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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries APPENDIX A Coverage, Definitions, Methods, and Data This appendix describes operational definitions adopted by the panel, approaches to data analysis, and chapter by chapter discussions of the specific data choices made and the reasons for those choices. The first section of the appendix presents data and methodological issues pertaining to the entire report as well as an introduction to Demographic and Health Survey (DHS) data, which are the only data used extensively in more than one chapter. The second section describes the data and methods used in each of the chapters in Parts II and III of the report. ENTIRE REPORT Coverage When data are presented in Chapters 3-8, countries are defined by the panel as developing if they fit the following criteria: (1) location in Africa, Asia, or Latin America and the Caribbean, using United Nations (UN) regional groupings, and (2) classification by the World Bank (2002b) as low, lower-middle, and upper-middle-income countries as of 2000. When the panel judged there to be sufficient coverage in terms of countries within regional groupings for a particular topic, regional averages were presented according to geographic and income categories. For the summary data on the size and distribution of young people in developing countries presented in Table 2-1, we use the United Nations definition of developing countries: “Less developed regions comprise all regions of Africa, Asia (except Japan),
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Latin America and the Caribbean plus Melanesia, Micronesia and Polynesia” (United Nations, 2003d:46). Regional Groups Geographical Categories: The panel grouped developing countries into eight geographic regions, which were constructed from the geographic subregions used by the United Nations for its population estimates and projections (United Nations, 2003b). For the purposes of the panel report, Latin America and the Caribbean consists of two subregions (the Caribbean and Central America1 and South America), sub-Saharan Africa consists of two subregions (Western and Middle Africa and Eastern and Southern Africa), Asia includes three subregions (Eastern Asia, South-central, and Southeastern Asia, and former Soviet Asia, which includes eight former Soviet countries from South-central and Western Asia), and the Middle East combines two subregions (Western Asia and Northern Africa). Wherever the data coverage was deemed sufficient to allow population-weighted estimates by geographic region, these are the categories used. This was typically the case for the DHS survey data as well as for the UN data base on marriage prevalence. Income Groups: The World Bank classifies countries (“economies”) into four economic groups. In 2000 the range for each of these four groups was as follows: low income (gross national income of $755 or less), lower-middle income ($756 to $2,995), upper-middle income ($2,976 to $9,266), and high income ($9,267 or more) (World Bank 2002b).2 Whenever the data allowed estimates by country income category, the panel used the first three country income categories described above. 1 Mexico is included in the Central America and Caribbean region even though in some international contexts (e.g., NAFTA) it is considered to be part of North America. 2 Gross national income is in current U.S. dollars converted using the World Bank Atlas method. The purpose of the Atlas conversion factor is to reduce the impact of exchange rate fluctuations in the cross-country comparison of national incomes. A full explanation can be found on page 380 of World Bank (2002b). Updates of country income groupings on the World Bank Website: http://www.worldbank.org/data/countryclass/classgroups.htm as of September 30, 2002, led the panel to make a few adjustments to these country groupings, including shifting Korea into the high-income group (and therefore out of the developing country group) and adding East Timor in the low-income category, for which no data on income were provided in World Bank (2002b).
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Approaches to Data Analysis Trends: The working group decided to concentrate primarily on data on recent trends, ideally the last two decades of the twentieth century wherever possible. In cases in which recent trend data were not available, we focused primarily on data that were sufficiently recent to characterize contemporary patterns and interrelationships. Two approaches were used to measure trends: (1) a comparison of comparable data collected for surveys or censuses at two separate points in time, and (2) cross-cohort comparisons within a single recent survey based on the retrospective reporting of specific experiences or events during the transition to adulthood. Age Ranges: The working group decided not to set a rigid range of ages but to explore broad age ranges that would allow a full exploration of transitions. For practical purposes, this usually meant concentrating on ages 10-24, but not always when transitions were found to continue until later ages. In several cases, constraints associated with available data limited our ability to analyze the most conceptually appropriate age group. For example, the DHS surveys restrict their samples of individual women or men, generally to the 15-49-year-old age range. The World Values Surveys do not interview youth younger than age 18. Mortality data by cause as estimated by the World Health Organization (WHO) are presented only for an aggregated age group: 15-29. Population Weights: To provide the basis for statements about broad regional and global trends in cases in which there were sufficient data from each regional grouping to allow some representativeness, data were aggregated by region and income level and weighted according to the size of the population of young people ages 10-24 in 2000 (United Nations, 2001). The aggregated data were produced by calculating a weighted average of a particular statistic using as a weight for each country the percentage of the population of young people from countries with available data that are estimated to reside in that country. When data are available for two periods in time, we weighted both figures with the UN 2000 population estimates. Holding the weight constant allows us to attribute any apparent change between the two years to changes in the indicator rather than changes in the weights (allowing us to look at the average change over the time span). Demographic and Health Surveys The panel used Demographic and Health Surveys extensively for Chapter 3 on schooling, for a few topics in Chapter 4 (sex and contraceptive
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries use), extensively in Chapter 7 on marriage, and exclusively in Chapter 8 on parenthood. Although other data on these topics are available, the DHS data have the special advantage of allowing comparative analysis over time and across countries while controlling for important social and economic factors like urban and rural residence, socioeconomic status, and education level. For each topic treated, all DHS data from publicly accessible surveys fielded since 1990 that included data for the topic in question were used (see Table A-1). The number of countries included in each analysis varied from 49 to 52 in the education, marriage, and parenthood chapters to as few as 39 in the case of a few topics—sex and contraceptive use—presented in the health chapter. This smaller sample of countries was necessitated because data on these topics for adolescents were not available for countries in which the DHS data were limited to ever-married women samples. Using the full sample of 52 countries, we can make certain generalizations about the timeliness and representativeness of the DHS. Survey years range from 1990 to 2001 and all but 7 of the 52 surveys were conducted post-1995. The median year of the 52 surveys is 1998. Fewer surveys (32) include data on men, mostly but not exclusively in Latin America and the Caribbean and Africa. The specific number of surveys included in each analysis varies for a variety of reasons, including (1) whether the survey interviewed all women regardless of marital status or only ever-married women of reproductive age, (2) whether a specific question was asked, and (3) whether the data were available at the time the tables were compiled. Table A-1 provides a listing of all the DHS data sets included in the panel sample along with sample sizes. The sample sizes for the survey of women of reproductive age varied from a little over 3,000 for the small island of Comoros to over 90,000 for the most recent sample in India. Typically, the samples of men are much smaller in size. The DHS data also include a household roster with some basic data on all household members, including the schooling level and current schooling participation of all household members. Together, the 52 DHS surveys of females provide representative data for 90 percent of the population of low-income countries as defined by the World Bank in 2000, 19 percent of the population in lower middle-income countries, and 53 percent of upper middle-income countries (see Table A-2 for regional and income categories). Thus, overall the DHS data are most representative of the experience in the poorest countries. In addition, DHS surveys of females are representative of the populations in Eastern and Southern Africa (92 percent), South-central and South-eastern Asia (86 percent), Western and Middle Africa (75 percent), South America (74 percent), and the former Soviet Asia (68 percent), but they are less representative of all women in the Middle East (55 percent) and the Caribbean and
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Central America (21 percent) (see Table A-2). They include no countries from Eastern Asia, most importantly China, which has over a fifth of the developing world’s young people. DATA FOR INDIVIDUAL CHAPTERS The panel’s working group on data reviewed data on each topic for quality and coverage before deciding whether or not to treat a topic and, when choices were available, determined which data were best to provide the most accurate and comprehensive information on a particular topic. Chapter 3: Schooling Since 1990, the Demographic and Health Surveys have included comparable questions on school attendance and attainment in all household surveys. In the absence of comparable census data, we have chosen to rely on DHS data for this report, supplemented when available by data on schooling from other household surveys to describe trends and patterns of schooling participation and attainment. These surveys allow us to calculate not only current schooling attendance rates, but also various cohort measures of schooling participation, grade attainment and progression between levels to estimate trends consistently over the past 20 years—a particular goal for the overall panel report. They also allow us to report current attendance figures according to household wealth categories and urban-rural residence. Before making this choice of data source as our primary source for the analysis of schooling patterns and trends, we carefully reviewed the pros and cons of United Nations Education, Scientific and Cultural Organization (UNESCO) data versus DHS data. These considerations are discussed below. These DHS data are supplemented for Latin America with a collection of household surveys assembled by the Inter-American Bank from the mid-1980s to mid-1990s that covers roughly 93 percent of the population of Latin America and includes more countries than available from DHS in the upper middle-income category (Behrman, Duryea, and Székely, 1999a) and for China with data on eight provinces from the China Health and Nutrition Survey (Hannum and Liu, 2005).3 The enrollment ratios published by UNESCO are the most widely used international statistics on education for measuring progress over time and 3 Unfortunately, we were not able to acquire data from the 2000 China census that would allow us to make comparable tabulations.
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries TABLE A-1 List of Countries with Recent DHS Surveys Used in Analysis, Including Estimates of Youth Population, Dates of Surveys, Sample Sizes, and Chapters in Which Data Were Used Country Survey Date(s) Youth Population, 10-24 UN Data Base 2000 (in thousands) Household Sample Size Armenia 2000 1,068 5,980 Bangladesh 1999-2000 44,726 9,854 Benin 1996 (2001) 2,115 5,796 Bolivia 1998 2,601 12,109 Brazil 1996 50,868 13,283 Burkina Faso 1998-1999 3,976 4,812 Cameroon 1998 4,996 4,697 Central African Republic 1994-1995 1,199 5,551 Chad 1996-1997 2,491 6,840 Colombia 2000 12,346 10,907 Comoros 1996 240 2,252 Côte d’Ivoire 1998-1999 5,595 2,122 Dominican Republic 1996 (1999) 2,603 8,831 Egypt 2000 21,991 16,957 Ethiopia 1999 19,988 14,072 Gabon 2000 348 6,203 Ghana 1998-1999 6,581 6,003 Guatemala 1998-1999 3,830 5,587 Guinea 1999 2,637 5,090 Haiti 2000 2,881 9,595 India 1998-2000 298,291 92,486 Indonesia 1997 64,059 34,255 Jordan 1997 1,610 7,335 Kazakhstan 1999 4,631 5,844 Kenya 1998 11,306 8,380 Kyrgyz Republic 1997 1,533 3,672
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Female Sample Size 15-49 Male Sample Size* Chapters in Which Data Were Used Education Health Marriage Parenthood 6,430 1,719 Y Y Y Y 10,544** 2,556 Y Y Y 6,219 2,709 Y Y Y Y (2001) 11,187 3,780 Y Y Y Y 12,612 2,949 Y Y Y Y 6,445 2,641 Y Y Y Y 5,501 2,562 Y Y Y Y 5,884 1,729 Y Y Y Y 7,454 2,320 Y Y Y Y 11,585 Y Y Y Y 3,050 795 Y Y Y Y 3,040 886 Y Y Y Y 8,422 2,279 Y Y Y Y 15,573 Y Y Y 15,367 2,607 Y Y Y Y 6,183 2,004 Y 4,843 1,546 Y Y Y Y 6,021 Y Y Y Y 6,753 1,980 Y Y Y Y 10,159 3,171 Y Y Y Y 90,303 Y Y Y 28,810 Y Y Y 5,548 Y Y Y 4,800 1,440 Y Y Y Y 7,881 3,407 Y Y Y Y 3,848 Y Y Y Y
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Country Survey Date(s) Youth Population, 10-24 UN Data Base 2000 (in thousands) Household Sample Size Madagascar 1997 5,025 7,171 Malawi 2000 3,722 14,213 Mali 2001 3,652 12,285 Morocco 1992 9,501 6,577 Mozambique 1997 5,848 9,282 Namibia 1992 572 4,101 Nepal 2001 7,152 8,602 Nicaragua 1997 (2001) 1,715 11,528 Niger 1998 3,505 5,928 Nigeria 1999 37,637 7,647 Pakistan 1990-1991 44,432 7,193 Paraguay 1990 1,751 5,683 Peru 2000 8,058 28,900 Philippines 1998 24,319 12,407 Rwanda 2000 2,689 9,696 Senegal 1992-1993 (1997) 3,082 3,528 South Africa 1998-2000 13,715 12,247 Togo 1998 1,496 7,517 Turkey 1998 19,311 8,059 Uganda 2000-2001 7,757 7,885 United Republic of Tanzania 1999 11,845 7,000 Uzbekistan 1996 8,152 3,703 Vietnam 1997 25,053 7,001 Yemen 1991-1992 5,563 12,836 Zambia 1996-1997 (2001-2002) 3,521 7,286 Zimbabwe 1999 4,489 6,369 NOTE: Y = Yes. * Male sample age ranges vary by country, falling within 12-70 years. ** Female sample age range 10-49 for this country.
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Female Sample Size 15-49 Male Sample Size* Chapters in Which Data Were Used Education Health Marriage Parenthood 7,060 Y Y Y Y 13,220 3,092 Y Y Y Y 12,817 3,390 Y Y Y Y 9,256 1,336 Y Y Y 8,779 2,335 Y Y Y Y 5,421 Y Y Y Y 8,726 2,261 Y Y Y 13,634 2,912 Y Y Y Y (2001) 7,577 3,542 Y Y Y Y 9,810** 2,680 Y Y Y Y 6,611 1,354 Y Y Y 5,827 Y Y Y 27,843 Y Y Y Y 13,983 Y Y Y 10,421 2,717 Y Y Y Y 6,310 1,436 Y Y (1997) Y (1997) Y (1997) 11,735 Y Y Y Y 8,569 3,819 Y Y Y Y 8,576 1,971 Y Y Y 7,246 1,962 Y Y Y Y 4,029 6,000 Y Y Y 4,415 Y Y Y Y 5,664 Y Y Y 5,687 Y Y 8,021 1,849 Y Y Y Y 5,907 2,609 Y Y Y Y
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries TABLE A-2 Demographic and Health Surveys (DHS) Country Sorted by Region Regiona Most Recent Survey * = includes Male Survey Dominican Republic Carib/CA 1996 * Guatemala Carib/CA 1998-1999 Haiti Carib/CA 2000 * Nicaragua Carib/CA 1997-1998 * Comoros E/S Africa 1996 * Ethiopia E/S Africa 1999 * Kenya E/S Africa 1998 * Madagascar E/S Africa 1997 Malawi E/S Africa 2000 * Mozambique E/S Africa 1997 * Namibia E/S Africa 1992 Rwanda E/S Africa 2000 South Africa E/S Africa 1998 Tanzania E/S Africa 1999 * Uganda E/S Africa 2000-2001 * Zambia E/S Africa 1996-1997 * Zimbabwe E/S Africa 1999 * Egypt ME 2000 Jordan ME 1997 Morocco ME 1992 Turkey ME 1998 *b Yemen ME 1991-1992 Bolivia SA 1998 * Brazil SA 1996 * Colombia SA 2000 Paraguay SA 1990 Peru SA 2000 * Bangladesh SC/SE Asia 1999-2000 India SC/SE Asia 1998-2000 Indonesia SC/SE Asia 1997 Nepal SC/SE Asia 2000-2001
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Country Sorted by World Bank Income Categories Income Most Recent Survey * = includes Male Survey Armenia Low 2000 *b Bangladesh Low 1999-2000 Benin Low 1996 * Burkina Faso Low 1998-1999 * Cameroon Low 1998 * Central African Republic Low 1994-1995 * Chad Low 1996-1997 * Comoros Low 1996 * Côte d’Ivoire Low 1998-1999 * Ethiopia Low 1999 * Ghana Low 1998-1999 * Guinea Low 1999 * Haiti Low 2000 * India Low 1998-2000 Indonesia Low 1997 Kenya Low 1998 * Kyrgyz Republic Low 1997 Madagascar Low 1997 Malawi Low 2000 * Mali Low 2001 * Mozambique Low 1997 * Nepal Low 2000-2001 Nicaragua Low 1997-1998 * Niger Low 1998 * Nigeria Low 1999 * Pakistan Low 1990-1991 Rwanda Low 2000 Senegal Low 1997 * Tanzania Low 1999 * Togo Low 1998 * Uganda Low 2000-2001 *
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Country Sorted by Region Regiona Most Recent Survey * = includes Male Survey Pakistan SC/SE Asia 1990-1991 Philippines SC/SE Asia 1998 Vietnam SC/SE Asia 1997 Armenia Soviet 2000 *b Kazakhstan Soviet 1999 *b Kyrgyz Republic Soviet 1997 Uzbekistan Soviet 1996 Benin W/M Africa 1996 * Burkina Faso W/M Africa 1998-1999 * Cameroon W/M Africa 1998 * Central African Republic W/M Africa 1994-1995 * Chad W/M Africa 1996-1997 * Cote d’Ivoire W/M Africa 1998-1999 * Gabon W/M Africa 2000 *c Ghana W/M Africa 1998-1999 * Guinea W/M Africa 1999 * Mali W/M Africa 2001 * Niger W/M Africa 1998 * Nigeria W/M Africa 1999 * Senegal W/M Africa 1997 * Togo W/M Africa 1998 * aKey: Carib/CA (Caribbean and Central America); E/S Africa (Eastern and Southern Africa); ME (Middle East [Northern Africa and Western Asia]); SA (South America); SC/SE Asia (South-central and South-eastern Asia); Soviet (Former Soviet Asia); W/M Africa (Western and Middle Africa). bMale survey data are available for these countries, but not in sufficient number to allow aggregation of data to generate regional averages. for making cross-national comparisons. Annual enrollment data provided by UNESCO are based on enrollments as reported officially by schools to national ministries of education. These annual enrollment counts are divided by United Nations estimates for the population for the year and ages in question to derive gross or net enrollment ratios for each level of schooling. Gross enrollment ratios, which are available for almost all countries for
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Country Sorted by World Bank Income Categories Income Most Recent Survey * = includes Male Survey Uzbekistan Low 1996 Vietnam Low 1997 Yemen Low 1991-1992 Zambia Low 1996-1997 * Zimbabwe Low 1999 * Bolivia Lower middle 1998 * Colombia Lower middle 2000 Dominican Republic Lower middle 1996 * Egypt Lower middle 2000 Guatemala Lower middle 1998-1999 Jordan Lower middle 1997 Kazakhstan Lower middle 1999 *b Morocco Lower middle 1992 Namibia Lower middle 1992 Paraguay Lower middle 1990 Peru Lower middle 2000 * Philippines Lower middle 1998 Brazil Upper middle 1996 * Gabon Upper middle 2000 *c South Africa Upper middle 1998 Turkey Upper middle 1998 *b cGabon data on women unavailable at time of this analysis; data on men do not include schooling. NOTE: Middle East, South-central, and South-eastern Asia are excluded from marriage chapter Table 7-9 because the surveys are based on ever-married samples. multiple decades, relate enrollment in primary or secondary levels regardless of age to the population age group appropriate to each level of schooling. Net enrollment ratios, which are confined to those enrolled in the eligible age range, are conceptually cleaner but less widely available particularly for earlier years, because many countries have not collected data on enrollment by age. Because these data are school based, they have
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries the potential to be broken down into geographic subgroupings but not by household characteristics, such as wealth. These enrollment data vary in quality according to the quality of the management information systems in each country. The development of good systems is a continuing challenge in many parts of the developing world (Moulton et al., 2001). School reform efforts, which often include improvements in management information systems that make current data more accurate, may compromise comparability over time. Furthermore, in some settings in which financial flows to schools are a function of the level of enrollment, there can be a substantial motivation to inflate reported enrollments. Some of the shortcomings of UNESCO enrollment data have been discussed in the literature (Behrman and Rosenzweig, 1994; Hewett and Lloyd, 2005; Lloyd, Mensch, and Clark, 2000). While some researchers feel comfortable relying on the enrollment data from UNESCO for trends and cross-country comparisons (e.g., Behrman and Sengupta, 2002), others doubt that the inherent biases in the data are sufficiently consistent across countries or over time to permit firm comparative conclusions about levels, trends, and differentials (Hewett and Lloyd, 2005; Lloyd et al., 2000). With the establishment of the UNESCO Institute of Statistics (UIS) in 2001, the international community has taken some important steps to improve systems of reporting on literacy and schooling, including launching several special initiatives with the Organisation for Economic Co-operation and Development (OECD) and the World Bank to strengthen the collection and reporting of comparative statistics and indicators. The World Education Indicators program (WEI) launched in 1997 is one example. This program now includes 17 developing countries (Argentina, Brazil, China, Egypt, India, Indonesia, Jamaica, Jordan, Malaysia, Paraguay, Peru, the Philippines, the Russian Federation, Thailand, Tunisia, Uruguay, and Zimbabwe). Eventually this program will permit comparisons between developed and developing country data on a more consistent basis. Recently, Bruns, Mingat, and Rakotomalala (2003) from the World Bank have used UNESCO data to calculate a primary school completion ratio using data from UNESCO on end of year enrollments in the last year of primary school (if available) or beginning-of-year enrollment data for the last year of primary school adjusted for repeaters. These estimates of numbers graduating from primary school are divided by UN estimates of the population of official graduation age to simulate a completion rate and are available now to assess changes in the 1990s. Relative to data on enrollment from UNESCO, data on school attendance and attainment derived from censuses and national sample surveys have some advantages and some disadvantages. The major advantages in-
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries clude (1) the fact that the data for the numerator and the denominator of any indicator are based on the same underlying population, thus allowing the construction of proper cohort-specific indicators on a consistent basis over time, (2) that data collected from households are more likely to capture current attendance rather than opening-day enrollment, thus providing a much more realistic measure of school participation, and (3) that attendance rates from household data can be compared by household income or wealth groups as well as other household characteristics. The disadvantages of household data include the facts that (1) they often are only collected periodically rather than annually, (2) differential mortality across education groups can bias the estimation of trends,4 and (3) in the case of household surveys, changing sample frames over time can compromise the comparability of successive surveys. Despite their advantages, household survey data rarely have been used for comparative analysis of educational trends, because of their lack of accessibility on a comparable basis. There has never been an international education survey program similar to the DHS program. Census data are published with a huge lag and, despite much UN technical assistance over the years, often lack comparability when presented in tabular form in printed reports (Lloyd et al., 2000).5 The fact that DHS data were collected on schooling on a comparable basis has allowed us to take advantages of some of the benefits offered by household data for the study of trends in schooling across countries and regions. See Table A-1 for the list of countries included in the presentation of data on schooling. The data presented on standardized text scores come primarily from Programme for International Student Assessment (PISA) of the Organisation for Economic Co-operation and Development (OECD) (Organisation for Economic Co-operation and Development, 2001) and from the Third International Mathematics and Science Study (TIMSS) undertaken in 1999 by the International Study Center at Boston College—both international efforts with some participation of developing countries. 4 When using cross-sectional cohort data to estimate trends, there is the danger that growth in schooling attainment will be underestimated if there is differential mortality by schooling in the relevant age groups. Given that we are comparing age groups between 10-14 and 30-34, for which group mortality rates are relatively low, this is unlikely to be a serious source of bias (Lloyd et al., 2000). 5 There are several current efforts to make census data more accessible: Integrated Public Use Microdata Series (IPUMS, http://www.ipums.umn.edu) based at the University of Michigan and the African Census Analysis Project based at the University of Pennsylvania (http://www.acap.upenn.edu).
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Chapter 4: Health The panel relied on multiple sources of data for the health chapter, depending on the topic. Data on mortality and morbidity were taken from WHO and the Joint United Nations Programme on HIV/AIDS. DHS surveys were used to analyze data on sexual initiation and on contraceptive use (see Table A-1). While data on sex and contraceptive use among young people have also been collected by the Centers for Disease Control and Prevention as part of their Young Adult Reproductive Health Survey, relatively few developing countries (as defined by the panel) have participated in these surveys and the data are not as easily accessible.6 The global tobacco surveys were used to describe levels and trends in smoking worldwide. For some topics, regional and global averages were not constructed, either because coverage was limited or because data were available for an insufficient number of countries. Chapter 5: Work The panel relied on data from labor force surveys provided by the International Labour Organization’s LABORSTAT (http://laborsta.ilo.org/ from November 24, 2003) trends in labor force participation rates, data on population trends from the UN Population Division, and data collected by the Population Council on time use. To analyze trends in transitions to education and to work for seven case study countries, the panel used large public-use samples from the two most recent censuses for Mexico (1990 and 2000), Kenya (1989 and 1999), and Vietnam (1989 and 1999), which are available from the IPUMS-International web site at the University of Minnesota (www.ipums.umn.edu), as well as the 1992 and 1999 surveys of Brazil’s Pesquisa Nacional por Amostra de Domicilios (PNAD); the 1993 South Africa Integrated Household Survey, SALDRU/World Bank and September 2000 South Africa Labour Force Survey, Statistics South Africa, courtesy of David Lam (University of Michigan); the Child Health and Nutrition Survey in China from 1989 and 1997 (http://www.cpc.edu/dataarch/primary), courtesy of Emily Hannum (University of Pennsylvania); and the 1987 Social and Economic Survey of Households, Statistical Center of Iran, and the 1998 Household Expenditure and Income Survey, Statistical Center of Iran, courtesy of Djavad Salehi-Isfahani (Virginia Polytechnic University). These data were also used in Chapter 7. Other data, typically using countries as examples, were drawn from previously published analyses and used to illustrate various points. 6 See http://www.cdc.gov/reproductivehealth/gp_spanrhs.htm.
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Chapter 6: Citizenship After an initial exploration of a range of data sets including the World Values Surveys, AfroBarometer surveys, LatinoBarometer surveys, and UNICEF young voices surveys, the panel decided to rely primarily on data from the World Values Surveys collected for the first time in a large sample of developing countries in 1995-1998. This survey project is guided by a steering committee representing all regions of the world. Coordination and distribution of the data are based at the Institute for Social Research at the University of Michigan under the direction of Ronald Inglehart. While this choice meant that we have very little coverage for Africa (except Nigeria, which has about a fifth of the continent’s population), we thought that the sampling procedures for the World Values Surveys were better documented than were alternative sources, such as the Afro- and Latino-Barometer surveys. Because of small sample sizes, however, we thought we needed to allow larger age ranges (18-34, 35+) in order to have a sufficient sample size to explore gender differences. These data were supplemented for some topics by published data from the UNICEF young voices surveys. More recent versions of the World Values Surveys (1999-2000) and AfroBarometer Surveys (1999-2000) are better documented and include more developing countries; however, neither of these newer data sets were publicly available at the time that this chapter was being completed. Chapter 7: Marriage In order to analyze marriage patterns, in particular trends in age at first marriage, it would be desirable to have accurate marriage registration data for at least two points in time. Such data are rarely available for developing countries. The United Nations Population Division collects data on the percentage of the population married in five-year age groups for most developing countries. For the most part, these data are available for men as well as women. For this analysis, we consider all countries in Africa, Asia, and Latin America and the Caribbean, with the exception of those identified by the World Bank as “high income” and those with a population under 140,0007 in population (World Bank, 2002b). Given the focus on trends, we have identified 73 countries of the 117 that meet our criteria for which recent data,8 i.e., data collected in 1990 or later, are available and for which there is information from two censuses or surveys at least 10 years apart (see Table A-3). In 2000, the United Nations estimated that 7 If a country had fewer than 140,000 in population, the UN did not provide an exact population figure. 8 There are a total of 152 countries in the three regions: 13 of these have fewer than 140,000 in population, 17 are listed by the World Bank as high income, and 5 have no World Bank income data, leaving 117 that meet our criteria.
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries TABLE A-3 United Nations Database on Marriage Sorted by Region Sorted by Region Categories Country Regiona Census/Survey Year 1 Census/Survey Year 2 Belize Carib/CA 1980 1991 Dominican Republic Carib/CA 1981 1996 El Salvador Carib/CA 1971 1992 Guatemala Carib/CA 1973 1990 Haiti Carib/CA 1989 2000 Mexico Carib/CA 1980 1990 Nicaragua Carib/CA 1971 1998 Panama Carib/CA 1980 1990 Puerto Rico Carib/CA 1980 1990 Trinidad and Tobago Carib/CA 1980 1990 Botswana E/S Africa 1981 1991 Burundi E/S Africa 1979 1990 Comoros E/S Africa 1980 1996 Ethiopia E/S Africa 1984 2000 Kenya E/S Africa 1969 1998 Malawi E/S Africa 1987 2000 Mauritius E/S Africa 1972 1990 Mozambique E/S Africa 1980 1997 Namibia E/S Africa 1960 1991 Rwanda E/S Africa 1978 1996 South Africa E/S Africa 1985 1996 Tanzania E/S Africa 1978 1996 Uganda E/S Africa 1969 1995 Zambia E/S Africa 1980 1999 Zimbabwe E/S Africa 1982 1999 China EA 1987 1999 Bahrain ME 1981 1991 Egypt ME 1986 1996 Jordan ME 1979 1994 Morocco ME 1982 1994 Occ. Palestinian Territory ME 1967 1997 Sudan ME 1983 1993 Tunisia ME 1984 1994 Turkey ME 1980 1990 Argentina SA 1980 1991 Bolivia SA 1988 1998 Brazil SA 1980 1996 Chile SA 1982 1992 Colombia SA 1973 1993 Ecuador SA 1974 1990 Guyana SA 1980 1991 Paraguay SA 1982 1992 Peru SA 1981 1996
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Sorted by World Bank Income Categories U.N. Marriage Data Country Income Census/Survey Year 1 Census/Survey Year 2 Azerbaijan Low 1989 1999 Bangladesh Low 1981 1991 Benin Low 1979 1996 Burkina Faso Low 1985 1999 Burundi Low 1979 1990 Cambodia Low 1962 1998 Cameroon Low 1987 1998 Central African Republic Low 1975 1994-1995 Chad Low 1964 1996 Comoros Low 1980 1996 Côte d’Ivoire Low 1978 1994 Ethiopia Low 1984 2000 Gambia Low 1983 1993 Haiti Low 1989 2000 India Low 1981 1992-1993 Indonesia Low 1980 1990 Kenya Low 1969 1998 Kyrgyz Republic Low 1989 1999 Malawi Low 1987 2000 Mali Low 1976 1995-1996 Mauritania Low 1988 2000-2001 Mozambique Low 1980 1997 Myanmar Low 1973 1991 Nepal Low 1981 1991 Nicaragua Low 1971 1998 Niger Low 1988 1998 Pakistan Low 1981 1998 Rwanda Low 1978 1996 Senegal Low 1978 1997 Sudan Low 1983 1993 Tanzania Low 1978 1996 Uganda Low 1969 1995 Zambia Low 1980 1999 Zimbabwe Low 1982 1999 Belize Lower Middle 1980 1991 Bolivia Lower Middle 1988 1998 Cape Verde Lower Middle 1980 1990 China Lower Middle 1987 1999 Colombia Lower Middle 1973 1993 Dominican Republic Lower Middle 1981 1996 Ecuador Lower Middle 1974 1990 Egypt Lower Middle 1986 1996 El Salvador Lower Middle 1971 1992
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Sorted by Region Sorted by Region Categories Country Regiona Census/Survey Year 1 Census/Survey Year 2 Uruguay SA 1985 1996 Venezuela SA 1974 1990 Bangladesh SC/SE Asia 1981 1991 Cambodia SC/SE Asia 1962 1998 India SC/SE Asia 1981 1992-1993 Indonesia SC/SE Asia 1980 1990 Iran SC/SE Asia 1986 1996 Malaysia SC/SE Asia 1980 1991 Maldives SC/SE Asia 1985 1995 Myanmar SC/SE Asia 1973 1991 Nepal SC/SE Asia 1981 1991 Pakistan SC/SE Asia 1981 1998 Philippines SC/SE Asia 1980 1995 Thailand SC/SE Asia 1980 1990 Azerbaijan Soviet 1989 1999 Kazakhstan Soviet 1989 1999 Kyrgyz Republic Soviet 1989 1999 Benin W/M Africa 1979 1996 Burkina Faso W/M Africa 1985 1999 Cameroon W/M Africa 1987 1998 Cape Verde W/M Africa 1980 1990 Central African Republic W/M Africa 1975 1994-1995 Chad W/M Africa 1964 1996 Côte d’Ivoire W/M Africa 1978 1994 Gabon W/M Africa 1961 2000 Gambia W/M Africa 1983 1993 Mali W/M Africa 1976 1995-1996 Mauritania W/M Africa 1988 2000-2001 Niger W/M Africa 1988 1998 Senegal W/M Africa 1978 1997 aKey: Carib/CA (Caribbean and Central America); E/S Africa (Eastern and Southern Africa); ME (Middle East [Northern Africa and Western Asia]); SA (South America); SC/SE Asia (South-central and South-eastern Asia); Soviet (Former Soviet Asia); W/M Africa (Western and Middle Africa). there were 1.4 billion young people ages 10-24 in these 117 countries; 87 percent or 1.2 billion were resident in the 73 countries for which marriage trend data are available. Because of the difficulty of interpreting such large volumes of information, we have aggregated these data by UN geographic groupings.
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Sorted by World Bank Income Categories U.N. Marriage Data Country Income Census/Survey Year 1 Census/Survey Year 2 Guatemala Lower Middle 1973 1990 Guyana Lower Middle 1980 1991 Iran Lower Middle 1986 1996 Jordan Lower Middle 1979 1994 Kazakhstan Lower Middle 1989 1999 Maldives Lower Middle 1985 1995 Morocco Lower Middle 1982 1994 Namibia Lower Middle 1960 1991 Occ. Palestinian Territory Lower Middle 1967 1997 Paraguay Lower Middle 1982 1992 Peru Lower Middle 1981 1996 Philippines Lower Middle 1980 1995 Thailand Lower Middle 1980 1990 Tunisia Lower Middle 1984 1994 Argentina Upper Middle 1980 1991 Bahrain Upper Middle 1981 1991 Botswana Upper Middle 1981 1991 Brazil Upper Middle 1980 1996 Chile Upper Middle 1982 1992 Gabon Upper Middle 1961 2000 Malaysia Upper Middle 1980 1991 Mauritius Upper Middle 1972 1990 Mexico Upper Middle 1980 1990 Panama Upper Middle 1980 1990 Puerto Rico Upper Middle 1980 1990 South Africa Upper Middle 1985 1996 Trinidad and Tobago Upper Middle 1980 1990 Turkey Upper Middle 1980 1990 Uruguay Upper Middle 1985 1996 Venezuela Upper Middle 1974 1990 Coverage varies considerably by region, with approximately 90 percent or more of the population represented by these data in Eastern and Southern Africa, South-central and South-eastern Asia, Eastern Asia, South America, and the Caribbean and Central America, but only 63 percent represented in the Middle East, 31 percent represented in Western and
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Growing Up Global: The Changing Transitions to Adulthood in Developing Countries Middle Africa, and 38 percent represented in the former Soviet Asia. Note that Eastern Asia consists entirely of China, as data are unavailable for the two other countries, Mongolia and North Korea. Populous countries for which data are unavailable include Afghanistan, the Democratic Republic of the Congo, Iraq, Nigeria, Saudi Arabia, Uzbekistan, and Vietnam. The Demographic and Health Surveys provide additional information to what is available from the United Nations data base (see Tables A-1 and A-2). Respondents’ specific age at first marriage is obtained on these surveys, enabling the calculation of the proportion married by a particular age rather than just the percentage of a particular group who are married. In addition, they enable one to examine differentials in the timing of marriage by schooling attainment, place of residence and household economic status and may therefore provide insights into the forces behind the changes we have observed. The one drawback is that the surveys have been conducted in fewer countries than we have UN data for. Note that regions vary considerably in the number of countries for which DHS surveys have been conducted. Coverage is highest in Eastern and Southern Africa, with approximately 92 percent of the population represented, and lowest in the Caribbean and Central America, where, because no recent survey is available for Mexico—by far the largest country—only about one-fifth of the population is represented. It is also important to keep in mind that no data are available for Eastern Asia, which includes China. Note, however, there are a few countries for which DHS data are available that are not included in the UN database: Armenia, Ghana, Guinea, Madagascar, Nigeria, Togo, Uzbekistan, Vietnam, and Yemen). Indeed, for two regions, Western/Middle Africa and Former Soviet Asia, coverage is considerably higher in the DHS at 75 percent and 68 percent, respectively. As with the UN data, the regional analyses based on the DHS data are weighted averages. Chapter 8: Parenthood All data, for the parenthood chapter, are based on DHS surveys (see earlier discussion of DHS data as well as Tables A-1 and A-2).
Representative terms from entire chapter: