Traces of the Second Demographic Transition in Four Selected Countries in Central and Eastern Europe: Union Formation as a Demographic Manifestation

  • Jan M. Hoem
  • Dora Kostova
  • Aiva Jasilioniene
  • Cornelia Mureşan
Open Access


Using data from the first round of the national Gender and Generations Surveys of Russia, Romania, and Bulgaria, and from a similar survey of Hungary, which were all collected in recent years, we study rates of entry into marital and non-marital unions. We have used elements from the narrative of the Second Demographic Transition (SDT) as a vehicle to give our analysis of the data from the four countries some coherence, and find what can be traces of the SDT in these countries. The details vary by country; in particular, latter-day developments in union formation patterns did not start at the same time in all the countries, but in our assessment it began everywhere before communism fell, that is, before the societal transition to a market economy got underway in 1990.


Marriage Cohabitation First union Joint analysis of competing risks Second Demographic Transition Central and Eastern Europe Russia Romania Hungary Bulgaria 


A partir des données de la première vague d’enquêtes du projet Générations et Genre en Russie, en Roumanie et en Bulgarie, et à partir d’une enquête comparable en Hongrie, toutes conduites récemment, cette étude s’intéresse aux taux d’entrée en union conjugale et non-conjugale. Nous avons utilisé des éléments du cadre descriptif de la seconde transition démographique comme grille d’analyse pour donner une cohérence aux données des quatre pays, et pour y explorer les traces de ce modèle de transition. Chaque pays a un contexte à part; en particulier, les évolutions récentes dans les modalités de formation des unions ont des calendriers variables, mais d’après notre étude le processus a commencé partout avant la chute du communisme, et donc avant la transition à l’économie de marché dans les années 90.


Mariage Cohabitation Première union Analyse conjointe des risques compétitifs Seconde transition démographique Europe centrale et de l’est Russie, Roumanie, Hongrie, Bulgarie 

1 Introduction

In this article, we study trends in family-formation behavior since 1960 in the countries that used to be called the Eastern Bloc. In this connection, the account of the Second Demographic Transition (SDT) is very attractive, both as a generalized summarizing description and because of its underlying theory of value change in the direction of increasing tolerance in family matters and of women’s increasing autonomy (Lesthaeghe and van de Kaa 1986; Lesthaeghe and Surkyn 2002; for a recent, independent assessment, see Sobotka 2008). The SDT account consists of a narrative of changes in demographic behavior and of an explanation for those changes. The changes on which the narrative focuses are a decline in marriage formation, an increase in non-marital cohabitation, a general decrease in fertility (particularly at higher birth orders) but an increase in non-marital childbearing, an increase in union disruption, and a postponement of marriage and childbearing. Briefly stated, the explanation given is that these developments are caused by ideational changes regarding family life and childbearing, i.e., changes in norms, values, beliefs, and attitudes, sometimes operating in tandem with political, economic, and social changes.

There is ample evidence of most of the demographic developments in the SDT narrative all over Europe, particularly concerning fertility trends; see for instance Frejka et al. (2008). There is also already quite some literature on recent changes in union-formation behavior in Central and Eastern Europe and on their interpretation (Carlson and Klinger 1987; Lesthaeghe and Surkyn 2002; Aassve et al. 2004; Spéder 2004 and 2005, Zakharov 2005, Gerber and Berman 2005; Koytcheva 2006, Thornton and Philipov 2007; Kostova 2007, Muresan (2007a, b), and Bradatan and Kulcsar 2008).1 Too little attention has been given so far to the finer structure of the trends in union-formation risks in the region, however, which is surprising, given that ideational change must be a force behind the growth in non-marital cohabitation and therefore a prime indicator of the very explanation given for the SDT. In this article, we focus therefore on non-marital cohabitation as a competitor to conventional marriage. Our account is for Bulgaria, Romania, Russia, and Hungary, for we are fortunate in having early access to the data from the first round of the Gender and Generations Surveys (GGS) in the first three of these countries and to their close counterpart for Hungary.2 All the surveys have used a random sample of women and men of all relevant ages. In this present study, we use the data for women only; for sample sizes (in terms of years of exposure) see Table 1.
Table 1

Person-years of exposure since 1960


Total person-years of exposure

Year of data collection

As childless, not pregnant

As childless, pregnant

At parity ≥1





















Note 1The first wave of the Hungarian GGS (originally called “Turning points of the life-course”) was conducted in November 2001 through January 2002, but we do not use data collected in 2002 in our study

Source Our own calculations based on GGS data

We started this investigation in a descriptive mood and without any strong preconceived ideas or hypotheses about union-entry trends, but with a series of open questions. We were curious to see to what extent the fall of communism around 1990 might have given a particular impetus to developments in union formation across the four countries, and what commonalities we could find in the patterns of such developments. The single-country background and previous literature has been described succinctly for Russia and Bulgaria by Philipov and Jasilioniene (2007),3 for Romania by Muresan (2007a, b),4 and for Hungary by Spéder (2005). The three former authors have provided extensive survival tables for Russia, Bulgaria, and Romania in the spirit of Andersson and Philipov (2002), who gave such tables for Hungary and fifteen other European countries for an earlier period. Following Carlson and Klinger (1987); Spéder (2004, 2005) maintained that post-divorce non-marital cohabitation has old roots in Hungary and that consensual first unions gained considerable ground in that country well before the regime change. We focus on first unions and find similar patterns also for Russia, Romania, and Bulgaria.

Table 2 contains some highlights for the three GGS countries for which period survival tables are available,5 and we see that there was considerable cohabitation already around the late 1980s and that in Bulgaria and Russia, it had outflanked direct marriage at least by the early 21st century. According to this table, Romania seems to be in a different category, where marriage had held up much better than in Bulgaria and Russia. Statistics like those of Table 2 have been derived from straightforward occurrence/exposure rates, with no standardization nor any other attempt at hedging against compositional effects; so, we started out wondering to what extent the considerable differences between the countries would hold up to closer scrutiny.
Table 2

Entry into marital and non-marital unions as competing events in Bulgaria, Romania, and Russia. Period survival-table estimates. Percent ever entered by age 35. Women





Ever entered into cohabitation marriage

Ever entered into cohabitation marriage

Ever entered into cohabitation marriage





















a Source Philipov and Jasilioniene (2007), Table A8

b Source Muresan (2007b), Tables 5.5 and 5.6



2 Method and Covariates

In demography, one of the ways to handle compositional effects is by using standardization, and we have applied this method in the form of an unusual variant of intensity regression where entry into marriage and into a non-marital union are studied jointly as competing risks in a manner that permits direct comparison between the two types of union formation in each of the four countries.6 This procedure has been described most fully by Hoem and Kostova (2008), to whom we refer for mathematical aspects of the approach we use. (We give some further discussion of such items in an appendix to this article.) They also gave a first application to the Bulgarian GGS data already. This article can be regarded as a further elaboration of the Bulgarian data and an extension to the three other countries for which we also have data.

Based on data in a monthly format for the years since 1960, we have used proportional-hazards event-history analysis with a piecewise constant baseline intensity to reflect the impact of a woman’s age, formally using the type of union formed as a fixed covariate in addition to the other fixed and time-varying covariates available to us (the determinants). Among the determinants we have included a time-varying covariate that we call pregnancy-and-parity status. It provides a differentiation between (i) non-pregnant childless women (ii) pregnant childless women,7 and (iii) mothers, i.e., women at parities 1 and above. The first of these three groups overwhelmingly dominates the exposures to the risk of first-union formation (Table 1) and we report most of our results for this group alone. Since our focus is on the changing trends in union formation, we display the interaction between calendar time and union type in our descriptions below, and let the other available covariates appear as control variables. These are most importantly (self-reported) ethnicity, but also a number of covariates that are intended to reflect other aspects of the respondent’s background, namely whether she grew up in an urban or rural region, whether she lived with both parents at age 15, her number of siblings, her own educational attainment, and the educational attainments of her mother and father.8 These are standard covariates readily available in our data, except the respondent’s own educational attainment. We would have used it more extensively if we had had enough information to make it a genuine time-varying covariate, but the data only contain the attainment made by the time of data collection plus the time at which the respondent had reached this level of education (according to her own report), so we have had to impute a non-fixed covariate using a method developed by Hoem and Kreyenfeld (2006). Since this is not the real thing, we do not report the outcome here, nor do we report the risk patterns for our other control variables, mainly in order not to detract attention from our main focus on union-entry trends, but also because they do not contain any really notable surprises, particularly since Bradatan and Kulcsar (2008) went this way before us. Among the findings that we do report is a strong drop in the marriage-formation risk in all the four countries and a counterpart increase in the risk of entry into non-marital unions, though surprisingly in Bulgaria (and possibly Hungary) this increase turned into a drop at the beginning of the 2000s.9 As one of our referees has pointed out, this may just be a sign of accelerated postponement of entry into a first union, which would be another typical trait of the SDT.

To give a feeling for the size order of the relative union-formation risks in our four data sets in the twilight years of state communism, we attach Table 3, where for each country we display the (two-way) empirical interactions between the type of union formation (marital and non-marital) on the one hand and pregnancy-and-parity status on the other. The estimates have been produced by an intensity regression where age and calendar time appear formally as (time-varying) control variables not involved in any interactions, so the figures represent a kind of average over active childbearing ages and over the forty-odd years since 1960.
Table 3

Relative risk of first-union formation by parity-and-pregnancy status, for each type of union. Our selected countries, 1960-ca. 2004


Childless, not pregnant

Childless, pregnant

Parity ≥1 (mother)

Russia 1960–2004





Marriage (direct)




Bulgaria 1960–2004





Marriage (direct)




Romania 1960–2005





Marriage (direct)




Hungary 1960–2001





Marriage (direct)




Note Standardized with respect to age, ethnicity, calendar period, character of region where respondent grew up (urban/rural), whether respondent lived with both parents at age 15, number of siblings, own educational attainment, and mother’s and father’s educational attainments. Some of these covariates have not been available for Hungary. For Romania the parents’ educational attainments were not included because of data quality problems

Source Our own calculations based on GGS data

The general pattern is that as long as a woman was childless and not pregnant, the risk of entry into a non-marital union most often was low by comparison to the risk of marriage formation. Bulgaria constitutes an exception, in that entry into cohabitation was the higher. (We return to this deviation below. Note that our method allows for a direct comparison of the union-formation risks across the two types of unions in each country.) Not surprisingly, the union-formation intensities increased strongly if the woman became pregnant, and the increase was particularly strong for marriage formation. If she did not form a union before she had her (first) child, then the entry intensities largely went back to the size order they had before she became pregnant, or even to something smaller. It is as if the arrival of the first child is some kind of watershed, after which the woman was less attractive as a partner, or alternatively that the remaining women were less attracted by partnership. Only in Hungary, mothers still ran a (somewhat) higher risk of entry into a union, especially a marital union, than before they became pregnant.

3 Trends Over the Years Since 1960

To get closer to the changing dynamics of union formation, we report the trends in (standardized) entry rates since 1960 in Fig. 1, computed separately for each of the four countries. These are relative risks of entry into cohabitation and into marriage for childless non-pregnant women10 in a two-way interaction between calendar period and decrement type, standardized for the control variables listed above. The basis of comparison is the country-specific risk of entry into a marital union for childless non-pregnant women in 1960–1964.11,12
Fig. 1

Trends in the rates of union formation, by type of union. Non-pregnant childless women in Russia, Romania, Bulgaria, and Hungary, since 1960. Rates relative to that of direct marriage during 1960–1964, separately for each country. Source Our own calculations based on GGS data

The following patterns strike the eye:

In Bulgaria and Hungary, marriage risks have decreased over time ever since the early 1980s (roughly); in Russia they have decreased strongly since half a decade later, and in Romania since another half a decade later again. In all the countries, the risks of entry into non-marital unions have increased ever since the 1960s, much as one would expect from descriptions of the SDT.13 Taken together, these manifestations started well before the fall of communism, particularly for entry into consensual unions. Developments of this nature have been noted earlier by Gerber and Berman (2005) and by Spéder (2004, 2005).

Bulgaria seems to be having a case of its own. As we just said, the marriage risk has fallen since the early 1980s, but the entry risk for cohabitation stabilized during the 1980s and 1990s. If anything, it dropped after the turn of the century. This looks like a deviation from (standard) patterns in the SDT, though one should note that the cohabitational entry risks continued to increase relative to the marriage risks throughout the whole period of our observation.14, 15

Romania is another exception from the general trend in the risks of entry into cohabitation, relative to that of marriage formation. Even if the process of first union formation largely follows the trends observed in the other three countries, marriage was the dominating type of first union throughout the entire period of observation.

If we add an interaction between age attained and decrement (union type) in the intensity regression that produces the standardized risk trends mentioned above, we get age profiles for the two entry risks as an extra bonus (Fig. 2). (For the mathematics, see our appendix once more.) We had expected entry into cohabitation to be shifted toward younger ages than the age profile for marriage formation, much as in the diagram for Bulgaria, but the diagrams for Russia, Hungary and Romania show how incorrect such a preconception could be.
Fig. 2

Age profiles of entry risks of union formation, by type of union. Non-pregnant childless women in Russia, Romania, Bulgaria, and Hungary, 1960-ca. 2004. Absolute risks per 1,000 person-months. Source Our own calculations based on GGS data

4 Shifting Age Profiles

The findings presented in Section 3 provide a neat and compact description of entry trends in the four countries, based on a standardization technique of a type that is ubiquitous in demography.16 Standardization is known to summarize risk trends and differentials well under wide conditions, and to be robust against mild deviations from those conditions.

One of the conditions that we have not addressed above is the assumption of a stable age profile in the risks, i.e., we have behaved as if each of the two piecewise constant baseline hazards (one for each decrement) were the same for all calendar periods in the analysis. This may have simplified matters unduly; after all, many authors document to their satisfaction that there has been a delay in union formation, so marriage and perhaps entry into cohabitation occur progressively later in life as calendar time increases. One question is, therefore, how robust the results above are against what may be a misspecification.

To check on this question, we have estimated the hazard parameters once more, but now with a three-way interaction between age, period, and decrement.17 The outcome is given in Fig. 3, where to avoid needless complication, we have temporarily used five-year age groups and have concentrated on the years between 1980 and the survey date.18 For each country, we have plotted the age profiles of the rates of union formation for each period k, and we get the following graphical patterns, which can serve as a simple optical goodness-of-fit test of our basic specification.
Fig. 3

Age profiles of entry risks of union formation, by type of union and period. Non-pregnant childless women in Russia, Romania, Bulgaria, and Hungary, 1980-ca. 2004. Absolute risks per 1,000 person-months. Source Our own calculations based on GGS data

For Hungary the entry risk for marriage formation has indeed shifted steadily toward higher ages; for entry into cohabitation they seem to have shifted somewhat in the opposite direction. For Romania we also see a bit of a shift toward later ages in the risk of entry into marriage, while in Bulgaria we can see a similar shift in the risk of entry into non-marital cohabitation. With some good will, one can even discern some tendency for the profile to shift a little toward younger ages in the risk diagrams for Russia. All in all, perhaps there is only a mild deviation from the requirement of a stable age profile in Bulgaria, Russia, and Romania.

By way of conclusion, to get a realistic representation it looks as if we may be able to make do with our original intensity specification for Russia, Romania, and Bulgaria, but not necessarily for Hungary. For the latter country, we have therefore tried the specification with a three-way interaction between age, period, and decrement once more, but now with our finer age specification and with periods back to 1960. The result is that for each age group we can essentially draw a diagram like that of the corresponding panel in Fig. 1 (details available from the first author). In our view, therefore, the whole story of the entry trends in Hungary since the 1960s is adequately represented in Fig. 1, in any case. Except for details, we draw the same conclusion concerning the intensity age profiles in Fig. 2.

5 Conversion of Non-Marital into Marital Unions

As we mentioned toward the end of Section 3, we have found that lately the risk of entry into cohabitation has dropped somewhat in Bulgaria. To see whether this means that Bulgarian women have given up on the SDT, at least as far as union formation is concerned, it pays to introduce an additional dimension, namely, the conversion of non-marital unions into marriages. One take on this is our Fig. 4a, which is similar to a corresponding figure presented by Hoem and Kostova (2008, Fig. 4), but which is now constructed in a way that covers the whole period and the entire population of this study. In Fig. 5 the same data are seen from a different angle, but it tells the same story, namely, that the SDT remains in progress in Bulgaria. Here is some further background information.
Fig. 4

Relative rates of conversion of cohabitation into marriage, by time since entry into cohabitation for each calendar period, women in Bulgaria and Hungary, 1960-ca. 2004. Rates relative to a conversion during the first 6 months in the period 1960–1969. Source Our own calculations based on GGS data

Fig. 5

Relative rates of conversion of cohabitation into marriage, by calendar period for each duration since entry into cohabitation, Bulgarian women, 1960–2004. Rates relative to a conversion during the first 6 months in the period 1960–1969. Source Our own calculations based on GGS data

Consensual unions seem to have been entrenched in Bulgaria for a long time. (Note how high the Bulgarian curve for entry into cohabitation is in Fig. 1.) Anecdotal evidence suggests that there may have been a long-standing pattern where couples who are engaged to be married, move in with one set of their parents and then marry only subsequently, when this fits the family economy and other practical circumstances (observation by Kostova 2007). [This fits well to the quick conversions of consensual to marital unions noted by Koytcheva (2006, Sect. 7.1.1) based on Bulgarian data sets different from the GGS.] In our data, this would be recorded as an entry into a consensual union and a later conversion of the union into a marriage. Figs. 4a and 5 show that after the fall of communism, the conversion activity was scaled down considerably. A consensual union became a much more durable arrangement, fully in agreement with what a description of the SDT would predict. Figure 4b extends this painlessly to Hungary, for which, as we remember, we have found a similar drop in the two years right after the turn of the century (Fig. 1). Extensions to the data for Romania and Russia largely show the same pattern for conversion risks (not documented here).

6 Summary and Reflections

The union-formation trends that we have revealed in this descriptive study of the four countries in Central and Eastern Europe turn out to have several features in common. Marriage formation has dropped in all the four countries since the fall of communism, and sometimes earlier. Consensual unions have gained ground all the time until the end of the twentieth century, and only in Bulgaria and Hungary does popular interest in consensual-union formation seem to have been reduced somewhat thereafter. In all the four countries, the wind has gone out of the sails of conversions of consensual unions into marriages; so non-marital unions have progressively stayed consensual longer.

Despite all commonalities, it is evident that the SDT, of which we have found some traces, is not a unitary movement that reached all the countries in Central and Eastern Europe roughly at the same time and had the same features throughout, no more than it was in Western Europe. If anything, such a transition did not start simultaneously in all of the four countries, and above all, it began well before the fall of communism and before the societal transition to a market economy got underway around 1990. If we take the distinct drop in marriage formation as a main marker of the start of the SDT as we study it in this article, then a rough estimate would be that it started in Hungary and Bulgaria after the early 1980s and in Russia and Romania half-a-decade and a full decade later, respectively. Such differences should fit with the economic and social developments in the countries, but establishing such a correspondence is a matter of future research. In particular, the special trends in Bulgaria (and possibly Hungary) need further investigation, most likely by bringing in further dimensions in the analysis. We doubt whether it will be enough to continue to study standardized trends in decrement-specific union formation. In any case, our empirical findings have put similar observations made by Lesthaeghe and Surkyn (2002); Gerber and Berman (2005); Zakharov (2005), and Spéder (2004, 2005) on a firmer empirical ground than before.

As a final reflection on our findings, we want to underline that interpretations should be made with some prudence, for it is possible that the perception of what constitutes a consensual union has varied across countries and has changed over time, and also that reporting inaccuracy may have exaggerated the early growth of entry risks for consensual unions. In brief, the reporting accuracy depends on the respondents’ ability to recall and willingness to reveal cohabitational episodes. It is possible that cohabitational episodes that occurred long ago may have been forgotten or suppressed more often than more recent episodes,19 and if this is the case, cohabitational behavior at the beginning of our period of observation may have been more extensive than what we can report. If so, then the value change central to the SDT explanation may have been smaller than what meets the eye.


  1. 1.

    A Russian-reading colleague has also made us aware of Maleva and Sinyavskaya (2007).

  2. 2.

    For a description of the GGS program, see Vikat et al. (2007); for a description of the Hungarian survey, see Spéder (2001).

  3. 3.

    See also Zakharov (2008) and Koytcheva & Philipov (2008).

  4. 4.

    See also Mureşan et al. (2008).

  5. 5.

    We have not found comparable information for Hungary, also because Spéder (2005 etc.) has worked consistently with birth cohorts rather than with calendar periods.

  6. 6.

    We also sometimes call the type of union formed (marital or non-marital) a decrement, in line with actuarial terminology, which focuses on the mode of exit from the non-partnered status.

  7. 7.

    In line with much demographic practice, we have counted a woman as knowingly pregnant during the seven calendar months just before the month in which she gave birth. We have used seven instead of nine months because initially we thought that few women can be sure they are pregnant and also able to enter a union during the first one or two months of a pregnancy. At the time when we complete our last revision, we are no longer sure that this argument is valid, because Kostova (2008) recently discovered that at least in Bulgaria and Russia union-entry behavior changes visibly already nine months before the first birth recorded. She also found that the choice between nine and seven months is unimportant for the analysis of union entry, however, so we have kept our alternative of seven months so as to avoid having to make recalculations to little effect.

  8. 8.

    Some of these covariates have not been available for Hungary. For Romania we did not include the parents’ educational attainments because of data-quality problems.

  9. 9.

    For the same feature see also Hoem and Kostova 2008, Fig. 3. The calculations in this article and in theirs extend to 2004. In work that has not been published yet, Kostova has found that the drop continued through 2007.

  10. 10.

    Because of the exposure dominance of the non-pregnant childless women, the interaction would not have been much different even if we had disregarded pregnancy-and-parity status.

  11. 11.

    The diagram for Bulgaria deviates somewhat from the corresponding diagram in the article by Hoem and Kostova (2008) because their computations were for the cohorts born in 1955 and later while the present diagram is for all the cohorts in our data, as it is for all the countries in our study.

  12. 12.

    We have further experimented with an intensity model that also contains (i) an interaction between the type of union formation and age attained as well as (ii) an interaction between union type and the control covariates. We have relegated an account of the mathematics involved to our appendix, which also contains a discussion of the items plotted in Fig. 1 and the subsequent Fig. 2 in terms of relative risks.

  13. 13.

    We are struck by the rather low rates of entry into a consensual union in Hungary (as compared to direct entry into marriage); nevertheless this country seems to conform to the SDT narrative reasonably well. Since about the year 2000 cohabitation has been the dominant choice of first union formation in this country (see similar findings by Spéder 2006 and Spéder and Kamarás 2008, Figs. 16 and 17), and the low total level of entry into a first union after 1995 fits with SDT arguments about a longer period of single living and delayed union formation in general.

  14. 14.

    The entry risk for cohabitation relative to the corresponding risk of marriage formation in Bulgaria rose steadily as follows:

    1960–64 1965–69 1970–74 1975–79 1980–84 1985–89 1990–94 1995–99 2000–04

    0.5 0.72 0.78 1.07 1.17 1.31 1.77 2.81 4.44.

  15. 15.

    There is a hint of a drop in the entry risk for cohabitation between the periods 1995–1999 and 2000–2001 in Hungary as well, but we do not pay much attention to this since the latter period is only two years long in Hungary as against five years for other periods and countries. Random variation may therefore play a greater role than otherwise at the tail end of the curve for Hungary.

  16. 16.

    Using hazard regression in our situation is just a practical manner of applying indirect standardization.

  17. 17.

    In the mathematical terms of our appendix, we specify \( \mu = \,ACD + B \) and see whether we can actually decompose ACD as AD + CD in our data. In a different formulation, this means that instead of a simple model \( \mu_{ijkh} = a_{ih} b_{j} c_{kh} \) we fit \( \mu = a_{ikh} b_{j} \) and see how realistic it is to suppose that \( a_{ikh} \)can be split as \( a_{ikh} = a_{ih} c_{kh} \) (if we allow ourselves some lenience in mathematical representation).

  18. 18.

    The use of five-year groups instead of the shorter age groups is intended to avoid an overly strong impact of random variation. An extension back to 1960 and the use of shorter age groups essentially give the same picture (not documented here). The results remain standardized with respect to the control variables in our analysis.

  19. 19.

    Compare the reflections and findings of Hayford and Morgan 2008, based on similar data for the United States.

  20. 20.

    Relation (1) is a suitable starting point for a general discussion of the issues that we raise. For reasons that we will make clear as we go along, Figs. 1, 2 have actually been based on simpler specifications, namely \( \mu_{ijkh} = a_{i} b_{j} c_{kh} \) for Fig. 1 and \( \mu_{ijkh} = a_{ih} b_{j} c_{kh} \)for Fig. 2. Thus for the diagrams, we use fewer factor interactions (double-subscript parameters) than the general theory allows for.

  21. 21.

    Note how we use a mnemotechnical device in the naming of the various factors involved.



We have benefitted from very constructive comments from anonymous reviewers, from conversations with colleagues in the Max Planck Institute for Demographic Research, and from impulses provided by Tomas Frejka and Tomas Sobotka. We are grateful to Zsolt Spéder for giving us access to the Hungarian data.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.


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Copyright information

© The Author(s) 2009

Authors and Affiliations

  • Jan M. Hoem
    • 1
  • Dora Kostova
    • 1
  • Aiva Jasilioniene
    • 1
  • Cornelia Mureşan
    • 2
  1. 1.Max Planck Institute for Demographic ResearchRostockGermany
  2. 2.University Babeş-BolyaiCluj-NapocaRomania

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