Women S Labor Force Participation in Mexico During the 20Th Century: Childbearing and Career

Women’s Labor Force Participation in Mexico During the 20th Century: Childbearing and Career Decisions

Aurora Gómez-Galvarriato Professor at Department of Economics Centro de Investigación y Docencia Económicas A.C. Carretera México-Toluca 3655 Lomas de Santa Fe, 01210 México D.F., México e-mail: [email protected]

Lucía Madrigal* Assistant Researcher Inter-American Development Bank 1300 New York Av, NW, Washington DC, 20577 [email protected]

* This paper represents the opinions of the author and not those of the Inter-American Development Bank or their boards of directors. Women’s Labor Force Participation in Mexico During the 20th Century: Childbearing and Career Decisions

ABSTRACT

Using census data, and a cohort analysis we find a U-shaped behavior evolution of female labor force participation (LFP) in Mexico during the 20th century. Parental preferences for mixed siblings are used as an instrumental variable to estimate of the effect of childbearing on the female LFP. The results show that an additional child reduces women’s employment and that the impact increases over time. The rising on the female

LFP rates observed during the 20th century can be explained by a decrease in the number of children and an increase in average years of schooling per woman.

INTRODUCTION

Understanding the relationship between fertility and labor force decisions is a relevant issue in Mexico’s economic and social history. The massive incorporation of the female labor force during the 20th century is a demographic trend that demands to be examined. Some of the most important possible reasons behind this trend could be the decrease of children per woman, the increase in women’s average years of schooling, the

2 use of contraceptives, and the opening up of the economy in the 1990s. This paper will try to find historical and empirical evidence to explain women’s labor force decisions.

The female labor force participation (LFP) in Mexico is still very low compared with that in developed countries. Whereas in 2004 in the United States the female LFP was

46%, it was only 35% in Mexico.1 Nonetheless, LFP in Mexico has experienced a substantial increase in the last three decades, growing from 17% in 1970 to 35% in 2004.

Fertility rates have decreased; the average number of children per woman was 3.5 in 1970 and 2.2 in 2004. These rates are still higher than the average high-income country’s rate of

1.7 children per woman in the same year.2

Women’s LFP in Mexico did not increase secularly over the 20th century. On the contrary, data evidences a decline in the LFP of Mexican women until the 1970s, when the cohort of women born in the 1940s decided to have fewer children and to spend more time working outside their households. It is the purpose of this paper to explore the reasons behind these changes.

There is a wide literature explaining women’s labor participation decisions and their evolution through several models linking economic conditions (Namkee A. and Mira P.,

2002), education (Álvarez-Llorente, 2002), and use of contraceptives (Goldin, C., and Katz,

Lawrence, 2002) with the female labor supply. 3 Some link these decisions with family size and structure (Angrist and Evans, 1998).4 Until very recently we knew very little about

1 Data from GenderStats, database gender of statistics, http://devdata.worldbank.org/genderstats/ 2 Data from Madrigal, La evolución de la participación, and from GenderStats. 3 See Goldin, Understanding the Gender Gap, ‘The U-shaped Female Labor Force”, “The Rising (and then Declining)”, “From the Valley to the Summit”; Goldin and Kats, “The Power of the Pill”; Levine “The Impact of Social Policy”; Namkee and Mira, “A note on the Changing Relationship”; Psacharopoulos, and Tzannatos, “Female Labor Force Participation.” 4 See Angrist and Evans, “Children and their parent’s labor supply”; Becker,The Economics, A Treatise; Cheng and Nwachukwu, “The Relationship between Fertility”; Connelly, “The Effect of Child Care Costs”; Nakamura and Nakamura, “The Econometrics of Female”.

3 female LFP in Mexico. However, recent studies allow us now to form a broad picture of its evolution and the forces that have shaped it.5 This literature is complemented by several studies on the earnings gap between female and male workers in Mexico.6

The purpose of this paper is to explore the impact of fertility decisions on women’s employment and to understand the reasons behind the labor force participation and fertility changes during the 20th century. We follow two different approaches to the problem. First, we carry out a cohort analysis using census data from 1960 to 2000 in order to give a broad view of the nature of the problem. Then we carry out an econometric analysis of the relationship between female employment and childbearing testing the instrumental variable

(IV) used by Angrist and Evans (1998) in data from Mexico (1970-2000). This technique is useful to solve the endogeneity problem that emerges from the labor decisions and fertility’s unobserved causal factors, which means that women’s preferences to have or not have children can reflect unobserved characteristics about their employment activity. To accomplish this we exploit a source of exogenous variability in family size. The parental preferences for mixed-sex siblings are used to construct an IV estimate of the effect of childbearing on the female LFP. This econometric analysis will allow us to contribute valid evidence about the impact of fertility on employment in Mexico. This study uses household data from the 1970, 1990, and 2000 Mexican microdata census.7

This paper is organized as follows: Section I describes the evolution of female LFP in Mexico, using cohort analysis, and explores the relationship between development and the LFP trend in Mexico. Section II explains the data and sample, the instrumental variable

5 See Anderson and Dimon, “Married Women’s Labor Force”, “Formal Sector Job”; Cordourier and Gómez-Galvarriato, “La Evolución de la Participación Laboral”; Dell, Widenning the Border; Knaul and Parker “Employment and Child Care”; Madrigal, La Evolución de la Participación. 6 See García-Cuéllar, “The Gender Gap”, “Do Women and Men Benefits Equally”, Essays on the Effects of Trade; Meza, “Wage Inequality”; Pagan and Ullibarri, “Group Heterogeneity.” 7 IPUMS-International (Integrated Public Use Microdata Series), Data from 1980 is not available,.

4 validation and the methodology used in the econometric analysis and shows the results using the instrumental variables econometric technique, explaining the fertility changes and how they have shaped LFP in Mexico. Section III deals with the causes behind fertility changes such as the use of contraceptives and education to complement the econometric analysis. Finally, we conclude.

THE EVOLUTION OF THE LABOR FORCE PARTICIPATION OF WOMEN: A COHORT

ANALYSIS

Female LFP in Mexico during the 20th century can be studied by dividing census information into different cohorts according to the decade in which women were born. Each cohort experiences a different set of opportunities and constraints in terms of schooling, work experience, fertility decisions, and attitudes toward paid jobs. As a result, analyzing data through cohorts allows us to describe and examine the evolution of the labor market decisions of women in Mexico from those born circa 1900 to those born from 1981 to

1990.8 From the census data available it was impossible to build the evolution of the LFP of every cohort through their whole life cycle, since we only have the data of older age groups for the older cohorts and only of younger age groups for the youngest cohorts. Yet, important insights can be obtained from this analysis.

Figures 1 and 2 show the percentage of LFP of each cohort according to its age group. By contrasting the evolution of LFP of men and women during this period (see

Figures 1 and 2) we discern the great differences between them. As can be seen in Figure 1, the LFP of men remained almost constant over time, regardless of the different cohorts they

8 The cohorts that we use are “synthetic” because they connect data across various census years by the birth year of the individuals and are not constructed from longitudinal data. Data from Censos Generales de Población y Vivienda (Mexico).con

5 belonged to. We find the expected inverted U-shape in which LFP increases until the age of

50 and then decreases, a behavior directly related to the life cycle. Men’s employment in each cohort seems not to be affected by any external circumstance in any age group.

[INSERT FIGURE 1]

In contrast, there is no inverted U-shape in Figure 2. Women’s LFP did not

smoothly increase and then decrease as women aged even when we look at a single

cohort. Instead, the information suggests that the LFP rate in each cohort diminishes

when women are in their reproductive age. The LFP of women is influenced by

external variables such as marriage, education, and fertility.

[INSERT FIGURE 2]

Moreover, the data evidences that important changes in the labor behavior of the different cohorts took place during this period. The data shows a decrease in the LFP of women from the cohort born in 1901-10 to that born in 1921-30. Then we find a substantial increase in the LFP of each cohort from the generation born in 1941-50 on. This generation of women increasingly decided to work outside the home and began a transformation that would affect women and their families for decades to come.9 What were the forces behind this transformation?

When we rearrange data by putting the cohorts in the horizontal axis, generational changes in the LFP of women become more explicit (see Figure 3). The Figure 3 was constructed with the data available for women 50 years and older for each cohort, which was the age group for which more data was available.10 As we can see, there was a decrease

9 Claudia Goldin argues that a quiet revolution took place in the United States about 30 years ago. She found changes occurred from the late 1960s to the early 1970s and for cohorts born during the 1940s. See Goldin, 2From the Valley to the Summit.” 10 This Figure reports the percentage of female LFP for women in the same age group for each cohort.

6 of the LFP of women from the cohorts born in the 1900s to those born in the 1930s, then the LFP of women began to increase. A similar pattern can be observed in Figure 4, which shows a U-shaped relationship between LFP and time for the women 40 to 49 years old who were part of the labor force from 1960 to 2000. In contrast, in Figure 5 we can see that when looking at the male LFP at same ages no U-shape can be found.

[INSERT FIGURE 3]

[INSERT FIGURE 4]

[INSERT FIGURE 5]

The decrease and then increase in the LFP in Mexican women during the 20th century is similar to a pattern found by Claudia Goldin11 for U.S. women for the period

1890-1980 and in a cross-country database of more than 100 countries for 1985, when she looked at the relationship between female LFP and development (measured by per capita income). Goldin explained the U-shaped relationship between female LFP and development in the following terms.

The initial decline in the participation rate was due to the movement of production away from agriculture and the production of manufactures inside the household. As income increased due to the expansion of markets and the introduction of new technologies, the labor participation of women fell. Families implicitly bought the work of women who returned to their homes, even though their hours of work may not have changed. This process was in part the result of an income effect but was reinforced by the decrease in the relative price of the goods produced at home and by a decrease in the demand for female labor in agriculture and manufacturing. Even when the relative wages of females increased,

11 Goldin, “The U-shaped Female Labor Force.”

7 social factors such as social norms and stigma against the work of women, or the preferences of employers, might have deterred the growth in the participation of women in the labor market. 12 However, as the education of women increased, the value of their time in the market rose in relation to the price of goods, and they came back to form part of the labor force. At the same time, the social stigma might have diminished because women came back as white-collar workers.13 Goldin develops a model that formalizes this explanation.

Similar forces to those described above might explain part of the reason for the U- shaped evolution of the LFP of women in Mexico. Table 1 shows the shift between women’s occupations in agriculture and manufacturing activities to commerce and other related activities that require some level of education. Likewise, the data shows an increase in women’s participation in white-collar activities, such as teaching and clerical work.

Therefore, data suggests that some of the forces behind the U-shape of the LFP of women in Mexico could be similar to those explained by Goldin that relate female LFP with economic development.

[INSERT TABLE 1]

However, in Mexico the relationship between female LFP and income per capita during the 20th century is also found for the industrial sector itself, as shown by Cordourier and Gómez-Galvarriato14 (see Figure 6). This indicates that other reasons beyond sector changes must be behind the U-shaped relationship for Mexico. Cordourier and Gómez-

Galvarriato did an econometric analysis for the textile industry during the period 1925-1934

12 Goldin, “The U-shaped Female Labor Force,”pp. 1-2. 13 Goldin, “The U-shaped Female Labor Force,” pp. 5-6. 14 Cordourier and Gómez-Galvarriato, “La Evolución de la Participación Laboral.”

8 and for the manufacturing industry during the period 1987-1999. Their results show that female LFP in manufacturing in the declining part of the U could be in part the result of the passage from artisan to industrial manufacturing and greater unionization of the labor force, and that strong regional divergence in the LFP of women prevailed. The rising part of the U was related with a regional convergence in which those regions where fewer women worked outside their homes caught up with those regions where female LFP was previously higher. This took place increasingly as a result of the opening up of the economy from 1985 on and more intensively after the North American Free Trade Agreement (NAFTA) in

1994.

[INSERT FIGURE 6]

The regional differences decreased over time in terms of their effect on the decision of LFP of women. Likewise, married women who lived in rural areas increased their LFP during the same period. These results suggest the influence of trade liberalization on female employment opportunities. Moreover, convergence between regions implied a change in the conditions under which women worked.

García Cuellar (2001) explored the impact of free trade on the gender wage gap in

Mexico.15 She found that the opening of the economy produced by NAFTA decreased the wage gap between males and females. Low-skilled female LFP increased in intensive industries and reduced the gender gap in wages. Moreover, her study suggests that after

NAFTA, the gender gap decreased more in industries that had been noncompetitive before

NAFTA.

15 García-Cuéllar, “Do Women and Men Benefit Equally.”

9 In a similar direction, Melissa Dell (2005) found that NAFTA caused female LFP to increase in Mexico, but its influence was not uniform throughout trade-impacted regions.

Both studies strongly suggest that NAFTA created more and relatively higher-paying employment opportunities for Mexican women than would have been available in the absence of trade liberalization.

These studies give us a fair idea of the forces behind an increase in Mexican women’s LFP after NAFTA. However, most of the increase in the LFP of women took place before the economy was opened up to international trade in the 1970s. (See Table 2)

[INSERT TABLE 2]

FERTILITY AND LABOR FORCE PARTICIPATION: AN ECONOMETRIC ANALYSIS

One of the most salient transformations that took place in Mexico during the years when female LFP increased was a substantial reduction in fertility rates. The number of children a woman has affects her decision to work outside the home. As part of the paid labor force, women have to face the difficulty of combining maternity with their job outside the home. Therefore, the number of children a woman decides to have and when she decides to have them are key determinants in female LFP.

Many studies have examined the impact of fertility in the labor participation of women. Rachel Connelly (1992) analyzed the effect of child care costs on the probability that married women with children would participate in the labor market.16 She found that the presence of young children is always expected to increase the reservation wage,

16 Connelly, “The Effects of Child Care Costs.”

10 lowering the probability of participation.17 Knaul and Parker (1997) analyzed the interaction between child care strategies and women’s employment in Mexico.18 Their results suggest that the presence of one child reduces the probability of women working outside their home even part time. Nevertheless, the probability of working increases with the presence of someone who helps at home in child care.19

Figure 7 shows the average number of children per women arranged by cohorts. It tells that fertility increased from the cohort of women born circa 1900 to that born in the

1930s, which had the highest average of children per women. The transformation took place with the cohort of women born between 1941 and 1950. Thereafter, fertility rates constantly diminished through the different cohorts. The largest decrease in fertility rates took place during the 1970s, when the women born in the 1940s were at their fertility age, as we can see in Figure 7.

[INSERT FIGURE 7]

Figure 8 shows the changes in the global rate of fertility (GRF). It shows that the inflexion point in GRF took place in 1965-1970; thereafter, it radically decreased, from a

GRF of 6.70 in 1966-1970 to one of 2.57 in 1996-2000. 20 This decline in fertility took place both in urban and rural areas of Mexico. From 1974 to 1996 the average number of children women had in rural areas declined from 7.4 to 3.5, while in urban areas it declined from 5 to 2.3. 21 At the same time Mexico’s rural population declined from 41.3% of the

17 Connelly, “The Effects of Child Care Costs.”

18 Knaul and Parker, “Employment and Child Care.” 19 Knaul and Parker, “Employment and Child Care.”

20 The global rate of fertility is the average number of children a woman of a synthetic cohort would have if during her fertile period (15 to 45 years) she had children according to the fertility rates by age and if she did not risk mortality from her birth until the end of her fertile period. Formula: GRF = n  f (x, x  n). García and De Oliveria, Trabajo Femenino. 21 Censos de Población 1930-1970, INEGI Censos generales de población y vivienda, 1990-2000.

11 overall population in 1970 to 28.7% in 1990. This process was accompanied by a decrease in mortality rates.22

[INSERT FIGURE 8]

The pace of the decline in fertility rates corresponds exactly with the data presented on labor participation rates in Figure 2. Both show that a breaking point took place with the cohort born between 1941 and 1950. These women decreased the number of children they bore and increased their labor participation. The cohorts born later increasingly did so.

Thus, fertility decisions appear to be completely interwoven with LFP decisions. The problem that arises is whether fertility decisions determine LFP or the other way around.

Data and Sample

The analysis in this section of the paper is based on the Integrated Public Use

Micro-data Series International (IPUMS), and it focuses specifically on information from

Mexico. This database is based on census data. The webpage of this project

(http://international.ipums.org/international/) allows access to census samples and to the original surveys.23

To analyze women’s employment behavior we construct a sample that represents

1% of the total population each year available and is representative at the state level. The information in the IPUMS is per household, which allows for identifying individuals and families.

This analysis focuses on married women from 12 to 49 years old. These women are either in civil and/or religious marriages, they have a family and a husband. We assume that

22 INEGI, Las mujeres. The mortality rate of children was 72% in rural areas and 51% in urban ones from 1975 to 1979. In 1990-1994 the rate was 40.2% in rural areas and 28% in urban zones. Source: Encuesta Nacional de la Dinámica Demográfica. INEGI. 23 The database version 1.1 was downloaded on January 2002.

12 they receive financial support from their husband. This analysis will allow us to disentangle the factors behind women’s labor and childbearing.24

The sample was restricted to the number of children alive matched with the number of children women reported to live in their home, in order to avoid mistakes. Then, the sex of the first and second birth in the household were identified; dummy variables were used to indicate if both children had a similar sex, and if they were female or male in each birth.25

Statistical Analysis and Instrumental Variable

The statistical analysis shows that the fertility rate decrease. In 1970, 72% of married women had two children or more and in 2000, 67% had two or more. From these women, in 1970 81% had a third child, in 1990 70.5% and in 2000 63.4%. For each year studied, 50% of the households had two children of the same sex, and more than 51% of the first births were boys.

To find evidence that the instrumental variable was appropriate for Mexico, we tested if there was a relationship between the sex of the first child and that of the subsequent children. We analyzed the fraction of women who had a second child conditional to the sex of the first and checked the relationship between the sex of the first and second birth and the probability of having a third child. We considered the fraction of women with two children who had a third child conditionally to the sex of the first two children.

24 The married women sample allows to capture an specific behavior due to its characteristics. 25 The information about how many marriages a woman had and when they happened is not available in the IPUMS sample.

13 The data showed that women had a second child whether or not the first child was a girl or boy; therefore, we did not find evidence that the second birth was a function of the sex of the first one. This is probably explained by the fact that women in Mexico tend to have large families. Women in the sample with two children of the same sex were more likely to have a third child than women with mixed-sex children. Therefore, we can assume a relationship between the sex of the first and second child with the decision to have a third child, but this relationship does not hold with just one birth, and therefore the instrumental variable will capture the fertility effect.26

The previous statistical analysis showed evidence that the proposed instrumental variable will work in Mexican data. Women’s decision to have an additional child is correlated with the sex of the first two children.

Methodology

Research on the labor supply consequences of childbearing is complicated by the endogeneity of fertility. The debate regarding the causal interpretation of associations between fertility and labor supply stems mostly from the fact that there are strong theoretical reasons to believe that fertility and labor supply are jointly determined.

This paper calculates the effect of fertility on the labor supply in families with two or more children by exploiting a source of exogenous variability in family size first introduced by Angrist and Evans (1998).27 This method uses an instrumental variable strategy based on the sibling sex mix in families with two or more children. This instrument exploits the widely observed fact of parental preferences for a mixed-sex sibling

26 Coefficient tests were applied and the differences are significant. 27 Angrist and Evans, “Children and their parent’s labor supply.”

14 composition. Parents of same-sex siblings are substantially more likely to go on to have an additional child. Because sex mix is randomly assigned, a dummy variable for whether the sex of the second child matches the sex of the first child provides a credible instrument for further childbearing among women with at least two children.

The endogeneity problem emerges when some regressors are correlated with the error term, and in this case the ordinary least squares (OLS) estimators are biased. Using instrumental variables allows solving this problem, and producing efficient and consistent estimators. The instrumental variable in this paper will be same sex to capture the effect of fertility, since it is not correlated with the employment decision. The dependent variable will be employment.28

The method used in this paper is two-stage least squares (2SLS). Angrist (2001) points out that the problem of causal inference with limited dependent variables is not fundamentally different from causal inference with continuous outcomes. If there are no regressors, or they are sparse and discrete, linear models like 2SLS are no less appropriate for LDV than for other types of dependent variables. Therefore, 2SLS gives similar outcomes as the nonlinear methods even if the constant effects assumption is not real.

Angrist argued that using the 2SLS conventional method can yield unbiased coefficients, even if the assumptions are not correct in the first stage.

According to Angrist and Evans (1998), the 2SLS accomplishes three objectives.

First, even of there is no association between the instrument and exogenous regressors, controlling for them can lead to more accurate outcomes. Second, 2SLS can be used to capture the effect for any secular additive effects of a child’s sex when using same sex as

28 The variable description is in the Appendix.

15 instrument. The instrumental variable is an interactive term involving the sex of the first two children and therefore correlated with the sex of either child. Assuming that a child’s sex is independent and identically distributed and the probability of giving birth to a male child is 0.5, there is a slight positive association between same sex and the sex of each child. A third advantage is that 2SLS allows to exploit the fact that same sex can be decomposed into two instruments, two boys and two girls in order to get more specific information.

The following regression models are used to link labor supply variables to the endogenous more than two (children), Xi variable.

Yi = α’o wi + α1s1i + α2s2i + βxi + εi (1)

Where:

wi is a vector of demographic variables.

xi is more than two.

s1i and s2i are indicators for the sex of the first two children of the mother i.

Initially, wi is limited to variables that are clearly exogenous to fertility such as a mother’s age and socioeconomic indicators.

The first-stage equation relating more than two children to sex mix is:

Xi = π’owi + π1s1i + π2s2i + γ(same sexi) + ηi (2)

Where:

γ is the first-stage effect of the instrument.

16 We also used the two components of same sex (two boys and two girls) as instruments for more than two children, and s2i was dropped to avoid collinearity.

Yi = α’o wi + α1s1i + βiXi + εi (3)

The first-stage relationship between Xi and sex mix is:

Xi = π’owi + π1s1i + γ0(Two boysi) + γ1(Two girlsi) + ηi (7)

Where:

Two boysi = s1is2i and Two girlsi = (1-s1i)(1-s2i)

We used a Hausman test to find evidence about the endogeneity of the more than two variable (fertility). To test which of the instruments explains more about more than two, we ran two sets for each year, one with same sex and other with two boys and two girls (not shown). And we found that by using the decomposed instrumental variable, more information can be found about the sex-mix preferences of women, such as, that if they had two girls they would be more likely to have an additional child than if they had two boys.

Once we proved that the instrumental variable worked to capture the effect of fertility, we ran a least squares estimator including the effect obtained in the first stage to find a relationship between labor force participation and fertility (more than two).

Additionally, we ran a Sargan test of overidentifying restrictions for a regression estimated via instrumental variables and the result was equal to cero. This outcome means that the equation is exactly identified and therefore shows that the instruments are not correlated with the error term (shown in Table 3).

Econometric Results

17 This section shows the regression results that allow us to analyze the increase in the labor force participation during 1970-2000. We examine women’s and household’s characteristics in the sample using the instrumental variable (same sex) proposed by Angrist and Evans (1998) to explore the reasons behind women’s labor decisions. A list of the variables used in these estimations is in the Appendix.

The econometric results of this study prove that there is a strong relation between fertility and LFP and that the causality goes in that direction. The results show that a third child reduces female LFP and that this effect was larger in 2000 than in 1970. At the same time, the female LFP of married women increased due to a decrease in the number of children per woman and to a substantial increase in the average years of schooling (see

Table 3).

[INSERT TABLE 3]

Table 3 reports two sets of two-stage least squares (2SLS) estimates using same sex as instrument. The first two columns show results for 1970, the next two for 1990, and, the last two for 2000. The difference between models (1) and (2) are geographical indicators.

That coefficients do not change in the two models indicates that instruments are orthogonal to the additional controls. This result validates the strategy of using linear models to identify the parameter of interest.

These estimates show that having a third child caused a 4.1% reduction in the women’s labor supply in 1970. The labor supply effects estimated using the 1990 data suggest a reduction of 10.8% in the women’s labor force. The result that seems noteworthy is the larger negative impact of childbearing on married women’s labor supply in 2000, of

12.5%.29 This outcome shows that the effect of fertility decisions on LFP is substantial. The

29 Data was not available for 1980.

18 increasing negative impact means that childbearing requires more time and resources over time, which indicates that the opportunity cost of having a third child is larger in 2000 than in 1970. Women have more years of schooling and the possibility of having a career, which makes it pricey for women stay at home.

These conclusions do not disagree with the fact that female LFP increased over the last 35 years; the extraordinary raise of LFP can be explained by the change in women’s fertility decisions. In Mexico between 1970 and 2000, the number of women who had more than two children diminished by 20%. As shown before, the fertility rate descended dramatically from 1970 to 2000.

In order to show the regional differences in the labor decisions of women, we divided Mexico’s data into four regions based on their export performance and geographic market conditions. The border states were separated from the rest of the country, since their cities have peculiarities determined by their proximity to the United States (region 1). The central region is characterized by larger cities and the centralization of resources and foreign direct investment (region 2). Region 3 includes the northern cities that are not on the border or in the center of the country. The south is a very similar region characterized by greater poverty and a less export-oriented economy. Moreover, this regionalization allows us to observe the effect of NAFTA because it considers trade openness.30 The omitted variable (comparison) in the estimation was region 2 (D.F., Jalisco and Mexico

City). The results show that in region 1 (border), women participated less than women who lived in region 2, but the effect was diminishing. In general, these results show that the

30 These regions are similar to those found in García-Cuéllar, “Do Women and Men Benefits Equally”, who divided the country by export performance of the states and similar to those found in Cordourier and Gómez, “La Evolución de la Participación Laboral.”

19 female labor supply in the different regions had a tendency to converge. A list of the states in each region is in the Appendix.

As can be seen, Mexican regions tended to converge from 1970 to 2000 in terms of the LFP of married women. The regional differences had less of an effect as time went by.

Likewise, married women who lived in rural areas increased their LFP during the same period. These results suggest the influence of trade liberalization on female employment opportunities. Moreover, convergence between regions implied a change in the conditions under which women worked.

The variable indicating if women lived in urban areas was negative for 1970; living in urban areas reduced the labor supply 1.6%. This result indicates that urban married women with more than two children were less likely to have a paid job outside the home than rural women. This could be explained by a social stigma that went against married women working outside the home. This changed between 1970 and 1990. For the 1990 and

2000 data, the urban variable became positive, by 27% and 38% respectively, which means that women living in urban areas were increasingly more likely to work outside the home.

It is generally argued that urban areas encouraged smaller families because of greater density, scarcer and more expensive housing, fewer child labor opportunities, better wage labor opportunities for women, improved enforcement of child labor laws, and compulsory education statutes. Child costs thus are thought to be higher in urban areas, as also might be the rewards to greater investment in human capital. Related to this are the views of Gary Becker that parents choose fewer children and more “quality” per child over time because of the decline in the implicit price of child “quality”. 31 This reduced price of

31 Becker, A Treatise.

20 child quality has been caused by increased returns to human capital in the path of economic growth.32

In rural areas, there are good opportunities for children to work; male wages are relatively high, encouraging early marriage. Differential net emigration of young adult males biased sex ratios in favor of earlier marriages. Higher child mortality tended to shorten birth intervals. All this combined favors higher marital fertility.

The effect of a mother’s age is positive for all the years studied. It shows that as women grew older the probability of working outside the home increased, which means that when children grew older women increased their chances to be part of the labor force.

Notwithstanding that the sample of this study is restricted to women with two or more children, the results are likely to be of general interest because a significant fraction of the change in fertility between 1970 and 1990 was due to a reduction in the 3-2 number- of-children range. These results show a set of variables that can be used in the study of female LFP. In the next section, we will analyze some of them. The results from the regressions are very robust. The sign and magnitude of the coefficients do not vary much from one specification to the other. Most of the coefficients are significant well beyond the

1% confidence level.

EXPLAINING THE DECREASE IN FERTILITY

An important reason behind the strong decrease in fertility rates was a radical change in government policy. As in other parts of the world, the birth control pill appeared in Mexico in 1960. However, the use of this contraceptive was not socially accepted for several years after its emergence. It was not until 1974, when the government drastically

32 Becker, A Treatise, chap. 5.

21 changed its policy on the issue and carried out a wide campaign to support population control, which women began to accept birth control methods as a way to provide well- being for their families. In 1974, the new general Law of Population came into effect. It was a modern, humanist, and respectful demographic policy that allowed couples to determine, freely and responsibly, their descendants.33 The use of birth control allows women to take control of their lives; it lowers the costs to young, unmarried women to pursue a career, particularly those involving substantial up-front investments of time. In addition, the use of contraceptives eliminates one potent reason for early marriage, and in that sense, allows women to make their own decisions about LFP and fertility. Goldin and

Katz in their study of the power of the pill pointed out that “the pill may have enabled more women to opt for careers by indirectly lowering the cost of career investment.” 34

The use of contraceptives constantly increased in Mexico from 1976 to 1997, as we can see in Table 4.35 The cohort of women born during the 1940s were between 25 and 34 years old in 1976. As Table 4 shows, around 38% of the women in this cohort used contraceptives, and they were the age group that more extensively used them. From the information available it is clear that the change in government policy in 1974 had an important effect on the reduction of fertility rates and on the concomitant increase in the labor participation of women in Mexico.

[INSERT TABLE 4]

Women reduced their fertility not only through contraceptives but also by delaying their first marriage or unmarried union. Unfortunately, we do not have data prior to the

33 Secretaría de la Presidencia, (1974). Seis informes de Gobierno: Luis Echeverría Álvarez, Crecimiento demográfico, 1 sept. 1974. México, 1974. 34 Goldin and Katz, “The Power of the Pill,” p. 731. 35 Data from CONAPO. The information presented is the most recent available.

22 cohort born in 1953-1957, but from the data available we can see that there is a substantial reduction in the percentage of women married before the age of 16 and an increase in the women who remained single until the age of 25, from the cohort born in the 1950s to that born in the late 1960s and the early 1970s (see Table 5).

[INSERT TABLE 5]

By 2003 the number of children born to women aged 15-19 remained substantially higher than in developed countries (see Table 6), but lower than in many Latin American countries, even lower than in those countries, such as Brazil or Costa Rica, where the use of contraceptives was more extensive.

[INSERT TABLE 6]

An important increase in schooling was another relevant change experienced by

Mexican women during the second half of the 20th century (see Table 7). At the same time, the education gap narrowed between males and females (see Table 8). The age group of 20-

29 went from an average of 2.62 years of schooling in 1960 to 6.44 in 2000. Yet it remains very low, indicating that on average in 2000 women had barely finished elementary school, a figure very similar to that for men.

[INSERT TABLE 7]

[INSERT TABLE 8]

The LFP of women is affected by their years of schooling in several ways. In the first place, the more education a woman has, the more income she receives per hour worked and the more expensive becomes the decision to not work outside the home. More years of schooling increase her opportunity cost of not working outside the home. Higher education

23 levels allowed more women to work in clerical and other white-collar jobs (see Table 1).

This must have diminished the social stigma against woman working outside the home in a process similar to that described by Goldin (1994).36 However, in Mexico there has also been a substantial increase in the LFP of women with very low schooling rates working in the manufacturing-export sector after the opening up of the economy.37

In the second place, education has an important influence on LFP by affecting fertility decisions, particularly by the diffusion of values and knowledge of family control practices. The data analyzed shows that the more educated a woman is the more likely she will use contraceptives and the later she will marry or have an unmarried partner (see

Tables 4 and 9). Psacharopoulus and Tzannatos (1989) stated that education exercises a positive effect on the decision to work.38 They said that “if education has been undertaken as an investment, a woman has to work to recoup the cost of that investment in human capital.”39 The authors point out that even if education was undertaken as a form of consumption, women would enter the labor market because their opportunity cost of not working increases. They also explain that since, in theory, education has a positive effect on female LFP and a negative effect on fertility, and if greater participation of women in the labor force is a desirable goal, education for women may be the main policy option.40

[INSERT TABLE 9]

The results show that the female LFP increase might be explained by a decrease in the number of children per woman and a substantial increase in the average years of

36 Goldin, “The U-Shaped Female Labor Force.” 37 García-Cuéllar, “Do Women and Men Benefits Equally”; Cordourier and Gómez-Galvarriato, “La Evolución de la Participación Laboral”; Dell, Widenning the Border. 38 Psacharopoulos and Tzannatos, “Female Labor Force Participation.” 39 Psacharopoulos and Tzannatos, “Female Labor Force Participation,” p. 196. 40 Psacharopoulos and Tzannatos, “Female Labor Force Participation,” p. 196-8.

24 schooling. The population laws of 1974, the use of contraceptives, and delaying marriage were reasons to understanding this phenomenon.

CONCLUSIONS

In this study we found some important reasons for women’s labor participation and fertility decisions in Mexico during the 20th century. In Section I we analyzed census data by cohorts, discovering different attitudes toward jobs and fertility between generations of women. In this part we found that there has been a U-shaped trend in the female’s LFP over time in Mexico. The LFP of Mexican women declined until 1970, when it started to rise.

During most of the 20th century Mexico experienced a decline in the LFP. This was a consequence of several forces that are yet to be explored. However, it seems it was partly caused by the decline in the percentage of population devoted to agriculture and to the passage from handmade to industrial manufacturing. Moreover, it seems that it was reinforced by unionization and the presence of social stigma against women working outside their homes, which was imbedded more strongly in some regions of the country than in others.

In Section II we carried out an econometric analysis with IPUMS data, and the outcomes showed the effect of fertility on labor force participation using an instrumental variable that avoids the bias generated by the variable fertility. It is important to consider the sample characteristics of married women used in this study; therefore not every conclusion can be applied to each woman in the period studied.

25 Through the results, we can establish that fertility has a negative effect on the labor force participation and increases in absolute values during 1970 to 2000. There is evidence that shows that the childbearing effect has not changed in terms women’s time and resources spent. That the female labor force participation has increased can be explained by the fact that the number of children per woman has decreased considerably and the average years of schooling has increased during the same period.

It was the generation of women born in the 1940s that started the change in the role of women in Mexico’s society that we now see at the beginning of the 21st century. These women were more educated than their mothers and grandmothers and were given the opportunity to use birth control methods by a change in government policy in 1974 that promoted the use of contraceptives. These women eagerly used them and were the first generation that chose to have fewer children than their mothers, a trend that would continue in the generations to come. All this meant that more of them decided to work outside the home than their mothers did, something that the generations to follow would increasingly do.

Then, the opening up of the economy came, which produced many jobs that required high manual abilities and low education. This generated many job opportunities for women in the export-manufacturing sector and changed the mores in some regions that had previously very deep social stigmas against women (especially married women) working outside home. Thus, Mexico experienced a regional convergence as some regions with previous very low levels of LFP caught up. It seems that the forces behind the increase in the female LFP will continue in the following decades, so the rising trend that we describe in this essay could be only the beginning of a larger process.

26 The evolution of female LFP in Mexico is just starting to be explored. There is much more that we do not know than we know. More and better studies will be necessary for us to have a better idea of the forces that have changed and keep changing the role of women in Mexico’s society.

REFERENCES

Anderson, Joan, and Denise Dimon. “Married Women’s labor force participation in developing countries: the case of Mexico.” Estudios Económicos 13, no.1 (1998): 3-34.

______, “Formal sector job growth and women’s labor sector participation: the case of Mexico.” Quarterly Review of Economics and Finance 39, no 2 (1999): 169-91. Angrist, Joshua D., and William N. Evans. “Children and their parents’ labor supply: Evidence from exogenous variation in family size.” American Economic Review 88, no.3 (1998): 450-77. Becker, Gary. The Economics of Discrimination. Chicago: University of Chicago Press, 1957. ______. A Treatise on the Family. Cambridge: Enlarged, 1991. Cheng, Benjamin, and Savior Nwachukwu. “The Relationship between Fertility and Female Labor Force Participation: A Comparison of White-Black Causal Patterns.” Pennsylvania Economic Review 10, no. 2 (2001): 19-28. Consejo Nacional de Población (CONAPO). Indicadores de salud reproductiva de la República Mexicana. Available online at http://www.conapo.gob.mx Connelly, Rachel. “The effect of child care costs on married Women’s labor force participation.” The Review of Economics and Statistics 74, no. 1 (1992): 83-9. Cordourier, Gabriela, and Aurora Gómez-Galvarriato. “La evolución de la participación laboral de las mujeres en la industria en México: una visión de largo plazo.” Economía Mexicana 3, no. 1 (2004): 63-104. Dell, Melissa. Widening the Border: The impact of NAFTA on Female Labor Force Participation in Mexico. Unpublished B.A. dissertation, Harvard University. Cambridge, MA: 2005. Integrated Public Use Micro-data Series International (IPUMS), version 1.1. Available online at http://international.ipums.org/international/

Knaul, Felicia, and Susan Parker. “Employment and child care strategies among Mexican women with young children.” CIDE Working Paper DTE 75, Mexico, October 1997. García, Brígida, and Orlandina de Oliveira. Trabajo femenino y vida familiar en México. Mexico: El Colegio de México, 1994. García-Cuéllar, M. Regina. “The gender gap and modernization of labor markets: the case of Mexico.” In Essays on the effect of trade and location on the gender-gap: a study of

27 the Mexican labor market. Unpublished doctoral dissertation, Harvard University. Cambridge, MA: 2001. ______. “Do women and men benefit equally from living in urban areas? Gender differential urban premium in Mexico.” In Essays on the effect of trade and location on the gender-gap: a study of the Mexican labor market. Unpublished doctoral dissertation, Harvard University. Cambridge, MA: 2001. ______. “Is Trade Good for Women: Evidence for the Lower-Skilled in Pre- and Post- NAFTA Mexico.” In Essays on the effects of trade and location on the gender gap: a study of the Mexican labor market. Unpublished doctoral dissertation, Harvard University. Cambridge, MA: 2001. Goldin, Claudia. Understanding the gender gap: an economic history of American women. New York: Oxford University Press, 1990. ______. “The U-shaped female labor force function in economic development and economic history.” NBER Working Paper w4707, Cambridge, MA, April 1994. ______. “The rising (and then declining) significance of gender.” NBER Working Paper w8915, Cambridge, MA, April 2002. ______, “From the valley to the summit: The quiet revolution that transformed women’s work.” NBER Working Paper w10335, Cambridge, MA, March 2004. Goldin, Claudia, and Lawrence Katz. “The power of the Pill: oral contraceptives and women’s career and marriage decisions.” Journal of Political Economy 110, no. 4 (2002): 730-77. INEGI. Las Mujeres en el México Rural. Mexico: INEGI, 2002. ______. Resumen del Censo General de Población y Vivienda, México, 1900–2000. Mexico: INEGI, 2000. ______. Encuesta Nacional de la Dinámica Demográfica (ENADID). Mexico: INEGI, 1992 and 1997. Levine, Phillip. “The impact of social policy and economic activity throughout the fertility decision tree.” NBER Working Paper w9021, Cambridge, MA, June 2002. Madrigal, Lucía. La evolución de la participación laboral de la mujer en México 1970- 2000: el efecto del tamaño de la familia. Unpublished B.A. dissertation, CIDE. Mexico: 2004 Mexico, Secretaría de la Presidencia. Seis informes de Gobierno: Luis Echeverría Álvarez, Crecimiento demográfico, 1st Sept. 1974. Mexico: Secretaría de la Presidencia, 1974. Meza González, Liliana. “Wage inequality and the gender wage gap in Mexico.” Economía Mexicana X, no.2 (2001): 290-323. Nakamura, A., and M. Nakamura. “The econometrics of female labor supply and children.” Econometric Review 11. no. 1 (1992): 1-71 Namkee, Ahn, and Pedro Mira. “A note of the changing relationship between fertility and female employment rates in developed countries.” Journal of Population Economics 15, no. 4 (2002): 667-82. Pagan, José, and Miren Ullibarri. “Group heterogeneity and the Gender Earnings Gap in Mexico.” Economía Mexicana IX, no. 1 (2000): 23-40. Psacharopoulos, George, and Zafiris Tzannatos. “Female Labor Force Participation: An International Perspective.” The World Bank Research Observer 4, no. 2 (1989): 186- 201. Samuelson, Paul. “International Trade and the Equalization of Factor Prices.” The Economic Journal 58 (1948): 163-84.

28 The World Bank Group. GenderStats, Database Gender of Statistics, 2003. Available online at http://devdata.worldbank.org/genderstats/ United Nations Population Fund. State of World Population, 2003. Avilable online at http://www.unfpa.org/worldwide/ Zavala de Cosío, María Eugenia. Cambios de fecundidad en México y políticas de población. Mexico: El Colegio de México and FCE, 1992.

TABLES

29 Table 1: Distribution of Occupations, Women, 1960 - 2000 (Percentages). Year 1960 1970 1990 2000 Agriculture, Mining, Oil and Natural Gas 30.6 8.5 3.0 3.7 Manufacture 12.2 14.2 15.5 15.2 Commerce, Communications and Transports 49.3 42.0 50.3 52.4 Housekeeping Activities n.a 16.4 8.7 9.4 Clerical Jobs n.a 5.5 3.5 3.4 Liberal Professions 7.1 1.0 7.5 7.1 Teachers na 5.2 7.3 5.8 Other 0.8 7.2 4.2 3.1 Total (%) 100 100 100 100 Women in Labour Force 2,035,293 2,466,257 5,521,271 10,750,400 % of Total Labour Force 18.0 19.0 23.6 31.5

Source: INEGI, Censo General de Población y Vivienda (Mexico, 1960,1970,1980,1990, 2000)

Table 2: Labor Force Participation, Women, 1960 – 2000.

Age Year 1960 1970 1990 2000 12 - 19 11.84 16.61 12.28 16.44 20 - 29 17.32 22.16 28.80 37.40 30 - 39 16.75 16.72 25.95 39.77 40 - 49 21.31 16.76 20.79 37.39 50 - 59 25.58 15.81 13.90 26.17 60 and more 19.32 12.63 6.69 11.50 Average 18.69 16.78 18.07 28.11

Source: INEGI, Censo General de Población y Vivienda (Mexico, 1960,1970,1980,1990, 2000) Note: Data of 1980 was not included because is not reliable.

30 Table 3: Female Labor Force Participation Estimates, 1970 – 2000.

Dependent variable: Labour force participation. Sample: Married Women. Variable description in appendix 1. Estimation method: 2SLS. Instrumental Variable: Same Sex. 1970 1990 2000 (1) (2) (1) (2) (1) (2) more than 2 -0.041 -0.040 -0.108 -0.108 -0.125 -0.125 [0.018]** [0.018]** [0.018]*** [0.018]*** [0.018]*** [0.018]*** children 1 -0.012 -0.012 -0.014 -0.014 -0.018 -0.018 [0.004]*** [0.004]*** [0.003]*** [0.003]*** [0.003]*** [0.003]*** children 2 -0.007 -0.007 -0.003 -0.003 -0.006 -0.006 [0.006] [0.006] [0.004] [0.004] [0.004] [0.004] schooling 0.015 0.015 0.028 0.028 0.029 0.029 [0.001]*** [0.001]*** [0.001]*** [0.001]*** [0.001]*** [0.001]*** urban -0.015 -0.016 0.024 0.027 0.033 0.038 [0.006]*** [0.006]*** [0.005]*** [0.005]*** [0.004]*** [0.004]*** ownership 0.001 0.001 -0.008 -0.008 -0.004 -0.007 [0.004] [0.004] [0.004]** [0.004]** [0.004] [0.004]* mother age 0.003 0.003 0.008 0.008 0.01 0.01 [0.000]*** [0.000]*** [0.001]*** [0.001]*** [0.000]*** [0.000]*** electricity -0.007 -0.008 -0.015 -0.016 -0.024 -0.022 [0.006] [0.006] [0.006]** [0.006]** [0.007]*** [0.007]*** water -0.006 -0.007 0.003 0.006 0.006 0.011 [0.006] [0.006] [0.005] [0.005] [0.006] [0.006]** sewage -0.001 -0.003 0.021 0.021 0.006 0.011 [0.006] [0.006] [0.005]*** [0.005]*** [0.004]** [0.004]** toilett 0.008 0.008 -0.001 0.002 0.001 -0.001 [0.005] [0.005] [0.005] [0.005] [0.005] [0.005] zone 1 -0.033 -0.017 0.019 [0.006]*** [0.004]*** [0.005]*** zone 3 -0.021 0.001 0.015 [0.005]*** [0.004] [0.004]*** zone4 -0.006 0.031 0.056 [0.008] [0.006]*** [0.005]*** constant -0.039 -0.02 -0.245 -0.253 -0.28 -0.313 [0.010]*** [0.011]* [0.009]*** [0.009]*** [0.010]*** [0.010]*** observations 17999 17999 54041 54041 67381 67381 R-squared 0.04 0.04 0.12 0.12 0.13 0.13 Sargan 0.000 0.000 0.000 0.000 0.000 0.000 Schwarz criteria 3.13 3.13 3.30 3.30 3.33 3.33 31 Source: IPUMS, 1970, 1990, 2000, and Madrigal, ‘La Evolución de la Participación’. Standard errors in parenthesis. *signif. at 10% **signif. at 5% ***signif. at 15% Note: Sargan test (overidentification test of all instruments): -0.000

Table 4: Women use of contraceptives, by characteristics, 1976 – 1997.

Percentage of Women, Married or with an Unmarried Partner 1976 1987 1992 1997

Total 30.2 52.7 63.1 68.5 Age Groups 15-19 14.2 30.2 36.4 45.0 20-24 26.7 46.9 55.4 59.3 25-29 38.6 54.0 65.7 67.8 30-34 38.0 62.3 70.1 75.4 35-39 37.9 61.3 72.6 76.1 40-44 25.1 60.2 67.4 74.5 45-49 11.8 34.2 50.5 61.4 Num. of children born 0 6.5 15.3 20.7 23.9 1 27.2 50.5 56.6 59.8 2 39.1 60.0 71.0 75.4 3 38.4 67.5 75.0 80.6 4 and more 29.6 51.3 62.6 70.4 Schooling Without Schooling 12.8 23.7 38.2 48.0 Incomplete Elementary School 25.5 44.8 56.4 61.3 Complete Elementary School 40.3 62.0 66.7 69.8 Secondary School and more 55.8 69.9 73.6 74.8 Place of residence Rural 13.7 32.5 44.6 53.6 Urban 42.1 61.5 70.1 73.3 Speak native tongue Speak n.a. n.a. n.a. 48.3 Not Speak n.a. n.a. n.a. 70.2

Source: Consejo Nacional de Población and EMF, 1976, ENFES, 1987, ENADID, 1992, 1997.

Table 5: Women age at first marriage.

Percentage in 1997 Less than 16 Single at 25 Cohort years old 16-19 years old 20-24 years old years old

1953-1957 14.9 34.9 28.2 22.0 1958-1962 14.2 33.4 27.4 24.9 1963-1967 12.6 32.2 27.5 27.7 32 1968-1972 9.9 30.6 28.1 31.3

Source: Consejo Nacional de Población and ENADID, 1997.

Table 6: Reproductive Health Indicators.

Contraceptive Prevalence, World Comparative Charts, 2003 Contraceptive Prevalence Birth per 1,000 women Any method Modern methods aged 15-19

Mexico 64 67 58 Costa Rica 78 75 65 Guatemala 111 38 31 Brazil 73 77 70 Venezuela 95 49 38 United States 53 76 71 Canada 16 75 73 Japan 4 59 53 China 5 84 83 France 9 75 69 Switzerland 5 82 78

Source: United Nations Population Fund, State of World Population, Monitoring ICPD Goals: Selected Indicators, 2003

Table 7: Average years of Schooling.

Women Age 1960 1970 1980 1990 2000

10 - 19 2.03 3.33 4.45 5.57 5.90 20 - 29 2.62 3.00 4.21 5.42 6.44 30 - 39 1.81 2.43 3.34 4.26 5.53 40 - 49 1.81 1.83 2.44 3.05 4.37 Average 2.07 2.65 3.61 4.57 5.56

Source: INEGI, Censo General de Población y Vivienda (Mexico, 1960,1970,1980,1990, 2000)

33 Table 8: Average years of Schooling.

Men - Women Difference Age 1960 1970 1980 1990 2000

10 - 19 0.02 0.11 0.04 -0.04 -0.07 20 - 29 0.14 0.27 0.35 0.44 0.19 30 - 39 0.29 0.27 0.40 0.52 0.45 40 - 49 0.29 0.03 0.40 0.76 0.53 Average 0.18 0.17 0.30 0.42 0.28

Source: INEGI, Censo General de Población y Vivienda (Mexico, 1960,1970,1980,1990, 2000)

Table 9: Women age at first marriage, by schooling and place of residence.

Percentage in 1997 Less than 16 Single at 25 Characteristics 16-19 years old 20-24 years old years old years old

Schooling Total 11.1 31.4 27.8 29.7 Without Schooling 34.9 34.3 14.1 16.7 Incomplete Elementary School 25.6 40.5 17.4 16.6 Complete Elementary School 15.0 40.0 23.8 21.1 Secondary School and more 4.0 25.7 33.2 37.1

Place of residence Rural 20.2 38.9 22.0 18.9 Urban 8.7 29.3 29.4 32.6

Source: Consejo Nacional de Población and ENADID, 1997.

34 FIGURES

35 Figure 1: Male Labor Force Participation.

Before 1900 50

40 n o 1901-1910 i t a p

i c 1941-1950 i t 1911-1920 r a P

e 30 c r

o 1921- F 1930 r 1951-1960 u o 1971-1980

b a L 20 % 1931-1940

1981-1990 1961-1970 10

0 12 - 20 - 29 30 - 39 40 - 49 50 - 59 60 and more 19 Age Group

25 1901-1910 - 1 1911-1920 - 1921-1930 - 3 1931-1940 - 4 1941-1950 - 2 5 1951-1960 - 6 1961-19701961-1970 - 1971-1980 - 8 1981-1990 - 9 Before 1900 - 7 0 1971-1980 1951-1960 20 Source: Censos Generales de Población y Vivienda, 1960, 1970, 1980, 1990, 2000. INEGI

1941-1950

Before 1900

10 1981-1990

1901-1910 Figure 2: Female Labor Force Participation. 1931-1940 5 1911-1920

1921-1930

o 12 - 19 20 - 29 30 - 39 40 - 49 50 - 59 60 and more

F Age Group

i c 1981-1990 - 9 1971-1980 - 8 1961-1970 - 7 1951-1960 - 6 1941-1950 - 5

o n 1931-1940 - 4 1921-1930 - 3 1911-1920 - 2 1901-1910 - 1 Before 1900 - 0 36

Source: Censos Generales de Población y Vivienda, 1960, 1970, 1980, 1990, 2000. INEGI Figure 3: U-shape Female Labor Force Participation.

e 10

r c 5

0 before 1900 - 0 1901-1910 - 1 1911-1920 - 2 1921-1930 - 3 1931-1940 - 4 1941-1950 - 5 1951-1960 - 6 1961-1970 - 7

Cohorts 37 Source: Censos Generales de Población y Vivienda, 1960, 1970, 1980, 1990, 2000. INEGI Figure 4: Female Labor Force Participation, Women 40 to 49 years old.

r 10

n 5

1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Year

Source: Censos Generales de Población y Vivienda, 1960, 1970, 1980, 1990, 2000. INEGI

Figure 5: Male Labor Force Participation, Men 40 to 49 years old.

38 60

r 20

n 10

1955 1960 1965 1970 1975 1980 1985 1990 1995 2000

60% Year

Source: Censos Generales de Población y Vivienda, 1960, 1970, 1980, 1990, 2000. INEGI

50%

Figure 6: Labor Force Participation of Mexican Women in Manufacturing. 40%

30%

20%

10%

0% 1900 1930 1940 1960 1970 1980 1990 2000 Year

North West Center Pue-Tlx-Ver South TOTAL 39 Source: Cordourier and Gómez Galvarriato, ‘La Evolución de la Participación’, p. 67 Figure 7: Fertility.

1931-1940

Population Policies 6

1941-1950

f 3

c h 1961-1970

1971-1980

1981-1990

0 12 - 19 20 - 29 30 - 39 40 - 49 Age Group

Before 1911 - 0 1911 - 1920 - 1 1921-1930 - 2 1931-1940 - 3 1941-1950 - 4

1951-1960 - 5 1961-1970 - 6 1971-1980 - 7 1981-1990 - 8

Source: Censos Generales de Población y Vivienda, 1950, 1960, 1970, 1990, 2000. INEGI 40 Figure 8: Global Fertility Rate from 1895 to 2000.

19 7 0 s In f l e x i o n P o i n t

P o p u l a t i o n P o l i c i e s

Y e a r s

S o u r c e : F r o m 18 9 5 t o 19 0 0 : M i e r y T e r á n , 19 8 2 , f r o m 19 7 1 t o 19 8 0 , C e l a d e , f r o m 19 8 1 t o 2 0 0 0 , C o n s e j o N a c i o n a l d e P o b l a c i ó n .