilities such as child care, household maintenance, and food production to women.

It is well known that conventional definitions of women's activities consistently underestimate their economic functions as well as their productive contribution to society. Several features of women's work at home contribute to this. The partial and sporadic nature of women's income-generating activities, payments in kind, and the fact that many of their tasks (for example, child care, washing, or sewing) are carried out concurrently with regular home-keeping duties make it difficult to observe and measure the full extent of their economic activities. Sometimes their work is not even perceived as such by women themselves, and although household activities which do not generate income also have significant economic value, they are not usually included in national accounts or statistics.

When an individual does not participate in the labour market, it is possible to estimate his or her reservation wage, that is, the maximum wage at which the individual is not willing to work in the market. In other words, the reservation wage represents the value assigned to time spent in activities outside the market. The individual's willingness to participate in the labour market will depend therefore on the difference between the market wage and his or her reservation wage. For example, a housewife may seek employment if the wage she can earn is greater than the opportunity cost of her time. Because of their greater domestic responsibilities, Pardo (1983) has postulated that, other things being equal, the reservation wage for women is significantly higher than for men and tends to increase with the number of children.

Women's labour-force participation rate will vary according to marital status, number of children, and other factors including education, previous workforce experience and training, health, nutrition, and, of course, economic pressures and opportunities. Its duration is not merely a matter of length of employment in terms of years or hours per week, but also of disruption and discontinuity. Research into these matters has implications for the well-being of the women and their households as well as for the economic development of their country.

The study

Two sources of information were used in this study: an employment survey of a sample of 1,060 households carried out by the Institute of Nutrition and Food Technology (INTA) and the Department of Agricultural Economics of the Catholic University (DEAUC) in October 1985; and a second survey, also implemented by INTA/DEAUC, which sought retrospective information on the work history of a subsample of approximately 1,000 women drawn from the earlier group and was carried out in April 1986. Both were carried out under contract with the Department of Economics of the University of Chile, which conducts periodic employment surveys in Santiago. Both samples covered households from all income levels. These surveys were conducted through personal interviews in the home, and aimed to measure employment rates and patterns and to reveal changes in these over time. Generally speaking, employment behaviour was considered within a reference period of one week. However, questions on the previous month and the previous year were also included in order to cover partial and sporadic economic activities.

The primary aim of the second survey, in April 1986, was to gather information on paid work and other events in each woman's life since she entered the formal educational system. As the study sought to observe change through time, two age-cohorts were defined: one of women between 15 and 32 and the other of those between 39 and 65. The data on the work history of each woman is continuous, with information on events at selected points in their lives. The respondents were asked about the sequence of their working activities between starting school and the time of the survey. They were requested to recall each job and to describe it, specifying the month and year in which they began, its duration, and the reasons for leaving. The same methodology was used to obtain data on other aspects of their lives - education, marital history, fertility and the use of family-planning methods - which could build up a more complete description of the main socio-economic factors which influence, and are influenced by, women's participation in the labour force.

The pattern of each of these life events is set out in frequency tables compiled on the basis of the woman's age at the time the events took place rather than the calendar year. The results are presented by age-cohort and by income group. The latter are designated low, medium, and high (strata 1, 2 and 3 respectively), with each level corresponding to one-third of the initial sample of 3,060 households classified according to per capita family income. However, the proportion of each cohort in the three income levels in the subsample of 1,000 households is not exactly one-third: women in cohort 1 are evenly distributed among the three income groups, but a slightly higher percentage of the women in cohort 2 belong to the lowest income group.

The findings

Labour-force Participation

The study showed that 51 .8 per cent of the economically active population in the sample were actually in the labour force; the participation rates were 70.1 per cent for men and 36.6 per cent for women. The male unemployment rate was higher (14 per cent) than the female rate (9.9 per cent).

A breakdown of the reported working population by economic sector showed the female workforce to be heavily involved in the service sector: 59 per cent of them were employed there as compared to 34 per cent of the male workforce. Women worked mainly in personal services (29.7 per cent), followed by manufacturing (17.5 per cent), commercial (16.8 per cent), and government services (11.2 per cent). A very small percentage of them worked in agriculture and fisheries (1.9 per cent) and in housing construction (1 per cent).

Figures for the distribution of the labour force by occupation indicated that approximately 38 per cent of women were white-collar workers, around 27 per cent were in domestic service, 15.5 per cent were self-employed, and 13 per cent were blue-collar workers. About 5 per cent worked in one of the government-subsidized employment programmes (PEM and POJH). Less than 5 per cent were employers. The number of women in domestic service stood out: 485 out of 2,930 working women in the sample, or one woman in less than every four, worked as housemaids. It is interesting that none of the female heads of household was so employed.

Eighty-nine per cent of the women worked for wages or income for 25 to 58 hours per week. Those who had permanent jobs and related social security coverage had slightly longer average working hours than other female workers; however, the women participating in one of the subsidized employment programmes, PEM or POJH, worked only about 25 hours per week.

Figure 1 shows the frequency of women's participation in the labour force by cohort: in other words, it shows the number of women who worked or sought a job at each age. Obviously, the frequency curves of the younger cohort are, by definition, truncated at 32 years of age, or at 29 if the number of observations above that age was too low to be representative. Nor was it feasible to estimate averages for the younger cohort as the relevant events had not yet been completed in most cases.

According to figure 1, a higher proportion of the older cohort was working when they were 20 or less, but the opposite is true after the age of 21. In the older cohort, the percentage of women in the labour force increased with age up to 49 per cent at 24 years, then declined by about 10 per cent between 24 and 27, and continued to do so very slowly thereafter. The participation of the younger cohort increased constantly up to the cut-off point at 29, when there was around 57 per cent. Only 42 per cent of the older cohort were working at this age. Although the younger cohort postponed entry into the labour force by an average of five years, its rate of participation was substantially above that of the older group.

Within cohort 1, the pattern of labour-force participation differs substantially according to income group (fig. 2). Women in the low-income group exhibit significantly higher frequencies of participation when they are younger than either the medium- or high-income women. However, from around 26 onwards, and particularly after 39, their labour-force participation drops. On the other hand, the participation of the high-income group increases with age up to 29, where it stabilizes at approximately 45 per cent till 46, when it begins to increase again, reaching a peak of around 56 per cent in the early fifties. The middle-income group presents the classic double-peak pattern of labour-force participation, in which women work before or during their childbearing years, leave the labour force to raise their children, and subsequently return to work.

Fig. 1. Women in the labour force at each age

Fig. 2. Cohort 1: Women in the labour force at each age by income group

Fig. 3. Cohort 2: Women in the labour force at each age by income group

Figure 3 shows that in the younger cohort the labour-force participation of the low-income group is generally not above that of the other two income strata. It increases up to 22 years and is maintained at an average rate of 43 per cent up to 29. The pattern of labour-force participation in the high-income group is similar to that in the older cohort, in that it increases with age, but the participation rates after 21 years are much higher, reaching 78 per cent at 29, compared to only 47 per cent of this segment of the older cohort at the same age.

The separate and joint impact of demographic, socio-economic, and behavioural variables on the women's labour-force participation was assessed by means of multivariate regression analysis. Econometric analysis of the survey data focused on the main factors that determine women's wages and the way in which wages and other factors like education and family formation influence women's decisions about employment.

A comparison of working behaviour by income strata independent of age shows that the impact of changes in wage rates was much more significant in the middle than in either the high- or low-income groups. Married women in the medium- and high-income groups spent fewer hours in formal work than single women, but marital status was not a significant determinant of low-income women's working behaviour. For women in the high-income group, the availability of domestic staff increased the probability of market work. The analysis shows that, in the lower socio-economic group, an increase in family income induced women to work fewer hours. This also occurred in the high socioeconomic group, but to a much smaller extent. On the other hand, increases in family income had a positive effect on women's employment in the middle-income stratum.

Real wage levels were shown to be an important factor in women's decision to enter the labour force and also in the number of hours worked per month. The positive impact of wage rates on hours of work and on the probability of working was stronger in the younger cohort. This, in combination with higher educational levels, was having a substantial effect on the labour-market time allocation of younger women.


Educational attainment was a major determinant of average earnings. The higher the level of school completed, the higher the wage which could be expected. The hourly income of women who had only completed primary school was not much better than that of those who were illiterate. However, secondary education or incomplete tertiary studies led to double the income of those who had only primary schooling, and those with a university degree earned four times as much. Women with technical training earned somewhat less than those who had secondary school qualifications. The impact of education on female earnings was greater in the younger cohort. Of course, age and working experience have a considerable influence on hourly earnings, but this cannot be considered so important in the younger cohort because of the early cut-off point.

The educational system in Chile is in four parts, primary (eight years), secondary (four years), technical (from one to three years) and university (five to seven years). In 1965, secondary education was reduced to four years, and primary schooling expanded from six to eight years, so that free compulsory education could be extended by two years. The data for the older cohort in this study have been adjusted so that valid comparisons between the cohorts can be made.

Important differences between them can be observed in the proportion of each completing primary education. The cumulative frequency distribution indicates that about 29 per cent of the older cohort had finished their primary education at 13, compared to 39 per cent of the younger cohort. About 53 per cent of cohort 1 had finished primary education by 16, compared to 76 per cent of cohort 2. This difference of approximately 23 per cent in favour of the younger generation remains unchanged thereafter.

Looking at the differences between income groups, a greater proportion of the high-income group completed their primary education in both cohorts, as might be expected, but this difference between the income groups decreased drastically within the younger cohort. The proportion of low- and medium-income groups finishing primary education by 13 increased from 12 to 29 per cent and from 15 to 34 per cent respectively between cohorts 1 and 2. This means that better access had more than doubled the proportion of low- and medium-income women completing primary education.

Turning to secondary education, the highest frequencies of completion among the older cohort occur at 17 and 18, while they are concentrated at 17 for the younger cohort. The cumulative profiles show that by 19, 39 per cent of the women in cohort 2 had finished secondary education, compared to only 19 per cent of cohort 1. The observed difference remains unchanged thereafter. In other words, the proportion of women who completed secondary education has also doubled among the younger group.

The probability of completing secondary education is much more restricted at the lower income levels in both cohorts, in spite of the narrowing differences between them in cohort 2. Among cohort 1, only 1.7 per cent of the low-income women had completed secondary education at 17, while in cohort 2 the proportion increased to 10 per cent. In the medium-income groups, the proportion increased from 2.3 to 15 per cent. The percentage of women who had completed secondary education at 17 also increased - from 15 to 34 per cent - in the high-income group. The data indicate not only improved access to secondary education but, even more important, a better rate of completing it.

The figures for female enrolment in higher education are much lower. Within the older group, the highest frequencies of women graduating from university occur at ages 22 and 24. In the case of cohort 2, this is at 22. Only 4.5 per cent of women in cohort I had finished university studies at 24. The proportion had increased to 7 per cent in the second cohort, a figure which may rise as some of the younger women were still university students at the time of the survey.

Looking at variation by income level within the two cohorts, none of the low-income women in the sample had graduated. Four women from this group in cohort 2 did enter university, but none had finished: they were either still studying at the time of the survey or had dropped out. Within the older cohort, the majority of high-income women graduated from university at 22, while women of the medium-income level did so two years later at 24. In cohort 2, the same difference between the income groups in age at graduation is maintained, but graduation rates increased. Most women graduates come from the higher-income strata. Comparing educational levels by gender suggested the greater socioeconomic vulnerability of households which were headed by women. Six-and-a-half per cent of these women were illiterate, compared to only 1.9 per cent of male heads of households. Logically, this unfortunate disparity continued as educational levels rose: 30 per cent of female heads of households had completed secondary schooling, compared to 35.4 per cent of the men, and the proportion of women in this position with a university education (8.8 per cent) was only about half that of men (16.3 per cent).

Fig. 4. Age at first marital union by cohort


Figure 4 indicates that women in first cohort married younger than those in cohort 2, although both frequency curves exhibit a similar shape. Two peaks are observed in cohort 1, at ages 19 and 21; within cohort 2, most married in their early twenties.

Within the older group, patterns vary according to income levels (fig. 5). A higher proportion of the women in the medium- and low-income groups married younger (before 19) than those in the higher-income stratum, with a fairly constant difference of about five percentage points. The highest frequency of marriage occurs at 19 among women of medium- and low-income groups, but at 27 for the high-income group. A second but lower peak is observed at 21 for low-income women, at 23 for medium-income women, and at 21 for those in the high-income group.

Fig. 5. Cohort 1: Age at first marital union by income group

Fig. 6. Cohort 2: Age at first marital union by income group

Analysing income groups within cohort 2 shows that a relatively higher percentage of low-income women marry before 21, as do a lesser proportion of the medium-income group The lowest incidence of marriage before age 21 is among the high-income group (fig. 6). The highest frequencies of first marriage occur at 21, 23, and 24 for the low-, medium-, and high-income groups respectively. The pattern in figure 6 reveals a clear decline from the older to the younger cohort in the proportion of women married at similar ages. Most (approximately 85 per cent) of the older cohort were already married at 30, compared to 64 per cent of the women in cohort 2. This lower nuptiality rate among the younger women appears to contradict the slight increase observed in the census data.

Contraception and Fertility

The women were asked about the age they began using contraception and their pattern of subsequent usage. The frequencies of first usage in both cohorts are shown in figure 7. Contraception was initiated earlier in the younger cohort. It is also clear from the data that, at least tip to 26, the younger women were much more likely to practice family planning, with a particularly rapid comparative increase in usage between 16 and 20. The peak frequencies are at 22 for the younger cohort and at 27 and 30 for cohort 1.

Figure 8 illustrates the proportions of women in cohorts and 2 practicing family planning at each age. Again, the higher proportion of younger women using contraceptive methods is evident: at 31, the last age at which the cohorts can be validly compared, about 45 per cent of the older cohort were practicing contraception, compared to 64 per cent of the younger group.

The difference in usage between income groups within cohort 1 can be observed in figure 9. It is minimal up to 30 years of age. Subsequently, the highest frequency in the low-income group occurs at age 33, while the peak occurs at 40 for both the medium- and high-income groups. Within the younger cohort, figure 10 shows that the use of contraceptives is highest in the low-income group, followed by the medium- and then the high-income group. For example, at age 22, 58 per cent of the low-income women were using contraceptives, compared to 28 and 20 per cent in the middle- and high-income segments respectively. The corresponding figures for the older cohort were considerably lower- 13 and 11 per cent. Wide access to family-planning programmes is reflected in the fact that there are no particular differences between the income strata apparent within cohort 1, and the lowest income group in the younger cohort includes the highest proportion of women using contraceptives at 29 or younger.

Fig. 7. Age at first use of contraceptive method

Fig. 8. Use of contraceptive methods at each age

Fig. 9. Cohort 1 Use of contraceptive methods at each age by income group

Fig. 10. Cohort 2: Use of contraceptive methods at each age by income group

Figures 11 to 20 show the frequencies of events related pregnancy according to age cohort and income level. Figure 11 depicts the distribution of women by age at the end of first pregnancy, showing the proportion of the total number of women in the respective cohorts becoming pregnant for the first time at each age. It should be remembered that in the younger cohort all first pregnancies may not necessarily have occurred by age 29. No clear differences between the cohorts are apparent in the shape of the frequency curve, although the curve for the younger cohort is usually below that of the older cohort.

This becomes clearer in figure 12, which gives the cumulated frequencies by cohort and shows that, from the age of 15, the proportion of first pregnancies occurring is lower among the younger women, with a difference between the cohorts which increases with age. Only about 64 per cent of the younger cohort had been pregnant by the time they were 29, compared to approximately 79 per cent of the older cohort.

A different pattern appears when differentiating by income level (figs. 13 and 14). In cohort 1, the older group, approximately 3 per cent of the women in the lower-income group had completed their first pregnancy at 15, and, up to 19, they had experienced a higher accumulated proportion of pregnancy events than those in the other two income groups. Those in the higher income stratum postponed their first pregnancies still later than the others, with the highest frequencies occurring between 22 and 28.

Within the younger cohort, there is a much more marked difference between the income groups, as shown in figure 14. The pattern of the low-income group shows that their first pregnancies occur at significantly younger ages, while the opposite is observed in the high-income stratum. The latter reaches a peak frequency at 26, compared to 20 in the low-income group. The peak for the middle-income group is at 24. Although it is not shown in the figure, first pregnancies begin at 13 in the low-income group, but not till after 15 in the middle-income stratum.

Data on second pregnancies are presented in figures 15 to 17. Figure 15 shows a higher proportion of second pregnancies at lower ages among the older cohort. These differences within the cohort are less evident when disaggregated by income level, although in the younger cohort considerably more of the poorer women had second pregnancies at lower ages (figs. 16 and 17).

Figures 18 to 20 refer to the frequency of pregnancy by age and cohort, independent of the number of pregnancies for each woman. It can be seen in figure 18 that the frequency curve of the older cohort is much higher than of the younger cohort. For example, at 22 about 11 per cent of the younger women were pregnant, compared to about 25 per cent of the older cohort. A similar difference is observed at later ages.

Looking at pregnancy and income level in both cohorts figs. 19 and 20), it may be seen that a higher proportion of women in the lower-income group were pregnant at each age. The difference in frequency between the low- and the high-income groups is particularly striking between ages 19 and 25 in cohort 1 and between ages 18 and 20 in the younger cohort. In the high-income stratum of cohort 2, the peak frequency occurs at ages 21 and 25 (11 per cent of the in each case), compared to 27 (20 per cent of the stratum) in the middle-income group and 19 (21 per cent of the relevant sample) in the low-income group.

Fig. 11. Age at first pregnancy by cohort

Fig. 12. Age at first pregnancy by cohort

Fig. 13. Cohort 1: Age at first pregnancy

Fig. 14. Cohort 2: Age at first pregnancy

Fig. 15. Age at second pregnancy by cohort

Fig. 16. Cohort 1: Age at second pregnancy by income level

Fig. 17. Cohort 2: Age at second pregnancy by income level

Fig. 18 Women who were pregnant at each age

Fig. 19. Cohort 1: Women who were pregnant at each age

Fig. 20. Cohort 2: Women who were pregnant at each age


Women's working behaviour in urban Chile varies markedly according to socioeconomic background, age, education, and the process of family formation. The data give a clear picture of many aspects of the female workforce, and, of particular importance to the country's human resource development, it delineates many of the factors that influence women's participation in it. It shows that younger women now postpone entry into the labour force. The life-histories of both cohorts indicate that, on average, the older group started working five years earlier than the younger group; however, the labour-force participation of the latter increased from 21 years of age on, although, as their participation curve is censored by their youth, it is not possible to draw any conclusions about their working patterns after the age of 29. In the older cohort, participation rates started declining at 23. Analysis by income groups reveals higher workforce participation among low-income women up to approximately 30 in the older cohort. After 35, labour-force participation among the low- and medium-income groups within this cohort decreases, but the opposite trend characterizes the high-income group. Within cohort 2 there is no difference in working behaviour according to income level up to 20. From there on, the women who arc better off show a substantially higher rate of participation, as in the older cohort.

The differences described are the result of a number of factors, one of the most important being changes over time in education. A higher percentage of women in the younger cohort had completed primary education. The proportion of women who finished primary education in both cohorts increased as income rose.

The difference in the higher proportion of the younger women completing secondary education is even greater than it is for primary schooling. Moreover, the gap between the socio-economic groups in terms of secondary education is narrower within the younger cohort. Only a few of the older women from the medium- and low-income groups stayed in the educational system until they had completed secondary schooling. Finally, it is clear that higher income has been closely associated with access to higher education in both cohorts. None of the low-income women in the sample had completed university-level education.

The data support the hypothesis that women are postponing entry into employment while they acquire better educational qualifications. As a result of these higher attainments, they can expect better wages, which in turn encourages them to join the workforce.

Family formation is also an important factor in participation. By the age of 30 approximately 64 per cent of the women in the younger cohort had married, compared to 85 per cent of those in the older cohort, which indicates a lower rate of nuptiality within the younger group. Consistent with this, age at first marriage has been delayed by an average of three years in the younger cohort. This postponement is longer among the high-income women within the cohort, so that their peak age at marriage is 24, compared to 19 for the poorest group.

The cumulative frequency of women pregnant for the first time at each age shows that fertility is lower among the younger women who use contraceptive methods sooner and more extensively. At 29, almost 63 per cent of them were practising contraception, compared to 38 per cent of the older cohort at the same age. Pregnancy occurs earlier among the low-income group in both cohorts. The frequency of second pregnancy at each age is also lower for the younger cohort, at least until the cut-off age at 29. Within this cohort, the second pregnancy takes place much earlier in the low-income group, with a peak at ages 21-22, compared to 28 for the medium- and high-income groups. Comparing the proportion of women who were pregnant at each age, whether it was their first, second, or subsequent pregnancy, shows that the proportion of women pregnant at 29 or less is approximately 50 per cent lower in the younger cohort, particularly in the high-income group.

Other trends identified in the survey suggest that while the number of hours worked per month tended to decrease with age in the older cohort, the opposite was true in the younger group. Married women have lower labour-force participation rates than single women, and those who were employed were likely to work considerably fewer hours than their single counterparts.

The availability of domestic help or others to provide substitute child care allowed mothers in both cohorts to increase their number of hours in the workforce considerably. Other things being equal, increased family income (apart from women's earnings) led to a reduction in formal work in the older cohort, suggesting that, at higher income levels, women allocate more time to domestic duties or leisure. Family income did not seem to influence working decisions in the younger cohort. Head of household status appeared to limit women's work in cohort 1, another indication of the competing demands on women's time.

Data from employment surveys in Santiago have been showing changes in the age structure of the female workforce. The life-history approach of the present study has made it possible to link these trends to behavioural differences between age-groups that have been induced by various socio-demographic changes. Information provided by life-history methodology has allowed more precise identification of the sequence and relationships of events and their impact on the structural changes observed in female labour-force participation.

The distinction made in the analysis between income strata was extremely useful in understanding important differences and patterns within each age-cohort. In certain areas, such as education, marriage, and age at first pregnancy, the differences between income groups within the age-cohorts were more striking than those between the two cohorts.

It is clear that the policies to increase access to education and family planning introduced since the mid-1960s have borne fruit. The data show that younger women tend to have much more education, to delay marriage and childbearing, and to have lower fertility rates than their older counterparts. In fact, the changes observed in the family formation process are similar to those described in developed countries.

Thus, an indirect result of these policies has been to enhance the ability and desire of women to participate in formal economic activity, and future policies must take their economic needs, workforce potential, and personal aspirations into account.

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