Social closure among the higher educated: trends in educational ...

1Social closure among the higher educated: trends in educational homogamyin 55 countriesJeroen Smits(http://home.planet.nl/~smits.jeroen)AbstractIn this paper, loglinear analysis is used to assess for 55 countries - and for two age groups withinthese countries - the degree of educational homogamy among persons with a high educational level.These analyses are conducted to gain insight in (the factors that affect) the strength of the tendencytowards social closure among the educational elite of the countries. In all 55 countries, the highereducated tend to marry within their own group. However, the strength of this tendency differsconsiderably among the countries. These differences are explained in terms of the level of economicdevelopment, the dominant religion, and the size of the group of higher educated. In countries withhigher levels of economic development, in Protestant countries, and in countries with more personswith a high educational level, the tendency among the higher educated to marry within the own groupis lower than elsewhere. Besides differences among countries, trends within countries are studied,too. The results of this analysis indicate that in the decades after World War II, the openness of theeducational elite has increased in most of the countries.1. IntroductionThe study of intermarriage is a major source of information on the openness of the social structure ofsocieties (Glass 1954; Hout 1982; Ultee and Luijkx 1990). If there are many marital ties between themembers of different groups in a society, there must also be other social contacts - like friendships -between them. Furthermore, the children of different groups must have the opportunity to meet eachother -- at school, in the neighborhood, or during leisure activities. Moreover, if intermarriage amongthe members of different groups is a common phenomenon, this indicates that the members of thesegroups accept each other as social equals (Kalmijn 1998).In this paper the marriage behavior 1 of persons with a high educational level - and hence withgood prospects on the labor market - is studied for a large number of countries. A central objective ofthe research is to find out whether and to what extent persons with a high educational level tend toclose themselves off from the rest of society. The “closure thesis” (Parkin 1974; Goldthorpe 1980)poses that the privileged groups in a society will use their resources to protect their position and thatthey will not let in more persons than are needed to fill up the open places. One of the ways in whichthey accomplish this is by marrying within their own group (Weber [1921] 1972). This idea is supportedby many empirical studies, which show that marriage partners tend to resemble each other

2with regard to status characteristics like the social class of their parents (Blau and Duncan 1967;Kalmijn 1991; Uunk 1996), their educational level (Berent 1954; Rockwell 1976; Ultee and Luijkx1990) and - if both spouses are employed - their occupational level (Lipset and Bendix 1958; Hout1982; Smits, Ultee and Lammers 1999).The tendency to marry someone with the same educational level is called educational homogamy.In modern societies, this tendency is a very important form of social closure. In these societies,education plays a major role in the distribution of individuals over social positions. In fact, it hasbecome very difficult to acquire a favorable social position without the required education (Blau andDuncan 1967; Treiman 1970; Hauser and Sewell 1986). In modern societies, the effect of socialbackground on occupational placement also runs to a large extent via the educational channel(Jencks et al. 1979; Treiman and Jip 1989). A high educational level, therefore, has become animportant prerequisite for social success.This is not only true for one’s own educational level; it also applies to the educational level ofone’s spouse. A spouse with a high educational level may contribute to one’s societal success inseveral ways. Obviously, such a spouse - if he or she is engaged in paid employment - will generallyearn more and hence contribute more to the family income than a spouse with a lower educationallevel. But besides this direct advantage of the spouse’s educational level, there are also someindirect advantages. It is common knowledge that married persons may profit from their partner’sresources. The classic example is the resourceful father-in-law who helps his son/daughter-in-lawfinancially or arranges a job for him/her. But the knowledge, skills, and social networks of thespouses themselves are also important. Research on so-called spouse effects (Bernasco 1994) hasshown that individuals with a spouse who has a high educational level or a favorable labor marketposition tend to have a higher probability of being employed (Ultee, Dessens and Jansen 1988;Bernasco 1994) and to have higher occupational levels and earnings (e.g., Benham 1974; Kerckhoff1978; Smits, Ultee and Lammers 1996) than individuals whose spouse has a lower educational levelor a less favorable labor market position.Another reason to study educational homogamy is that educational homogamy may be a majorsource of social inequality. If individuals with a high educational level tend to select spouses with higheducational levels, individuals with less educational credentials have less choice. The only marriagecandidates left are those with lower educational levels. This may lead to a concentration of coupleswith two high educational levels at the upper end of society and a concentration of couples with twolow educational levels at the lower end of society. Thus, an unequal distribution of education overindividuals may be transposed via their marriage behavior into a larger inequality in the distribution ofeducation over couples (compare Ultee 1989; Bernasco 1994). The need for insight in this processhas become urgent because of the sharp rise in the labor force participation of married women inrecent decades in most countries of the world. If more married women with a high educational levelactually translate their education into a high-level occupation, income inequality among families mightincrease (Björklund 1992). After all, if the number of hours worked in a week is the same, womenwho have had more education can be expected to earn more money than women with a lowereducational level.Comparative researchBecause social closure among the higher educated may exacerbate social inequality, it is importantto understand the factors that influence educational homogamy among the members of this group.Comparative research can provide that insight. In cross-national or cross-temporal research,

3differences in the degree of educational homogamy among countries and/or time periods can berelated to differences in other characteristics of the countries and/or time periods. This is theapproach taken here.Large-scale cross-national research on educational homogamy was conducted earlier by Ulteeand Luijkx (1990) and by Smits, Ultee and Lammers (1998). These studies, which pertain to 23 and65 countries respectively, show that countries differ in their degree of educational homogamy. Theyalso show that these differences are related to differences in the countries’ level of economicdevelopment, to their dominant religion, and - for the least developed countries - their technologicalbackground. When the level of economic development of the countries increases, their degree ofeducational homogamy first increases, then reaches a peak, and subsequently decreases again.Furthermore, countries with a predominantly Protestant population show less educational homogamythan predominantly Catholic or Confucian countries and developing countries with a horticulturalbackground show less educational homogamy than developing countries with an agrarian background.These studies did not find any consistent relationship between the degree of politicaldemocracy and educational homogamy.To analyse the differences among countries in educational homogamy, both Ultee and Luijkxand Smits et al. used a rather general measure of educational homogamy, the loglinear stepparameter, which indicates the degree to which married persons in a country tend to have a spousewith a closely related educational level. This measure gives a good impression of the importance ofeducation in choosing a partner for the vast majority of the population of a country, but it does notgive insight in educational homogamy among specific educational groups. Therefore, these studiesdo not shed light on the tendency towards social closure among the higher educated. 2A further restriction of the work of Smits et al. is that they test hypotheses on the effect of level ofeconomic development on the basis of data for countries of different level of development at thesame point in time. Their conclusions, therefore, depend on the key assumption that with increasinglevel of development the pattern of educational homogamy changes in all countries in the same way.Because Smits et al. do not test the validity of this assumption, their conclusions with regard to theeffects of level of economic development are tentative. To draw more definitive conclusions, it isnecessary to study trends within countries, using data for more points in time or for different agegroups.In this paper, we follow the way set out by Smits et al. to study differences in educationalhomogamy among a large number of countries. However, instead of using a general indicator foreducational homogamy among the vast majority of the population, we focus on the tendency towardseducational assortative marriage of a more clearly defined educational group, which will be called the"higher educated". This group will be defined as persons who have at least completed secondaryeducation. In the most developed countries of the world, this group may not be very exclusive,because a rather large part of the population belongs to it. However, the countries which we studyalso include some of the least developed countries of the world, where the group of persons withcompleted secondary or higher education is very small and hence really forms an elite. By comparingthe tendency towards educational homogamy for the same educational group over a large range ofcountries, we hope to find out what happens to the boundary of an elite group when, with increasingdevelopment of the country, that group becomes less special. A second difference between thispaper and the work of Smits et al. is that the hypotheses on the effect of level of economic developmentare not only tested on the basis of differences among countries, but also on the basis ofdifferences among age groups of married couples within the countries. In this way we hope to be

5decrease in educational homogamy, as predicted by the romantic-love hypothesis, will mainly takeplace in the later phase of the industrialization process. By then, rising wages and social securitylaws will have decreased the dependency between parents and children and individuals will havemore freedom to marry whom they choose. Because of the predicted shape of the association, thishypothesis is called the inverted-U-curve hypothesis.The question of whether there is a trend toward more openness within industrial societies - ashas been predicted by industrialization theorists (Kerr et al. 1960; Treiman 1970) - has led to somedebate in the stratification literature. On the basis of an extensive study of 149 occupational mobilitytables for 35 countries, Ganzeboom, Luijkx and Treiman (1989) claim to have found such a trend.But Erikson and Goldthorpe (1992), using more strictly comparable data for nine countries, concludethat there are only "trendless fluctuations", and Wong (1994), using the same data as Ganzeboom etal., found this trend to be present in only a few countries. A possible explanation for these contradictoryfindings may be that the direction and strength of the trend vary over the different levels of thesocial structure. By focusing on only one social group, the educational elite, this paper may present amore restricted but also clearer picture of the presence and strength of this trend.Non-economic factorsBesides the level of economic development, cultural factors might influence the strength of educationalhomogamy among the higher educated. Smits and coauthors found both the dominant religionof a country and - for the least developed countries - the technological background to be related totheir degree of educational homogamy. With regard to dominant religion, the degree of traditionalismis expected to play an important role. In more traditional societies, children are expected to complywith the wishes of their social environment - especially their parents. As a result, status differenceswithin marriage will probably be considered more important. With regard to Western societies, thisreasoning leads to the prediction that Protestant countries are more open than Roman Catholiccountries. One indication is couched in Weber’s famous thesis that Catholicism takes a moretraditional position with regard to economic activities than Protestantism (Weber [1920] 1972). Giorgiand Marsh (1990) show that even in the highly secularized European societies of the 1980s, differencesin the work ethic still exist between Catholics and Protestants. Another indication, lying outsidethe area of work, regards marriage and the family. Castles (1994) shows that Catholics are moretraditional with regard to women’s rights and family politics. And Greeley (1989) found that Catholicsin several Western societies more than Protestants consider agreement on crucial issues andshared background with their spouses to be conditions for a successful marriage. Greeley alsoshows that Catholics in these countries generally live closer to their parents and other relatives andvisit them more often than Protestants. As a result, the possibilities for social control are greateramong Catholics. Together, these arguments make it plausible that Catholics are more traditionalwithin marriage than Protestants. Therefore, we expect to find more educational homogamy incountries with a predominantly Catholic population.With regard to non-Western societies, we expect Confucian and Islamic countries to be lessopen than Protestant countries. According to Weber ([1920] 1972), Confucianism - unlike Protestantism- does not espouse a world-view emphasizing man’s mastery over nature. Rather, it stressesthe adaptability of man to nature. The same has been said of Islam (Schluchter 1988, p. 102).However, yet another point may play a role. According to Tai (1989), the rapid economic developmentof the East Asian countries was stimulated by their Confucian tradition. It offered individuals the- unique - opportunity of social mobility via the educational channel (compare Weber [1920] 1972). If

6this is correct, education may be a good predictor of societal success in these countries and thusplay an important role in partner choice. The role of education might be more restricted in Islamiccountries. There, family relationships play an important role in partner selection (Atoun 1976).Furthermore, as a result of the low level of labor force participation of married women in thesecountries, the economic significance of the education of women might be lower than elsewhere.The hypothesis of Smits and coauthors about the technological background of the least developedcountries is less important for our analysis. The reason is that it concerns individuals working inagriculture, a group that generally has little education. Instead of testing their hypothesis, a new onewill be tested here. It poses that the tendency for higher educated people to marry within the owneducational group will be stronger when that group of persons is relatively smaller. The members ofa small elite will generally be much more aware of their exclusive position than the members of agroup that includes a large part of the population. Moreover, the value of a high educational level inthe marriage market may increase when fewer candidates with a high educational level are available.Persons with a high educational level, then, may increase their demands. In a society where educationis a valuable resource, one of these demands will probably be a high educational level. Theprediction that when the size of the group of higher educated is smaller the members of this groupwill tend to close themselves off from the rest of society more strongly will be called the exclusivityhypothesis.Trends within countriesAn important improvement over much of the foregoing cross national research is that trends withincountries are studied too. That allows more stringent testing of the hypotheses about effects ofeconomic development. Countries that differ in level of economic development may also differ in acertain way with regard to their levels of educational homogamy. But this does not necessarily meanthat educational homogamy within individual countries changes in the same way when the level ofdevelopment increases. According to Gagliani (1987, pp. 322-23), who developed the rationale forthe study of income inequality, hypotheses about the effects of economic development can be testedbetter by studying development within countries. This paper does just that by distinguishing two agegroups within each country.There is good reason to use data on trends within countries when testing hypotheses about theeffects of economic development. Except for brief periods of stagnation or crisis, in almost allcountries of the world the level of economic development rose steadily in the period between about1945 and 1975. That development comes to light when the proportion of the labor force workingoutside agriculture is used as indicator of level of development, as well as when the energy consumptionper capita or the GNP per capita is used (compare for example Taylor and Hudson 1972;Taylor and Jodice 1983). The three hypotheses on effects of economic development, therefore, canbe easily translated into predictions about differences between older and younger married couples.The prediction derived from the status-attainment hypothesis would be that younger couples willshow more educational homogamy than older couples. According to the romantic-love hypothesis,younger couples will show less educational homogamy than older couples. And according to theinverted-U-curve hypothesis, younger couples in the least developed countries will show moreeducational homogamy than the older couples, whereas younger couples in the most developedcountries will show less.

73. Data and methodsThe association between the educational levels of spouses is influenced by the degree to whichindividuals have a preference for a partner with a certain educational level, but it is also influenced bythe availability of partners with that educational level (Kalmijn 1998). If there are fewer women thanmen with a high educational level, as is the case in many countries, some highly educated men willnot be able to find a partner with a comparable educational level. If we want to use educationalhomogamy as an indicator of the openness of educational groups, we have to control for suchdifferences in the educational distributions of men and women and to measure what is called relativehomogamy (Ultee and Luijkx 1990). For this purpose, loglinear analysis will be used (Agresti 1990).To answer our research questions, we use representative data sets with individual level informationon married persons for 55 countries. These data sets are a subsample of the data sets used bySmits et al. (1998). The data pertain to the 1970s and early 1980s. For the analyses, the educationalvariables of these data sets were recoded into two categories: a category “higher education” consistingof all persons with a completed secondary or higher education; and a category “lower education”including all persons with an uncompleted secondary or lower education. In a number of datasets, education was not classified as level but according to years of education completed. For thesecountries, the category “higher education” consisted of persons who completed at least eleven yearsof schooling and “lower education” included persons with less than eleven years of schooling. Elevenof the 65 countries studied by Smits and colleagues could not be used in our analyses, because,even with the relatively low boundary, the category "higher education" was almost empty. One newcountry (Poland) was added to the data set.We restricted our analyses to wives aged 18 to 49 and men aged 18 to 52. The upper limit of 49for women was chosen because some of our data sets only contain information on women under 50.The upper limit for men was set somewhat higher because married men are generally slightly olderthan their wives. For some countries, it was not possible to make this age selection. That was eitherbecause the age of only one of the partners was available, or because age was only measured incategories (mostly five-year classes). For those countries, the available information was used tomake age selections that resemble the preferred ones as much as possible. More information aboutthe data sets, the coding of the educational variables, and the age selections is available in AppendixB.On the basis of the recoded educational variables, for each country, two 2X2 crossclassificationswere made: one for the older couples, and one for the younger couples. The distinctionbetween older and younger couples was based on the age of the wife. 3 Given the age selectionsthat were chosen and the years of data collection, the great majority of the marriages to which ouranalyses apply took place between 1940 and 1980. The boundary between older and youngercouples lies roughly in the early 1960s.4. ResultsTable 1 shows a number of loglinear models with their fit measures. Because of the large number ofcases in the homogamy table (490,620), the traditional fit measure for this kind of model - theLikelihood ratio (G 2 ) - cannot be used here to assess the fit of the models. Therefore, we will rely onthe Bayesian Information Criterion or BIC (Raftery 1986, 1995).

8Besides the G 2 and the BIC, Table 1 also presents a rG 2 statistic (Erikson and Goldthorpe 1992,p. 88). This measure indicates the proportion of reduction in G 2 compared to Model 1, which containsonly parameters for the differences between the educational distributions of the younger and oldermarried men and women for each of the countries. Model equations of the most important loglinearmodels can be found in Appendix C.---------------------------------Table 1 about here---------------------------------Model 1 in Table 1 is the model of independence. It is based on the assumption that, for eachage group in each country, the frequency of occurrence of each combination of educational levels ofhusbands and wives is determined entirely by the numbers of men and women in the margins of thehomogamy table of that age group in that country. If this model does not fit the data well enough tobe accepted, at least in some of the countries some relative association between the educationallevels of spouses will exist.The other models in Table 1 give a further description of this association. Model 2 supposes thatthe association is equally strong for both age groups in all countries. The difference between thismodel and Model 1 is so large that there must be a strong association between the educationalgroups of the spouses.---------------------------------Table 2 about here---------------------------------Models 3 and 4 show that educational homogamy among the higher educated differs among theage groups and among the countries. The lower BIC value of Model 4 indicates that the differencesamong the countries are more important than the differences among the age groups. Model 5 isbased on the assumption that educational homogamy differs among age groups and countries butthat the difference between the age groups is equally strong in all of the countries. In Model 6, thislast restriction is released and educational homogamy is allowed to vary among age groups andcountries. Of the models in Table 1, Model 5 fits best according to the BIC criterion. Therefore, thismodel is chosen as the starting model for the explanation of the differences in educational homogamyamong the countries. The parameters for the degree of educational homogamy in the countries,averaged over the older and the younger couples, are presented in Table 2. For each country, boththe loglinear (B) and the multiplicative (exp(B)) versions are presented. The multiplicative version ismost easily understood. It is equivalent to an odds ratio. This measure gives a good indication of thedegree to which the higher educated are inclined to marry within their own group. For example, thevalue of 6.4 for Australia means that the odds of having a spouse with a high educational level is 6.4times as high for somebody with a high educational level than for somebody with a low educationallevel.4.1 Differences among countries explainedTable 2 shows that there are substantial differences among the countries in the extent of educationalhomogamy among the higher educated. In this section, we try to explain these differences on thebasis of differences in other characteristics of the countries. For this purpose, the parameters for thedegree of educational homogamy in the countries of Model 5 are replaced by covariates which holdthe values of the explanatory variables for the countries. The percentage of the labor force workingnot in agriculture, and the natural logarithm of per capita energy consumption (in kilograms of coal

9equivalents) are used for the level of economic development. These measures will be used asinterchangeable indices, so as to arrive at a strong test of our hypothesis on the effects of the level ofeconomic development. Because these variables are meant to measure the same phenomenon andare highly correlated, we will not bring them together into one model.For dominant religion, we use a five-category variable: (0) other, (1) Roman Catholic, (2)Protestant, (3) Muslim, (4) Confucian, and (5) mixed Catholic/Protestant. A religion is considered tobe dominant if the majority of the population of the country belongs to it and if there is no secondreligion to which a substantial part of the population belongs. The category “other” is a residualcategory. It contains the countries in which another religion is dominant and the countries that havemore than one dominant religion (except the mixed Catholic/Protestant countries, for which there is aseparate category). For the size of the group of the higher educated in a country, we used thepercentage of persons with a completed secondary or higher education in our data set of the country.Because in some countries (e.g. the USA, Canada) this percentage is much higher than in most ofthe other countries, in our analyses the natural logarithm of this percentage will be used. To preventthe values of the parameters from becoming too small, the percentage of workers outside agriculturewill be divided by 100 before we perform the analysis. For the indicators of level of economicdevelopment, not only linear models but also models with both a linear and a quadratic term will beused to test for nonlinearities.The data we use pertain to existing marriages, which were registered some time before thesurvey was held. Because societal factors are expected to have their greatest impact around thetime of a wedding, we use country characteristics for a year that lies some time before the surveyyear (compare Ultee and Luijkx 1990). The indices for the level of economic development refer to apoint in time 15 years prior to collecting the data.The information on dominant religion pertains to the1960s and early 1970s. The values of the explanatory variables can be found in Appendix A.---------------------------------Table 3 about here---------------------------------The results of the explanatory analyses are presented in Table 3. In the model that takes theproportion of workers outside agriculture as an indicator of development, the effect of the level ofeconomic development turns out to be significantly negative. Thus, in countries with higher levels ofeconomic development, educational homogamy among the higher educated is lower. In the modelwith the (log) energy consumption per capita, educational homogamy also decreases when the levelof economic development of the countries increases. However, this decrease tends to slow down atthe intermediate levels of development and to reach its minimum in the most developed countries.Besides the level of economic development, the size of the group of the higher educated plays arole, too. As was expected, the extent of homogamy is lower in countries where the proportion ofpersons with a high educational level is greater. The effects of dominant religion are significant, too.Countries with a predominantly Catholic, Muslim, Confucian, or mixed Catholic/Protestant populationshow significantly more educational homogamy among the higher educated than countries with apredominantly Protestant population. Social closure among the higher educated is strongest in theMuslim and Confucian countries. The rG 2 statistic shows that the models of Table 3 explain a largeproportion (about 86 percent) of the differences in educational homogamy among the countries.4.2 Differences in trends among the countries

10The results of the analyses of the differences in educational homogamy among the countries are inline with the prediction of the romantic-love hypothesis. Countries with higher levels of economicdevelopment show lower levels of educational homogamy among the higher educated. The statusattainmenthypothesis and the inverted-U-curve hypothesis should be rejected on the grounds ofthese results. However, earlier in this paper it was already mentioned that one has to be carefulwhen drawing conclusions about developments on the basis of data on differences among countries.The fact that countries with different levels of economic development differ in a certain way withregard to their levels of homogamy does not necessarily imply that the changes that occur within acountry when the level of development increases will show the same pattern. In this section, therefore,the trends in educational homogamy within countries will be examined.---------------------------------Table 4 about here---------------------------------The parameter for the difference between the older and younger couples of Model 5 in Table 1has a value of -0.368 in its logarithmic form and a multiplicative value of 0.692. This means that -averaged over the countries - the degree of educational homogamy among the younger couples isabout 31 percent lower than among the older couples. Thus, in the period between about 1940 and1980, educational homogamy among the higher educated has decreased substantially.Because we are also interested in differences among the countries in the size and direction ofthe trend in educational homogamy, the relevant parameters from Model 6 of Table 1 are presentedin Table 4. They show that in only six of the 55 countries educational homogamy increases somewhat,and that in none of these countries this increase is significant. In 49 countries, we see adecrease of educational homogamy; in 29 countries, this decline is significant. In that light, decreasingeducational homogamy among the higher educated seems to be a rather general phenomenon.To gain insight in the factors that affect the trend towards more openness within the countries,an explanatory analysis was conducted, in which the differences in the strength of this trend amongthe countries are explained on the basis of country characteristics. In this analysis, the sameexplanatory variables are used as in the analysis that was presented in Table 3. Obviously, countrieswith higher levels of homogamy have more room for a decrease than countries with lower levels ofhomogamy (a society in which education does not play any role at all in partner choice seems veryunlikely). Therefore, the degree of homogamy among the older couples was controlled for in thisanalysis. This control factor was computed on the basis of Model 6 in Table 1. This model also formsthe point of departure for the explanatory analysis, in which the parameters for the differences intrends among the countries were replaced by covariates.---------------------------------Table 5 about here---------------------------------Table 5 presents the parameters of this explanatory analysis. We see that in countries withhigher levels of economic development 15 years before the data collection the decrease in educationalhomogamy is stronger. In the model that takes the proportion of workers outside agriculture asan indicator of development, the relationship between economic development and the decrease ofeducational homogamy is linear. In the model with per capita energy consumption, this relationship isnonlinear. Countries with higher levels of energy consumption show a stronger decrease in educationalhomogamy, but this effect slows down in the countries with the highest levels of energyconsumption.

12educational homogamy is stronger in the countries with a higher level of economic development.These findings are in line with the prediction of the romantic-love hypothesis that when the level ofeconomic development of countries increases, the importance of emotional considerations inmarriage choice will increase and the role of status considerations will decrease. The outcomesindicate that as far as homogamy among the more highly educated part of the population is concerned,we have to reject the other two hypotheses about the effects of economic development,namely the status-attainment hypothesis and the inverted-U-curve hypothesis.The finding of a rather general trend towards more openness among persons with a higheducational level is largely in line with the results presented previously by Ultee and Luijkx (1990) andSmits et al. (1998). Those studies found that educational homogamy tends to decrease in industrializedsocieties. Only the relatively low levels of educational homogamy which were found by Smits etal. for the least developed countries did not appear in our results. This may be due to the fact thatSmits et al. used a measure of educational homogamy which reflects the importance of education inmarriage choice for the vast majority of the population in a country. Because the vast majority of thepopulation in the least developed countries has very little education, this measure was probably notaffected very much by the high levels of educational homogamy among the small elites of thesecountries. The results of this paper may also shed new light on the debate within comparativemobility research about whether or not there is a general trend toward more openness in the occupationalstructure of societies. One reason for the contradictory results of those studies may be thatthere is a trend towards more openness, but that this trend is only present in the higher levels of theoccupational structure of the countries.Besides the level of economic development, also the relative size of the educational elite wasfound to be an important explanatory variable. In countries where the proportion of the populationwith a high educational level is higher, educational homogamy among the higher educated is lower.This finding supports the exclusivity hypothesis, which supposes that smaller elite groups tend toclose themselves off from the rest of society more strongly than larger (and less “elite”) groups.As far as the effects of a country’s dominant religion are concerned, the results are largely inagreement with the predictions. Countries with a predominantly Protestant population show lesseducational homogamy (and in most cases also a stronger decrease of educational homogamy) thancountries with a predominantly Catholic, Muslim, Confucian, or mixed Catholic/Protestant population.This finding is in line with the expectation that the lower strength of traditional family values inProtestant countries would lead to more open marriage patterns. The expectation that Confuciancountries would show more educational homogamy than Muslim countries did not turn out. TheMuslim countries had the highest level of homogamy of all countries. Despite the low level of laborforce participation of married women, the educational level of women in these countries seems toplay an important role in partner choice. At least this holds for individuals with a high educationallevel. Of course, in these countries, a high educational level of women might be strongly correlatedwith a high social background, and social background might play a major role in spouse selectionthere.

13Notes1 Besides legal marriages, other kinds of permanent or semi-permanent unions can be found inmany countries. When we use the term marriage in this paper, we also mean these other kinds ofrelationships.2 Although Smits et al. (1998) in their loglinear analysis test for differences in educational homogamyamong educational levels, their results do not give insight in educational homogamy among specificeducational groups. The reason is that they used “relative” educational categories, the meaning ofwhich depends on the educational structure of the country.3 The boundary between old and young was not the same in each country. For some countries it wasnecessary to make the boundary somewhat higher or lower to keep the difference between thenumber of younger and older couples within reasonable proportions and to prevent the occurrence ofempty cells. Information about this age boundary is presented in Appendix A.ReferencesAgresti, Alan. 1990. Categorical Data Analysis. New York: Wiley & Sons.Atoun, Richard T. 1976. "Anthropology." Pp. 166-8 in The study of the Middle East, edited by L.Binder. New York: Wiley and Sons.Barrett, David B. 1982. World Christian Encyclopedia. Nairobi: Oxford University Press.Benham, Lee. 1974. "Benefits of Women's Education within Marriage." Journal of Political Economy82:S57-S71.Berent, Jerzy. 1954. "Social Mobility and Marriage." Pp. 321-46 in Social Mobility in Britain, edited byD. V. Glass. London: Routledge.Bernasco, Wim. 1994. Coupled Careers: The Effects of Spouse's Resources on Success at Work.Amsterdam: Thesis Publishers.Björklund, Anders. 1992. "Rising Female Labour Force Participation and the Distribution of FamilyIncome: The Swedish Experience." Acta Sociologica 35:299-309.Blau, Peter. M., and Otis D. Duncan. 1967. The American Occupational Structure. New York: Wiley.Castles, Francis G. 1994. "On Religion and Public Policy." European Journal of Political Research25:19-40.Erikson, Robert, and John H. Goldthorpe. 1992. The Constant Flux. Oxford: Clarendon Press.Gagliani, Giorgio. 1987. "Income Inequality and Economic Development." Annual Review ofSociology 13:313-34.Ganzeboom, Harry B.G., Ruud Luijkx, and Donald J. Treiman. 1989. "Intergenerational ClassMobility in Comparative Perspective." Research in Social Stratification and Mobility 8:3-84.Giorgi, Liana, and Catherine Marsh. 1990. "The Protestant Work Ethic as a Cultural Phenomenon."European Journal of Social Psychology 20:499-517.Glass, D. V. 1954. Social Mobility in Britain. London: Routledge.Goldthorpe, John H. 1980. Social Mobility and Class Structure in Modern Britain. Oxford: ClarendonPress.Goode, William J. 1982. The Family. Englewood Cliffs, NJ: Prentice-Hall.

14Greeley, Andrew. 1989. "Protestant and Catholic: Is the Analogical Imagination Extinct?" AmericanSociological Review 54:485-502.Hauser, R.M., and W.H. Sewell 1986. "Family Effects in Simple Models of Education, OccupationalStatus, and Earnings." Journal of Labor Economics, 4:S83-S115.Hout, Michael. 1982. "The Association between Husband's and Wife's Occupations in Two-EarnerFamilies." American Journal of Sociology 88:397-409.ILO. 1990. Yearbook of Labour Statistics. Retrospective Edition on Population Censuses, 1945-1989.Geneva: International Labour Office.Jencks, C., S. Bartlett, M. Corcoran, J. Crouse, D. Eaglesfield, G. Jackson, K. McClelland, P.Mueser, M. Olneck, J. Schwartz, S. Ward, and J. Williams. 1979. Who gets Ahead? The Determinantsof Economic Succes in America. New York: Basic Book.Kalmijn, Matthijs. 1991. "Status homogamy in the United States." American Journal of Sociology97:496-523.Kalmijn, Matthijs, 1998. "Intermarriage and Homogamy: Causes, Patterns, Trends." Annual Reviewof Sociology 24:395-421.Kerckhoff, Alan C. 1972. "The Structure of the Conjugal Relationship in Industrial Societies." Pp. 53-69 in Cross-National Family Research, edited by M. Sussmann and B. Cogswell. Leiden: Brill.Kerckhoff, Alan C. 1978. "Marriage and Occupational Attainment in Great Britain and the UnitedStates." Journal of Marriage and the Family 40:595-99.Kerr, Clark, John T. Dunlop, Frederick H. Harbison, and Charles A. Myers. 1960. Industrialism andIndustrial Man. Cambridge, Mass.: Harvard University Press.Lane, Jan-Erik, David McKay, and Kenneth Newton. 1991. Political Data Handbook OECD Countries.New York: Oxford University Press.Lipset, Seymour M., and Reinhart Bendix. 1959. Social Mobility in Industrial Society. Berkeley:University of California Press.Parkin, Frank 1971. Class Inequality and Political Order. London: McGibbon & Kee.Raftery, Adrian E. 1986. "Choosing Models for Cross-Classifications." American Sociological Review51:145-146.Raftery, Adrian E. 1995. "Bayesian Model Selection in Social Research." Sociological Methodology25:111-163.Rockwell, Richard R. 1976. "Historical Trends and Variations in Educational Heterogamy." Journal ofMarriage and the Family 38:83-95.Schluchter, Wolfgang. 1988. Religion und Lebensführung, Band 1: Studien zu Max Webers KulturundWerttheorie. Frankfurt: Suhrkamp.Smits, Jeroen, Wout Ultee, and Jan Lammers. 1996. "Effects of Occupational Status DifferencesBetween Spouses on the Wife’s Labor Force Participation and Occupational Achievement:Findings From 12 European Countries." Journal of Marriage and the Family 58:101-115.Smits, Jeroen, Wout Ultee, and Jan Lammers. 1998. "Educational Homogamy in 65 Countries: AnExplanation of Differences in Openness Using Country-Level Explanatory Variables." AmericanSociological Review 63:264-285.Smits, Jeroen, Wout Ultee and Jan Lammers. 1999. "Occupational Homogamy in Eight Countries ofthe European Union, 1975-1989." Acta Sociologica 42:55-68.Tai, Hung-Chao. 1989. Confucianism and economic development. Washington, D.C.: TheWashington Institute Press.

15Taylor, Charles L., and Michael C. Hudson. 1972. World Handbook of Political and Social Indicators.Second edition. New Haven & London: Yale University Press.Taylor, Charles L., and David A. Jodice. 1983. World Handbook of Political and Social Indicators.Third edition. New Haven & London: Yale University Press.Treiman, Donald J. 1970. "Industrialization and Social Stratification." Pp. 207-34 in SocialStratification: Research and Theory for the 1970's, edited by E. O. Laumann. Indianapolis:Bobbs-Merill.Treiman, Donald J., and Kam-Bor Yip. 1989. "Educational and Occupational Attainment in 21Countries." Pp. 373-94 in Cross-National Research in Sociology, edited by M. L. Kohl. NewburyPark: Sage.Ultee, Wout. 1989. "Beyond Stratification and Mobility." Pp. 161-90 in Similar or Different?Continuities in Research on Stratification and Mobility in the Netherlands, edited by W. Jansenand K. Verrips. Amsterdam: SISWO.Ultee, Wout, Jos Dessens, and Wim Jansen. 1988. "Why does unemployment come in couples?"European Sociological Review 4:111-122.Ultee, Wout, and Ruud Luijkx. 1990. "Educational Heterogamy and Father-to-Son OccupationalMobility in 23 Industrial Nations." European Sociological Review 6:125-49.Uunk, Wilfred. 1996. Who Marries Whom? PhD. thesis, University of Nijmegen, Netherlands.Weber, Max. 1972[1920]. Gesammelte Aufsätze zur Religionssoziologie. Tübingen: Mohr.Weber, Max. 1972[1921]. Wirtschaft und Gesellschaft. Tübingen: Mohr.Wong, Raymond S. 1994. “Postwar Mobility Trends in Advanced Industrial Societies.” Research inSocial Stratification and Mobility 13: 121-144.World Bank. 1979. World Development Report, 1979. New York, Oxford: Oxford University Press.

16Table 1. Loglinear models of the association between the educational levels ofspouses in 55 countries at two points in time (N=490,620)BIC G 2 DF rG 21. H*C*T+W*C*T 78765 80206 110 0.0%2 1+H*W 5957 7386 109 90.7%3. 1+H*W*T 5388 6803 108 91.4%4. 1+H*W*C 102 822 55 99.0%5. 1+H*W*C+H*W*T -268 440 54 99.5%6. H*W*C*T 0 0 0 100%H = Education husband. W = Education wife. C = Country. T = Time (younger vs oldercouples)

17Table 2. Loglinear parameters with their antilog for educational homogamy among the higher educated,averaged over older and younger couples, on the basis of Model 5 in Table 1Country B se(B) exp(B) Country B se(B) exp(B)Australia 1,864 0,036 6,4 Jordan 3,363 0,166 28,9Austria 3,141 0,095 23,1 Kenya 3,663 0,248 39,0Belgium 1,901 0,118 6,7 Korea South 3,918 0,197 50,3Brazil 3,418 0,046 30,5 Malaysia 4,014 0,164 55,3Cameroon 3,821 0,256 45,6 Mexico 3,269 0,160 26,3Canada 1,958 0,025 7,1 Morocco 4,359 0,400 78,1China 2,975 0,042 19,6 Netherlands 2,069 0,025 7,9Colombia 3,667 0,218 39,1 New Zealand 1,543 0,023 4,7Costa Rica 3,316 0,138 27,5 Norway 2,165 0,228 8,7Czechoslovakia 2,168 0,034 8,7 Panama 2,718 0,118 15,2Denmark 2,855 0,180 17,4 Paraguay 3,719 0,168 41,2Dom.Republic 3,295 0,244 27,0 Peru 3,655 0,163 38,7Ecuador 3,981 0,136 53,6 Philippines 3,122 0,068 22,7Egypt 4,803 0,160 121,8 Poland 2,981 0,046 19,7Fiji 3,181 0,165 24,1 Portugal 4,037 0,136 56,7Finland 3,029 0,303 20,7 Rwanda 4,036 0,253 56,6France 2,739 0,138 15,5 Sri Lanka 4,039 0,265 56,8Germany 2,358 0,135 10,6 Sweden 2,215 0,227 9,2Ghana 3,148 0,211 23,3 Syria 3,671 0,200 39,3Guyana 3,180 0,183 24,1 Thailand 5,103 0,387 164,5Hong Kong 3,818 0,160 45,5 Trinidad & T. 3,110 0,147 22,4Hungary 2,866 0,053 17,6 Tunisia 4,595 0,358 99,0Indonesia 4,181 0,060 65,4 Turkey 2,448 0,173 11,6Ireland 3,283 0,152 26,7 United Kingdom 1,960 0,072 7,1Israel 2,179 0,112 8,8 United States 2,139 0,034 8,5Italy 2,969 0,149 19,5 Venezuela 2,804 0,167 16,5Jamaica 3,866 0,300 47,7 Yugoslavia 3,407 0,174 30,2Japan 2,672 0,140 14,5

18Table 3. Loglinear parameters with their standard errors for the effects of selected independentvariables on educational homogamy among the higher educated in 55 countries (N=490,620) aCountry characteristic MODEL A MODEL BB se(B) B se(B)Constant 4.360** 0.096 9,131** 0.485Percent outside agriculture / 100 -1.578** 0.107 - -(Percent outside agriculture / 100) 2 - - - -Log energy consumption - - -1,454** 0.129(Log energy consumption) 2 - - 0.089** 0.009Log group size -0.307** 0.024 -0.377** 0.031Dominant religion- Catholic 0.608** 0.036 0.822** 0.029- Muslim 1.111** 0.073 1.109** 0.070- Confucian 1.059** 0.100 1,146** 0.099- Catholic/Protestant 0.444** 0.024 0.411** 0.026- Other 0.152* 0.063 0.517** 0.050- Protestant Reference category Reference categoryTrend (younger-older) -0.395** 0.019 -0.391** 0.019G 2 (DF) 1330 (101) 1176 (114)BIC -357 -336rG 2 86,0 b 87,2 ba A positive sign of a parameter in this table means that a higher level of the variable goestogether with more educational homogamy.b Proportion explained of the difference in G 2 between Models 3 and 5 in Table 1* p

19Table 4. Parameters for the differences between older and younger couples in strength ofeducational homogamy among the higher educated, on the basis of Model 6 in Table 1Country Diff se(Diff) Country Diff se(Diff)Australia -0,400** 0,073 Jordan -0,717* 0,343Austria -0,435* 0,191 Kenya -1,356* 0,543Belgium -0,356 0,237 Korea South -0,311 0,411Brazil -0,168 0,092 Malaysia -1,878** 0,412Cameroon -1,662** 0,576 Mexico 0,301 0,333Canada -0,054 0,050 Morocco 0,697 0,852China -1,620** 0,090 Netherlands -0,461** 0,049Colombia 0,268 0,440 New Zealand -0,012 0,051Costa Rica -0,802** 0,282 Norway -0,461 0,461Czechoslovakia -0,257** 0,068 Panama -0,258 0,237Denmark -0,314 0,373 Paraguay -0,028 0,338Dom.Republic -1,219* 0,504 Peru 0,313 0,329Ecuador -0,844** 0,278 Philippines -0,520** 0,137Egypt -0,231 0,321 Poland -0,673** 0,092Fiji 0,054 0,352 Portugal -0,963** 0,282Finland -1,724** 0,642 Rwanda 0,462 0,504France -0,824** 0,283 Sri Lanka -1,492* 0,579Germany -0,526 0,274 Sweden -1,122* 0,472Ghana -0,967* 0,457 Syria -1,251** 0,419Guyana -0,633 0,402 Thailand -0,127 0,778Hong Kong -1,133** 0,384 Trinidad & T -0,572 0,297Hungary -0,699** 0,111 Tunisia -1,461* 0,727Indonesia -0,626** 0,121 Turkey -0,542 0,351Ireland -0,366 0,312 United Kingdom -0,516** 0,148Israel -0,149 0,223 United States -0,125 0,068Italy -0,244 0,299 Venezuela -0,341 0,339Jamaica -2,165** 0,635 Yugoslavia -0,815* 0,358Japan -0,766** 0,280* p

20Table 5. Loglinear parameters with their standard errors for the effects of selected independentvariables on the differences in trends among 55 countries (N=490,620) aCountry characteristic MODEL A MODEL BB se(B) B se(B)Constant -0.771** 0.341 -4.737** 1.139Percent outside agriculture / 100 0.523* 0.242 - -(Percent outside agriculture / 100) 2 - - - -Log energy consumption - - 1.021** 0.278(Log energy consumption) 2 - - -0.061** 0.020Log group size -0.064 0.056 -0.050 0.072Dominant religion- Catholic -0.210* 0.083 -0.296** 0.079- Muslim -0.411* 0.165 -0.243 0.163- Confucian 0.016 0.233 0.032 0.236- Catholic/Protestant -0.120** 0.059 -0.139* 0.060- Other 0.434** 0.135 0.325** 0.120- Protestant Reference category Reference categoryHomogamy among older couples 0.410** 0.058 0.480** 0.057G 2 (DF) 140,4 (46) 109,9 (45)BIC -462 -480rG 2 68.2 b 75.0 ba A positive sign of a parameter in this table means that the decrease in educational homogamyis stronger in countries with higher levels of the variable.b Proportion explained of the difference in G 2 between Models 5 and 6 in Table 1* p

21Appendix A: Country characteristicsCOUNTRY YEAR AGE NAGRI ENER RELI HIGH OLD NAustralia 81 33 91 4795 2 29 2,07 197511Austria 82 35 83 2887 1 11 3,36 7556Belgium 79 33 94 4424 1 36 2,08 1632Brazil 80 29 51 447 1 11 3,51 31056Cameroon 78 29 14 100a 0 3 4,94 5962Canada 76 32 88 5941 5 47 1,97 33916China 82 33 30 647 0 7 3,92 57514aColombia 76 29 50 522 1 6 3,49 2509Costa Rica 76 31 50 235 1 17 3,75 2456Czechoslovakia 80 34 78 5560 1 31 2,29 22246aDenmark 79 32 85 3415 2 16 3,00 1396Dom.Republic 75 30 39 158 1 7 3,98 1649Ecuador 79a 31 45 247 1 13 4,44 3818Egypt 80 29 44 333 3 12 4,91 6677Fiji 74 31 43 350b 0 6 3,08 4522Finland 72 32/35a 61 1034 2 18 4,05 449France 79 31 82 2824 1 32 3,20 1510Germany 79 33 89 4122 5 27 2,63 1576Ghana 79a 29 38 118 0 10 3,73 3239Guyana 75 30 62 566 0 10 3,55 2729Hong Kong 71 35 52a 255 4 21 4,55 3358Hungary 73 34 60 1907 1 20 3,26 13981Indonesia 76 30 26 137 3 9 4,51 33883aIreland 79 39b 69 2164 1 27 3,47 1522Israel 70 34c 84 734 0 37 2,26 1890Italy 79 34 76 1661 1 34 3,08 1424Jamaica 75a 31 61 521 2 7 5,13 1144Japan 71 34c 59 544 4 46 3,04 1307Jordan 76 30 65 206 3 14 3,76 3322Kenya 77a 27 15 143 0 6 4,49 4568Korea South 74 32 33 211 4 24 4,06 4734Malaysia 74 31 36 258 0 8 5,27 4967Mexico 76a 31 46 936 1 7 3,03 4916Morocco 80 28 40 180 3 4 3,81 2726Netherlands 77 31 90 3136 5 23 2,30 53364New Zealand 81 39b 87 2780 2 36 1,47 39983aNorway 72 32/35a 79 2267 2 30 2,40 519Panama 75a 30 49 616 1 22 2,84 2481Paraguay 79 31 45 106 1 13 3,72 2333Peru 77a 31 49 520 1 8 3,47 4579Philippines 78 32 41 173 1 24 3,39 8129Poland 72 34 50 2713 1 24 3,33 16921Portugal 79a 33 62 567 1 10 4,57 4604Rwanda 83 28 6 60a 0 4 3,78 2965Sri Lanka 75 31 44 110 0 2 4,98 5038Sweden 72 32/35a 85 3075 2 30 2,85 527Syria 78 29 47 351 3 10 4,38 3664Thailand 75 30 16 100a 0 7 5,17 2750Trinidad/Tobag 77 30 79 2233 5 13 3,41 2863Tunisia 78 29 45 219 3 4 5,31 3383Turkey 78 30 27 329 3 7 2,73 3681United Kingdom 72 34 96 4834 2 25 2,23 5629United States 80 32 95 9031 5 79 2,21 27393aVenezuela 77 29 67 2780 1 11 2,97 2091Yugoslavia 71 34c 31 593 0 22 3,84 1814

22NOTES:YEARAGENAGRIENERYear of data collectiona In these countries the data collecting continued into the next yearAge of the wife at which the boundary between younger and older couples is drawna Based on age of the respondent; wives first number, husbands second numberb Based on age of the husbandc Based on age of the respondent; husbands and wives same valuePercentage of the labor force not working in agriculture, 15 years before data collection.Sources: Lane, McKay, and Newton (1991); Taylor and Jodice (1983); Taylor and Hudson(1972); ILO (1990).a Average of Taiwan, South Korea, and Japan.Consumption of commercial energy per capita in kilograms of coal equivalents, 15 yearsbefore data collection. Sources: Taylor and Jodice (1983); UNDP (1992); World Bank(1979)a For these countries the value was increased because a substantial proportion of the energyconsumption is in the form of fuelwood, which is not included in the energy consumptionmeasureb Estimated using information from the 1970sRELI Dominant religion. Categories: (0) Other, (1) Catholic, (2) Protestant, (3) Muslim, (4)Confucian, (5) Mixed Catholic/Protestant. Sources: Taylor and Hudson (1972) and Barrett(1982).HIGHOLDNProportion of respondents in the category “higher educated”. Source: own data setsLog(odds ratio) for educational homogamy among the older couples on the basis of Model6 in Table 1Number of cases in the educational homogamy table.a Because the number of cases in the original data sets of these countries was extraordinaryhigh, the homogamy table was based on a random sample from the original data set.

23APPENDIX B. DATA SETSFor each country, information is presented on the machine readable data file or table and on the coding of theeducational variable. For countries in which the age selection differs from the one used in most of the countries,also the age selection is given.Australia '81 Census of Population and Housing, 1981, 1% Household Sample. Social Sciences DataArchives, The Australian National University, Canberra. Nat,100%. Higher education: leftschool at 16 years or higher.Austria '82 Mikrozensus 1982 (Berufslaufbahn). Österreichisches Statistisches Zentralamt.Nat,100%. Higher education: completed upper secondary or higher.Belgium '79Poverty Study Europe (P0867). Nat,100%. Higher education: completed secondary orhigher.Brazil '80Census 1980, 0.8% public use sample. Instituto Brazileiro de Geografia e Estatistica, Riode Janeiro. Nat,100%. Higher education: >10 years.Cameroun '78 World Fertility Survey. Nat,100%. Higher education: >10 years. Selection: wives 20-49.Canada '76Census of Canada, 1976: Public Use Sample, Statistics Canada (I7969). Nat, exceptPrince Edward Island, Yukon, Northwest Territories. Higher education: grade 12-13 withcertificate/diploma or higher.China '82Census of Population of China, 1982, 1% sample (M375). Nat,100%. Higher education:completed senior secondary or higher.Colombia '76 World Fertility Survey. Nat,100%. Higher education: >10 years.Costa Rica '76 World Fertility Survey. Nat,97%. Higher education: >10 years.Czechoslovakia '80 Census 1980. Federalni Statisicky Urad, Praha. Table. Nat,100%. Higher education:secondary 2e level or higher. Selection: wives 10 years. Selection: wives 20-49.Ecuador '79/80 World Fertility Survey. Nat,97%. Higher education: >10 years. Selection: wives 20-49.Egypt '80World Fertility Survey. Nat,100%. Higher education: >10 years.Fiji '74 World Fertility Survey. Nat,96%. Higher education: >10 years. Selection: wives, 20-49.Finland '72Scandinavian Welfare Survey (M025). Nat,100%. Higher education: completed middleschool plus or matriculation. Selection: respondents, male 23-52, female 20-49.France '79Poverty Study Europe (P0867). Nat,100%. Higher education: BAC or higher.Germany West '79 Poverty Study Europe (P0867). Nat,100%. Higher education: completed middle school orhigher.Ghana '79/80 World Fertility Survey. Nat,100%. Higher education: >10 years.Guyana '75 World Fertility Survey. Nat,92%. Higher education: >10 years. Selection: wives 20-49.Hongkong '71 Population and Housing Census of Hongkong: 1/100 Household Sample (M098).Nat,100%. Higher education: completed higher secondary or higher.Hungary '73Social Mobility and Occupational Changes in Hungary (M315). Nat,100%. Highereducation: completed secondary or higher.Indonesia '76 World Fertility Survey (SUPASII). Nat,97%. Higher education: >10 years.Ireland '79Poverty Study Europe (P0867). Nat,100%. Higher education: leaving certificate/othersecondary or higher.Israel '70Israeli Culture Survey (M357). Nat,100%. Higher education husbands: completedsecondary or higher. Higher education wives: > 10 years. Selection: respondents 18-49.Italy '79Poverty study Europe (P0867). Nat,100%. Higher education: completed upper secondaryor higher.Jamaica '75/76 World Fertility Survey. Nat,100%. Higher education: >10 years.Japan '71Verba, Sidney; Nie, Norman H.; Kim, Jae-On. Political Participation and Equality inSeven Nations, 1966-1971 (I7768). Nat,100%. Higher education: senior secondary orhigher. Selection: respondents 20-49.

24Jordan '76World Fertility Survey. Nat,excl.West-Bank,100%. Higher education: >10 years.Selection: wives 20-49.Kenya '77/78 World Fertility Survey. Nat,95%. Higher education: >10 years.Korea South >74 World Fertility Survey. Nat,99%. Higher education: >10 years.Malaysia '74 World Fertility Survey. Peninsular Malaysia,100%. Higher education: >10 years.Mexico '76/77 World Fertility Survey. Nat,100%. Higher education: >10 years.Morocco '80World Fertility Survey. Nat,99%. Higher education: >10 years.Netherlands '77 Labour Force Survey. Central Bureau of Statistics. Nat,100%. Higher education:completed secondary or higher.New Zealand '81 Census of Population and Dwellings, 1981. Table. Nat,100%. Higher education: 7e formor higher. Selection: husbands 15-49.Norway '72Scandinavian Welfare Survey (M025). Nat,100%. Higher education: middle school plusor higher. Selection: respondents, male 23-52, female 20-49.Panama '75/76 World Fertility Survey. Nat,90%. Higher education: >10 years.Paraguay '79 World Fertility Survey. Nat,94%. Higher education: >10 years.Peru '77/78World Fertility Survey. Nat,100%. Higher education: >10 years.Philippines '78 World Fertility Survey. Nat,95%. Higher education: >10 years.Poland >72Polish Social Mobiliy Survey (M324). Nat, only employed persons. Higher education:Completed secondary or higher.Portugal '79/80 World Fertility Survey. Nat, excl. islands, 100%. Higher education: >10 years.Rwanda '83World Fertility Survey. Nat,100%. Higher education: >10 years.Sri-Lanka '75 World Fertility Survey. Nat,100%. Higher education: >10 years.Sweden '72Scandinavian Welfare Survey (M025). Nat,100%. Higher education: middle school plusor higher. Selection: respondents, male 23-52, female 20-49.Syria '78World Fertility Survey. Nat,100%. Higher education: >10 years.Thailand '75World Fertility Survey. Nat,100%. Higher education: >10 years.Trinidad & Tobago '77 World Fertility Survey. Nat,100%. Higher education: O-level or higher. Selection: wives20-49.Tunisia '78World Fertility Survey. Nat,100%. Higher education: completed secondary or higher.Turkey '78World Fertility Survey. Nat,100%. Higher education: completed secondary or higher.United Kingdom '79 Oxford Social Mobility Inquiry (M142). England and Wales, 100%. Higher education: O-level or higher.United States '80 Census of Population and Housing, 1980: Public Use Microdata Sample. B-sample,1/1000 (I8211). Nat,100%. Higher education: completed highschool or higher.Venezuela '77 World Fertility Survey. Nat, 98%. Higher education: >10 years. Selection: husbands 23-52, wives 20-45.Yugoslavia '71 Verba, Sidney; Nie, Norman H.; Kim, Jae-On. Political Participation and Equality inSeven Nations, 1966-1971 (I7768). Only Slovenia, Croatia, Serbia and Macedonia.Higher education: completed secondary or higher. Selection: respondents