Formal sector job growth and women’s labor sector participation

The Quarterly Review of Economics and Finance 39 (1999) 169 –191

Focus: International issues

Formal sector job growth and women’s labor sector participation The case of Mexico Joan B. Anderson, Denise Dimon* Department of Economics, School of Business Administration, University of San Diego, 5998 Alcala´ Park, San Diego, CA 92110, USA

Abstract This paper looks at the effects of demand and supply on the determinants of labor sector (school, home work, informal, and formal) participation between Torreon and Tijuana, Mexico for married and single women. Comparisons between the two cities are used to capture differences in labor demand. Torreon is a traditional city with an agri-industrial base and Tijuana is a border city with large export processing (maquiladora) and tourism sectors, both of which demand female labor. Factors influencing labor supply include both individual and household characteristics. Married women, given the strong cultural tradition of working in the home, do not significantly increase their paid labor participation with higher labor demand or changing characteristics of the household. Personal characteristics have the greatest impact on labor sector participation. Single women do, however, increase their formal sector participation with additional employment opportunities and respond to household needs by moving in and out of the paid labor market. Results indicate that increases in labor demand in Mexico from the NAFTA could expand formal sector labor force participation of single women. © 1999 Board of Trustees of the University of Illinois. All rights reserved.

1.

Introduction

The signing of the North American Free Trade Agreement (NAFTA) is but one more step in the trend toward globalization of production. This phenomenon of dividing production * Corresponding author. Tel.: ⫹1-619-260-4836; fax: ⫹1-619-260-4891. E-mail address: [email protected] 1062-9769/99/$ – see front matter © 1999 Board of Trustees of the University of Illinois. All rights reserved. PII: S 1 0 6 2 - 9 7 6 9 ( 9 9 ) 0 0 0 1 0 - 1

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processes between countries, the “global factory” as it has been called by Grunwald and Flamm (1985), minimizes costs by utilizing comparative advantages through separating production operations across international borders. By performing capital intensive processes in capital abundant countries and labor intensive processes in labor abundant countries, costs of production are reduced as long as transportation and communication costs are low. In Mexico, one form of globalized production has been the development of the maquiladoras, off-shore export processing plants. The maquiladora program was established in 1964 under the Border Industrialization Program (BIP) to encourage foreign investment into Mexico. Under the BIP there currently are approximately one million workers employed with many of these jobs being filled by women, especially young women. This paper investigates how women’s labor sector participation will be impacted as a country industrializes through globalization, creating more formal sector job opportunities. Specifically, much of this job creation in Mexico began initially through the maquiladoras, but after joining GATT and later NAFTA, the lower tariff and non-tariff barriers resulted in an increase in production sharing and export processing activity.1 This research empirically investigates the extent to which the resulting increase in demand for formal sector female labor would affect women’s work activity decisions. The paper addresses the following questions: With increased formal sector jobs, are women being drawn into the labor force who would otherwise have remained in traditional roles in the home or are they simply providing better job opportunities for women who would otherwise be working for lower pay and with less labor protection in the informal sector? Do personal and/or household characteristics make a difference in the extent to which demand from formal sector jobs, such as those in the maquiladoras, influences women’s work activity decisions? Stages of national economic growth suggest that participation rates for women tend to decrease with initial modernization and then begin to expand, over time, forming a “Ushape” pattern. As modernization initially contracts agricultural and traditional non-agricultural employment, men and women released from these jobs compete for the new jobs in the modern sectors. With women usually considered by employers as a less desirable group of workers, given cultural biases and the probability that women will leave jobs to raise children, the number of employment opportunities available to women is reduced which in turn discourages their labor market entry and lowers their rates of participation. Modernization is generally accompanied by growth of relatively more formal sector job opportunities which may be less compatible with the domestic responsibilities borne by women, thus reducing their rates of labor market participation. However, as development proceeds, the formal labor market sector expands, absorbing some of the excess supply of the male workers, and the demand for female workers begins to increase. Over time, with the increased probability of finding non-traditional, formal sector employment and the corresponding increase in wages, women increase their participation rates.2 The work of Mincer (1962) and Cain (1966) laid the foundation for studies of women’s labor force participation, which coincided with the growth of the entry of women into the paid labor market. This pioneering research generated significant literature, both theoretical and empirical, on the determinants of women’s labor force participation in the US. (For examples, see Cogan, 1975, 1978; Gronau, 1977; Heckman 1974, 1980; and Smith 1980.) In Latin America, women’s participation in the labor force increased more in the 1980s than in

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the 1970s, with rates averaging 25% in the early 1970s and increasing to 34% in 1990, perhaps demonstrating the increase in participation rates with expanding industrialization. Other factors may also have impacted the increases of women into the paid labor force. In countries where there is internal migration, which is predominately male migration, more opportunities for education and employment may become available to women. In addition, more female-headed households increase the need for women to find employment to support their families. With the decline in fertility, women devote fewer years to child-bearing and child care that can often conflict with time available to spend in the paid labor force (United Nations, 1995). The study of Baker and Benjamin (1997) found that when the entire family migrates, the women initially work to support the family while the male head of household acquires the skills needed in the new environment. Although women’s participation is growing in both developed and developing countries, one difference between the labor markets of these two groups is that the developing nations contain a large informal sector. In many of these countries, it is estimated that more than half of the economically active population may be working in the informal sector (Otero, 1989). The functioning of this sector and the role of women in it has been studied by several researchers, including Connolly (1985), de Soto (1986), Charmes, (1990), Fields (1990), and McKean (1994), among several others. These studies have found that women’s work within this sector is often similar to tasks of work in the home, making it more acceptable in societies where women working outside the home are not culturally acceptable (Fernandez Kelly, 1983 Tiano, 1990a). Furthermore, women in the informal sector tend to work in the lowest paid, dirtiest jobs within that sector (Sanchez et al., 1981; Benerı´a and Roda´n, 1987; Rakowski, 1987; Telles, 1993; Anderson and Dimon, forthcoming). It is hypothesized that the motivations, and hence the determinants, of women’s participation in this sector are fundamentally different from those in the formal sector. Hill (1983) investigated the effect of entry into the informal sector as a separate choice from formal sector entry and found that the motivations and determinants for labor market participation of Japanese women did differ between the two sectors. Another difference in developing country labor markets that may affect women’s labor force participation rates within the formal sector is the growth of export processing or assembly manufacturing (Grunwald and Flamm, 1985; Ward, 1990). In particular, much has been written of the Mexican maquiladoras (off-shore assembly plants) which have historically maintained a labor force predominately of women. During the 1970s and 1980s, over 80% of the labor force in the electronic industry maquiladoras was female (Carrillo and Hernandez, 1982; Fernandez Kelly, 1983; Tiano, 1990a, 1990b; Stoddard, 1987; and Sklair, 1989). This study, like the Hill (1983) study, quantitatively investigates determinants of women’s labor force participation and allows for the choice between the formal and informal labor sectors to be different. This research extends the work of Hill in three significant ways. First, it applies this analysis to Mexican data, where there is a significantly larger informal sector than in Hill’s Japanese study. Second, the Mexican data from the border city, Tijuana, is a case where there is a large and active export processing industry that prefers hiring young women to men, giving them more options for formal sector participation. Third, the women are separated between married and single women. These differences allow us to test whether

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or not the determinants are different for entering the formal than from entering the informal sectors in a setting where the informal sector accounts for a large proportion of the labor force. Further, it lets us test whether the determinants of entering the paid labor force are affected by the existence of a large assembly manufacturing sector with a high demand for female labor providing the opportunity for more formal sector jobs. Finally, it permits us to test whether or not marital status affects their participation decision. An expanded definition of work, which includes informal labor sector work and unpaid work in the home, is used in this study.3 Women’s labor market participation decision is viewed as a choice between education (generating a future higher income stream), production in the home (without pay), and production in the market, including both the formal and informal sectors. 2. The model The model used to test the effects of demand and supply factors on women’s work decision is summarized in the following equation: P共D j兲 ⫽ 关demand, personal, household]

(1)

where P(Dj) is the probability of the jth woman’s work activity decision as a function of the level of formal sector labor demand; personal variables: marital status, age, education, and migration status; and household variables: number of children broken into two age groups (preschool– under 5 years old and 5–12 years of age), the number of other members of the household doing housework, other family income, and the level of technological aids to housekeeping. Women’s work activity is divided into four choices: (1) school; (2) unpaid housework; (3) paid informal sector; and (4) paid formal sector work.4 The school option in Mexico applies mainly to young women and almost exclusively to single women. Schooling is considered less valuable for women than for men, given the culturally dictated view of women’s career role as that of homemaker. Work in the home in the Mexican setting is a necessity for family survival. In low-income homes, where there are very few technological advances like running water, washing machines, and vacuum cleaners, the necessary chores of maintaining a family require full-time work. This means that, for low-income families, at least one person (traditionally a woman) is needed to remain in the home to accomplish these tasks. For those entering the paid labor force, the formal sector is usually preferred over the informal sector. It offers benefits such as paid vacation, medical care under social security, and the protection of labor laws. Work in the informal sector is the alternative, often a last resort for families needing to survive in an environment that provides no unemployment compensation or government welfare payments. The informal sector is characterized by a lack of regulation; including health, safety and minimum wage requirements; and lack of access to capital, both physical and human. At the same time, it has the advantages of free entry and flexible hours. Furthermore, much informal sector labor involves similar tasks to those performed in housework, making this type of paid labor more acceptable as women’s work (Fernandez Kelly, 1983). Traditional discrimination in the labor market and the need

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for flexibility, therefore, make it more likely for women to be employed in this sector. It is estimated that, in most regions, 60% of the informal sector workers are women (Otero, 1989.) Further, there is a pyramid structure within this sector with those of “entrepreneurial spirit,” as praised by de Soto (1986), at the top and increasingly poorer workers going down the pyramid. Studies have shown that women tend to form the base, concentrated in traditional domestic activities which are seen as an extension of women’s domestic role: washing; sewing; cleaning; and selling. Anderson and Dimon (forthcoming), using a dual informal sector model, show that women predominately are in the “free entry” (in other words, little or no capital requirements for entry) bottom tier of the informal sector. A subset of the informal sector, that of industrial homework, provides a low cost, flexible way for the formal sector firms to meet fluctuating demands and to lower labor costs. Outside the labor laws and often at sub-minimum wages, firms contract with primarily female labor to perform certain labor intensive tasks. The pioneering study by Benerı´a and Rolda´n (1987) focused attention on women’s labor in this “hidden” segment of industrial production. The woman can combine this paid activity, often done in the home, with her traditional household duties. Though she has independence in arranging her schedule, her livelihood remains dependent on the whim of the firm and the market it serves. Labor market demand determines wages and the level of difficulty of job entry, including skill and education prerequisites. Demand in this model is indirectly included by comparing women’s work activity decisions in the border city of Tijuana, where there are a large number of maquiladoras and a high demand for “maquiladora grade” labor, with those in Torreon, an interior city with little export processing. Torreon has a more traditional agri-industrial base and an excess supply of labor. On the supply side, characteristics can be divided into personal and household. Personal characteristics affect the woman’s wage earning ability. In the literature on women’s labor force participation, age and education have both been found to be important influences. Several studies have found the age-paid labor force participation relationship to be non-linear for both men and women (Roos, 1985). While the male relationship is a fairly consistent inverted “U”, Durand (1975) found women’s age patterns of participation to vary by country between three patterns: early peak, (only working when young), double peak (dropping out of the labor force during child-bearing years) and single peak (the male pattern). In addition to age’s impact on childbearing years, as age increases, experience increases, but dexterity decreases. If the dexterity factor outweighs experience, there will be a shift from the likelihood of formal to informal sector work. Maquiladoras and other manufacturing plants often have a preference for employing young women. Thus an expansion in export processing may increase the relative importance of age by decreasing the likelihood that a woman will work in the formal sector as age increases. Additional education increases productivity and the potential market wage. This raises the opportunity cost of nonmarket activities, which is expected to increase the probability of women working in the paid labor force, especially the formal sector (Mincer, 1974). Investment in education at an early age has a higher expected life-time return. Once a woman is married in the Mexican culture, expected returns to education may fall to close to zero, since culturally she is not expected to work in the paid labor force (even though she may in fact do so).

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Migration status may affect women’s work force participation, especially the choice between the formal and informal sector if job information is imperfect. It takes time to establish one’s self; develop contacts; and learn about job opportunities. Empirical studies on the effects of migration to a new area on women’s labor force participation have found it to be negatively related or indeterminate (Sandell, 1977; Gail Shields and Michael Shields, 1989; Suet-ling Pong, 1991) or depending upon family composition, greater than native-born (Baker and Benjamin, 1997). Marital status is expected to impact women’s labor force participation rate in Mexico significantly, given the Mexican cultural ideology of women’s domestic and child-bearing roles (Tiano, 1990a). Women working outside the home are perceived by many Mexicans to be threatening to the integrity of the family: daughters may challenge parental authority and wives may refuse to comply with the demands of their husbands (Fernandez-Kelly, 1983). Therefore, it is expected that marriage will dramatically decrease the probability of a woman attending school or working in the paid labor force. If she does participate in the paid labor force, it is more likely to be in the informal sector, which is regarded as an extension of women’s work. Household characteristics affect the elasticity of substitution between providing for household survival needs and income. The higher this elasticity, the more likely it is that a woman will respond to higher wages with increased participation. Factors affecting the elasticity of substitution are: the number of children; the amount of labor-saving technology in the home; the number of others in the household with whom to share the tasks; and the income of other family members. The presence of younger children will decrease the elasticity of substitution between unpaid home work and paid formal or informal sector work, while older children, who can help with household tasks, increase the elasticity of substitution. Cohen (1970) found that the presence of a child under 6 years old has the largest effect of any factor in determining labor force participation of married women in the U.S. The existence of another woman in the home to do the house work is expected to increase the elasticity of substitution, increasing the probability that a woman would work in the paid labor force. In addition, the higher the level of labor-saving technology (running water, automatic washer, dish washer,) the greater the elasticity of substitution between homework and market work. A multinomial logit model is used to predict the work activity of individual women. The general form of the equation is: ln e共P i/P 0兲 ⫽ a i ⫹ b iX ⫹ e

i ⫽ 1, 2, 3

(2)

where P0 refers to the probability that a woman attends school and the Pi’s refer to the probability a woman works in the home, in the informal sector, or the formal sector. The work choices are mutually exclusive, and the sum of the probabilities are constrained to equal one. The vector of independent variables, which includes the personal and household characteristics of the women specified in Eq. (1), is designated by X. The estimated parameters enable one to determine the effect of the independent variables on the probability that a woman will work in each of the four sectors.

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3. The data and methodology The data set used to estimate this model are from a household survey done in two Mexican cities: Tijuana, Baja California; and Torreon, Coahuila in 1987. This setting has two advantages: First, it is in Mexico where there is a strong traditional role for women (the cultural element); and second, these two cities offer a clear contrast in the demand for labor. Tijuana is on the U.S.-Mexican border and 1987 was a period of high formal sector demand for female labor due to a maquiladora boom, as evidenced, in part, by the permanently displayed help wanted signs on the plants. Other supports for the claim of an existence of high, if not excess, demand for maquiladora workers, were the high turnover rates of the plants and the fact that new migrants reportedly found work within two or three weeks of their arrival. Torreon, on the other hand, is an interior city with a more traditional, agriindustrial base. At the time of the survey it was in economic crisis with an excess supply of labor.5 The total data set (both cities) consist of a usable sample of 1394 women, age 13 and older. The questionnaire and statistical sampling were designed and data collected by the Colegio de la Frontera Norte (COLEF). The sampling is random, based on the sampling table established by the Mexican National Institute of Statistics, Geography and Data (INEGI) for the Mexican census. The sampling is stratified by income and is proportional to the number of houses (according to the census) in each category classified as either high, medium, or low income.6 In this survey, household is defined as the family unit, including extended family. It is possible to have multiple households in one physical house. Where more than one household existed, a separate questionnaire for each was administered. The data include both information on individual women and on the members of their households. Information on domestic employees who do not live in the household is not included in the survey. A women was categorized as in the paid work force if she answered yes to working, on leave due to illness or vacation, or actively looking for work. If in the paid work force, she was grouped into either the informal or formal work sector. The key variable for differentiating between these two sectors was whether or not the person was covered by social security. Those with social security were classified as being in the formal sector. For those without social security, we used two methods of classification: one based on occupation; and the other on industrial classification. Specifically, the definition based on occupation defined “formal” as those who receive social security or are a professional, government official, or private sector manager. “Informal” are those who receive no social security and who are in any of the other 17 occupational categories. For example, self-employed professionals, such as medical doctors, do not receive social security, yet they are not considered part of the informal sector. In other occupations, such as seamstresses, receiving social security distinguishes between the formal and informal sector. The alternative method, based on the industrial branch, defined “formal” as those who receive social security or who work in education or government. “Informal” are those who receive no social security and who fall in any of the other of the 17 industrial branches. If there was a discrepancy between these two definitions, then each case was individually evaluated.7

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The data are separated into four subgroups: single women in Torreon (364), single women in Tijuana (295), married women in Torreon (386) and married women in Tijuana (349). These four subgroups are estimated and analyzed separately. By analyzing the determinants for each city independently, the effect of the export processing boom on women’s labor force participation can be indirectly estimated. It can also be determined if there is a difference by marital status. The advantage of estimating the equations in separate subgroups, rather than using dummy variables, is that the coefficients are then allowed to differ between the various groups. Table 1 gives the means of the independent variables in Eq. (2) for single and married women by city for each work activity. Means of the variables are similar between the two cities, but tend to differ between single and married women. Average years in school is lowest for women working in the home, and highest for women working in the formal sector. The average number of young children is higher in Tijuana than Torreon, and is highest for women working in the home. Average income, both personal and other family income, is lower in Tijuana than Torreon, except for women working in the informal sector. In all cases, average income from formal sector work is higher than from informal. To measure laborsaving technology in the home a proxy variable, whether or not the house has piped in water, is used. The average is higher in Torreon than Tijuana, which is to say that a higher proportion of households have running water. This is probably from the more rapid population growth due to migration in Tijuana. Indirectly, the data also shed some light on the extent of (paid) industrial homework in Tijuana and Torreon. While the questionnaire did not address this issue directly, it did isolate the proportion of women working in manufacturing and maquiladoras who receive no social security, even though it is required by law. It is assumed that this subgroup of maquiladora and manufacturing workers are either subcontracting in the home or working in small, illegal “sweatshop” factories. The proportion of the sample in that category is small. Of 72 women employed in maquiladoras and manufacturing in Tijuana, 8 receive no social security (11.1%) and of 30 in Torreon, 7 receive no social security (23.3%.) This represents 14.7% of all women employed in maquiladoras and manufacturing and 7.8% of all women employed in the formal and informal sector. Of note is the much higher proportion of women, 23% compared to 11%, involved in this informal use of labor in Torreon where formal sector labor demand is significantly lower than in Tijuana. On average, women working in this category earn 220,500 pesos (U.S.$160.00) per month, and supply 50% of the family income, roughly the same proportion as for all women working in the informal sector. Our study includes them in the informal sector.

4. The results and probabilities The multinomial logit results are displayed in Table 2 and Table 3. The logit coefficients, displayed in brackets, can be interpreted as the change in the natural log of the ratio of odds with respect to a unit change in the independent variables. The coefficients thus enable one to determine the direction of effect of each independent variable. For example, in Table 2, since the dependent variable is Pi /P0, a negative coefficient can be interpreted as a lower

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Table 1 Means of variables by work participation Total

School

Work in home

Informal sector

Formal sector

44.82 0.85 5.84 0.44 0.70 34.77 0.93 0 504,438 89

32.42 0.54 6.94 0.29 0.56 23.68 0.93 220,729 656,354 48

28.00 0.89 11.51 0.30 0.88 22.50 0.94 346,395 865,816 76

37.28 0.90 5.70 0.78 0.82 18.96 0.43 0 607,833 60

33.00 0.77 7.48 0.46 0.77 20.01 0.51 243,461 703,410 39

25.69 0.79 9.15 0.57 0.78 16.61 0.59 260,470 839,956 68

35 .27 6.75 1.76 1 .92 25.55 0 614,164 304

35 .25 6.67 .75 1.11 .86 27.18 260,714 626,964 28

33 .11 11.87 .74 .55 .96 23.96 463,754 794,698 53

35 .26 5.94 .94 .89 .57 18.34 0 569,783 268

38 .17 6.14 .66 .86 .52 21.43 323,068 486,689 29

35 25 10.23 .65 .60 .81 19.95 309,312 735,187 48

Single women in Torreon Age (years) Other homemakers Years of school Children 0–5 years Children 6–12 years Years in city Running water (1 ⫽ yes) Monthly income of woman (pesos) Monthly other family income (pesos) Sample size

27.82 0.82 8.67 0.32 0.85 22.12 0.96 101,431 769,722 364

16.24 0.85 9.45 0.27 1.03 13.97 0.99 0 913,754 151

Single women in Tijuana Age (years Other homemakers Years of school Children 0–5 years Children 6–12 years Years in city Running water (1 ⫽ yes) Monthly income of woman (pesos) Monthly other family income (pesos) Sample size

24.85 0.78 8.17 0.48 0.80 16.73 0.55 92,227 731,186 295

16.10 0.72 9.02 0.30 0.81 14.75 0.60 0 739,687 128

Married women in Torreon Age (years) Other homemakers Years of school Children 0–5 years Children 6–12 years Running water (1 ⫽ yes) Years in city Income earned by woman (pesos) Other family income (pesos) Sample size

35.02 0.24 7.46 0.75 0.95 0.92 25.38 82,588 638,932 386

33 0 9 1 0 0 1 0 248,000 1

Married women in Tijuana Age (years) Other homemakers Years of school Children 0–5 years Children 6–12 years Running water (1 ⫽ yes) Years in city Income earned by woman (pesos) Other family income (pesos) Sample size

35.05 0.26 6.58 0.87 0.86 0.60 18.67 69,386 586,146 349

20 1 8.75 .50 1.50 .75 5.56 0 615,000 4

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Table 2 Multinomial logit results: Single women Tijuana (n ⫽ 295) Work in home ⭸Ph/⭸X [␤h] ⫺12.1807 (⫺5.16) Age ⫺0.0346 [0.9847] (5.22) Age2 0.0006 [⫺0.0093] (⫺3.81) Years of school ⫺0.0289 [⫺0.5610] (⫺4.58) Years in the city ⫺0.0016 [⫺0.0239] (⫺0.59) No. of children ages 0–5 0.0374 [0.6294] (2.28) No. of children ages 6–12 ⫺0.0087 [0.4695] (1.83) No. of other homemakers ⫺0.0289 [0.8541] in the house (2.66) Running water to dwelling ⫺0.0470 [⫺0.4906] (1 ⫽ yes) (⫺0.91) Other family income 0.0000003 [0.0000005] (1.49) Log of likelihood function

Constant

Informal sector ⭸Pin/⭸X [␤in]

Torreon (n ⫽ 364) Formal sector ⭸Pf/⭸X [␤f]

⫺19.3609 ⫺16.5570 (⫺7.04) (⫺7.04) 0.0480 0.0307 [1.3792] [1.2374] (6.74) (6.46) ⫺0.0005 ⫺0.0005 [⫺0.0144] [⫺0.0134] (⫺5.40) (⫺5.16) ⫺0.00887 0.0259 [⫺0.4473] [⫺0.3495] (⫺3.59) (⫺3.02) 0.0043 ⫺0.0033 [0.0022] [⫺0.0206] (0.05) (⫺0.53) ⫺0.0397 0.0184 [0.2607] [0.4481] (0.79) (1.66) 0.0254 0.0030 [0.6179] [0.5245] (2.14) (2.24) ⫺0.0887 0.0259 [1.0967] [0.7329] (3.07) (2.45) ⫺0.0845 0.1197 [⫺0.5511] [⫺0.0080] (⫺0.94) (⫺0.02) ⫺0.0000004 0.00000001 [0.0000007] [0.0000003] (0.18) (0.93) ⫺230.989

Work in home ⭸Ph/⭸X [␤h]

Informal sector ⭸Pin/⭸X [␤in]

Formal sector ⭸Pf/⭸X [␤f]

⫺11.2036 (⫺5.00) ⫺0.0016 [0.9870] (6.06) 0.0001 [⫺0.0091] (⫺4.16) ⫺0.0458 [⫺0.5514] (⫺5.89} 0.0035 [0.0598] {1.45) 0.0571 [0.7746] (2.21) ⫺0.0199 [⫺0.0225] (⫺0.12) 0.1127 [0.8358] (2.71) 0.0459 [⫺1.9532] (⫺1.49) 0.0000001 [0.0000001] (0.43)

⫺8.5932 ⫺13.5546 (⫺3.79) (⫺5.96) ⫺0.011 0.0237 [0.9440] [1.0497] (5.77) (6.30) 0.000008 ⫺0.0003 [⫺0.0091] [⫺0.0103] (⫺4.11) (⫺4.48) ⫺0.1049 0.0775 [⫺0.5752] [⫺0.2311] (⫺6.11) (⫺2.51) ⫺0.0018 ⫺0.0011 0.4183] [0.0470] (1.02) (1.16) ⫺0.0630 0.0124 [0.3465] [0.6426] (0.88) (1.88) ⫺0.0638 0.0838 [⫺0.2348] [0.2394] (⫺1.08) (1.52) ⫺0.1469 0.0392 [⫺0.1042] [0.6111] (⫺0.30) (2.05) 0.1011 ⫺0.1694 [⫺1.6572] [⫺2.4985] (⫺1.23) (⫺1.90) ⫺0.0000006 ⫺0.0000006 [⫺0.000005] [0.0000003] (⫺1.08) (⫺1.03) ⫺274.836

Notes: Ph is the probability of working in the home, Pin is the probability of working in the informal sector and Pf is the probability of working in the formal sector. Partial derivatives are evaluated at the sample means. The logit coefficients are reported in brackets where Bi is the natural log of the odds of working in category i with respect to being in school. Asymptotic t-ratios are in parentheses.

probability of working (either at home or the informal or formal sectors) relative to being in school, given an increase in that independent variable, and controlling for differences in the other independent variables. Because of the difficulty in interpreting these coefficients, partial probability coefficients are also presented. The probability of being in each of the alternatives: work in the home, Ph; being in school, Ps; paid informal sector, Pin; and paid formal, Pf; are calculated, assuming the independent variables equal their respective means. The equation for the probabilities is:

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Table 3 Multinomial logit results: Married women Tijuana (n ⫽ 345) Informal sector ⭸Pin/⭸X [␤in] Constant Age Age2 Years of school Years in the city No. of children ages 0–5 No. of children ages 6–12 No. of other homemakers in the house Running water to dwelling (1 ⫽ yes) Other family income Log of likelihood function

Torreon (n ⫽ 385) Formal sector ⭸Pf/⭸X [␤f]

⫺5.4572 ⫺8.6195 (⫺2.55) (⫺3.76) 0.0457 0.0773 [.1726] 0.2802] (1.62) (2.14) ⫺0.0005 ⫺0.0010 [⫺0.0020] [⫺0.0036] (⫺1.52) (⫺2.03) 0.0251 0.0607 [0.5746] [.2521] (0.93) (5.07) 0.0038 0.0039 [0.0191] [0.0101] (0.97) (0.59) ⫺0.0538 ⫺0.0940 [⫺0.1969] [⫺0.3462] (0.73) (⫺1.38) ⫺0.0409 ⫺0.0879 [⫺0.1160] [⫺0.3517] (⫺0.56) (⫺1.64) 0.0173 0.0801 [⫺.0384] [0.3795] (⫺0.96) (1.25) ⫺0.0776 ⫺0.0070 [⫺0.5438] [0.1917] (⫺1.22) (0.42) ⫺0.0000009 ⫺0.00000003 [⫺0.0000006] [0.0000001] (⫺1.10) (0.35) ⫺200.752

Informal sector ⭸Pin/⭸X [␤in]

Formal sector ⭸Pf/⭸X [␤f]

⫺2.7201 ⫺7.6099 (⫺1.38) (⫺3.74) 0.0193 0.042 [0.0458] [0.2233] (0.44) (2.07) ⫺0.0003 ⫺0.0005 [⫺0.0008] [⫺0.0027] (⫺0.59) (⫺1.89) 0.0179 0.0534 [0.0021] [0.3046] (0.04) (6.21) 0.0019 0.0005 [0.0149] [⫺0.0036] (0.85) (⫺0.25) ⫺0.0163 ⫺0.0359 [⫺0.0385] [⫺0.1189] (⫺0.15) (⫺0.84) ⫺0.0332 ⫺0.1025 [⫺0.0051] [⫺0.5886] (⫺0.03) (⫺2.84) ⫺0.0117 ⫺0.0267 [⫺0.0248] [⫺0.1420] (⫺0.07) (⫺0.36) ⫺0.1250 ⫺0.1144 [⫺0.7372] [⫺0.3296] (⫺1.21) (⫺0.34) ⫺0.00000001 ⫺0.00000003 [0.0000009] [⫺0.0000002] (0.23) (⫺0.73) ⫺210.695

Notes: Pin is the probability of working in the informal sector and Pf is the probability of working in the formal sector. Partial derivatives are evaluated at the sample means. The logit coefficients are reported in brackets where Bi is the natural log of the odds of working in category i with respect to working in the home. Asymptotic t-ratios are in parentheses.

P ij ⫽

e ␤ixj e ␤sxj ⫹ e ␤inxj ⫹ e ␤fxj ⫹ e ␤hxj

(3)

where Xj is a vector of independent variables explaining labor force participation, ␤i is the parameter vector and the subscript s is for school, in for informal sector, f for formal sector, and h for working in the home. By differentiating Eq. (2), the marginal effects of the independent variables on the probabilities can be calculated.

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⭸P i ⭸␤i ⭸␤k ⭸␤l ⭸␤h ⫽ P i(1 ⫺ P i) ⫺ Pi Pk ⫺ Pi Pl ⫺ Pi Ph ⭸X X ⭸X ⭸X ⭸X

(4)

where i,k,l ⫽ s, in, f, i⫽k⫽l. The partial probability of a variable, Xi, shows the change in the probability of a woman working in a given sector with respect to a change in Xi, evaluating the other variables at their means. Table 3 presents the results for single women in Torreon or Tijuana. Both cities give similar results with regards to individual and household characteristics. With regards to individual characteristics, there is a strong curvilinear (convex to origin) relation between single women’s age and their labor participation. As years of schooling increases, single women are more likely to go to school than work. Years in the city does not appear to impact the labor sector participation decision. With respect to household characteristics, single women in both cities are less likely to go to school as the number of small aged children (0 to 5 years) in the household increases. They are also less likely to go to school if the number of other homemakers living in the house increases. The presence of older children (6 to 12 years), running water to the dwelling (the proxy variable for labor-saving technology), and other family income do not significantly impact the relative probabilities between schooling and work. To test whether the results are statistically significantly different between single women in Tijuana and Torreon, a likelihood ratio test is used. This tests the null hypothesis that the vector of coefficients in Tijuana, ␤TJ, is equal to the vector of coefficients in Torreon, ␤TN. The test statistic is given as:

␻ ⫽ ⫺ 2兵L共 ␤ 兲 ⫺ 关L共 ␤ TJ兲 ⫹ L(␤TN兲兴}

(5)

␻ is asymptotically chi-squared distributed with 30 degrees of freedom and L(␤) is the log-likelihood function of the equation estimated for the whole sample, including both Tijuana and Torreon, L(␤TJ) is the log-likelihood function of the equation estimated for the Tijuana subsample and L(␤TN) for that of the Torreon subsample (Ben-Akiva, 1985). The test statistic, ␻, equals 40.7 and the null hypothesis of no difference is rejected at the 10% level of significance. It is therefore concluded that single women’s choices are affected differently in Tijuana’s export processing environment than those choices made in Torreon. Table 3 gives the multinomial results for married women in the two cities. Because only 5 of a total 735 married women were in school, the choice of going to school was not included in the equation. So, looking at Pi/P1, the relative probabilities are interpreted as the probability of working in the informal or formal sector relative to working in the home. Only age and years of schooling are statistically significant.9 A second likelihood ratio test was done to test the hypothesis that there is no difference in the probabilities of married women’s labor force participation between married women in Tijuana and married women in Torreon. This test statistic equals 4 and is chi-squared distributed with 20 degrees of freedom. The hypothesis is accepted, concluding that there is no statistically significant difference in labor force determinants between the two cities for married women, despite the differences in labor market conditions. A final likelihood ratio test was performed to test the hypothesis that there is no difference

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Fig. 1. Participation by sector evaluated at the mean for all individual and household characteristics.

between all married and single women. This test yields a chi-squared distributed ␻ equal to 274 with 30 degrees of freedom. The hypothesis is therefore rejected at the 1% level of significance and we conclude that the determinants affect married women differently than single women. From the multinomial logit equations, we can determine the probability of being in either of the three work alternatives for specified values of the independent variables.10 Fig. 1 shows these probabilities for the four data subsets where all the independent variables are evaluated at their means (Table 1). Single women in Torreon have a much higher probability of working in the home than single women in Tijuana (.35 compared to .18). Their probability of participation in the informal sector is virtually the same, but the probability of working in the formal sector is much higher in Tijuana. For married women, this same contrast of more formal sector and less home work in Tijuana is in evidence. However, the difference for married women is very small, consistent with the likelihood ratio results of no significant difference between married women in Torreon and Tijuana. From these results alone, it is not clear how much of the difference in formal sector participation can be accounted for by the higher level of demand for formal sector work in Tijuana due to the maquiladora boom, rather than differences in household and personal characteristics. To isolate demand effects, the average personal and household characteristics of Torreon women are substituted into the Tijuana women’s equation and probabilities of work activity are calculated. As Fig. 2 shows, there is only a 6% smaller probability of working in the home for a married woman of average Torreon characteristics were she to reside in Tijuana with its higher labor demand. All of this shift is into the formal sector. For single women, the impact is much greater. There is a 23% smaller probability of working in the home for a single woman with average Torreon characteristics were she to reside in Tijuana. This shift is mostly into the formal sector, 17%, leaving only a 6% increase in informal sector participation. There is virtually no change in the probability of attending school. This indicates that conditions in labor market demand do appear to make a significant difference for single women’s activity, but not for married women, consistent with the results of the log likelihood tests.

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Fig. 2. (a) Probability of a married woman (evaluated at the mean) from Torreon working in Tijuana or Torreon. (b) Probability of a single woman (evaluated at the mean) from Torreon working in Tijuana or Torreon.

Varying the assumed values of independent variables can give added insight into the effects personal and household characteristics have in determining the probability of labor sector participation. Figs. 3 and 4 show the effects of age on the probabilities of informal and formal labor sector participation. For single women (Fig. 3,) the probability of working in the formal sector in Tijuana is higher, peaking at an earlier age (23 years), and declining more quickly as women get older. This is probably due to the greater demand for young women originating from the maquiladoras. There is also a much higher probability for single women in Tijuana older than 25 years to work in the informal sector. The significantly higher probability of informal labor sector participation of older single women in Tijuana may be due to additional informal jobs created to support maquiladora activity, for example: work as domestics; subcontract take-out work; and lunch stand vendors. For married women (Fig. 4) the differences between the cities are very small. The probability of formal sector participation is very low and the peaks are less than a .01 probability difference between the two cities. Labor sector participation for married women in Torreon, in both the informal and formal sectors, does, however, show the traditional

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Fig. 3. (a) Age of single women and the probability of informal sector participation. (b) Age of single women and the probability of formal sector participation

inverted “U” pattern of developed countries with the peak participation level around 40 years of age. Fig. 5 graphs the impact of education on the probabilities of participation by sector for single women. Theory suggests that, with additional years of schooling, there will be a lower probability of participation in the informal sector and a higher probability of participation in the higher wage formal sector. This relationship is more evident in Torreon than in Tijuana. In Torreon, as years of schooling increases, the probability of working in the formal sector increases at a high rate, while in Tijuana it increases at a lower rate. The probability of formal sector participation with eight years of education is .55 in Tijuana and .35 in Torreon. With a high school degree (12 years of schooling,) the probabilities for formal sector participation are the same in both cities at .67. The formal sector labor market in Tijuana provides less reward for additional years of education. Examining the type of formal sector jobs available in the two cities helps explain these differences in response to education. In this sample, for example, 20% of the single working women in Torreon are employed in education and 16% in manufacturing and maquiladoras. This compares to 4% in education and 48% in manufacturing and maquiladoras in Tijuana. Not only does employment in educational fields require more years of education than work in manufacturing and maquiladoras, but, due to the high demand for young women in

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Fig. 4. (a) Age of married women and the probability of informal sector participation. (b) Age of married women and the probability of formal sector participation.

Tijuana, plants there require less education from job applicants than those in Torreon. Despite the higher returns to education in Torreon, the probability of being in school for any given age is virtually the same in both cities (data not shown). For informal sector jobs, the participation is higher with less education in Torreon than in Tijuana. In Tijuana, export processing appears to have created more options for participation in the formal sector even for those with very little education. Fig. 6 displays the impact of additional years of education on work sector participation for married women. Formal sector participation increases at the same level and rate of increase with additional years of school in both cities. In fact, even though married women have a low level of paid labor market participation in both cities, participation increases significantly with higher levels of education. With a college degree, measured by 16 years of education, married women in both cities have a probability of .60 of working in a formal sector job. It appears that the opportunity costs for not working in the formal sector with higher levels of schooling is the same for married women in both Torreon and Tijuana. For married and single women in Tijuana there is very little relationship between informal sector participation and years of education. In Torreon, increased education leads to a fall in informal sector participation. The final personal characteristic which is expected to affect labor sector participation is

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Fig. 5. (a) Level of education and the probability of informal sector participation of single women. (b) Level of education and the probability of formal sector participation of single women.

the number of years of living in the city. The results show no significant impact on formal or informal labor sector participation in either city, comparing probabilities for women who have been in the city for one year vs. twenty years. A household characteristic expected to impact women’s paid labor force participation is the presence of small children (birth to 5 years). This is true for both married and single women since single women, including older daughters in the household, help care for younger children. This study found that the changes in the probabilities of formal and informal labor force participation for married women from additional children in the household are small (not shown). For Tijuana, the fall in participation in either sector is more rapid than in Torreon as the number of children increase in the household. This is because the number of children has no impact on the probability of married women’s participation in the informal sector in Torreon, while in Tijuana participation decreases in both the formal and informal sectors as the number of children increases. For single women in Tijuana and Torreon, the number of young children in the household reduces the probability of informal sector participation. Single women in the informal sector

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Fig. 6. (a) Level of education and the probability of informal sector participation of married women. (b) Level of education and the probability of formal sector participation of married women.

reduce their level of paid labor force participation and increase their participation of working in the home. However, the presence of small children does not impact formal sector work. This is true in both cities, but with Tijuana having a higher level of formal sector participation. The presence of small children does not impact the probability, overall, of working at home for single women in Tijuana. There is merely a slight shift in the probability of participation from the formal to informal sectors as the number of small children increases. This suggests that single women tend to drop out of informal sector jobs to care for small children, but, with the higher opportunity cost of formal sector jobs, the probability of participation is not reduced, despite the presence of small children. The results indicate that the number of other homemakers in the household does not have a large impact on paid labor sector participation. The strongest impact is not with married women, but with single women. Married women in Mexico are traditionally already working in the home, but single women appear to respond more significantly to changing household needs, such as the number of small children, and the number of other homemakers in the

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household. Single women in Tijuana increase their probability of participation in the informal sector with another homemaker in the house (.21 to .27,) decreasing their participation in the formal sector by about the same amount (.60 to .54). In Torreon, the shift in paid labor force participation is the opposite. With an additional homemaker in the house single women are slightly less likely to work in the informal sector and more likely to work in the formal sector. The running water variable was included to capture the effects of home technology. For married women, there is the perverse result that the probabilities of working in the home increase and in the informal sector decrease with running water to the home for both Torreon and Tijuana. There is very little impact on formal sector participation for married women in either city. As expected, single women in Tijuana increased their probability of working in the home without running water (.15 with and .20 without,) whereas single women in Torreon had a slightly lower probability of working in the home without running water (.35 with and .29 without). This variable does not appear to be capturing the differences in household technology as modeled. For Tijuana these contradictory results may be due to this proxy variable capturing more the effect of poverty than of home technology. For Torreon, with over 90% of the households having running water, the variable does not appear to be able to capture differences in home technology. Theoretically it is expected that other family income would impact the labor sector decisions of women. This study found other income to have very little impact on the probability of working in the home (or outside the home) for married women in both cities. For single women, the probability of working in the home increases with income very slightly in Tijuana and much more strongly in Torreon. In Tijuana, higher income does not impact the probability of participation in the formal sector, but does reduce informal sector participation. In Torreon, both formal and informal sector participation decrease for single women, increasing the probability of working in the home as income rises. Thus, single women in Torreon and single women in the informal sector in Tijuana appear to respond more as secondary workers supplementing family income, whereas single women’s participation in the formal sector in Tijuana appears to be unrelated to family income.

5. Conclusion This paper compares the determinants of formal and informal labor sector participation between Torreon and Tijuana, Mexico, for single and married women. The rapid expansion of export processing in Tijuana allows an indirect empirical measure of the impact of expanding formal sector jobs on the probability of women going to school, working in the home, working in the informal sector, or working in the formal sector. The empirical results and log likelihood ratio tests indicate that the determinants for labor force participation affect married women differently than single women. In addition, they concur with the findings of Hill (1983), that the determinants of the decision for informal labor sector participation differ from formal sector participation. Single women’s participation decisions also appear to be affected by the demand and supply conditions, whereas for married women the decision appears to be predominantly based on supply factors.

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From the log likelihood tests and the experiment in controlling for personal characteristics (Fig. 2), it appears that the opportunity of additional formal sector jobs has very little impact on married women’s work alternatives. Strong cultural traditions for married women to work in the home may be offsetting any additional formal sector employment opportunities. Labor force participation for married women appears to be determined almost exclusively from the supply side by household and personal characteristics. On the other hand increased demand in formal sector jobs does significantly affect the probabilities of work choices. Overall the additional employment opportunities provided in Tijuana through the maquiladoras are attracting single women from traditional home work activities to formal sector work for pay. To a smaller extent there is a shift from the informal to the formal sector. These results indicate that increased employment opportunities in the formal sector may reduce the number of women working in the informal sector, including industrial subcontracting jobs. Married women predominantly work in the home and appear to be less responsive to changing characteristics of the household. It is the single women, in both cities, who respond to household needs by moving in and out of the paid labor market. Specifically, single women in both cities drop out of informal sector jobs to care for additional small children in the home. Nonetheless, formal sector participation does not vary with an increase in the number of small children in the household. This result is true for both cities. Single women in Tijuana do not reduce their participation in formal sector jobs at higher levels of family income, but higher income reduces informal sector participation. In Torreon both formal and informal sector participation falls with higher family income. Older single women and those with less education are less likely to participate in formal sector jobs in Tijuana. There may be less incentive for single women to pursue additional years of schooling in Tijuana where formal sector employment is available without several years of schooling, and the opportunities for that employment fall with age. One might expect young women not to take time out of paid labor participation to pursue additional education. Nonetheless, there is no evidence that their education is being cut short. In fact, average years of education is slightly higher in Tijuana. The results presented here suggest that single women in developing countries might expand their formal sector labor force participation as export processing production and other formal sector opportunities increase. At the same time it appears that the formal sector job expansion would have little impact on married women’s participation in the paid labor force. Acknowledgment The authors wish to thank two anonymous reviewers for their comments. All errors remain the responsibility of the authors. This research was funded, in part, by the School of Business Administration at the University of San Diego. Notes 1. The dynamic benefits from a free trade agreement for countries at similar stages of economic development are generally realized through economies of scale and inten-

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2. 3. 4.

5.

6.

7.

8.

9.

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sification of competitive pressures resulting from a larger market base. Given the different relative supplies of capital and labor skills between the countries in North America, it has been hypothesized that the efficiency gains from the NAFTA will be realized through increased specialization and reallocation of production facilities (Lustig et al., 1992). See Hill, 1983 and Steel, 1981 for further discussion on the impact of development of female economic activity. This expanded definition has also been adopted by Mies (1988) and Ward (1990), among others. Data for leisure time are not available since we do not have direct data on hours spent working. However, indirectly, it can be inferred that women who work in the paid labor force continue to have unpaid housework responsibilities (Safa, 1976). Fernandez Kelly (1983) found that the majority of women in her study, working in the maquiladoras, performed double duty. She found that working mothers with young children averaged 15 hours per day of the combination of formal sector and unpaid house work. It is inferred that the number of other women sharing household duties, in conjunction with the woman’s work activity, yields an indirect assessment of leisure. At that time, Mexico had been experiencing a rapid decrease in real wages. Real wages fell 48% between 1982 and 1987. In Tijuana, despite the high demand, wages remained somewhat tied to the legislated minimum wages. There is evidence of collusion among maquiladora managers to not compete for labor on the basis of wages. Although they did compete through the quality of the work environment, for example, by providing uniforms, shoes, parties, and sport teams. (Sklair, 1993). The sampling universe is limited to the urban areas of Tijuana and Torreon, which omits many of the marginal, less-established neighborhoods. This biases the population by omitting a significant proportion of the poorest population. For example, according to official Tijuana municipal figures for 1987, 48.1% of Tijuana houses have running water. In the COLEF Tijuana sample 58.6% have water inside the home and another 10.5% have running water outside the home (or 69% compared to the 48% overall). This bias needs to be taken into account when examining the means of the variables and the empirical results. When the results of the two definitions were compared, only 16 discrepancies existed. Each of these was examined and a decision made as to formal or informal sector participation based on their answers to the whole questionnaire, including their own (not the family’s) monthly income. In a couple of cases where it was very unclear which was the correct category, the observations were omitted. Calculating a .95 confidence interval around the estimated proportion of .078 gives a range of the proportion of women working for pay who are either engaged in industrial homework or “sweatshop” production as being between 5.9% and 9.7% for both of the cities combined. When married women in the two cities are combined, yielding more efficient estimators, (since the log likelihood ratio test suggests no significant difference between the two cities) the number of other children and years in the city also become significant. See Anderson and Dimon (1992).

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10. For the technique of obtaining specific probabilities from multinomial logit equations, see Schmidt and Strauss, 1973. The probabilities are presented in graphic form in order to aid comprehension. For tables of the exact probabilities, please contact the authors.

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