1. 1 Assortative Mating Patterns in the Developing World Albert Esteve* and Robert McCaa** Presented by: Sula Sarkar** * Centre d ’ Estudis Demogr à fics **Minnesota Population Center, University of Minnesota IUSSP International Seminar on Changing Transitions to Marriage: Gender Implications for the Next Generation

2. 2 Data source: IPUMS 1. Preserve census microdata and documentation for all the countries in the world 2. Integrate microdata and metadata 3. Disseminate--without cost--extracts of samples to bona- fide researchers worldwide, regardless of country of birth, citizenship or residence. » Sustained, major funding since 1999 by: » National Science Foundation (USA) » National Institutes of Health (USA) » https://international.ipums.org/international/

3. 3 IPUMS-International census microdata, Sept. 2008 dark green = already integrated (35 countries, 111 censuses, 263 millon person records) green = to be integrated (40 countries, 104 censuses, 150 mill.) Mollweide projection www.ipums.org

4. 4 Introduction Basic concepts Homogamy versus hetrogamy Hypergamy versus hypogamy Unions between people with similar characteristics make up the predominant pattern Impact of education on assortative mating patterns

5. 5 Objectives Study effect of changes in age at marriage and increasing schooling on the prevalence and conditions of unions in various contexts of the developing world Assess levels of educational homogamy in eight developing countries How do gender differences in educational attainment translate into gender differences in heterogamy

6. 6 Countries included in this study

7. 7 Samples included in study Census Sample Fraction (%) Total Persons records (IPUMSI database) Weighted Brazil 19915.88,522,740Yes Brazil 2000610,136,022Yes China 1982110,039,191 – China 1990111,835,947 – Colombia 1993103,213,657 – Colombia 2005104,117,607Yes India 19830.2623,494Yes India 19930.2564,740Yes India 20050.2602,833Yes Iraq 1997101,944,278 – Kenya 198951,074,098 – Kenya 199951,407,547 – Mexico 1990108,118,242 – Mexico 200010.610,099,182Yes Philippines 1990106,013,913Yes Philippines 2000107,417,810Yes South Africa 1996103,621,164Yes South Africa 2001103,725,655Yes Vietnam 198952,626,985Yes Vietnam 199932,368,167Yes

8. 8 Hypothesis -- Higher levels of educational homogamy correspond to groups located at the extremes of the hierarchy. -- Positive relationship between gender inequalities in access to education and levels of educational hypergamy.

9. 9 Methodology -- Sampling methods: stratified sampling stratified cluster sampling (2005 Colombia, 2000 Mexico, all India samples) -- Variables of interest: “ever married” and “never married” educational homogamy -- Statistical Methods Loglinear models Logistic regression

10. 10 Percentage of never married (nor in union) by sex and country (ages 30 - 34), last census available NOTE: Brazil 2000; China 1990; Colombia 2005; Iraq 1997; Kenya 1999; Mexico 2000; Philippines 2000; South Africa 2001; India 2005

11. 11 Estimated log odds ratios from a logistic regression of the highest educated (univ. degree) and never married (age 25-34) NOTE: Brazil 2000; China 1990; Colombia 2005; Iraq 1997; Kenya 1999; Mexico 2000; Philippines 2000; South Africa 2001; India 2005

12. 12 Distribution of women (age 15 - 34) in union by educational attainment and country NOTE: Brazil 2000; China 1990; Colombia 2005; Iraq 1997; Kenya 1999; Mexico 2000; Philippines 2000; South Africa 2001; India 2005

13. 13 Distribution of men (age 15 - 34) in union by educational attainment and country NOTE: Brazil 2000; China 1990; Colombia 2005; Iraq 1997; Kenya 1999; Mexico 2000; Philippines 2000; South Africa 2001; India 2005

14. 14 Distribution of women (age 30 - 34) in union by educational homogamy - heterogamy and country

15. 15 HomogamyHypergamy Estimated log odds ratios from a loglinear regression of overall educational homogamy and hypergamy (women age 15 - 34)

16. 16 Less than Primary Primary Completed Estimated log odds ratios from a loglinear regression of educational homogamy by educational attainment, Women ages 15 - 34

17. 17 Secondary CompletedUniversity Completed Estimated log odds ratios from a loglinear regression of educational homogamy by educational attainment, Women ages 15 - 34

18. 18 Concluding remarks Availability of international census microdata offers an unprecedented opportunity to carry out cross-national research on marital homogamy and other topics Significant changes are underway as union formation, particularly for females, is postponed to the mid-twenties and beyond. The proportions of never-marrying (or not in union) increase Educational attainment is an important factor in all these developments While homogamy rules everywhere, there is a surprising shift away from the conventional heterogamous pattern It is the female who brings greater educational attainment to the union than the male There are important differences between and within broad cultural regions

19. 19 Thank you!! Albert Esteve: aesteve@ced.uab.es Robert McCaa: rmccaa@umn.edu Sula Sarkar: sula@socsci.umn.edu aesteve@ced.uab.esrmccaa@umn.edusula@socsci.umn.eduaesteve@ced.uab.esrmccaa@umn.edusula@socsci.umn.edu