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The Changing Transitions to Adulthood in Developing Countries: Selected Studies 7 Marriage in Transition: Evidence on Age, Education, and Assets from Six Developing Countries Agnes R. Quisumbing and Kelly Hallman Marriage is an event of great social and economic significance in most societies. It is a rite of passage that marks the beginning of an individual’s separation from the parental unit, even if families continue to be socially and economically interdependent. In many developing countries, it represents the union not only of two individuals, but also of two families or kinship groups. In many societies, it also entails a substantial transfer of assets from the parent to the child generation. Assets brought to marriage are more than a form of intergenerational transfer—they may affect the distribution of bargaining power and resources within the marriage itself. Recent work testing the collective versus the unitary model of household behavior suggests that conditions at the time of marriage may affect the distribution of welfare within marriage. In particular, it has been shown that the distribution of assets between spouses at the time of marriage is a possible determinant of bargaining power within marriage (Quisumbing and de la Brière, 2000; Quisumbing and Maluccio, 2003; Thomas, Contreras, and Frankenberg, 2002). Assets at marriage confer bargaining power because they influence the exit options available to spouses. Although assets at marriage may not completely determine the distribution of assets upon divorce (Fafchamps and Quisumbing, 2002), these measures are, in themselves, worth investigating because they shed light on the institution of marriage and inheritance. Given the centrality of marriage in an individual’s life history, surprisingly little has been written regarding trends in marriage patterns. Because the timing of first marriage critically influences subsequent life events for women, most of the analyses have focused on the female mean singulate age
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies at marriage (e.g., United Nations, 1990) and its determinants. Singh and Samara (1996), using data from 40 Demographic and Health Surveys (DHS) in developing countries, found that, although age at marriage is increasing, a substantial proportion of women in developing countries continue to marry as adolescents. Increases in age at marriage are associated with major social-structural changes such as increases in educational attainment, urbanization, and the emergence of new roles for single women. Jejeebhoy (1995), analyzing 51 studies based on a number of data sources, mostly the World Fertility Survey and the DHS, found that education is the single factor most strongly related to the postponement of marriage, but the relationship may be subject to threshold effects. In many countries, the tendency for education to raise marriage age becomes universal only after a few years of primary education. However, because the results of the few studies available are contradictory, little can be said about trends in the relationship between education and age at marriage over time (Jejeebhoy, 1995, p. 66). Because research on marriage timing has been motivated largely by a demographic interest in the initiation of reproduction (Malhotra, 1997), and because few fertility surveys collect marriage data for men, most of the studies on age at marriage have been limited to women’s experiences (Singh and Samara, 1996). As Malhotra (1997) argues, the focus on women neglects the fact that entry into marriage is also an important life course transition for men, which reflects family structure, gender relations, and social change. Malhotra’s own work in Indonesia is one of a few recent studies that examines the determinants of marriage timing for both men and women. Although not examining determinants, Hertrich (2002) documents trends in marriage age for men and women in Africa. (Earlier studies include Dixon, , and Smith, .) In addition, the literature on marriage rarely pays attention to the resources that men and women bring to marriage. This is a serious gap because empirical work on intrahousehold behavior suggests that the distribution of resources at marriage may affect bargaining power within marriage. Part of this gap is because of data limitations. Anthropological studies are detailed and informative, but only for a small set of people in a particular setting, and they rarely follow the same group through time. However, anthropological techniques have been used innovatively to study changes in marriage patterns. For example, Caldwell, Reddy, and Caldwell (1983) combine data collected using quasi-anthropological approaches and small-scale surveys in a rural area of the south Indian state of Karnataka to examine the changing nature of marriage. Economic analyses have focused mainly on transfers at marriage such as dowries and brideprice (Rao, 1993b; Zhang and Chan, 1999), and not the totality of assets that spouses bring to marriage. Even if dowries or
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies brideprice have great social and cultural significance, there is evidence that they account for only a small proportion of assets brought to marriage, at least in rural Ethiopia (Fafchamps and Quisumbing, 2002), and none at all in countries that do not practice either dowry or brideprice. In general, there are little quantitative data that capture both cross-sectional and longitudinal variation with enough detail to capture the significance of marriage conditions in different cultures. Thus, work analyzing marriage patterns and resources at marriage in a number of countries, using comparable data collection methodologies and empirical analyses, has been scarce. This chapter contributes to the literature on marriage patterns by analyzing data on husband’s and wife’s human and physical capital and conditions surrounding marriage; the data were collected by the International Food Policy Research Institute (IFPRI) in six developing countries.1 Four data sets—Bangladesh, Ethiopia, Guatemala, and South Africa—were collected as part of a larger research program on gender and development policy at IFPRI (Bouis et al., 1998; Fafchamps and Quisumbing, 2002; Hallman, 2000; Hallman et al., 2005; Maluccio, Haddad, and May, 2000; Ruel et al., 2002; Quisumbing and de la Brière, 2000); the Mexico data were collected for the evaluation of PROGRESA (Programa Nacional de Educación, Salud, y Alimentación), a nationwide conditional transfer program (de la Brière and Quisumbing, 2000; Skoufias, 2001); and the Philippines data were part of an earlier study on gender difference in intergenerational transfers (Quisumbing, 1994).2 The data sets in all six countries used comparable data collection methodologies, drew from qualitative studies or the anthropological literature to formulate quantitative survey modules, and contain retrospective data on family background and physical and human capital at marriage for both husbands and wives. The IFPRI study countries were also chosen to capture geographic and cultural variation, as well as to focus on specific policy issues related to gender. Assets at marriage are deflated using the appropriate consumer price index (CPI) to make the real value of assets from earlier and later marriages comparable. Unlike the DHS, the samples are relatively small and are not nationally representative; the study sites are not, however, outliers relative to living conditions within each country (see Table 7-1). Moreover, because the surveys were not designed to 1 In this chapter, we use “union” and “marriage” interchangeably, although for most of our countries, the data refer to actual marriages. The exception is urban Guatemala, which has a high percentage of consensual unions (40 percent of unions in our sample). 2 The first author directed the overall research program at IFPRI while the second author worked intensively on the Bangladesh and Guatemala studies. The modules on assets at marriage were similar to those used in the Philippine study (Quisumbing, 1994), but were adapted for specific country conditions.
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies examine demographic variables (e.g., fertility histories, age at marriage), it is possible that these aspects of the data are less reliable than the economic modules. These caveats need to be borne in mind when interpreting some of the regression results, particularly those on age at marriage. We use these data to estimate similar regressions for all countries: (1) regressions on levels of human capital (education), age at marriage, and assets at marriage, separately for husband and wife, as a function of parental background for each spouse, the population sex ratio (ratio of females to males of mean sample marriageable age, an indicator of the “marriage market squeeze”) in the 5-calendar-year interval during which the marriage took place, and the year of marriage; and (2) regressions on differences in age, human capital, and assets at marriage between husband and wife, as a function of the year of marriage, the sex ratio when the marriage took place, and differences in the corresponding parental background variables. The second set of regressions enables us to examine whether schooling differences, age differences, and asset differences are changing through time, controlling for parental background effects. Our results show that both husbands and wives are more educated and older in more recent marriages. Although husbands bring more physical assets to marriage than wives, trends in physical assets at marriage are less clear cut. Asset values of husbands increase through time in four countries, and remain constant in the Philippines and Ethiopia. Asset values of wives increase in three countries (South Africa, Mexico, and Guatemala), remain constant in the Philippines and Ethiopia, and decline in Bangladesh. In terms of differences between spouses, in four out of six countries, age differences between husband and wife have decreased; the exceptions are the Philippines and South Africa where females marry relatively later. In three out of six countries, husband-wife gaps in schooling attainment at marriage have also decreased. Despite trends toward equality in education and age, the distribution of assets at marriage continues to favor husbands. In three out of six countries, the husband-wife asset difference has not changed through time—and therefore continues to favor husbands—and has increased in the other three countries. The reduction of husband-wife gaps in schooling and age argue well for an improvement in the balance of power within the family, but asset ownership continues to favor husbands. Persistent differences in assets in favor of men have important implications for household well-being and the welfare of future generations, given recent findings which show that increasing women’s status and control of assets has favorable effects on a number of human capital outcomes, particularly of the next generation.
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 7-1 Description of Data Sets Country Description of Data Country-Level Descriptors Bangladesh Project title: Commercial Vegetable and Polyculture Fish Production in Bangladesh: Their Impacts on Income, Household Resource Allocation and Nutrition % urbana 23.9 Survey coverage and dates: 955 rural households; 4 rounds of data collection from June 1996 to September 1997 % literateb Female: 29.3 Study sites: The data were collected as part of an impact evaluation of vegetable and fish pond technologies being disseminated in rural areas through nongovernmental organizations (NGOs). The survey sites were areas where new Consultative Group for International Agricultural Research (CGIAR) technologies had been introduced but their impact not yet evaluated. CGIAR technology is highly prevalent in rural Bangladesh. These areas are in no way unusual relative to others in rural Bangladesh. Male: 51.7 Estimated earned incomec Female: 1,076d Sampling design and notes: In each of the 3 survey sites (47 villages total), 3 types of households were identified: A households—NGO member adopting households in villages where the technology has been disseminated (A villages); B households—NGO member likely adopter households in villages where the technology has not been introduced (B villages); and C households—a sampling of all other households in both types of villages (C villages). The general sampling approach involved a multistage design using unique sampling methodologies in each site that randomly selected the A, B, and C villages followed by the A, B, and C households. Male: 1,866d Collaborator: Data Analysis and Technical Assistance, Dhaka, Bangladesh Philippines Project title: Gender Differences in Schooling and Land Inheritance % urbana 57.7 Survey coverage and dates: 275 rural households; Round 1–1989, Round 2–1996-1998 % literateb Female: 94.9
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Study sites: The five survey sites are rice-growing villages that were surveyed by the International Rice Research Institute for a study on the differential impact of modern rice technology (1985-1986). These are typical rice-growing villages that span the range of environmental conditions, from fully irrigated to rainfed. Male: 95.3 South Africa Estimated earned incomec Sampling design and notes: For this survey, the data came from two retrospective surveys conducted in 1989 covering 339 households and a resurvey in 1997 covering 275 of the same sample households in 1989. Female: 2,684 Male: 4,910 Collaborators: Tokyo Metropolitan University and International Rice Research Institute Ethiopia Project title: Gender and Intrahousehold Resource Allocation % urbana % literateb 17.2 Survey coverage and dates: 1399 rural households; 4th-round data were collected from May to December 1997 Female: 31.8 Male: 42.8 Survey sites: This survey added a 4th-round to a panel collected by IFPRI, the Centre for the Study of African Economies, and Addis Ababa University (CSAE/AAU) in 1994-1995. Six of the 15 village sites were originally surveyed by IFPRI in 1989 for the Ethiopia Famine Project. IFPRI added 3 villages to the sample in 1994 for a study assessing vulnerability to droughts. The rest of the other villages represent different ecological zones. Although not nationally representative, the sample is representative of the country’s agroecological zones. Estimated earned incomec Female: 414d Male: 844d Sampling design and notes: The original sample size of 1,500 households was decided jointly by IFPRI and CSAE/AAU. The sample was to be allocated based on the wereda (the level of administration next to region) population of each site, with a minimum of 60 households per site. Collaborators: CSAE/AAUa
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Country Description of Data Country-Level Descriptors Project title: KwaZulu-Natal Income Dynamics Study % urbana 50.1 Survey coverage and dates: 1,200 rural and urban households; Round 1 – August-November 1993, Round 2 – March-June 1998 % literateb Female: 84.2 Survey sites: This was a resurvey of households in the KwaZulu-Natal area that were part of the 1993 national survey of South Africa. IFPRI has access to the 1993 data set. KwaZulu-Natal is 43% urban and has a slightly higher proportion of inhabitants of Indian descent than other provinces. Its poverty, education, unemployment, and infrastructure indicators are just slightly worse than the country average, but the majority of these differences are not statistically significant. It has a higher than average HIV/AIDS prevalence (South Africa Department of Social Development, 2000). Male: 85.7 Estimated earned incomec Female: 5,473d Male: 12,452d Sampling design and notes: The sampling design was a two-stage, self-weighting procedure. In the first stage, clusters were chosen proportional to population size from census enumeration areas or approximate equivalents where not available. In the second stage, all households in each chosen cluster were enumerated and then a random sample of them selected. In 1998, only African and Indian households were targeted. Sample is representative at the province level. Collaborators: University of Natal-Durban and University of Wisconsin
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Mexico Project title: Evaluation of the National Program for Education, Health, and Nutrition (Programa Nacional de Educación, Salud, y Alimentación [PROGRESA]) % urbana 74.2 % literateb Guatemala Survey coverage and dates: 24,000 households in rural Mexico; census survey in November 1997 (ENCASEH) to select beneficiary households; evaluation surveys (Encuesta Evaluation de los Hogares or ENCEL) in March 1998 (prior to distribution of benefits); October/November 1998 (ENCEL98O), June 1999 (ENCEL98M), and November 1999 (ENCEL99N). The module on family background and assets at marriage was fielded as a part of the June-July 1999 round (ENCEL99M). Female: 89.1 Male: 93.1 Estimated earned incomec Survey sites: 506 localities in the seven states of Guerrero, Hidalgo, Michoacan, Puebla, Queretaro, San Luis Potosi, and Veracruz. Of the 506 localities, 320 localities were assigned to the treatment group (T=1) and 186 localities were assigned as controls (T=0). Female: 4,486 Male: 12,184 Sampling design and notes: The 320 treatment localities were randomly selected using probabilities proportional to size from a universe of 4,546 localities that were covered by phase II of the program in the 7 states mentioned above. Using the same method, the 186 control localities were selected from a universe of 1,850 localities in these 7 states that were to be covered by PROGRESA in later phases. The coverage of the program in its final phase constitutes around 40% of all rural families and one ninth of all families in Mexico. Collaborators: Programa Nacional de Educación, Salud, y Alimentación, Mexico; University of Pennsylvania; Yale University and University of California
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Country Description of Data Country-Level Descriptors Project title: Strengthening and Evaluation of the Hogares Comunitarios Program in Guatemala City % urbana 39.4 % literateb Survey coverage and dates: 1,340 urban households in Guatemala City, surveyed in 1999 Female: 60.5 Survey site: Site was one of three areas where the Hogares Comunitarios Program was operating in Guatemala City at the time of the survey. Characteristics of this area did not differ from other two program areas. All program areas were among the lower half of the urban socioeconomic strata. The study site is representative of urban poor areas of the country. Male: 75.6 Estimated earned incomec Sampling design and notes: This survey was designed to provide a qualitative and quantitative assessment of the operations and impact of the Hogares Comunitarios Program, a day care program under the auspices of the office of the First Lady of Guatemala. Two surveys were carried out: a random sample of 1,340 households with preschool children, and an impact evaluation sample of 550 households with preschool children divided into participating and control households. The current manuscript uses the random sample data. Female: 1.691d Male: 5,622d Collaborator: Staff from the Programa de Hogares Comunitarios aUnited Nations, Human Development Report 2001. Rates as of 1999. bUnited Nations, Human Development Report 2001. Age 15 and above in 1999. cUnited Nations, Human Development Report 2001. Figures are PPP US$ (Purchasing Power Parity—see technical note 1 in HDR 2001 report). Note: Because of the lack of gender-disaggregated income data, female and male earned income are crudely estimated on the basis of data on the ratio of the female nonagricultural wage to the male nonagricultural wage, the female and male shares of the economically active population, the total female and male population and GDP per capita (PPP US$) (see technical note 1 in HDR 2001 report). Unless otherwise specified, estimates are based on data for the latest year available during 1994-1999. dUnited Nations, Human Development Report 2001. Note: No wage data available. For purposes of calculating the estimated female and male earned income, an estimate of 75 percent, the unweighted average for the countries with available data, was used for the ratio of the female nonagricultural wage to the male non-agricultural wage.
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies BACKGROUND AND METHODS Assets at Marriage and Bargaining Power The IFPRI studies collected data on assets at marriage and conditions surrounding marriage in order to arrive at quantifiable indicators of bargaining power within marriage that are exogenous to current marital decisions. While data on human capital at marriage, such as schooling, have been collected in numerous surveys, data on assets at marriage are relatively rare. This data collection effort was motivated largely by the desire to test the collective model of the household, which predicts that one’s share of resources received within a relationship will be determined by one’s bargaining power within that relationship.3 Because bargaining power is an elusive concept, candidate proxies for bargaining power have included: (1) public provision of resources to specific household members and exogenous policy changes that affect the intrahousehold distribution thereof (Lundberg, Pollak, and Wales, 1997; Rubalcava and Thomas, 2002); (2) shares of income earned by women (Hoddinott and Haddad, 1995); (3) unearned income (Schultz, 1990; Thomas, 1990); (4) current assets (Doss, 1999); (5) inherited assets (Quisumbing, 1994); and (6) assets at marriage (Thomas et al., 2002). Of course, none of these measures is perfect. In most contexts there is no public program that can serve as a natural experiment. Labor income, typically included in the calculation of income shares, is problematic because it reflects time allocation and labor force participation decisions that are likely to have been the result of some bargaining process within the marriage. Several studies use nonlabor income, either directly, or as an instrument for total income (Thomas, 1993). However, the assumption that nonlabor income is independent of tastes and labor market conditions may not be true if much of it comes from pensions, unemployment benefits, or earnings from assets accumulated over the lifecycle. Current asset holdings, used by Doss (1999) in her study of Ghanaian households, also may be affected by asset accumulation decisions made within marriage. Depending on provisions of marriage laws, assets acquired within marriage may be considered joint property and will not be easily assignable to husband or wife. The validity of inherited assets as an indicator of bargaining power may be conditional on the receipt of assets prior to marriage, unless bargaining power also depends on the expected value of inheritance. Inherited assets could also be correlated with individual unobservables, such as previous investments in the individual during 3 For a discussion of tests of the collective versus the unitary model of the household, see Haddad, Hoddinott, and Alderman (1997); Quisumbing and Maluccio (2003); Thomas and Chen (1994).
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies childhood (Strauss and Thomas, 1995). Assets brought to marriage, however, are plausible indicators of bargaining power that are not affected by the decisions made within the marriage—that is, they are exogenous to those decisions, although assets of husband and wife could be correlated if the marriage market is characterized by assortative matching. Differences in Other Husband-Wife Characteristics and Their Implications Although a clear body of evidence has begun to emerge on how husband versus wife assets affect various human capital investments and outcomes within the household, assets at marriage are only one aspect of the conditions surrounding marriage and later bargaining power within the union. Husband age and education seniority also have been used to connote male control over women (e.g., Cain, 1984; Miller, 1981). Education differences can be viewed as a proxy for differences in earning power, which carries bargaining power (e.g., Sen, 1989). For example, Smith and colleagues (2003) measure of women’s decision-making power relative to their male partners (usually their husbands) is based on four underlying indicators: whether a woman works for cash; her age at first marriage; the age difference between her and her husband; and the education difference between her and her husband. Aside from their use as proxies for differential economic resources, the effects of spouse age differences on power imbalances have not been well studied. One issue has to do with measurement error: Measurement error in the age variable is likely in low-literacy populations with unreliable civil registration systems. Another issue is the difficulty of predicting the effect of age differences outside a particular social and cultural context. Recent studies from sub-Saharan Africa, for example, show that wider age differences between sexual partners confer greater HIV vulnerability to young women (e.g., Gregson et al., 2002; Kelly et al., 2001), presumably via greater male sexual experience and their correlation with male wealth advantage in sexual relationships. However, the reverse effect could also be true if women, especially in patriarchal settings, derive status from their husband’s characteristics. This would imply that having a husband who is senior in age, education, or economic means would impart well-being (e.g, Kishor, 1995). The fact is that only a handful of studies have even documented the extent of such spouse differences. Notable exceptions include Luke and Kurz (2002), who in reviewing literature on the extent of age mixing in sexual relationships in sub-Saharan Africa find that a sizable proportion of sexual partners of adolescent girls are at least 6 to 10 years older. Hertrich (2002) documents trends in age at first marriage for men and women in
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Value of Assets at Marriage Tobit Husband Coeff t Wife Coeff t 310.33 3.59 47.37 3.19 −23,718.53 −0.99 −11,101.02 −2.70 −337.09 −0.20 −561.59 −1.74 −321.77 −1.59 −155.87 −0.42 56.87 1.07 −118.10 −2.16 −79.13 −0.43 611.11 3.27 −587,440.60 −3.25 −81,150.60 −2.62 976.00 976.00 16.42 57.45 0.00 0.00 0.00 0.01 Human capital at marriage has been increasing for both men and women in the majority of our study countries. In all six countries, years of schooling at marriage have increased for husbands and wives. Consistent with rising educational attainment, age at marriage is increasing for husbands and wives in the majority of countries; that is, men and women are marrying at later ages in more recent marriages. This upward trend can be observed for husbands in five out of six countries. Age at marriage for men is decreasing in Ethiopia, although the latter could reflect measurement error in the age variable. Women are also marrying at later ages in five out of six countries. In Ethiopia, age at marriage is decreasing, possibly reflecting both measurement error and isolation from outside forces
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 7-16 Determinants of (Husband-Wife) Differences in Years of Schooling, Age at Marriage, and Assets at Marriage, Guatemala, First Marriages, OLS with Robust Standard Errors Variance Name Years of Schooling Age at Marriage Coeff t Coeff t Coeff t Coeff t Year of marriage −0.02 −1.10 −0.10 −3.54 −0.10 −3.68 −0.01 −0.47 Sex ratio −0.06 −0.01 −9.07 −1.18 −9.17 −1.20 0.55 0.11 Indigenous ethnicity 1.51 4.05 −0.94 −1.93 −0.44 −1.03 0.78 1.95 Rural upbringing 0.88 2.43 1.13 4.56 Mother a single mom −0.01 −0.02 −0.86 −2.53 No. of brothers −0.01 −0.11 0.06 0.90 No. of sisters −0.18 −1.96 −0.01 −0.21 Mom worked for pay 0.18 0.58 0.46 2.03 Mother literate −0.56 −1.71 −0.73 −3.19 Constant 40.93 1.07 211.21 3.61 221.43 3.74 17.19 0.45 No. of observations 976.00 976.00 976.00 976.00 F-statistic 6.20 2.51 4.80 7.67 Prob > F 0.00 0.01 0.00 0.00 R-squared 0.02 0.03 0.02 0.06 NOTE: t-statistics in bold are significant at 10 percent or better. in these rural villages. In spite of considerable political turmoil over the past decades, local traditions regarding marriage and inheritance have remained relatively untouched, given the lack of roads and the relative isolation of the countryside.20 There is no clear trend regarding land ownership at marriage, although grooms seem to be bringing more physical assets to marriage in four out of six countries. In the two countries where land holding information is not aggregated with total assets, husbands’ land ownership at marriage remains constant in one case (Philippines) and declines in the other (Mexico). Land ownership at marriage by women is decreasing through time in the Philip- 20 This is not to say that local traditions have not changed at all—they have, especially in areas influenced by urbanization and labor migrations. But, in our opinion, they have changed much less than in African countries previously colonized by Europe.
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Value of Assets at Marriage Coeff t Coeff t 134.66 2.79 146.06 3.05 −12,030.85 −0.74 −8,569.73 −0.54 314.44 0.27 −39.64 −0.03 1,171.24 1.31 −987.86 −1.08 525.09 1.89 99.04 0.46 356.19 0.45 658.89 0.84 −24,9076.30 −2.60 −27,7950.70 −2.91 976.00 976.00 2.69 1.94 0.05 0.04 0.01 0.02 pines, and remains constant, though very low (less than 1 percent of marriages) in Mexico. Asset values of husbands increase through time in four countries, remaining constant in the Philippines and Ethiopia. Asset values of wives increase in three countries (South Africa, Mexico, and Guatemala), remain constant in the Philippines and Ethiopia, and decline in Bangladesh. (In the two countries for which we have data on marriage payments, trends have been in opposite directions: increasing for husbands and decreasing for wives in Bangladesh, and decreasing for both in South Africa.) We now turn to how differences in human capital, age, and assets at marriage between husband and wife have changed through time. In three out of six countries, husband-wife gaps in schooling attainment at marriage have decreased—pointing to an equalization of human capital at marriage. The exceptions are the Philippines, where the difference in years of schooling has not changed over time; Guatemala, where the evidence is mixed as to whether the difference is stable or falling; and Ethiopia, where the differ-
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 7-17 Trends by Marriage Year in Age, Human Capital, and Assets at Marriage Trends Husband Wife Difference (Husband-Wife) ASIA Bangladesh Years of schooling Increasing Increasing Decreasing Age at marriage Increasing Increasing Decreasing Value of assets + transfers at marriage (1996 taka) Increasing Decreasing Increasing Philippines Years of schooling Increasing Increasing Constant Age at marriage Increasing Increasing Constanta Land area at marriage Constant Decreasing Increasing Value of nonland assets (1989 pesos) Constant Constant Constant AFRICA Ethiopia Years of schooling Increasing Increasing Increasing Age at marriage Decreasing Decreasing Decreasing Value of assets at marriage (1997 birr) Constant Constant Constant South Africa Years of schooling Increasing Increasing Decreasing Age at marriage Increasing Increasing Constant Count of assets at marriage Increasing Increasing Constant Value of transfers from family at marriage (1998 Rand) Decreasing Decreasing Decreasing LATIN AMERICA Mexico Years of schooling Increasing Increasing Decreasing Age at marriage Increasing Increasing Decreasing Owned land at marriage (1 if yes) Decreasing Constant Decreasing Asset score Increasing Increasing Increasing Guatemalab Years of schooling Increasing Increasing Constant Age at marriage Constant Increasing Decreasing Value of assets at marriage (1999 Quetzales) Increasing Increasing Increasing a“Constant” implies that t-statistic on the marriage year variable is not significant at 10 percent or better, regardless of the magnitude of the coefficient. bGuatemala difference results are for the first specification reported in Table 7-16, without female family background variables.
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies ence is increasing. In the Philippines, there is no gender gap in schooling in current marriages (see Table 7-2), however, in urban Guatemala the difference is still greater than one year. The disturbing trend in Ethiopia is consistent with a leveling off of enrollment rates for girls and persistent through diminishing gender gaps in education in sub-Saharan Africa, a consequence of lack of improvement in public education facilities and high opportunity costs of education for girls.21 In line with the closing of the education gap, in four out of six countries, age differences between husband and wife have decreased—a move toward increasing equality, given the possibility that seniority and experience may give husbands a bargaining advantage over their wives. The two countries where the difference in age at marriage has not decreased are South Africa and the Philippines, the two countries where women’s age at marriage is the highest among our study countries. The distribution of assets at marriage continues to favor husbands. In three out of six countries, the husband-wife asset difference has not changed through time—and therefore continues to favor husbands—and has even increased in the two Latin American countries. Finally, transfers at marriage are increasingly favoring men in Bangladesh, while the gap in transfers at marriage is decreasing in South Africa. What do these trends imply for the distribution of power within marriage? The reduction of husband-wife gaps in age and schooling indicates a potential improvement in the balance of power within the family, but asset ownership continues to favor husbands. These findings from our data mirror changes in investment in human capital and asset ownership worldwide (Quisumbing and Meinzen-Dick, 2001). In general, investment in women’s human capital has improved markedly in the past 25 years: Life expectancy has increased 20 percent faster for females than for males, fertility rates have declined, and gaps in educational attainment have begun to close. However, gender gaps in physical assets and resources that women can command through available legal means continue to persist. In large part this is due to social and legal mechanisms that do not give women equal rights to own and inherit property, particularly land (Crowley, 2001; Gopal, 2001). Persistent differences in assets in favor of men have important implications for household well-being and the welfare of future generations, given recent findings that increasing women’s status and control of assets 21 Although the gender gap in schooling worldwide has decreased over time, girls’ primary enrollment rates have leveled off in sub-Saharan Africa at around 54 percent. Absolute levels of female enrollment and schooling remain lower in sub-Saharan Africa than in other developing regions, with female secondary enrollment rates of 14 percent in 1995 (World Bank, 2001).
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The Changing Transitions to Adulthood in Developing Countries: Selected Studies has favorable effects on child nutrition and education (Hallman, 2000; Quisumbing and Maluccio; 2003; Smith et al., 2003). These trends do not only affect the distribution of power within marriage, but also the role that marriage plays in the transition to adulthood. Rising education levels, particularly of women, increase the role of individual choice rather than parental choice of a spouse or partner. Indeed, the increasing importance of personal rather than parental characteristics in characterizing matches in the marriage market point to increased individual choice. At the same time, globalizing and modernizing economies raise the expectations of young people beyond traditional roles. Young people delay marriage in the hopes of getting payoffs for their educational investments in the form of secure and well-paying jobs (Caldwell et al., 1998). However, structural adjustment programs have altered the employment structure of many developing economies; with the contraction of the public sector, there are now fewer government and other types of jobs historically considered “good.” Transition to paid work, especially for adult males, often precedes the transition to marriage and adulthood; rising youth unemployment is associated with the feeling of frustration with the inability to move on in life. If marriage marks the transition to adulthood in most societies, this transition is being delayed, either due to the desire to stay in school or capture returns to schooling through employment, or to the inability to find gainful employment. The impact of this delayed transition on the institution of marriage itself deserves further investigation. REFERENCES Adato, M., de la Brière, B., Mindek, D., and Quisumbing, A. (2000). Final report: The impact of PROGRESA on women’s status and intrahousehold relations. Washington, DC: International Food Policy Research Institute. Ahmed, A., and del Ninno, C. (2002). The food for education program in Bangladesh: An evaluation of its impact on educational attainment and food security. (Food Consumption and Nutrition Division Discussion Paper No. 138.) Washington, DC: International Food Policy Research Institute. Anderson, J.N. (1962). Some aspects of land and society in a Pangasinan community. Philippine Sociological Review, 19, 41-58. Bloch, F., and Rao, V. (2002). Terror as a bargaining instrument: A case study of dowry violence in rural India. American Economic Review, 92, 1029-1043. Bouis, H.E., Palabrica-Costello, M., Solon, O., Westbrook, D., and Limbo, A.B. (1998). Gender equality and investments in adolescents in the rural Philippines. (Research Report No. 108.) Washington, DC: International Food Policy Research Institute. Brush, L., Heyman, C., Provasnik, S., Fanning, M., Lent, D., and De Wilde, J. (2002). Description and analysis of the USAID girls’ education activity in Guatemala, Morocco, and Peru. Report produced for the Bureau for Economic Growth, Agriculture, and Trade, Office of Women in Development, U.S. Agency for International Development.
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Representative terms from entire chapter: