No. 12
13 November 2015
* Department of Sociology
Tilburg University, the Netherlands www.tilburguniversity.edu/howcome
Funded by the
European Research Council
Grant Agreement No. 283615

Does divorce reduce housing wealth in later life? The role of housing regimes
Barend Wind* & Caroline Dewilde*
* Department of Sociology, Tilburg University, the Netherlands
Abstract: Since the 1970s, divorce has become more common as a part of the wider destandardization of the life course. Previous research finds that divorce has negative economic outcomes, especially for women. Evidence shows that divorcees have a larger chance of residing in rental housing, even in later life. Implicitly, previous research assumes that divorcees that remain in homeownership, or regain access to this housing tenure at a later moment in the life course, are able to maintain their socioeconomic position. This article challenges this assumption by focusing on the housing wealth holdings of individuals (age 50 and over) with different marital trajectories. The analysis is conducted across 10 European countries, using the third and fourth wave of the Survey of Health, Aging and Retirement in Europe (SHARE 2007/8 – 2011/2). Our findings point out that elderly men, and especially women, with divorce experience have lower housing wealth holdings than individuals with an intact first marriage due to moves down the property ladder and larger indebtedness. We conclude that the effect of a divorce on the accumulation of housing wealth is larger in countries with dynamic housing markets and deregulated housing finance systems. In such a situation, divorcees are able to remain in, or regain, access to (mortgaged) homeownership, but at the cost of lower housing equity
Keywords: Life course, housing wealth, welfare state, homeownership, SHARE, divorce, inequality.
Introduction
Since the 1970s, divorce has become more common across the Western World, although there is considerable international variation. In Europe, the highest divorce rates can be found in the
Nordic countries (around 50%), whereas the Mediterranean countries have the lowest rates
(Eurostat, 2015). Sociologists have studied the rise of divorce in two ways. First, there are studies
that explain the rising divorce rate and its determinants as part of the wider de-standardization
of the life course (Fogli & Veldkamp, 2011). Second, there is a large body of research on the social
and economic consequences of divorce. Divorce is found to impact negatively upon the wellbeing of children, the economic situation of women and the likelihood of intergenerational transfers
(Gruber, 2000; Kalmijn, 2007; Uunk, 2004). Housing researchers have pointed out that many of
the negative effects of divorce pertain to the housing situation. Divorce increases the likelihood
of a move out of homeownership (Dewilde, 2008). This effect persists until old-age, and is
stronger for women than for men, since women re-partner less often and later, and have in
general a weaker economic position (Dewilde & Stier, 2014). The basic idea is as follows: the
decayed economic position (of especially women) after a divorce, combined with reduced economies of scale, leads to moves out of homeownership, which excludes divorcees from the financial and other benefits of homeownership. Previous research hence starts from the implicit assumption that those who do not permanently move out of homeownership, are able to maintain their socioeconomic position.
Instead of focusing on tenure status, this paper investigates the housing wealth holdings of elderly homeowners with divorce experience. Housing wealth is operationalized as the current market value of the owned home, minus any mortgage debts. In doing so, we shed light on the differentiation among a majority of all divorcees (60-70% in most countries), namely those who do not permanently move out of homeownership. It is likely that divorced homeowners display lower housing wealth holdings than couples with an intact first marriage, due to downward moves on the property ladder, temporary episodes in rental housing, or increased mortgage debt.
However, institutional arrangements (e.g. welfare and housing regimes) might mitigate or reinforce the housing wealth consequences of the housing strategies followed by divorcees.
Studying the housing wealth-effect of divorce is urgent because (1) divorce rates are expected to remain high, and (2) housing wealth plays an increasingly important role in the
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provision of welfare. First, although there is large international variation, divorce rates have
increased across Europe (González & Viitanen, 2009). Some scholars argue that divorce rates will
fall again, because an increasing number of people cohabit rather than marries (Stevenson &
Wolfers, 2007). However, the complex tangle of living arrangements is here to stay, and by
researching the consequences of divorce, conclusions can be drawn about the broader economic implications. Second, a shift towards asset-based welfare becomes politically more attractive now that a large share of the elderly possesses housing wealth, which can be used in order to cater for
welfare needs (Livsey & Price, 2013). The large share of elderly with housing wealth is mainly the
result of a continuous policy focus on the promotion of homeownership in most European
countries since the Second World War (Angelini, Laferrère, & Weber, 2013). The relative upswing
in house prices since the 1980s, which accompanied the liberalization of housing finance (OECD,
2014), resulted in financial gains for housing market insiders. Especially the baby boom cohort
has been able to profit (Cowell, Karagiannaki, & McKnight, 2012). When disruptive life course
events like divorce impede the accumulation of housing wealth into later life for more people, asset-based welfare strategies however need to be reconsidered.
This paper investigates housing wealth holdings of elderly homeowners with divorce experience, relative to couples with an intact first marriage in the same age group. Different mechanisms that could result in lower housing wealth holdings for divorcees, are tested. Since the analysis is limited to homeowners, our results are partly driven by the selectivity of homeownership in different countries. Housing regimes and welfare regimes determine the selectivity of homeownership, and are tested as explanation of cross-country variations in the effect of a divorce on housing wealth holdings. The empirical work is based on the Survey of
Health, Aging and Retirement in Europe (SHARE, wave 3 and 4, conducted in 2008/9 and
2011/2). This article solely focuses on individuals in later life (50+ at the moment of data collection), which enables us to grasp the long-term consequences of divorce.
This study adds to previous research in three ways. First, it investigates the housing wealth consequences of a divorce, rather than focusing on tenure transitions. Second, building on
Dewilde and Stier (2014), a focus on the elderly enables us to investigate the long-term effects of
disruptive life course events in different institutional contexts, and how these come about. Third, it studies housing wealth from an international-comparative perspective, whereas most authors focus on single countries.
Why divorce has a price tag: the micro-level
We expect that differences in housing transitions between divorcees and couples with an intact first marriage result in lower housing wealth holdings of elderly homeowners with divorce
experience. Beer and Faulkner (2011) describe these housing transition as “a series of housing
decisions about whether to move or not move, the quality and quantity of housing to occupy, location relative to employment and social networks” (p. 31). We envisage three housing wealthreducing housing transitions for elderly divorcees who did not permanently move out of homeownership at the time of the survey. First of all, moves down the property ladder could reduce housing wealth holdings in a direct way. The strong effect of divorce on residential
mobility implies that in many cases both partners move to another dwelling (Speare Jr &
Goldscheider, 1987). A reduced demand for space and a weakened financial position often results
in downward moves on the homeownership market (Feijten & van Ham, 2010). Second, housing
wealth holdings of divorced homeowners are likely to be temporary or permanently lower than those of married couples, even when the housing consumption does not decline after the divorce.
A larger housing loan may be needed when the ex-partner takes out his/her share of the housing wealth. Third, temporary moves into rental housing after a divorce might reduce housing wealth holdings when house prices increase faster than incomes. In such a situation, it becomes relatively more expensive to buy a home with the same quality as the former marital home. Therefore, moves down the property ladder, or larger residential debts are expected to be more common among those with an episode in rental housing.
Divorce hypothesis: Homeowning elderly with divorce experience have smaller housing wealth holdings than couples with an intact first marriage.
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Especially women are economically vulnerable after a divorce (Uunk, 2004). Because of their
lower labour market participation and weaker financial position, women have a larger chance than men to move into rental housing after a divorce. The financial position of women after a
divorce is often worse than men because they re-partner less often and less quickly (Dewilde,
2008). We expect the effect of a divorce on the accumulation of housing wealth to be gendered as
well. In this line of reasoning, lower female wages translate into smaller purchasing power on the housing market, and subsequently lower housing wealth holdings. There are however two reasons why women may also have a higher chance to remain in the former marital home, allowing them to maintain the housing wealth accumulation process. First of all, since neighbourhoods with owner-occupied housing are often considered as a better place for children to grow up, women with children and a sufficient income have a larger chance to remain in the
former marital home (Andersen, 2011). Second, there are countries in which it is common
practice that the male partner keeps his pension wealth, whereas the female partner is entitled
to the housing wealth (see Joseph and Rowlingson (2012) for the UK). Altogether however, we
expect that the weaker financial position of women impacts negatively upon their housing wealth accumulation after a divorce.
Gender hypothesis: Homeowning elderly divorced women have smaller housing wealth holdings than homeowning elderly divorced men.
When re-partnering co-occurs with the establishment of a new shared household with a stable future perspective, possibilities for income pooling enable the couple to exercise more purchasing
power on the housing market (Lersch & Vidal, 2014). In this way re-pooling (1) increases the
likelihood of re-entering homeownership for those who dropped out of this tenure after the divorce, or (2) increases the likelihood of upward movements in the housing market for those who remained in homeownership after a divorce. Empirical evidence shows that couples of which at least one of the partners has been married before display comparable housing transitions as
couples with an intact first marriage (Beer & Faulkner, 2011; Feijten & van Ham, 2010).
Re-pooling hypothesis: Homeowning elderly re-partnered men and women have comparable housing wealth holdings as couples with an intact first marriage.
Variation across Europe
The later-life housing wealth consequences of divorce are expected to vary between countries due to institutional differences in housing and welfare regimes. Furthermore, we expect the institutional effect to vary over time due to policy changes within these countries.
Previous research on the effect of partnership dissolution on the likelihood of residing in homeownership in later life, stresses that the orientation of the welfare state mediates the economic situation of women after a divorce. In countries with extensive family policies and affordable, accessible childcare, and subsequently higher female employment rates, divorced
women have a larger chance of residing in homeownership (Dewilde & Stier, 2014). State support
for female employment might impact upon the accumulation of housing wealth as well. Higher female employment rates enable women to start working after experiencing a divorce, to move from part-time to full time work, or to remain in the labour force (especially for mothers). Higher levels of economic independence allow them to exercise more purchasing power on the housing market. Whether the increase in purchasing power allows divorcees to remain in homeownership depends on the social selectivity of homeownership. Controlling for the social selectivity of homeownership, we expect that divorced women have more opportunities for housing wealth accumulation in countries with higher female employment rates. For divorced re-partnered men a similar effect can be expected because a double income increases their purchasing power. Other parts of the welfare state, e.g. social assistance, are found to relieve the income fall for non-
working partners (Dewilde, 2008). However, these kinds of schemes only mitigate the economic
consequences of a divorce for those with low incomes. Since a certain level of affluence is needed to be a homeowner in most countries, social assistance is not expected to have a large impact on the accumulation of housing wealth.
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Female employment hypothesis: The negative effect of divorce experience on housing wealth accumulation of homeowning elderly is smaller in countries with higher female employment rates.
Divorce laws structure the financial agreements that are made by the two former partners and also show considerable cross-country variation. In all countries in the sample, unilateral no-fault
divorce laws are implemented (González & Viitanen, 2009), allowing both partners to apply for a divorce without proving any wrongdoings from the other partner. Adema, del Carmen Huerta,
Panzera, Thevenon, and Pearson (2009) show however that the financial arrangements between two partners after a divorce differ between European countries. In more conservative welfare states with lower female employment rates, child maintenance payments, spousal support or alimony are much higher than in liberal or social-democratic welfare states. These payments flow in general from the male to the female partner and can increase the financial position of divorced women considerably. Because entering the labour market is troublesome for women in these countries, spousal support might be essential for women to remain in the former marital home.
The payments are most likely not high enough to damage the position of men on the housing market.
Alimony hypothesis: The negative effect of divorce experience on housing wealth holdings of homeowning, elderly women is smaller in countries with more generous alimony systems.
The relative size of homeownership in the total housing stock moderates the odds of remaining in homeownership after the experience of a divorce. In countries with higher homeownership rates, homeownership is less socially selective because smaller and cheaper properties belong to the owner-occupied stock, whereas more larger and expensive properties form part of the homeownership sector in countries with a higher homeownership rates. The most socially selective model can be found in rental societies like Switzerland and Germany, with
a large and non-stigmatized rental sector (Bourassa & Hoesli, 2010). The least selective model
can be found in Mediterranean countries, with a long tradition of (semi/illegal) self-construction
and a large role of the family in the provision of housing (Allen, 2006). We expect that the social
selectivity of homeownership impacts upon the housing wealth holdings of homeowners because a larger homeownership sector allows divorcees to remain in homeownership by moving down
the property ladder, instead of moving into rental housing. Wind, Lersch, and Dewilde (2015)
furthermore find that a market-based promotion of homeownership allows more lower- and middle-class households to enter homeownership, but indeed translates into smaller housing wealth holdings. When less divorcees move out of homeownership permanently, but move down the property ladder instead, we expect larger housing wealth inequalities between elderly homeowners with and without divorce experience.
Homeownership hypothesis: The negative effect of divorce experience on housing wealth accumulation of homeowning elderly is stronger in countries with larger homeownership sectors.
A possible housing wealth gap between homeowning elderly with divorce experience and couples with an intact first marriage, might furthermore be the result of housing transitions of both
groups. Morrow-Jones and Wenning (2005) suggest that the relative disadvantage of divorcees
could increase even while staying put in the marital home: “Inability to move upward between units, or the inability to move up as other groups, can reinforce exiting social disparities” (p.
1740). The idea is simple: when most divorcees stay put in comparable housing or move down on the property ladder, whereas most couples that remain married are able to move up within the homeownership sector, their relative disadvantage increases. The turnover rate on the housing market indicates how common moves on the housing market are among the general
population. On the basis of these turnover rates, Van der Heijden, Dol, and Oxley (2011)
distinguish between two groups of countries. First, they identify countries with static housing markets (e.g. Belgium and Germany), where people buy a dwelling for their entire life time.
Second, they identify dynamic housing markets (e.g. the Netherlands), where it is or has become common to ‘trade up’ on the market for owner-occupied housing. In other words, the housing
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wealth gap between divorced and married elderly can be expected to be larger in dynamic housing markets, because those with an intact first marriage are more likely to move upwards
Turnover rate hypothesis: The negative effect of divorce experience on housing wealth accumulation of homeowning elderly is larger in countries with higher turnover rates on the market for owneroccupied homes.
The availability of mortgage finance is likely to influence the chance of re-entering homeownership, the necessity of (temporary) moves into rental housing, and the consequences of housing transitions. More liberal housing finance systems take ‘the waiting out of wanting’ and
provide households directly with sufficient resources to buy a house (Van der Heijden et al.,
2011). Higher loan-to-value ratios and loan-to-income ratios decrease the necessity to move into
rental housing in order to accumulate the necessary down-payment, and increase the chance that at least one of the partners can stay put in the former marital house. Moving down the property ladder, temporary spells in the rental sector, or increased mortgage debts were put forward as the main mechanisms behind the negative effect of divorce experience on the accumulation of housing wealth on the micro-level (see previous section). However, we also expect housing finance systems to have an additional, ‘independent’ macro-level effect on top of the compositional effects arising from these mechanisms, since these systems are strongly influencing house price developments. The deregulation of mortgage markets that took place in many European countries since the 1980s has contributed to inflated and more volatile house
prices, i.e. booms and busts (OECD, 2014). Especially the elderly population has been able to
profit from house prices booms. In times of rising house prices, and declining affordability, downward moves on the property ladder are more likely, and the consequences of a temporary move into rental housing more severe. Since house price inflation has been more widespread among deregulated housing markets, we expect a stronger effect of divorce on the accumulation of housing wealth in these countries.
Mortgage finance hypothesis: The negative effect of divorce experience on housing wealth accumulation of home-owning elderly is larger in countries with more liberal housing finance systems.
Data and method
Data and sample
Our analysis is based on the third and fourth wave of the SHARE (2008-2009 / 2011-2012), an ex-ante harmonized longitudinal panel study, carried out in 13 European countries among the population aged 50 and over. The third wave of the SHARE contains retrospective life histories, including housing careers and family transitions. We enrich these data with information from wave 4 about housing wealth. The SHARE data are valuable for at least three reasons. First, they contain comparative information on housing careers and housing wealth. Second, the national sample sizes are large. Third, the countries in the dataset cover a wide variety of continental welfare and housing regimes.
The analysis sample consists of elderly who have ever been married (or still are), and reside in homeownership at the moment of interview. Those who never married are not included because they have never been ‘at risk of divorce’. Tenants are not included, since moves out of homeownership as a consequence of divorce are not the focus of this study, and widely
researched by others (e.g. Dewilde (2008) or Feijten (2005)). A small number of respondents (3%
of the total sample) that entered homeowner after a divorce, is included in the sample. Only respondents belonging to the main sample of the SHARE are included. Others living in the household, like co-resident children or co-resident parents, are excluded because they are likely not entitled to the household’s housing wealth. Furthermore, respondents born before 1920 are excluded because their number is too small to draw conclusions about cohort effects. The sample of countries is restricted to Austria, Germany, Sweden, the Netherlands, Spain, Italy, France,
Denmark, Switzerland and Belgium. We exclude the Czech Republic and Poland, since the transition from communism to capitalism dramatically changed their housing and welfare
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regimes, and macro-level indicators about the period before 1990 are unavailable. Furthermore, we dropped Greece, because of the low incidence of divorce, and the unavailability of macro-level indicators for the period before 1990. Altogether, the analysis sample consists of 10 countries with 318 (Austria) to 1595 (Belgium) respondents. The number of respondents in Austria is disproportionally low because of the small initial sample and the large share of tenants (see appendix Table 2).
Micro-level variables
Net housing wealth is our dependent variable. It is calculated as the value of the first dwelling and
– when applicable – a second home, minus the value of all outstanding debts. The housing wealth estimate is derived from self-evaluation of the market value of the house at the moment of the interview (2011/2012). Previous studies have proven such subjective evaluation of housing
wealth to be reliable (Ansell, 2013; Mulder, Dewilde, Van Duijn, & Smits, Forthcoming). We use
top coding at the 99.8 per cent level to remove outliers in the housing wealth distribution per country. For reasons of international comparability, housing wealth holdings are calculated as a percentage of the national median. Although housing wealth can be considered as a household characteristic, it is treated as an individual, non-equivalized characteristic for analytical reasons.
The complex tangle of marital pathways is summarized in four categories, based on the result of the first marriage (still living together, divorced, widowed, not living together) and the current situation for those who entered a new partnership (still living together, divorced, widowed, not living together). The fifteen trajectories that follow from this evaluation (see appendix: Table 1) are summarized in four categories. The first category includes all respondents who are still in their first marriage. Widows who never re-partnered, and those with a partner in a nursing home are included in this category as well. Their housing wealth is expected to be accumulated by two partners.. The second category includes all respondents whose first marriage ended in divorce and who are currently single. The third category contains all respondents whose first marriage ended in divorce and who are currently cohabiting with a new partner. We do not differentiate between re-partnering and re-marrying due to the small number of cases.
Widow(er)s of new partners, and those who are living alone because the new partner moved to a nursing home are placed in this category as well because the housing wealth is likely to be accumulated by the couple. The fourth category consists of respondents that are not living together due to unknown reasons, and re-partnered widow(er)s. In the remainder, we do not comment on the results of this category, because they fall outside the scope of this research.
Three mechanisms behind a negative effect of divorce experience on the housing wealth accumulation of the elderly, can be tested directly. First, the effect of downward moves on the property ladder is measured by a variable indicating (1) whether someone lives in a house (freestanding house) or an apartment (row house/small flat, large flat, housing for elderly), and (2) how many rooms the house has. Together, both variables give an indication of the housing quality.
Second, the effect of episodes in rental housing is measured by a variable indicating how many times someone has moved within the rental sector, after the first-time entry into homeownership.
Third, the effect of increased indebtedness is measured by a variable indicating which percentage of the housing value is covered by a residential loan.
Re-partnering is hypothesized to mitigate the negative effect of divorce experience on the accumulation of housing wealth among the elderly. It is measured in terms of the abovementioned marital trajectories. We use the following micro-level variables to control for factors that are expected to influence the odds of experiencing a divorce, or the housing wealth accumulation process: age of first marriage, age of entering homeownership, residing in rental housing five years after the first marriage, number of children, migrant status, receiving a financial gift from a family member (5000 Euro or more), the urbanity of surroundings (ruralsmall town/large town-big city), highest achieved educational level (ISCED-scores: no education
/primary education/lower secondary education/higher secondary education/post-secondary education/tertiary education), income (lower than median/higher than median/higher than two times the median).
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Macro variables
Macro-level indicators are measured on the country-period level, since the context within one country changes over time. Macro-level variables are assigned to individuals on the basis of country and moment of divorce. We distinguish between respondents who divorced before 1985, and respondents who divorced after 1985. Both groups have a comparable size. To assign macrovariables to non-divorcees, we use the ‘most likely year in which a divorce would take place’. We calculate the average duration of a marriage before divorce in every country, and add this to the year of marriage. This is the context in which both divorcees and non-divorcees make the decision to divorce or not. Six macro variables, describing the welfare- and housing regime context at the moment of a (non-)divorce are taken into account.
First, we take into account female employment rates. For respondents who divorced before 1985, we use the average female employment rate of the 1980s, for those who divorced
after 1985, we use the average female employment rate of the 2000s (Olivetti, 2014).
Second, the generosity of private child maintenance arrangements between former partners, is measured as the relative importance of child maintenance payments in the income of divorced
women. This indicator is derived from the OECD Family Database (Adema et al., 2009) and is
based on information from the Luxemburg Income Study (LIS) in the year 2000. We only take into account cross-country variation, since the availability of information is limited to the year 2000.
The indicator is furthermore not available for Spain, Italy and the Netherlands.
Third, we measure homeownership rates as a percentage of the total housing stock. For the respondents who divorced before 1985, we use the homeownership rate of 1980, or the earliest observation available. For respondents who divorced after 1985, we used information from 2000
(in the case of Germany information from 2004) (Atterhög & Song, 2009; Dol & Haffner, 2010).
Fourth, turnover rates on the housing market are based on estimates derived from SHARE. The average turnover rate on the housing market is calculated as the average number of owned homes that the current sample of homeowners has owned during their life course. We only take into account cross-country variation. A cohort comparison is not feasible because younger cohorts had less time to move through the housing stock than the older cohorts. A comparison of the average number of homes different birth cohorts have lived in, shows that the variation between cohorts is very limited.
Finally, we measure the accessibility of housing finance with an index of financialisation,
constructed by the IMF (2008). The index evaluates national mortgage systems on the
possibilities for mortgage equity withdrawal, possibilities for refinancing, loan-to-value ratios, and information on the market for covered bonds and mortgage backed securities. Unfortunately, this index is not available for Switzerland. An overview of all macro-variables is given below.
Country
Female employment rate in 1980 and 2000
Child maintenance payments in 2000
Homeownership rate in 1980 and 2000
Turnover rate
Index mortgage market liberalizations
Austria 51,2% 67,5% 18,3 52% 52% 1,2 0,31
Belgium 36,4% 46,5% 14 59% 68% 1,9 0,34
Denmark
France
Germany
Italy
60,5%
43,9%
41,5%
35,0%
60,9%
50,6%
51,8%
37,9%
Netherlands 36,8% 58,4%
Spain
Sweden
28,6% 48,3%
70,0% 59,7%
9,4
16,2
17,1 x x x
11,1
56% 59%
47% 55%
39% 46%
59% 71%
42% 53%
73% 84%
58% 53%
2,3
1,6
1,2
1,2
1,9
1,3
2,1
0,82
0,23
0,28
0,26
0,71
0,4
0,66
Switzerland 51,4% 75,6% 49,7 30% 44% 1,3 x
Table 1: Overview of macro-level indicators. Source: (Atterhög & Song, 2009; Dewilde & Stier, 2014; Dol & Haffner, 2010;
Gwartney, Lawson, & Hall, 2013; OECD, 2015; Scruggs, Jahn, & Kuitto, 2014)
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Methods
For setting the scene, descriptive analyses are presented. First, homeownership rates among three marital categories (always married, divorced and single, divorced and re-partnered) are shown. This puts analyses on the effect of divorce experience on the accumulation of housing wealth among homeowning elderly in perspective, because it shows which part of divorcees is excluded from the accumulation of any housing wealth at all. Second, average housing wealth holdings (as percentage of the national median) are displayed for all three marital groups, to show international variations in the consequences of divorce experience in later life. We proceed with two country-fixed effects analyses (using OLS regression), focusing on the individual-level mechanisms behind housing wealth inequalities, controlling for all unobserved heterogeneity on
the macro- level (Möhring, 2012). Robust standard errors are used to allow residuals to vary in a
non-random way due to the structured nature of the data. One analysis investigates whether men and women in two divorce cohorts (before and after 1985) display a different effect of divorce experience on the accumulation of housing wealth in later life. Another analysis tests to what extent lower housing wealth holdings among ever-divorced homeowners in later life are the result of moves down the property ladder, temporary residence in rental housing or increased indebtedness. These three mechanisms are not included in the final model, in which cross-level interactions between institutional characteristics and marital categories are presented. Indeed, we assume that these institutional factors are the driving forces behind the three mechanisms associated with lower housing wealth holdings of divorcees, compared to those in an intact first marriage. We run all models for men and women separately. Main effects of macro-level variables cannot be added in such a country fixed-effect model, because country-level variations are captured by the model itself.
Results
Setting the scene
Homeownership rates among elderly with divorce experience are lower than among those without divorce experience in all countries (see Appendix: Table 2). Moreover, homeownership rates among re-partnered divorcees in later life are higher than among elderly singles with divorce experience. The tenure outcomes of a divorce match the conclusions of previous research
(Dewilde, 2008; Dewilde & Stier, 2014; Feijten & van Ham, 2010). Homeownership rates among
elderly couples with an intact first marriage resemble the well-known pattern, with high homeownership rates in the Mediterranean homeownership societies (80%-90%), low homeownership rates in the German-speaking rental societies (60%-70%), and moderate homeownership rates in the rest of continental Europe and Scandinavia (70%-80%). In the
German-speaking rental societies, homeownership rates among single elderly homeowners with divorce experience are around 20/30 percent points lower (ranging from 35% in Switzerland to
44% in Austria) than among couples with an intact first marriage. In the Mediterranean homeownership societies, single elderly with divorce experience display only 10 percent points lower homeownership rates than couples with an intact first marriage in Spain (85%), but 40 percent points lower homeownership rates in Italy (42%). Among the continental European and
Scandinavian welfare states with relatively large social rental sectors, the difference in homeownership rates between single elderly homeowners and couples with an intact first marriage is smaller in France and Sweden (around 15 percent points lower) than in Belgium,
Denmark and the Netherlands (around 25 percent points lower).
Elderly homeowners with divorce experience who are single have significantly lower housing wealth holdings than couples with an intact first marriage in most countries(appendix:
Table 2). The largest differences can be found in Denmark, Austria and the Netherlands. Divorced and re-partnered individuals take a middle position, but differences with married couples are in many countries non-significant. The association between divorce experience and lower housing wealth holdings of divorced elderly is confirmed by the four country-fixed effects analyses in
Table 2 (see appendix: Table 3 for an extended version), after controlling for various variables.
The first two models describe the situation of men who experienced a (non-)divorce before and
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after 1985, the second two models describe the situation of women. A comparison of the four models shows that the effect of a divorce on the accumulation of housing wealth for single homeowners in later life (1) is stronger for women than for men, and (2) strengthened over time for men and weakened over time for women. For those who experienced a divorce (or not) before
1985, the results for men are not significant, whereas they are strongly negative for women (47 percent points lower housing wealth holdings than the national mean). For those who experienced a divorce after 1985, the effect is slightly more negative for women than for men (-
33 percent compared with -31 percent). These findings match previous research that indicates that the economic position of divorced women has increased due to higher female employment rates, whereas the position of divorced men has declined, as one income is no longer enough to
afford homeownership (DiPrete & McManus, 2000). For re-partnered elderly divorced
homeowners, the negative effect of divorce experience on the accumulation of housing wealth grows over time from non-significant to moderate (-19 percent for men and -29 percent for women). Furthermore, the significant results of many country dummies (appendix: Table 3) show that there is considerable cross-country variation in the association between divorce experience and housing wealth holdings in later life.
Marital category
Intact first marriage (ref.)
Divorced and single
Divorced and re-partnered
Control variables not shown constant
R-square
Degrees of freedom
BIC
-
Men Women
Before 1980 After 1980 Before 1980 After 1980
- - -
-22,40
-10,24
-
-30,54***
-19,00**
-
-46,90***
-8,09
-
-32,90***
-29,24***
-
15,63
0,12
2257,00
27635,60
115,00**
0,10
2284,00
28128,90
6,26
0,10
2879,00
35123,30
25,29
0,10
2388,00
29505,70
* p<.1, ** p<.05, ***, p<.01
Table 2: Country fixed-effects models, estimating the effect of divorce experience on housing wealth holdings in later life for men and women in two divorce cohorts. Source: SHARE (2008/2011).
Explaining the housing wealth effect: the micro-level
The first model in Table 3 and 4 (see Appendix: Table 4 & 5 for the complete table) presents the effect of different marital categories (couples with an intact first marriage as reference category) on the accumulation of housing wealth for men and women separately, controlling for a variety of individual characteristics. Not surprisingly, the results are similar to the results of Table 2, in which the same variables are used to investigate the difference between an earlier and a later
‘divorce cohort’. Model 1 in Table 3 shows that single, elderly, homeowning men with divorce experience have 27 percentage points less housing wealth then men in an intact first marriage, whereas re-partnered elderly homeowning men have 15 percentage points less housing wealth than men in an intact first marriage. Model 1 in Table 4 shows that the association between divorce experience and reduced housing wealth in later life is stronger for women. Single elderly home-owning women have 40 percentage points less housing wealth than their counterparts in an intact first marriage, whereas those who re-partnered have 17 percentage points less housing wealth than women in an intact first marriage. The control variables in the model show the expected results (see Appendix: Table 4 & 5). Higher educational and income levels, a more urban environment, large financial gifts, a higher marital age and a lower number of children, are correlated with larger housing wealth holdings. Altogether, Model 1 in Table 3 and 4 provides evidence for the first three hypotheses. First of all, it shows that elderly homeowners with divorce experience have lower housing wealth holdings than elderly homeowners in an intact first marriage. Second, it provides evidence for the hypothesis that housing wealth holdings of women with divorce experience are lower than those of men. Finally, the higher housing wealth holdings of re-partnered divorcees relative to single divorcees show that re-partnering partly mitigates the negative effect of divorce experience on the accumulation of housing wealth over the life course.
10

Men
Marital category
Intact first marriage (ref.)
Divorced and single
Divorced and re-partnered
Control variables not shown
Time-out in rental housing
Dwelling type
Number of rooms
Mortgage size constant
R-square
Degrees of freedom
BIC
Model 1 Model 2 Model 3 Model 4
- - - -
-27,25*** -25,94*** -19,17*** -16,37***
-14,50*** -11,79** -9,27** -5,94
- - - -
-4,50 -2,47 -0,03
-28,77*** -25,55***
10,27*** 10,15***
-130,47***
70,79***
0,09
73,57***
0,09
47,36**
0,13
45,22***
0,19
9,00 9,00 9,00 9,00
55.424,00 55.418,30 53.875,50 53.584,90
* p<.1, ** p<.05, ***, p<.01
Table 3: Country fixed-effects models, estimating the effect of divorce experience on housing wealth holdings in later life for men. Source: SHARE (2008/2011).
Women
Marital category
Intact first marriage (ref.)
Divorced and single
Divorced and re-partnered
Control variables not shown
Time-out in rental housing
Dwelling type
Number of rooms
Mortgage size constant
R-square
Degrees of freedom
BIC
Model 1 Model 2 Model 3 Model 4
- - - -
-39,71*** -38,32*** -24,35*** -23,05**
-17,35*** -14,45*** -10,52*** -10,20***
- - - -
59,95***
-3,849*
63,09***
-1,97
-22,43***
12,84***
25,91**
-1,21
-20,69***
12,59***
-108,92***
28,12**
0,08
9,00
64296,40
0,08
9,00
64290,40
0,13
9,00
61336,90
0,17
9,00
61052,10
* p<.1, ** p<.05, ***, p<.01
Table 4: Country fixed-effects models, estimating the effect of divorce experience on housing wealth holdings in later life for women. Source: SHARE (2008/2011).
Two mechanisms behind the lower housing wealth holdings of elderly homeowners with divorce experience stand out: downward moves on the property ladder, and the increased usage of mortgage finance. The second model in Table 3 and 4 (see Appendix: Table 4 & 5 for the complete table) shows that temporary spells in rental housing after the first-time entry into homeownership are associated with lower housing wealth holdings for elderly, divorced, homeowning women (only significant at the 0,10 level), but not for men. However, this effect becomes non-significant in Model 3, after the addition of variables describing the housing quality.
In other words: women who have resided in rental housing after a divorce have lower housing wealth holdings than those who did not, especially because they moved into smaller properties when they re-entered homeownership. A substantial part of the lower housing wealth holdings among divorced elderly homeowners can be explained by downward moves on the property ladder, which can be concluded from a comparison of Model 2 and 3 (see Table 3 for men, Table
4 for women). Model 3 shows that living in an apartment rather than a house, and living in a home with fewer rooms, is associated with lower housing wealth holdings. The lower coefficients of the different marital categories in Model 3 compared to Model 2, imply that elderly men and women with divorce experience are over-represented in smaller apartments. For men, the effect of being divorced and single on housing wealth holdings in later life declines from -26 percent (Model 2) to -19 percent (Model 3) after the addition of variables that describe the dwelling type and size.
For women, the effect of being divorced and single declines from -38 percent (Model 2) to -24 percent (Model 3) after the addition of variables that describe the dwelling type and size. Model
5 (Table 3 and 4) confirms that elderly homeowners who have relatively larger mortgage, have lower housing wealth holdings than those who are outright owners. The lower coefficients of the divorced elderly in Model 4 compared to Model 3, imply that elderly men and women with divorce experience have larger residential debts than those in an intact first marriage. This finding provides evidence for the idea that housing wealth holdings of elderly divorced homeowners are
11

lower due to their larger indebtedness. Even after the introduction of three mechanisms that might reduce housing wealth holdings in model 2, 3 and 4, a fairly strong negative association between divorce experience and lower housing wealth holdings in later life remains in place.
Local house price developments are expected to explain another share of the variation, but could not be measured in our analysis.
Explaining the housing wealth effect: the macro-level
The effect of divorce experience on the accumulation of housing wealth in later life shows considerable cross-country variations, as can be concluded from the significant country dummies in the country-fixed effects model (Appendix: Table 2) and the cross-country differences in average housing wealth holdings of elderly home-owning divorcees (Appendix: Table 3). By including cross-level interactions between macro-level indicators and the marital trajectories to the previously presented country-fixed effects model, we investigate the influence of different institutional characteristics on the housing wealth holdings of single- and re-partnered divorcees.
The first cross-level interaction presented in Table 5 shows that the association between divorce experience and housing wealth holdings in later life does not vary across countries on the basis of their female employment rates. This result is remarkable, since previous research shows that higher female employment rates increase the odds of residing in homeownership for
divorced women (Dewilde, 2008). In other words, the selection into homeownership is driven by
different institutional factors than the accumulation of housing wealth. We suggest that it is indeed easier for previously non-working women to start working after a divorce in countries with higher female employment rates. It is however also likely that the incomes of the new entrants of the labour market are not sufficient for the accumulation of large housing wealth holdings.
The alimony hypothesis can be confirmed on the basis of the second cross-level interaction in Table 5. For single elderly divorced women, the negative impact of divorce experience on housing wealth holdings in later life is somewhat mitigated in countries with more generous systems of spousal maintenance payments. In these conservative welfare states, women often need alimony payments to be able to remain located in the former marital home. Also, because of the lower female labour market participation rates in these countries, many women without financial spousal support fall out of homeownership after a divorce, which results in a more selective (i.e. more affluent) group of homeowners with divorce experience.
The third cross-level interaction, that describes the effect of overall homeownership rates in a country, shows no significant results (Table 5). The descriptive analyses (appendix: Table 2) already showed that overall homeownership rates do not necessarily reflect the selectivity of homeownership in a country. Elderly with divorce experience live disproportionally often in a rental home in Italy (a country with relatively high homeownership rates), and disproportionally often in an owned home in Sweden, a country with relatively moderate homeownership rates. In short: different factors than the overall chance to reside in homeownership, structure the odds of
dropping out of homeownership due to a divorce (e.g., see (Dewilde & Stier, 2014)).
The fourth cross-level interaction, between the marital categories and the turnover rate on the housing market in the country, confirms the turnover rate hypothesis. In more dynamic housing markets, moving up the property ladder is essential for divorcees to keep up with couples in an intact first marriage. The results suggest that it is harder for single women with divorce experience to keep up with couples in an intact first marriage in countries with higher turnover rates on the housing market. Moreover, the stronger negative effect for single divorced women shows that their housing transitions differ more from couples in an intact first marriage than those of single divorced men. Our results suggest that re-partnered male divorcees also have relatively lower housing wealth holdings in countries with higher turnover rates on the market for owned homes. For re-partnered elderly home-owning women, the interaction is not significant.
Housing finance liberalization has a strong negative impact on the housing wealth holdings of divorced elderly home-owners, is shown by the fifth interaction in Table 5. This confirms the mortgage finance hypothesis, stating that the effect of a divorce on the accumulation
12

of housing wealth is larger in countries where re-entering homeownership is easier due to liberal mortgage finance, and where it is easier to prolong indebtedness into later life. The effect of housing finance liberalizations have a stronger impact on single women than on men. This means that men (1) make less use of advanced mortgage finance to remain in homeownership or reenter this tenure, or (2) that they are better able to amortize their debt during their life course after a divorce than women, who find themselves in general in a weaker economic position.
Moreover, house price inflation and price volatility in countries with more liberal housing finance might increase the relative difference between elderly homeowners with and without divorce experience.
Cross-level interaction Men
Female employment rate * Divorced and single
Female employment rate * Divorced and repartnered
0,08
-0,33
Generosity of maintenance payments * Divorced and single 0,16
Generosity of maintenance payments * Divorced and repartnered 0,28
Homeownership rate * Divorced and single
Homeownership rate * Divorced and repartnered
0,01
-0,04
Turnover rate * Divorced and single
Turnover rate * Divorced and repartnered
Mortgage liberalization index * Divorced and single
Mortgage liberalization index * Divorced and repartnered
-9,66
-15,20**
-23,98**
-33,30***
Women
-0,38
0,43
1,63**
-0,21*
-0,1
-0,24
-57,15***
6,25
-81,63**
-0,2
* p<,1, ** p<,05, *** p<,01
Table 5: Cross-level interactions between marital trajectories and institutional characteristics for men and women.
Source: SHARE (2008/2011).
Conclusion
After a divorce, it is common that one or both partners move to a new home. Previous research concluded that (especially female) divorcees have a larger likelihood of moving into the rental sector. This might damage their economic position, because it excludes them from a common means to wealth accumulation. Although a large majority of the divorcees stays in homeownership, or re-enters this tenure at a later moment in the life course (around 60%), it has never been researched how a divorce impacts on their housing wealth holdings in later life.
The results of our study suggest that housing wealth holdings of elderly homeowners with divorce experience are lower than of couples in an intact first marriage. The negative effect of divorce experience on the accumulation of housing wealth is found to be stronger for single elderly homeowners than for re-partnered elderly homeowners. In other words: re-partnering partly mitigates the housing wealth consequences of a divorce. The impact of a divorce on housing wealth holdings in later life is stronger for women than for men. Interestingly, the effect of a divorce on the accumulation of housing wealth differs between those who divorced before and after 1985. The potential for housing wealth accumulation after a divorce increased in the last decades for women, but decreased for men. We suggest that the stronger position of women is the result of the increased labour market equality between men and women in many countries
(DiPrete & McManus, 2000), whereas the weaker position of men results from the increased need
of a double income to pay for housing costs.
The negative association between divorce experience and housing wealth holdings of homeowners in later life can partly be explained by two mechanisms. First, elderly men and women with divorce experience live more often in smaller houses and apartments than couples in an intact first marriage. In other words: divorce is associated with downward moves on the property ladder. Second, elderly men and women with divorce experience have larger mortgages relative to the value of their home than couples in an intact first marriage. Increased indebtedness, or prolonged indebtedness into later life, is often the only way for divorcees to remain in homeownership, or to re-enter this tenure.
A negative association between divorce experience and housing wealth holdings of homeowners in later life is found in all 10 researched European countries. However, there is considerable cross-country variation in the size of this association on the basis of housing and welfare regime characteristics. We find that the negative association between divorce experience
13

and housing wealth holdings in later life is stronger in countries in which divorcees have a larger chance of moving down the property ladder within homeownership instead of moving into rental housing. Larger housing wealth consequences of divorce experience are not necessarily found in countries with higher homeownership rates, but in countries that facilitate a transition from renting into owning. We point at the importance of two institutional factors. First of all, in countries with more liberal housing finance systems, the negative effect of a divorce on the accumulation of housing wealth is stronger because the wide-spread availability of mortgage finance makes it easier for divorcees to remain in homeownership or to re-enter this tenure, and remaining indebted until later life. Second, in countries with ‘dynamic housing markets’ in which
trading up in the property market is common (Van der Heijden et al., 2011), the effect of a divorce
on the accumulation of housing wealth is stronger. In these countries, divorcees are not able to trade up the housing market to the same extent as couples with an intact first marriage. We point at one mechanism that partly mitigates the negative association between divorce experience and housing wealth holdings of elderly, home-owning women, namely the generosity of alimony in a country. Especially in conservative welfare states, with low female employment rates, child maintenance payments are essential for women to remain in the former, owned, marital home.
The question under which institutional circumstances elderly with divorce experience are better off, is hard to answer because of two reasons. First of all, due to the selective sample
(homeowners only), a relatively small difference between elderly homeowners with and without divorce experience might simply mean that a large share of those who experience a divorce are excluded from the accumulation of housing wealth, because they rent in later life (these respondents are hence not in our sample). Yet, the accumulation of a relatively low amount of housing wealth might be preferable over no housing wealth at all. Indeed, in most countries owners enjoy a higher level of tenure security compared with renters. Second, a large difference in housing wealth holdings between elderly homeowners with and without divorce experience might hide a more equal distribution of net worth, a variable which we did not include. For instance, those who move out of homeownership permanently might exchange their housing wealth for financial wealth. However, previous research found housing wealth to be the prime
source of wealth for most households (Cowell et al., 2012). Moreover, many couples divorce at a
moment in the life course when they did not yet accumulate much housing wealth.
To conclude, divorce experience is associated with a lower likelihood of residing in
homeownership in later life (Dewilde & Stier, 2014), but also with lower housing wealth holdings
among those who remain in homeownership or re-enter this tenure again after a spell in rental housing. Differences between elderly with and without divorce experience are larger in countries that facilitate moves from rental housing into homeownership. To grasp in more detail in which way divorce experience affects the accumulation of housing wealth, future research needs to be directed to the interplay between housing wealth and financial wealth, and to the local housing market dynamics in which the housing transitions before and after the divorce take place.
Acknowledgement
This research is funded by the European Research Council (Grant Agreement No. 283615, directed by Caroline Dewilde). This paper uses data from SHARE wave 4 release 1.1.1, as of March
28th 2013(DOI: 10.6103/SHARE.w4.111) or SHARE wave 1 and 2 release 2.6.0, as of November
29 2013 (DOI: 10.6103/SHARE.w1.260 and 10.6103/SHARE.w2.260) or SHARELIFE release 1, as of November 24th 2010 (DOI: 10.6103/SHARE.w3.100). The SHARE data collection has been primarily funded by the European Commission through the 5th Framework Programme (project
QLK6-CT-2001-00360 in the thematic programme Quality of Life), through the 6th Framework
Programme (projects SHARE-I3, RII-CT-2006-062193, COMPARE, CIT5- CT-2005-028857, and
SHARELIFE, CIT4-CT-2006-028812) and through the 7th Framework Programme (SHARE-PREP,
N° 211909, SHARE-LEAP, N° 227822 and SHARE M4, N° 261982). Additional funding from the
U.S. National Institute on Aging (U01 AG09740-13S2, P01 AG005842, P01 AG08291, P30
AG12815, R21 AG025169, Y1-AG-4553-01, IAG BSR06-11 and OGHA 04-064) and the German
Ministry of Education and Research as well as from various national sources is gratefully acknowledged (see www.share-project.org for a full list of funding institutions).”
14

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16

Appendix
Situation first partner
Living with first partner
Widowed
First partner in care center
Not together due to unknown
Divorced
Divorced
Divorced and remarried
Divorced and remarried
Divorced and remarried
Widowed
Widowed
Widowed
Not together due to unknown
Not together due to unknown
Not together due to unknown
Current state
"
"
"
"
Not repartnered
Repartnered
Widowed
Partner in care center
Not together due to unknown
Widowed again
Repartnered
Not together due to unknown
Widowed
Partner in care center
Not together due to unknown
Classification
Men Women Total
1
0
1
4
8
96
0
3,951 3,955
203 798
3
12
2
13
174 258
437 350
19
1
77
1
4
2
5
10
22
82
1
5
2
6
14
30
178
1
432
787
96
2
7,906 Intact first marriage
1,001 Intact first marriage
5
25
Intact first marriage
Other trajectory
Divorced and single
Divorced and repartnered
Divorced and repartnered
Divorced and repartnered
Other trajectory
Other trajectory
Other trajectory
Other trajectory
Other trajectory
Other trajectory
Other trajectory
Total 4910 5580 10490
Table 1: Marital trajectories, followed by respondents in SHARELIFE, and their final classification. Source: SHARELIFE, own calculation.
17

country
Austria
Germany
Sweden
Marital trajectory
Always married
Lower bound
63%
Divorced with partner 34%
Divorced without partner 32%
Other trajectory
Always married
60%
66%
Divorced with partner 52%
Divorced without partner 29%
Other trajectory 42%
Always married
Divorced with partner
79%
68%
Divorced without partner 57%
Other trajectory 74%
Netherlands Always married
Divorced with partner
Divorced without partner
Other trajectory
69%
70%
38%
57%
Spain
Italy
France
Always married
Divorced with partner
93%
93%
Divorced without partner 69%
Other trajectory 69%
Always married 84%
Divorced with partner 66%
Divorced without partner 26%
Other trajectory
Always married
60%
85%
Divorced with partner 74%
Divorced without partner 62%
Other trajectory 59%
Denmark Always married
Divorced with partner
Divorced without partner
Other trajectory
Switzerland Always married
81%
72%
42%
67%
64%
Belgium
Divorced with partner 55%
Divorced without partner 27%
Other trajectory
Always married
27%
86%
Divorced with partner 71%
Divorced without partner 45%
71%
77%
46%
69%
59%
40%
55%
81%
73%
65%
83%
Homeownership rate
64%
48%
44%
75%
69%
80%
68%
70%
83%
77%
49%
77%
67%
63%
35%
42%
87%
76%
52%
76%
42%
75%
87%
94%
98%
84%
85%
85%
Other trajectory 59% 69% 78% 62 110 132 154 42
Table 2: Descriptive statistics, showing the homeownership rate and housing wealth holdings of people in different marital trajectories. Source: SHARE (2008/2011), own calculations.
85%
74%
81%
84%
81%
57%
86%
70%
72%
43%
56%
89%
81%
59%
86%
58%
89%
88%
95% 1257 128
104% 17 96
99% 17
101% 14
87%
72
86
1715 128
48
27
26
1271
96
57
107
123
168 114
148 97
45 114
1080 142
236 115
127 73
53 79
719 139
92
98
106
89
34 58
1553 118
194 104
136 95
73%
84%
55%
81%
66%
50%
69%
83%
79%
73%
93%
Higher bound N
70%
Lower bound
416 107
63%
57%
91%
71%
34
45
23
1036
84
54
73
126
136 96
67 74
39 80
866 144
197 136
94
44
86
95
1224 119
103 80
94
45
65
103
123
92
83
123
Housing wealth
114
97
72
99
132
114
104
122
153
153
115
119
127
109
136
150
132
106
113
149
136
134
104
121
114
110
115
98
140
127
134
146
132
123
133
128
103
101
144
132
133
164
162
170
144
144
Higher bound N
120 263
110
90
125
138
17
20
15
717
81
25
21
707
151
62
37
867
77
44
29
139
122
158
157
149
138
148
159
165
180
150
124
125
125
135
139
173
132
139
196
193
160
137
122
98
32
883
178
61
40
470
57
35
12
1331
148
69
1141
16
14
12
1482
38
10
21
1052
18

Marital category
Intact first marriage (ref.)
Divorced and single
Divorced and re-partnered
Non-standard trajectory
Age of first marriage
Age entering homeownership
Number of children
-
Men
Before 1980
-22,40
-10,24
-7,06
1,79***
-0,65***
1,08
Urbanity
Received gift (5000E)
Migrant status
18,16***
34,53***
-1,43
Homeownership 5 years after marriage -0,81
Educational level
Pre-primary (ref.) -
Primary education
Lower secondary
(Upper) secondary
Post-secondary
First stage tertiary
Birth cohort
Before 1930 (ref.)
1930-1939
24,76***
33,62***
43,06***
59,01***
82,41***
-
12,03**
1940-1949
1950 and later
Income
Lower than median (ref.)
Higher than median
Higher than two * median
Country dummies
Austria (ref.)
Germany
Sweden
Netherlands
Spain
Italy
France
Denmark
Switzerland
Belgium constant
R-square
Degrees of freedom
BIC
6,53
-24,65
-
4,98
40,57***
-
10,60
42,15***
2,32
18,44*
36,15***
31,99***
25,16**
38,02***
5,66
15,63
0,12
2257,00
27635,60
-48,21
-61,56
-
10,163*
15,85***
-
-10,31
39,97***
-14,10
40,42***
35,74***
18,46*
23,68*
19,86
1,90
115,00**
0,10
2284,00
28128,90
-
Women
After 1980 Before 1980 After 1980
- -
-30,54*** -46,90***
-19,00** -8,09
-28,77* -9,86
-0,52
-0,13
0,36
2,89***
-0,81***
-1,52
-32,90***
-29,24***
3,86
0,51
0,16
3,61*
13,82**
16,02**
5,62
-9,45
-
9,11**
26,57***
-2,54
8,911*
-
27,06***
55,28***
56,92***
23,27***
45,39***
52,67***
-
89,63*** 51,46***
104,58*** 91,34***
-49,13
-
-5,86
7,67
27,63***
1,37
-12,41**
-
27,96**
59,68***
69,27***
-
123,54***
103,64***
-2,64
4,38
-11,17
-
1,30
12,13
-
16,59*
42,27***
14,74*
39,22***
41,58***
32,74***
31,93***
41,77***
11,08
6,26
0,10
2879,00
35123,30
17,26
3,79
-
-3,65
0,42
-
-12,28
17,33
-17,55*
40,87***
29,16***
0,29
8,02
23,10
0,91
25,29
0,10
2388,00
29505,70
* p<.1, ** p<.05, ***, p<.01
Table 3: Country-fixed effects analysis, with country dummies, for two divorce cohorts, and men and women separately.
Source: SHARE (2008/2011).
19

Men
Model 1 Model 2
Marital category
Intact first marriage (ref.)
Divorced and single
Divorced and re-partnered
Non-standard trajectory
Age of first marriage
- -
-27,25*** -25,94***
-14,50*** -11,79**
-12,72 -11,66
0,18 0,21
Age entering homeownership -0,41
Homeownership 5 years after marriage -4,69
Number of children
Urbanity
Received gift (5000E)
0,73
16,19*
22,28**
Migrant status
Educational level
Pre-primary (ref.)
1,02
-
-0,50
-5,15
0,82
16,40*
22,34**
1,42
-
Primary education
Lower secondary
(Upper) secondary
Post-secondary
First stage tertiary
Birth cohort
Before 1930
1930-1939
1940-1949
1950 and later
Income
Lower than median
Higher than median
Higher than two * median
Time-out in rental housing
Dwelling type
Number of rooms
Mortgage size constant
28,47***
48,27***
51,77***
76,19***
96,10***
-
8,01
3,77
-13,22
-
6,12
23,66**
70,79***
-4,50
73,57***
28,64***
48,30***
51,84***
76,35***
96,52***
-
8,13
3,52
-13,38
-
6,41
23,87**
R-square
Degrees of freedom
BIC
0,09
9,00
55.424,00
0,09
9,00
55.418,30
* p<.1, ** p<.05, ***, p<.01
Table 4: Country-fixed effects models for men. Source: SHARE (2008/2011), own calculations.
Model 3
30,74***
49,39***
52,03***
78,06***
88,92***
-
5,73
1,79
-16,23*
-
5,56
22,24**
-
-19,17***
-9,27**
-9,34
-0,20
-0,24
-5,64
-2,54**
28,64***
18,37**
5,81
-
-2,47
-28,77***
10,27***
47,36**
0,13
9,00
53.875,50
Model 4
28,42***
46,80***
51,39***
79,38***
88,01***
-
9,66
11,74
-0,26
-
6,20
24,57***
-
-16,37***
-5,94
-3,99
-0,19
-0,14
-4,73
-1,63
26,87***
15,79**
4,75
-
-0,03
-25,55***
10,15***
-130,47***
45,22***
0,19
9,00
53.584,90
20

Women
Model 1 Model 2
Marital category
Intact first marriage (ref.)
Divorced and single
Divorced and re-partnered
Non-standard trajectory
Age of first marriage
- -
-39,71*** -38,32***
-17,35*** -14,45***
-7,21 -6,12
1,10*** 1,14***
Age entering homeownership -0,43**
Homeownership 5 years after marriage -0,09
Number of children
Urbanity
Received gift (5000E)
0,41
9,11
27,297***
-0,51**
-0,56
0,46
9,26
27,25***
Migrant status
Educational level
Pre-primary (ref.)
3,34
-
3,39
-
Primary education
Lower secondary
(Upper) secondary
Post-secondary
First stage tertiary
Birth cohort
Before 1930
1930-1939
1940-1949
1950 and later
Income
Lower than median
Higher than median
Higher than two * median
Time-out in rental housing
Dwelling type
Number of rooms
Mortgage size constant
26,65**
54,29***
61,81***
88,69***
98,05***
-
-8,43
3,11
-11,43
-
-1,44
3,11
59,95***
-3,849*
63,09***
26,24**
53,72***
61,45***
87,81***
97,68***
-
-8,48
2,83
-11,99
-
-1,29
3,11
R-square
Degrees of freedom
BIC
0,08
9,00
64296,40
0,08
9,00
64290,40
* p<.1, ** p<.05, ***, p<.01
Table 5: Country-fixed effect models for women. Source: SHARE (2008/2011).
Model 3
27,81**
52,14***
58,09***
83,86***
89,43***
-
-8,96
-0,01
-15,875*
-
-2,22
2,39
-
-24,35***
-10,52***
-2,75
0,67**
-0,27
0,45
-2,95*
20,789*
24,98***
1,90
-
-1,97
-22,43***
12,84***
25,91**
0,13
9,00
61336,90
Model 4
27,33**
44,95***
57,24***
85,79***
88,22***
-
-9,10
4,05
-6,11
-
-1,15
5,86
-
-23,05**
-10,20***
-2,00
0,69** *
-0,21
2,15
-2,11*
19,74*
22,72***
1,39
-
-1,21
-20,69***
12,59***
-108,92***
28,12**
0,17
9,00
61052,10
21