The Changing Transitions to Adulthood in Developing Countries Selected Studies (2005) / Chapter Skim
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7 Marriage in Transition: Evidence on Age, Education, and Assets from Six Developing Countries--Agnes R. Quisumbing and Kelly Hallman
7 Marriage in Transition: Evidence on Age, Education, and Assets from Six Developing Countries--Agnes R. Quisumbing and Kelly Hallman
Pages 200-269
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From page 200... ...
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.
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From page 201... ...
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.
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From page 202... ...
.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.
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From page 203... ...
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")
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From page 204... ...
204 d d 23.9 29.3 51.7 1,076 1,866 57.7 94.9 Descriptors b earned b a a c urban literate urban literate Country-Level % % Female: Male: Estimated income Female: Male: % % Female: fish Their June for their of (B and villages villages but in from member types of unique 1996-1998 Group 3 villages 2 Bangladesh. types using C Bangladesh: introduced vegetable in collection of introduced total)
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From page 205... ...
205 d d continued 95.3 2,684 4,910 17.2 31.8 42.8 414 844 earned b earned a c c urban literate Male: Estimated income Female: Male: % % Female: Male: Estimated income Female: Male: rice of the for of surveys of the from Institute by modern range 275 Centre wereda 1994-1995. the decided of Ethiopia the the in assessing ecological of the minimum collected the was on a Research surveyed span retrospective impact covering were IFPRI, for study with that two Rice based were 1997 by a different data 1989 in (CSAE/AAU)
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From page 206... ...
206 d d 50.1 84.2 85.7 5,473 12,452 Descriptors b earned a c urban literate Country-Level % % Female: Male: Estimated income Female: Male: part is of were majority from second sample set. HIV/AIDS the size the Sample that and August- data In but random 1 area average inhabitants a 1993 targeted.
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From page 207... ...
207 continued 74.2 89.1 93.1 4,486 12,184 b earned a c urban literate % % Female: Male: Estimated income Female: Male: of by (T=0)
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From page 208... ...
208 port)
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From page 209... ...
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.
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From page 210... ...
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)
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From page 211... ...
examine spouse age differences in 28 developing countries using World Fertility Survey data; they find that age differences are generally largest in societies which are patriarchal and have patrilineal kinship organization (much of sub-Saharan Africa and the Middle East Crescent, and some of South Asia) , and smallest in settings where the traditional social structure allows for more equal status of spouses and/or where processes of modernization have improved the status of women (many in Southeast and East Asia, Latin America, and the Caribbean)
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From page 212... ...
; year of marriage is the reported year of marriage, which is the same for husband and wife; the sex ratio is the ratio of females to males of marriageable age in the 5-calendar-year interval when the marriage took place; human capital of parents is an indicator of the parents' educational attainment (usually years of schooling) ; physical capital of parents includes land holdings of parents (in some cases, disaggregated for fathers and mothers)
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From page 213... ...
Thus, the coefficients on the sex ratio variable should be interpreted with caution because it is a highly imperfect measure of the "marriage squeeze." We use year of marriage rather than year of birth as an explanatory variable because of difficulties in recalling birth year; because marriage is a more recent event, respondents were better able to recall the year of marriage, or the number of years they had been married. We do not include education as a regressor in the age at marriage equation because the same variables that determine age at marriage may also influence educational attainment, especially in societies where young women leave school to get married.
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From page 214... ...
. The reported values of these assets at the time of marriage have been converted to current values using the national consumer price index.
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From page 215... ...
.6 In no case are the transfers at marriage enough to overcome the value of the other resources including cattle and housing, that men bring to the union, however, as indicated by the husband's advantage in the sum total of prewedding assets and marriage transfer payments. Bangladeshi women have the youngest age of marriage across the six studies (Table 7-2)
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From page 216... ...
Years of schooling Value of assets at marriage (1997 birr) South Africa Age at marriage (years)
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According to this study, Filipino parents invest in
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From page 218... ...
Husband Wife Husband Wife Husband Wife Bangladesh 1930-1934 1 0.00 0.00 27.00 9.00 0.00 0.00 1935-1939 2 0.00 0.00 28.19 12.50 0.00 0.00 1940-1944 3 5.00 1.67 19.42 11.33 0.00 0.00 1945-1949 16 2.31 0.88 20.84 11.32 0.00 0.00 1950-1954 34 2.82 0.82 22.93 13.05 8,621.90 21,507.74 1955-1959 50 2.64 0.86 22.47 13.62 40,355.99 19,638.39 1960-1964 62 2.44 0.97 22.40 12.70 33,399.62 23,142.25 1965-1969 94 3.86 1.77 24.39 14.45 37,466.66 20,959.34 1970-1974 120 3.54 1.42 22.92 14.16 65,319.44 18,201.53 1975-1979 121 4.38 2.15 23.22 14.98 44,708.19 11,703.86 1980-1984 141 2.76 1.46 24.09 16.01 28,593.82 6,524.70 1985-1989 108 2.42 1.44 24.64 16.28 27,741.57 6,919.89 1990-1994 83 3.13 3.39 26.26 17.45 27,482.85 5,679.25 1995-1999 6 3.33 5.17 26.54 16.00 30,184.62 3,228.01 Years of Schooling Age at Marriage Land at Marriage No. Husband Wife Husband Wife Husband Wife Philippines 1925-1929 2 5.50 9.50 16.00 22.00 0.00 0.50 1930-1934 4 4.75 3.25 23.25 19.75 0.25 0.67 1935-1939 8 2.75 3.63 21.50 23.50 0.10 0.24 1940-1944 12 4.08 4.08 24.17 19.75 0.18 0.50 1945-1949 14 4.64 4.86 25.21 22.14 0.02 0.52 1950-1954 29 4.34 5.24 24.45 22.45 0.27 0.40 1955-1959 28 7.32 5.46 25.75 22.25 0.89 0.26 1960-1964 27 5.93 6.63 24.04 21.30 0.48 0.39 1965-1969 33 6.61 6.15 24.45 21.97 0.66 0.11 1970-1974 34 6.85 6.74 25.29 21.38 0.72 0.12 1975-1979 38 7.37 7.58 27.71 24.13 0.37 0.00 1980-1984 30 7.87 7.73 24.20 21.80 0.52 0.03 1985-1989 3 10.00 10.00 34.00 31.00 0.00 0.64
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From page 219... ...
MARRIAGE IN TRANSITION 219 Assets at Marriage Transfers to Sex Ratio Husband Wife Husband Wife 0.00 0.00 0.00 0.00 1.02 0.00 0.00 0.00 0.00 1.02 0.00 0.00 0.00 0.00 1.02 0.00 0.00 0.00 0.00 1.02 5,679.54 5,335.48 2,770.26 19,021.64 1.02 28,739.80 19,257.46 9,955.70 15,727.31 1.06 27,329.91 11,918.45 5,621.68 19,977.07 1.12 32,792.70 7,388.71 4,673.96 18,009.26 1.11 58,167.31 5,800.13 5,442.83 15,576.75 1.31 39,691.58 16,617.34 4,355.09 7,400.15 1.10 28,571.70 3,468.11 3,243.71 4,995.88 1.11 24,637.40 13,602.81 2,400.25 4,085.83 1.08 24,900.69 1,885.30 3,547.63 4,703.04 1.07 26,947.19 1,334.24 3,237.43 2,548.52 1.06 Assets at Marriage Sex Ratio Husband Wife 407.64 472.45 1.15 693.72 299.84 1.15 723.82 413.82 1.15 888.83 442.27 1.15 704.53 435.28 1.15 902.62 506.99 1.15 790.80 582.67 1.29 516.27 434.45 1.15 757.92 490.17 1.17 595.65 388.06 1.13 868.60 449.85 1.26 847.86 440.84 1.17 1,243.85 700.34 1.16 continued
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From page 220... ...
Husband Wife Husband Wife Ethiopia 1955-1959 144 0.69 0.08 31.68 20.11 1960-1964 56 0.67 0.09 25.52 16.44 1965-1969 84 1.20 0.36 23.76 15.72 1970-1974 62 2.29 1.00 23.65 16.32 1975-1979 72 2.31 1.03 24.08 17.01 1980-1984 99 2.86 1.52 24.17 17.98 1985-1989 53 3.29 1.24 26.29 19.43 1990-1995 1 5.00 0.00 50.25 46.25 Years of Schooling Age at Marriage Asset at Marriage No. Husband Wife Husband Wife Husband Wife South Africa 1950-1954 7 2.57 2.14 17.86 11.57 1.14 0.00 1955-1959 14 3.36 2.50 25.36 17.93 2.00 0.36 1960-1964 30 3.30 3.00 24.03 18.17 1.60 0.63 1965-1969 66 4.15 3.62 26.03 21.42 1.89 0.53 1970-1974 67 5.51 4.69 26.55 21.82 1.96 0.55 1975-1979 92 5.39 5.30 26.08 20.75 2.20 0.77 1980-1984 83 6.00 6.04 30.13 24.18 2.22 0.80 1985-1989 72 5.75 5.57 31.92 26.19 2.47 0.82 1990-1995 47 5.68 6.38 34.04 28.87 2.40 1.04 1995-1999 14 6.29 7.43 39.00 35.93 1.93 1.57 Years of Schooling Age at Marriage LATIN AMERICA No.
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From page 221... ...
MARRIAGE IN TRANSITION 221 Assets at Marriage Sex Ratio Husband Wife 6,664.50 2,360.70 1.37 6,661.85 3,450.78 1.38 4,964.11 1,789.68 1.39 3,818.32 2,548.83 1.39 2,925.50 1,233.61 1.39 2,873.41 1,059.34 1.45 2,565.61 1,133.21 1.47 1,605.21 500.00 1.45 Transfers From Sex Ratio Husband Wife 17,477.13 7,413.69 1.06 44,270.71 6,480.63 1.07 51,014.27 8,110.00 1.12 46,676.74 8,617.73 1.18 46,719.09 15,143.04 1.17 55,176.04 7,624.90 1.20 29,727.18 3,713.56 1.12 16,419.83 1,792.36 1.17 11,608.50 937.60 1.19 6,517.53 1,007.00 1.11 Land Assets Sex Ratio Husband Wife Husband Wife 0.00 0.00 0.00 0.00 1.15 0.00 0.00 0.00 0.00 1.15 0.21 0.00 0.01 0.01 1.15 0.23 0.00 0.02 0.02 1.15 0.16 0.01 0.01 0.02 1.15 0.15 0.00 0.01 0.01 1.15 0.15 0.01 0.02 0.01 1.15 0.15 0.00 0.01 0.01 1.14 0.15 0.01 0.02 0.01 1.20 0.14 0.00 0.02 0.01 1.19 0.14 0.00 0.02 0.01 1.24 0.14 0.01 0.02 0.01 1.24 0.13 0.01 0.02 0.01 1.22 0.12 0.01 0.03 0.01 1.26 0.11 0.00 0.03 0.01 1.24 0.13 0.00 0.04 0.02 1.10 continued
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From page 222... ...
of their parents and in-laws, their own and their spouses' education and inheritance, and schooling and proposed bequests to their children. Spouses were present during most of the interviews, facilitating collection of data on spouses' family background.7 The respondents were also asked about the transfers of land and assets received by each sibling regardless of whether the individual lived in the survey area or had migrated.8 7Wives of the predominantly male respondents usually answered the fertility and child schooling questions; questions on proposed bequests were answered jointly by husband and wife.
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From page 223... ...
bestowal were available were inflated to 1989 values using the farm gate rice price index for farm animals, farm assets, on-farm residential house and lot, or a region-specific CPI for readily tradeable consumer durables. Because mobility and fungibility of farm assets is limited, and the value of farm property is linked to returns on rice production, the rice price index may be a better adjustment factor than the CPI.
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From page 224... ...
Nonetheless, clear patterns emerge. On average men bring substantially more physical and human capital to the marriage than do women (Table 7-2)
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From page 225... ...
Although both husbands and wives appear to be obtaining more schooling through time, the improvement in schooling attainment seems to be greater for husbands. South Africa KwaZulu-Natal, South Africa's most populated province, is ethnically diverse, although not to the extent of Ethiopia.
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From page 226... ...
However, marriage payments from each 11The first South African national household survey, the Project for Statistics on Living Standards and Development (PSLSD) , was undertaken in the last half of 1993 (PSLSD, 1994)
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From page 227... ...
in February 1999 as a pilot. Based on the results of the pilot and further discussion with PROGRESA staff, a module on family background was fielded as a part of the June-July 1999 evaluation survey round.13 The module on family background and assets at marriage asked the wife to report whether or not she and her husband owned land, farm assets, farm animals, a house, or consumer durables at the time of marriage.
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From page 228... ...
Table 7-2 also indicates that husbands have more years of schooling than wives, suggesting that they enter a union with significantly more human capital as well. If, as the literature suggests, human and physical capital significantly influence bargaining power within marriage, rural Mexican husbands wield more power within their households than their wives.
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From page 229... ...
Because the purpose of the original study was to evaluate the benefits children and their mothers received from the Hogares Comunitarios day care program, family background information was not collected for husbands. Human capital information is available, however, for current husbands.
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From page 230... ...
Matching based on wedding transfer payments is greater than that on assets brought to marriage, while the correlation between parental land of spouses is higher than that with parental schooling. The strength of sorting based on personal versus parental characteristics is a possible indication of individual choice, as individuals -- particularly girls -- become more educated and exercise a stronger role in the choice of a spouse, even if marriages are still arranged by parents.
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From page 231... ...
Interestingly enough, the correlation between marriage payments is weak, and is turning negative, indicating both that traditional marriage systems are weakening, and that, instead of competing to bestow their children with assets, families of the bride and groom may "trade off" or compensate transfers from each side. While we have limited information on family background in the South Africa survey, the available data show that sorting along paternal education exists, and is stronger than that along maternal education.
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From page 232... ...
of Age at Years of Land at ASIA Marriages Marriage Schooling Marriagea Bangladesh 1945-1949 16 0.69 0.78 -- c 1950-1954 34 0.49 0.57 -1955-1959 50 0.71 0.80 -1960-1964 62 0.27 0.62 -1965-1969 95 0.58 0.72 -1970-1974 121 0.58 0.68 -1975-1979 122 0.56 0.68 -1980-1984 144 0.63 0.54 -1985-1989 108 0.63 0.49 -1990-1994 83 0.81 0.58 - Correlation Coefficients Between Husband and Wife No. of Age at Years of Land at Marriages Marriage Schooling Marriage Philippines 1930-1934 4 -- -- -1935-1939 8 -- -- -1940-1944 12 -- -- -1945-1949 14 0.73 0.51 0.10 1950-1954 29 0.86 0.37 0.09 1955-1959 28 0.78 0.05 0.10 1960-1964 27 0.64 0.54 0.30 1965-1969 33 0.75 0.53 0.48 1970-1974 34 0.18 0.44 0.02 1975-1979 38 0.70 0.63 0.03 1980-1984 30 0.59 0.13 0.20 1985-1989 3 -- -- - Correlation Coefficients Between Husband and Wife No.
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From page 233... ...
MARRIAGE IN TRANSITION 233 Assets + Assets to Transfers to Father's Transfersb Marriage Marriage Schooling -- -- -- -0.32 0.09 0.45 0.02 0.34 0.03 0.07 0.30 0.03 0.05 0.52 0.01 0.12 0.08 0.22 0.14 0.08 0.01 0.28 0.30 0.00 0.02 0.43 0.13 0.03 0.04 0.47 0.17 0.20 0.00 0.18 0.12 0.10 0.02 0.39 0.22 Assets at Father's Mother's Parents' Marriaged Schooling Schooling Land -- -- -- -- - -- -- -- - -- -- -0.80 0.27 0.44 0.37 0.91 0.12 0.22 0.02 0.58 0.13 0.50 0.25 0.57 0.07 0.11 0.15 0.79 0.38 0.65 0.24 0.76 0.25 0.56 0.20 0.90 0.29 0.25 0.12 0.80 0.41 0.04 0.09 -- -- -- - Assets at Father's Mother's Parents' Marriageb Schooling Schooling Land 0.20 0.02 -- 0.00 0.37 0.03 0.03 0.29 0.37 0.26 -- 0.46 0.01 0.28 -- 0.06 0.25 0.27 0.70 0.41 0.45 0.06 0.29 0.01 0.54 0.07 0.43 0.32 -- -- -- - continued
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From page 234... ...
of Age at Years of Marriage Payments South Africa Marriages Marriage Schooling From This Side 1955-1959 14 0.51 0.85 0.87 1960-1964 30 0.70 0.65 0.47 1965-1969 66 0.74 0.68 0.13 1970-1974 67 0.66 0.84 0.35 1975-1979 92 0.65 0.72 0.05 1980-1984 83 0.82 0.79 0.13 1985-1989 72 0.60 0.61 0.07 1990-1994 47 0.90 0.66 0.02 1995-1999 14 0.55 0.60 0.14 Correlation Coefficients Between Husband and Wife No. of Age at Years of Land at Latin America Marriages Marriage Schooling Marriagea Mexico 1930-1934 19 0.28 0.01 -1935-1939 53 0.36 0.58 -1940-1944 134 0.10 0.24 0.04 1945-1949 220 0.25 0.57 -1950-1954 437 0.25 0.30 0.09 1955-1959 679 0.35 0.30 0.02 1960-1964 904 0.33 0.39 0.04 1965-1969 1,233 0.37 0.38 -1970-1974 1,484 0.42 0.44 0.00 1975-1979 1,899 0.39 0.45 0.01 1980-1984 2,038 0.47 0.45 0.03 1985-1989 2,198 0.45 0.41 0.03 1990-1994 2,075 0.49 0.42 0.05 1995-1999 1,086 0.49 0.44 0.03 Correlation Coefficients Between Husband and Wife No.
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From page 235... ...
MARRIAGE IN TRANSITION 235 Assets at Father Has Any Mother Has Any Marriagee Educationf Educationf 0.37 0.15 0.21 0.52 0.43 0.39 0.47 0.54 0.53 0.41 0.65 0.36 0.47 0.49 0.35 0.33 0.42 0.39 0.39 0.55 0.39 0.39 0.50 0.27 0.63 0.28 0.03 Assets at Father's Mother's Parents' Marriageb Schooling Schooling Land 0.14 -- -- 0.14 0.44 -- -- 0.65 0.71 -- -- 0.16 0.29 0.50 0.71 0.43 0.19 0.40 0.58 0.55 0.21 0.00 0.00 0.30 0.25 0.39 0.77 0.24 0.16 0.44 0.38 0.37 0.23 0.36 0.23 0.29 0.19 0.23 0.23 0.31 0.18 0.31 0.23 0.27 0.19 0.30 0.16 0.27 0.24 0.17 0.23 0.25 0.18 0.30 0.13 0.34 dCorrelation coefficients not reported for cell sizes less than 14. eCount of assets.
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From page 236... ...
, Bangladesh Age at Marriage OLS with Years of Schooling Robust SEs Tobit Husband Wife Husband Variance Name Coeff t Coeff t Coeff t Year of marriage 0.04 1.88 0.10 4.54 0.09 4.10 Sex ratio 3.89 1.17 6.78 1.98 3.94 1.61 Own birth order 0.04 0.27 0.15 1.17 0.20 1.87 No. of brothers 0.03 0.17 0.16 1.05 0.03 0.22 No.
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From page 237... ...
. The female-to-male marriageable age population sex ratio at the time of the marriage has the effect of reducing women's schooling and age at marriage, consistent with a female competition for scarce males hypothesis.
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From page 238... ...
with of significant OLS are bold land in Determinants Bangladesh, in: 7-6 parents' Name schooling schooling marriage brothers sisters F of observations t-statistics > of of of ratio of TABLE Marriage, Variance Year Sex Differences No.
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From page 239... ...
In an earlier specification with assets and transfer payments entered separately, not reported here, it was found that net wedding transfer payments are made increasingly to husbands, consistent with evidence of dowry inflation in South Asia. The sex ratio significantly increases husband's schooling advantage.
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From page 240... ...
Father's schooling increases nonland assets of the wife, but has a slight negative effect on husband's land, probably because fathers with more schooling are likely to be working in nonagricultural occupations and may have less land. Mother's schooling has a positive and significant effect on wife's schooling, which is larger than the effect of father's schooling, and a negative (but only weakly significant)
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From page 241... ...
The only gap that seems to be increasing through time is that in land area: husbands are bringing more land to marriage than their wives. Although this may seem to increase the bargaining power of men within the household, it is offset by women's rising education levels and their increasing propensity to be employed in nonfarm jobs, which have higher returns to schooling (Estudillo et al.,
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From page 242... ...
242 0.81 1.15 0.13 1.66 t 1.37 0.91 0.95 Assets 1.97 0.99 1.31 0.25 0.04 Marriage, 24.11 755.26 16.17 13.36 259 at Nonland Coeff 4,459.98 Assets and 3.83 0.00 0.30 0.20 2.54 1.11 t 3.87 Schooling, 0.02 0.00 0.01 0.01 0.05 0.03 4.49 0.00 0.08 of Land Area Coeff 33.61 259 Years Age, 0.22 0.31 0.42 0.47 1.62 t 0.20 0.29 in of better. 0.00 1.28 0.02 0.02 0.22 0.70 0.65 0.04 Years Schooling Coeff 0.01 7.05 or 259 Differences percent Errors 10 at t 0.79 1.05 0.12 0.80 0.92 0.03 0.71 (Husband-Wife)
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From page 243... ...
.18 Husbands whose parents have more land appear to marry later, while those with more brothers marry earlier, perhaps because of the availability of substitutes for male labor on the family farm. Although human capital has been increasing at marriage, however, the real value of physical capital brought to marriage has not changed appreciably through time, contrary to the descriptive results.19 Parental land increases the value of assets that husbands bring to marriage, while mother's schooling increases the assets that wives bring.
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From page 244... ...
How have differences between husbands and wives changed over time? Age differences between husbands and wives have declined (Table 7-10)
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From page 245... ...
In contrast to its effects on levels, the sex ratio does not affect age differences between spouses nor differences in the resources that they bring to marriage. South Africa Table 7-11 presents regressions on years of schooling, age, asset counts, and transfers made at marriage of husband and wife.
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From page 246... ...
246 0.47 1.57 1.69 Marriage t 1.52 1.53 13.11 1.40 1.57 at Marriage, at Assets of 0.00 0.09 19.17 43.47 552 124.89 8,407.69 750.54 2,982.81 155.96 152.99 Assets Value Coeff 236,732.10 and Schooling, 1.72 3.82 0.04 of t 0.08 0.01 4.62 1.29 2.10 Years Schooling Age, of in 0.04 1.26 0.00 0.00 0.00 0.07 Years Coeff 0.55 0.01 0.05 11.81 76.84 525 better. or Differences 1.31 0.38 4.27 percent t 3.45 0.27 0.45 1.90 1.10 10 at (Husband-Wife)
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From page 247... ...
Both factors may delay marriage, in part by reducing family resources available for marriage ceremonies and bridewealth payments. Marginal increases in the female-to-male population sex ratio raise the value of bridewealth payments.
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From page 248... ...
A higher female-to-male marriageable age population ratio at the time of the wedding increases the marriage payments made by husbands. This result runs contrary to a "scarce husband hypothesis" and the same caveat as above applies.
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From page 249... ...
Mexico Table 7-13 presents regressions of the effects of parental characteristics on husband's and wife's schooling, age, land ownership, and asset scores. For both husband and wife, years of schooling increase with later marriage
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From page 250... ...
250 2.37 3.02 1.86 0.60 1.03 4.50 t 4.85 1.39 0.38 0.21 1.03 at Marriage 7.04 0.00 0.12 of 845.10 492.00 Assets 1015.40 9,275.94 3,613.20 769.80 23,929.24 2,248.93 1,001.00 155,126.70 10,446.60 Value Payments Coeff 1,837,739.00 Marriage, 1.37 5.19 1.26 0.53 1.02 2.30 0.49 at t 0.66 3.13 1.03 2.65 Assets Age of Errors Marriage 0.00 2.36 0.92 0.20 0.08 0.17 0.05 5.95 0.00 0.19 0.55 0.14 0.08 15.18 Count at Coeff 492.00 Schooling, of Standard 1.81 1.65 0.25 1.30 t 0.99 0.71 1.29 0.13 4.82 1.85 2.77 Years Marriage in Robust at 1.08 0.84 0.02 5.47 0.00 0.14 0.02 4.67 0.76 0.09 3.65 0.85 0.26 57.10 with Age Coeff 492.00 OLS Differences better. 0.26 1.46 0.79 0.62 0.55 0.72 0.77 2.61 t 2.59 2.49 0.19 or Africa, Schooling of 0.94 0.50 0.30 0.18 0.18 0.04 0.04 3.87 0.00 0.08 percent 0.03 0.98 0.05 60.61 South Years Coeff 492.00 10 at (Husband-Wife)
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From page 251... ...
The sex ratio has opposite effects for husbands and wives. A larger supply of women of marriageable age exerts downward pressure on women's age at marriage and increases men's age at marriage.
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From page 252... ...
Note, however, that because our land ownership measure is only a dummy variable for whether the husband or wife owned land at the time of marriage, this measure is more imprecise relative to the other measures of physical and human capital. The sex ratio affects years of schooling and asset score differences in opposite ways: A larger supply of females of marriageable age increases the schooling gap between husbands and wives, while it reduces the gap between husband and wife asset scores.
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From page 253... ...
It is then possible that, facing a larger supply of marriageable females, prospective grooms do not feel they need to accumulate more assets to be worthy candidates in the marriage market.
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From page 254... ...
A higher female-to-male marriageable age population ratio at the time of the wedding decreases the assets wives bring to marriage, perhaps be
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From page 255... ...
Indigenous ethnicity is associated with low levels of human capital (education) for both sexes, younger marriage age for men, and fewer assets brought to marriage by females.
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From page 256... ...
Differences in Age, Years of Schooling, Land Ownership, and Assets at Marriage, Mexico Age Years of Schooling OLS with Robust SE OLS with Robust SE Coeff t Coeff t Year of marriage 0.03 8.88 0.01 4.57 Sex ratio 1.39 1.55 1.28 2.34 Differences in: Father is literate 0.12 0.76 0.25 2.76 Mother is literate 0.10 0.58 0.31 3.20 Father has some primary schooling 0.09 0.56 0.10 1.05 Mother has some primary schooling 0.16 0.97 0.06 0.63 Father completed primary 0.21 0.56 0.42 1.95 Mother completed primary 0.26 0.63 0.05 0.18 Father wore shoes 0.22 1.33 0.08 0.91 Mother wore shoes 0.26 1.39 0.16 1.70 Parents' landholdings 0.02 2.31 0.01 1.43 Constant 6,5.91 9.25 15.06 4.39 No. of observations 1,1177 11,072 F-statistic 8.19 1,1.28 Prob > F 0.00 0.00 R-squared 0.01 0.01 Chisquared Prob > chi2 Pseudo R2 NOTES: t-statistics in bold indicate significance at 10 percent or better.
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From page 257... ...
Therefore, two versions of the difference results are presented: one with only year of marriage, population sex ratio, and ethnicity, and a second that also includes levels of family background characteristics for women. In the first specification, spouse age differences are declining over time, but male advantage in the value of assets brought to marriage is rising.
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From page 258... ...
The population sex ratio variable does not have any effect on spouse differences. SUMMARY AND CONCLUSIONS Table 7-17 presents a summary of trends in schooling, age, and assets at marriage, based on the regression coefficients on the year of marriage.
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From page 259... ...
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.
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From page 260... ...
Differences in Years of Schooling, Age at Marriage, and Assets at Marriage, Guatemala, First Marriages, OLS with Robust Standard Errors Years of Schooling Age at Marriage Variance Name Coeff t Coeff t Coeff t Coeff t Year of 0.02 1.10 0.10 3.54 0.10 3.68 0.01 0.47 marriage Sex ratio 0.06 0.01 9.07 1.18 9.17 1.20 0.55 0.11 Indigenous 1.51 4.05 0.94 1.93 0.44 1.03 0.78 1.95 ethnicity Rural 0.88 2.43 1.13 4.56 upbringing Mother a 0.01 0.02 0.86 2.53 single mom No. of brothers 0.01 0.11 0.06 0.90 No.
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From page 261... ...
, 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.)
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From page 262... ...
AFRICA Ethiopia Years of schooling Increasing Increasing Increasing Age at marriage Decreasing Decreasing Decreasing Value of assets at marriage Constant Constant Constant (1997 birr) 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 Decreasing Decreasing Decreasing family at marriage (1998 Rand)
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From page 263... ...
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.
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From page 264... ...
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.
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From page 265... ...
. Poverty, livelihood, and class in rural South Africa.
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From page 266... ...
. Age differences in sexual partners and risk of HIV-1 infection in rural Uganda.
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From page 267... ...
1993-1998: A longitudinal household database for South African policy analysis. Development Southern Africa, 17, 567-581.
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From page 268... ...
Pretoria, South Africa: Depart ment of Social Development, National Population Unit. Statistics South Africa.
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From page 269... ...
MARRIAGE IN TRANSITION 269 World Bank.
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Key Terms
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