The Divorce Gender Gap: Gender Differences in Economic Conditions and General Well-Being After Divorce

Abstract

Does divorce influence the economic gender gap between men and women? To answer this question, we use two datasets from Israel for the years 2012–2017 which provide information on both objective and subjective measures of economic and general well-being. We find that divorced women encounter a steep and persistent decline in their household income compared to divorced men. In addition, divorced women increase their employment significantly. Further, we find that divorced women report less satisfaction with their economic situation. We also find some indication that divorced women experience less ability to cover their monthly expenses, and possibly experience more stress compared to divorced men. We suggest that these factors may be interrelated. The decline in household income on one hand, and the increased employment on the other hand, decrease satisfaction with economic situation, and possibly lead to stress. This suggests a transmission pathway from objective economic disruption to subjective dissatisfaction and psychological stress among divorced women.

Keywords

gender gap divorce/separation economic issues well-being poverty/welfare

Introduction

The gender gap in income and wages between men and women is well documented in the academic literature (see, among many others, Rosenfeld & Kalleberg, 1990), but do these differences amplify after going through a divorce? There is evidence to suggest that gender influences motives for divorce as well as the way a person deals with divorce (Walzer & Oles, 2003). Yet, in what way does it affect the economic consequences of the divorce? Most research focused on objective economic measures, such as household income before and after the divorce. The vast majority of studies demonstrated that women experience a decline in their standard of living as a result of divorce compared to men (Weitzman, 1985; Hoffman & Duncan, 1988; Burkhauser et al., 1990, 1991; Poortman, 2000; Andreß et al., 2006; de Regt et al., 2013; Sharma, 2015; De Vaus et al., 2017; Leopold, 2018; Mortelmans et al., 2020; Brüggmann & Kreyenfeld, 2023). However, a few studies find that divorce does not lead to an increase in the gender gap in economic well-being (Aassve et al., 2007; Braver, 1999; McManus & DiPrete, 2001). Despite the significance given in recent years to subjective measures of economic well-being (i.e., one’s perception of the economic state), very few studies have examined gender differences in subjective economic perceptions of divorcees.

The gendered economic consequences of divorce are rooted in the dynamics of marriage itself. Holden and Smock (1991) established that women bear a disproportionate share of divorce costs because marriage typically involves gender specialization in the division of labor: women reduce their labor market investment in favor of domestic and caregiving roles, accumulating human capital deficits that render them economically vulnerable upon dissolution. Bröckel and Andreß (2015) extended this framework, showing that the degree of specialization during marriage directly predicts the magnitude of women’s post-divorce income loss. These economic shocks, however, do not remain confined to the material domain. Drawing on the family stress model (Conger et al., 1990), we argue that income decline and increased employment burden are jointly linked to subjective economic dissatisfaction and psychological distress—a potential transmission mechanism that has been empirically underdeveloped in the divorce literature. Understanding why this penalty persists in contemporary societies also requires attention to broader processes of family change. Esping‐Andersen and Billari (2015) and Goldscheider et al. (2015) argue that gender inequality in family outcomes reflects a stalled gender revolution: women have entered the labor market but men have not equally assumed domestic responsibilities, and institutional supports have not fully compensated for this asymmetry. Israel is a theoretically informative case in this regard, combining high female labor force participation with one of the largest gender pay gaps in the OECD and strong familist norms—a context where the first half of the gender revolution has progressed but the second half has stalled, predicting that divorced women will face acute and multi-dimensional penalties. This is further compounded by Israel’s relatively large religious population, which is associated with higher fertility rates and lower divorce rates, meaning that those who do divorce do so against a normative backdrop that may intensify economic and psychological strain. Herbst-Debby et al. (2021), using Israeli administrative data, confirm that divorce sharply increases poverty risk for women with children while decreasing it for men, but do not examine subjective economic or psychological dimensions. The present study fills this gap.

We use two large and representative contemporary datasets from Israel in order to explore the effect of divorce on subjective and objective measures of the economic and psychological condition of divorced women compared to divorced men. We offer a holistic approach to study the well-being of individuals and explore both subjective and objective economic measures as well as psychological measures. We document several gender differences which are related to divorce. Specifically, we find that divorced women suffer greater loss of household income compared to divorced men. On the other hand, divorced women report higher levels of employment than married women, while divorced men report a slight decrease compared to married men. In addition, women report lower levels of subjective economic well-being, lower ability to cover monthly expenses, as well as somewhat higher levels of stress. The decline in the economic and psychological situation of divorced women can be explained by a loss of household income on one hand, and by the increased employment due to being the prime caregiver on the other hand. Both factors lead women to experience economic hardship, to express less satisfaction with their economic situation, and possibly to experience more stress. Israel is particularly well-suited for this analysis, as its national social survey provides unusually rich data on non-economic well-being alongside standard economic measures.

Our main contribution to the literature is threefold. First, we extend the marital specialization framework by theorizing and providing empirical evidence regarding the pathway through which objective economic disruption transmits into subjective economic dissatisfaction and psychological stress. Prior work, including Leopold (2018), which is the closest study to ours, documents multi-domain outcomes in parallel, but stops short of the mechanism connecting them. We show that income decline and increased employment burden are jointly linked to divorced women’s subjective and psychological deterioration, offering an integrated account that goes beyond cataloging outcomes across domains. Second, we contribute to the limited literature on the Israeli context, combining panel data of pre- and post-divorce change with cross-sectional survey data that provide a richer set of subjective and psychological outcomes—a two-dataset approach that is rare in this literature. Third, by situating our findings within the gender revolution framework, we show that Israel’s specific combination of high female employment, a large gender pay gap, and strong familist norms produces a post-divorce penalty that is both economically severe and psychologically consequential, with implications for similarly positioned societies where labor market integration of women has outpaced normative and institutional change.

Literature Review and Theoretical Considerations

Divorce is a key life-course risk event, which usually has both significant economic consequences and a general negative effect on well-being. It is well known that a divorce has several economic costs due to the loss of the partner’s income, necessity of running the household without a partner, divorce procedures and divorce arrangements. Some authors describe these costs as a “divorce penalty” (Kalmijn, 2005; Raz-Yurovich, 2013). The divorce penalty is paid by both ex-partners but is not equally shared by men and women. According to the current research, women (and their dependent children) are typically those who lose more after divorce, while men experience a moderate decline, if any, in their economic status. The main reason for this difference is that children tend to stay with their mother after a divorce, meaning that household size is larger for divorced women compared to divorced men. In addition, since men’s labor earnings are usually greater than those of women, divorce leads to larger declines in household income for women than for men (Blau & Kahn, 1992). This loss is partly compensated by child support and alimony payments.

Indeed, some differences in the economic situation of men and women may pre-exist the divorce procedure. The most typical example is the gap in wages between men and women. Although this gap has diminished considerably over the past 20 years, men continue to earn more than women in virtually all industrialized countries (see, e.g., Albrecht et al., 2003; Arulampalam et al., 2007; Blau & Kahn, 1992, 2003). The reasons for the male-female wage gap lie both in gender-specific factors, such as employer discrimination against women or shortage in female human capital, and in the overall structure of the labor market (Blau & Kahn, 2003). Our main purpose, however, is to isolate the specific part of the economic gap between men and women that can be related to the influence of divorce.

How can the changes in the economic situation following divorce be estimated? The prevailing approach in the research literature is to use household income adjusted to family size as the measure for economic well-being. This measure captures the loss of a partner’s income to the household. A simple division of the household income by the number of individuals in the household is not enough, because this method does not account for economies of scales. Therefore, household income is usually adjusted by means of equivalence scale (Fisher & Low, 2015). Several equivalence scales are used in the literature, while the common standard has not yet been found (Andreß et al., 2006).

A large body of research examined changes in women’s household income following divorce. Virtually all studies find a decline in household income, but there are conflicting estimates regarding the extent of the decline. More than 30 years ago Weitzman in her influential book (1985) documented a 73% decline in the standard of living of women following divorce. Peterson (1996) re-evaluated Weitzman’s sample and found a substantially lower decline of 27%. Similarly, Hoffman and Duncan (1988) reported that women’s standard of living declines by only about one-third after divorce. Similar estimates were reported by Poortman (2000), Dewilde (2002) and Uunk (2004). On the other hand, Smock (1994) showed that per-capita income of divorced women drops to 55%–66% of per-capita income of divorced men.

Research on household income of men after divorce presents a more complicated picture. Weitzman (1985) reported an increase of 42% in the standard of living of men, but Peterson’s re-evaluation of Weitzman’s data (Peterson, 1996) estimated a 10% increase only. Duncan and Hoffman (1985) found only a slight increase in men’s family income after divorce. Poortman (2000) reported similar results. However, the majority of authors suggested that both men and women experience a decline in their household income, but for women the decline is larger (e.g., Burkhauser et al., 1990, 1991; Andreß et al., 2006; de Regt et al., 2013; De Vaus et al., 2017; Mortelmans et al., 2020; Brüggmann & Kreyenfeld, 2023). A gender gap in economic conditions was documented also among separated partners who cohabited but were not previously married (Avellar & Smock, 2005). However, this gap is estimated as relatively small, because the income loss of separated women was found to be both less substantial and less persistent compared to divorced women, while there is no difference between divorced and separated men (Fisher & Low, 2009, 2015; Manting & Bouman, 2006).

In contrast to most studies, some authors find no evidence for a gender economic gap resulting from divorce. Braver (1999) proposed to amend the calculations of standard of living after divorce made by Weitzman (1985), Duncan and Hoffman (1985) and Hoffman and Duncan (1988) by introducing adjustments for unequal taxes and parents’ sharing of expenses on children. He found that after this adjustment is made, there is virtually no difference between men’s and women’s standard of living after divorce. McManus and DiPrete (2001), using panel data from the US found that men also experience a significant decrease in their standard of living, due to loss of partner’s income, as well as to both compulsory and voluntary support payments. According to their findings, men can improve their economic situation after divorce only when the income of their ex-partner was less than one-fifth of the total household income. According to McManus and DiPrete these results show a clear trend towards higher economic interdependence between men and women.

To provide a complete picture of economic well-being after divorce, its measurement must include government welfare payments received by a single parent, as well as divorce arrangements, such as child support and spousal support (alimony) payments by ex-partner. However, even when household income is measured after these payments, most studies still find a significant gender gap. Poortman (2000) used disposable income, that is, income after taxes and transfers, including alimony payments, and found a substantial gender gap after divorce. Bayaz-Ozturk et al. (2018) compared household income before and after taxes and welfare transfers and found that women suffer greater declines than men in both measures of income. Fisher and Low (2009) suggested that governmental benefits matter only for a small group of divorced women, mainly uneducated. De Vaus et al. (2017) concluded that the negative effect of divorce on household income for men is much smaller than for women, even when divorce arrangements and governmental payments are considered.

Besides household income, changes in economic well-being after divorce may be reflected in non-monetary outcomes. Aassve et al. (2007) find a substantial gender gap after divorce in household income; however, when non-monetary measures were used, gender gap was found to be significantly lower, and in some cases even non-existent. Non-monetary measures used by these authors are indices of deprivation of household and personal economic needs. Their conclusion is that divorced women suffer a reduction in income, while divorced men suffer from deprivation of economic needs due to the need to find a new dwelling.

To cope with the loss of the partner’s income after divorce or separation ex-partners may implement two main strategies: increasing employment and finding a new partner (Jansen et al., 2009). Tamborini et al. (2015) reported a long-lasting increase in women’s personal earnings after divorce, particularly among those who did not remarry. However, several studies find that finding a new partner is a much more effective strategy for women than increasing employment (de Regt et al., 2013; Fisher & Low, 2009; Jansen et al., 2009; Mortelmans et al., 2020). However, men do not benefit economically from finding a new partner (Jansen et al., 2009).

The difference between the economic well-being of divorced or separated men and women is influenced by the presence of children in the household. Divorced women typically remain with their dependent children, while men only provide external support. In absence of children the gender gap was found to be much smaller (Aassve et al., 2007; Gray & Chapman, 2007). The presence of children in the household, especially the young ones, has negative effect on the chances of divorced women in the labor market (Jansen et al., 2009).

Divorce is reported to have negative effects on the non-economic well-being of both ex-partners, especially during the first years after divorce (see for instance Kurdek, 1991). As for gender differences in non-economic conditions after divorce, some studies point to an advantage of women over men. For example, Diedrick (1991) suggested that women after separation and divorce fare better in health and psychological terms than do males. Sheets and Braver (1996) found that women are more satisfied with divorce settlements than men, possibly because men perceive the process as biased against them. Kalmijn (2007) showed that divorced fathers receive less support from their children compared to divorced mothers.

While assessing changes in overall well-being after divorce, it is important to look at both objective and subjective measures. Men and women may have different preferences regarding the same economic and social conditions; therefore, well-being analysis based solely on objective measures presents only a partial picture. For instance, Croson and Gneezy (2009) found that risk, cooperation, and competition preferences differ between men and women. Unfortunately, most of the contemporary studies consider only objective well-being measures. Leopold (2018) is one of few studies examining both objective and subjective outcomes concerning economic and general well-being conditions. He finds that in the short run men are more adversely affected from divorce in terms of subjective well-being measures, but the gender difference is alleviated later. In the medium run there are not many differences between men and women in most of the outcomes. As for economic measures, such as household income and the risk of poverty, he finds that the divorced women suffer from disproportionate and persistent deterioration, when compared to men.

Two studies have been conducted using data for Israel. Raz-Yurovich (2013) studied the impact of divorce on economic activity and salary of men and women, using unique register-based panel dataset. She found that women increase their employment stability and the number of jobs held after divorce, while men after divorce experience a decline in these outcomes. However, women’s earnings do not increase after divorce, and their salary grows slower, as compared to married women, while men’s salary growth is not influenced by divorce. According to Raz-Yurovich, the possible explanation for this discrepancy is that divorced women switch to part-time jobs; therefore, the increase in their economic activity does not lead to an increase in salary growth. Recently, Lewin and Stier (2018) studied the economic consequences of divorce for both men and women, using the cross-sectional data from the Israeli Social Survey. They found that women were more likely than men to experience poverty and economic hardship after divorce. They also found that long divorced individuals of both genders were worse off than married, but the individuals who divorced and remarried did not differ from those who remained married. More recently, Herbst-Debby et al. (2021), using administrative panel data, found that divorce increases poverty risk for women with children while decreasing it for men, but did not examine subjective economic or psychological dimensions. We extend these studies by adding additional objective income measures as well as subjective non-economic measures of well-being. This allows us to offer a holistic approach which we believe more accurately describes gender differences post-divorce.

To sum up, the findings from the literature lead to two main conclusions. First, divorce has some consequences for well-being of both men and women. Second, there is a gender gap in favor of men in some economic conditions regardless of marital status (Arulampalam et al., 2007; Blau & Kahn, 2003). Finally, there is an overwhelming evidence for the gender gap in objective economic conditions in the effect of divorce (Andreß et al., 2006), but little evidence on the effect of divorce on gender differences in subjective and non-economic measures of well-being.

The contribution of our study is in providing a holistic view of the implications of divorce for men and women by analyzing both objective and subjective economic, as well as non-economic well-being measures. Considering the aforementioned conclusions from the research literature we tested the following hypotheses.

Before the divorce, both objective and subjective measures of economic condition are higher for men.

There is a decline in both economic and non-economic well-being measures after divorce for both men and women.

The decline in both economic and non-economic well-being measures is larger for divorced women than for divorced men.

Data, Methods, and Results

Background

Hypotheses H1-H3 were tested using data on married and divorced men and women in Israel. In recent years rates of divorce in Israel were lower than in most OECD countries. The OECD Family Database reports of divorce rates, as well as of gender gaps in employment and wages (OECD, 2019, 2020, 2021). On one hand, in 2019 crude divorce rate (i.e., divorces per 1,000 people) in Israel was 1.8, as compared to an average rate of 2.0 in the OECD. On the other hand, rates of divorce in Israel grew rapidly during recent decades. Israel is among those OECD countries whose crude divorce rates more than doubled during the period from 1970 to 2019 (OECD, 2021).

OECD data on gender gaps in the labor market present a complex picture. On one hand, the gap between employment rates of men and women in Israel in 2018 was much narrower than in most OECD countries: 5.2%, as compared to an average gap of 11.1% in OECD countries. The gap in full-time employment in Israel in the same year was only slightly narrower than the OECD average: 18.0% and 20.3%, respectively (OECD, 2019). On the other hand, the pay gap between men and women, based on median earnings of full-time workers, is much wider in Israel (22.7%) than in the OECD on average (13.0%). In Israel, as in most OECD countries the gender pay gap fell between 2002 and 2018, but the decline in Israel was slower: 1.5 percentage points, compared to 3.9 percentage points in the OECD on average (OECD, 2020).

Our data come from two main surveys carried out by the Israel Central Bureau of Statistics: The Longitudinal Survey and the Social Survey. Both are annual, national representative surveys that provide updated information on the living conditions and welfare of the permanent population of Israel. Both surveys provide both subjective and objective measures of economic conditions and well-being and are therefore very appropriate to the questions we investigated.

Data

The Longitudinal Survey: Panel Data

Sample

Our main goal is to explore the relationship between gender and marital status of individuals on the one hand, and their economic, social, and psychological situation on the other hand. For this purpose, we use the panel data from the Longitudinal Survey of the Israel Central Bureau of Statistics. This survey is conducted once a year, beginning with 2012 and provides continuous data on a sample of individuals and their households’ members which represents the permanent population of Israel. The Longitudinal Survey has questionnaires for both households in general and their individual members. The individual-level questionnaire deals with household members of all ages and contains various questions on demographics, health, education, employment, and income. We use data from the Longitudinal Survey on the same individuals observed during the years 2012–2017. This period comprises 6 years, but only five waves of the survey, because in years 2014 and 2015 only one survey was conducted.

The survey follows only individuals who were sampled during the first wave (2012) and the members of their households. The individuals who joined the sampled households in the subsequent waves are surveyed together with other members of the household. In contrast, the individuals who left the sampled households drop from the survey. Therefore, the obtained panel data is unbalanced, that is, some individuals may not appear in all waves of the survey. We consider individuals who appear at least in two waves. Our sample includes those who were married during their first appearance in the panel and got divorced in one of the later panel years. Current research suggests that a new partner may offset the negative economic consequences of a divorce. The Longitudinal Survey includes some divorced individuals who remarried later, but their number is too small to allow us to perform any significant analysis. Therefore, the remarried individuals were excluded from the sample. It leaves us with a panel of 322 observations of 95 individuals who divorced during the panel period. Out of them there are 181 observations of 54 women. In total there are 168 observations of individuals after divorce (out of them 74 of men and 94 of women), which comprise 52% of this sample.

Measurement

To assess the association between personal well-being, gender and divorce we use several measures of well-being. First, we consider income measures that provide monetary estimates of economic well-being. The standard economic analysis looks at percentage rather than unit changes in income; therefore, we use the natural logarithm of income (below: log of income). We use two income measures:

1.-2. Log of adjusted and unadjusted annual household income from work. Household income is a primary measure of economic well-being examined in the research on the economic consequences of divorce. Household income is especially relevant for women who are usually the care takers of the children. This measure is generally adjusted to household size to account for economies of scale. In the literature several scales of adjustment are used, but the common standard has not been found yet. Following Andreß et al. (2006) we use the simple square root scale:

a d j u s t e d h o u s e h o l d i n c o m e = \frac{household income}{\sqrt{n u m b e r o f h o u s e h o l d m e m b e r s}}

Second, we analyze the influence of divorce on employment status of men and women. On the one hand, the literature provides evidence that increasing employment is one of the main strategies of coping with negative economic consequences of divorce. On the other hand, both men and women may experience difficulties with increasing their employment after divorce because of the lack of time due to an increase in household duties, or meeting arrangements with the children. The measures indicating employment are dummy variables that receive a value of one or zero. We examine three employment outcomes.

3. Working during the last year.

4. Participation in the labor force during the last week, including both employed and unemployed individuals who can work and search for work, excluding pensioners, students, soldiers, household workers, etc.

5. Working full time during the last week out of those who reported working during the last week.

Third, we use two subjective self-reported well-being measures. In the survey these measures are based on rating scale questions with four possible answers. We construct dummy variables from these answers which receive a value of one for the higher rated options and zero for the lower rated ones. These subjective well-being measures are.

6. Considered themselves poor: the variable receives a value of one if an individual reports that he thought of him- or herself as poor at least sometimes, and a value of zero otherwise.

7. Reported good health condition: the variable receives a value of one if a person reports that his health condition is very good or good, and a value of zero otherwise.

In addition to gender and marital status, we control for several background characteristics that may influence the outcomes we study: age, years of schooling, and belonging to certain sectors of the Israeli society, as the Arab or new immigrants who came to Israel after 1990 (our sample does not include members of the ultra-Orthodox community). The Longitudinal Survey data on years of schooling provides ranges instead of exact numbers. This data was converted into mid-range points in order to obtain the continuous variable for the purposes of calculating descriptive statistics. Descriptive statistics for the outcome variables and the background characteristics in our sample are reported in Table 1. From the panel of 322 observations, the number of observations for Arabs and new immigrants is identical (66 observations for each group); therefore, their proportion in the sample is the same.

Table 1.

Descriptive Statistics. The Longitudinal Survey

Panel A. Outcomes		Panel B. Background variables
Log of adjusted household income from work	11.22	Women	0.562
Log of adjusted household income from work	(1.07)	Women	(0.497)
Log of unadjusted household income from work	11.70	Divorced	0.522
Log of unadjusted household income from work	(1.10)	Divorced	(0.500)
Worked during last year	0.769	Number of household members	3.03
Worked during last year	(0.422)	Number of household members	(1.75)
Labor force participation (weekly)	0.720	Age	45.00
Labor force participation (weekly)	(0.449)	Age	(13.09)
Worked full time (weekly, out of working population)	0.772	Years of schooling	14.23
Worked full time (weekly, out of working population)	(0.421)	Years of schooling	(3.85)
Considered themselves poor	0.381	Arabs	0.205
Considered themselves poor	(0.487)	Arabs	(0.404)
Good health condition	0.861	New immigrants (1990+)	0.205
Good health condition	(0.347)	New immigrants (1990+)	(0.404)

Source: CBS, The Longitudinal Survey, 2012-2017. Standard deviations are presented in parentheses.

The Social Survey: Cross-Sectional Data

Sample

The panel data of the Longitudinal Survey enables us to estimate the impact of divorce on the same individuals observed in different points in time both before and after divorce. However, this data has several shortcomings. First, in assessing the gender-specific economic consequences of divorce it is important to look at total household income, while the Longitudinal Survey provides data only on income from work. In this context, income from other sources, including transfers received or paid by the divorced men and women should be considered. Second, the Longitudinal Survey does not provide much data on possible non-monetary impacts of divorce. To fully understand the consequences of divorce on both men and women one needs to look at the perspective of the divorced themselves on their own economic situation as well as on psychological aspects of divorce.

To overcome these shortcomings, we use data from the Social Survey of the Israel Central Bureau of Statistics. The Social Survey is conducted once a year and provides information on the living conditions and welfare of the permanent population of Israel. It provides data on net income of all household members from all sources, including work and capital, after taxes and transfers. The data on net income is especially relevant for measuring the economic situation of the divorced because tax exemptions and welfare support for single parents are accounted for. Unfortunately, this data does not include alimony payments. The Social Survey also includes data on various non-monetary measures of both economic and psychological well-being, provided as self-reported evaluations by the participants.

However, the Social Survey data also has several shortcomings. First, it provides only cross-sectional data, as all participants are surveyed at a given point in time. Therefore, we cannot compare the participant’s situation before and after the event of divorce and can only provide descriptive comparisons. Thus, the Social Survey data enables us only to compare between the divorced and married individuals of both genders, to examine the basic differences between them, which is vulnerable to selection bias. These results should be interpreted as descriptive complements rather than confirmatory evidence. Second, the Social Survey indeed provides data on household income after taxes and transfers, but, like the Longitudinal Survey, it does not contain any data on alimony payments which are very important in assessing the economic well-being of both divorced men and women. In order to tackle this shortcoming, we follow Lewin and Stier (2018) and look at subjective variables which measure the economic situation of the individual. Specifically, we examine whether divorced men report giving up food due to financial difficulties which may indicate the influence of alimony payments on economic well-being.

We use data from the most recent Social Survey, which was conducted in 2017. Overall, 7,230 individuals of age 20 and above participated in this survey. To estimate the association between divorce and gender we examine the sub-sample of 5,287 participants (2,621 men and 2,666 women), who reported that they were either married or divorced. Note that this sample is much larger than the sample of the Longitudinal Survey which includes panel data only on individuals who divorced during the sample years. The total number of divorced individuals in the Social Survey sample is 504 (184 men and 320 women), which comprise about 10% of this sample.

Measurement

We examine eleven outcomes. Some of them deal with economic well-being, both monetary and non-monetary, while others deal with psychological well-being.

The economic outcome variables are as follows:

1. Net adjusted monthly household income. This variable represents the household income during the month of the survey after taxes and welfare payments. The income measure is adjusted to household’s size by dividing it by the square root of the number of household members.

2. Gave up food due to financial difficulties. Yes or no question represented by a dummy variable.

3. Satisfaction with income from work

4. Satisfaction with economic situation

5. Economic optimism. This variable indicates self-evaluation of one’s economic situation in the future.

6. Ability to cover monthly expenses

The psychological variables are.

1. Satisfaction with life

2. Experienced feeling of loneliness

3. Experienced feeling of stress

4. Experienced feeling of depression

5. Ability to cope with personal situation

Four economic variables (3, 4, 5, and 6), as well as all psychological variables are based on rating scale questions with 4 options, which we use in their original ordinal form as the dependent variables in our regression models.

In addition to gender and marital status, in our estimation we consider several background characteristics that may influence the outcomes: age, number of children, years of schooling, and belonging to the Arab, ultra-Orthodox or new immigrant sectors of the Israeli society. Note that the Social Survey sample includes data on ultra-Orthodox individuals, both married and divorced, while the Longitudinal panel data does not. Data on net household income, household size, personal income from work, age, and years of schooling provides ranges instead of exact numbers. We converted these ranges into mid-range points to obtain continuous numeric measures.

Descriptive statistics for the outcomes and relevant background factors are presented in Table 2.

Table 2.

Descriptive Statistics. The Social Survey

Panel A. Economic outcomes		Panel B. Background variables
Log of adjusted net	8.69	Women	0.504
Household income (monthly)	(0.63)		(0.500)
Gave up food due to	0.074	Divorced	0.095
Financial difficulties	(0.261)		(0.294)
Satisfaction with income	0.626	Number of household members	3.73
From work	(0.484)		(1.67)
Satisfaction with economic	0.652	Age	49.16
Situation	(0.476)		(15.61)
Economic optimism	0.464	Number of children	2.87
	(0.499)		(1.73)
Coverage of monthly	0.675	Years of schooling	14.446
Expenses	(0.469)		(3.904)
Panel C. Psychological outcomes		Arabs	0.186
Satisfaction with life	0.904		(0.389)
	(0.295)
		Ultra-orthodox	0.097
Feeling of loneliness	0.185		(0.297)
	(0.389)
Feeling of stress	0.600	New immigrants (1990+)	0.171
	(0.490)		(0.376)
Feeling of depression	0.208
	(0.406)
Coping with situation	0.938
	(0.241)

Source: CBS, The Social Survey, 2017. Standard deviations are presented in parentheses.

Methods

Our data enables us to test the following two hypotheses.

(1) Divorce is associated with changes in both economic and general personal well-being.

(2) The changes in well-being associated with divorce are different for women and for men.

Both hypotheses may be tested using a simple ordinary least squares (OLS) multivariate linear regression, as described by the following equation:

y_{i} = α + β_{1} {F e m a l e}_{i} + β_{2} {D i v o r c e d}_{i} + β_{3} {D i v o r c e d}_{i} {F e m a l e}_{i} + β_{4} {C o n t r o l s}_{i} + ε_{i},

(1)

where

$y_{i}$ – well-being outcome y of individual i.

$α$ – intercept term.

${F e m a l e}_{i}$ – dummy variable; equals 1 if individual i is female, 0 otherwise.

${D i v o r c e d}_{i}$ – dummy variable; equals 1 if individual i is after a divorce, 0 otherwise.

${D i v o r c e d}_{i} {F e m a l e}_{i}$ – the interaction variable specific for women after divorce.

${C o n t r o l s}_{i}$ – a vector of control variables for individual i.

$ε_{i}$ – individual’s unobserved error term.

Note that the association between divorce and men’s well-being is captured by $β_{2}$ only, while the association between divorce and women’s well-being is captured by $(β_{2} + β_{3})$ . The difference in the effect of divorce between women and men is therefore captured by $β_{3} .$ equation (1) will be estimated using the Social Survey dataset.

The longitudinal panel data on individuals observed during several points in time both before and after divorce creates an opportunity to assess the dynamic impact of divorce on men and women over time. DID model can be estimated using fixed-effects (FE) linear regression. For that purpose, equation (1) (OLS Model) should be rewritten in the following way:

y_{i t} = α_{i} + β_{1} {D i v o r c e d}_{i t} + β_{2} {D i v o r c e d}_{i t} {F e m a l e}_{i} + β_{3} {C o n t r o l s}_{i t} + γ_{i} + γ_{t} + ε_{i t},

(2)

where

$y_{i t}$ – outcome y of individual i in period t.

${D i v o r c e d}_{i t}$ – dummy variable; equals 1 if individual i is divorced in period t, 0 otherwise.

${D i v o r c e d}_{i t} {F e m a l e}_{i}$ – the interaction term which captures the differential impact of divorce for women in period t.

${C o n t r o l s}_{i t}$ – vector of control variables of individual i in period t.

$γ_{i}$ – individual fixed effects.

$γ_{t}$ –year fixed effects.

$ε_{i t}$ – individual error term in period t.

Note that in the FE model all time-invariant individual variables are captured by the individual’s fixed effect $γ_{i}$ . These variables include all individual’s characteristics that do not change over time, such as gender dummy ${F e m a l e}_{i}$ and control dummy variables for Arabs and new immigrants. Therefore, ${C o n t r o l s}_{i t}$ vector includes only two dummy variables indicating age above median and years of schooling above median.

Results

The Longitudinal Survey: FE Model

Table 3 presents the results of the estimation of the Fixed-Effects Model described by equation (2) using the Longitudinal Survey data. The Survey does not provide the complete data on dependent variables for all observations in the sub-sample; therefore, the number of observations for each outcome is different. The results suggest that divorce is associated with an increase of about 33% in adjusted household income of men, though this result is only marginally statistically significant. Non-adjusted household income does not increase for men. This means that the possible rise in adjusted household income for men may be interpreted as a result of differences in household size and not in income per-se. Divorced women experience a decrease of 66% in adjusted household income, respectively, relative to divorced men. Their unadjusted household income decreases by 51%, but this result is only marginally statistically significant. Thus, for women the divorce is associated with an overall decline of adjusted household income of about 33% (33%–66%). This result reflects the fact that the children usually stay with their mother after divorce. Indeed, in our sample of divorced women and men, mean household size is 3.13 for divorced women but only 1.73 for divorced men. We do note that our data does not take into account arrangements between men and women regarding alimony payments, which may change the magnitude of our estimated effects.

Table 3.

Gender and Divorce Effects on the Outcomes. The Longitudinal Survey

Panel A. Objective outcomes
	Log of adjusted household income from work (annual)	Log of unadjusted household income from work (annual)	Worked during last year (annual)	Labor force participation (weekly)	Worked full time (weekly, out of working population)
	(1)	(2)	(3)	(4)	(5)
Divorced	0.334*	0.044	−0.066**	0.033	0.160†
	(0.156)	(0.158)	(0.022)	(0.055)	(0.089)
Divorced * female	−0.660**	−0.505*	0.071*	0.066	−0.136
	(0.218)	(0.220)	(0.029)	(0.073)	(0.119)
R-squared	0.050	0.047	0.053	0.033	0.043
N (individuals)	83	83	95	95	73
N (observations)	264	264	311	312	206

Panel B. Subjective outcomes
	Considered themselves poor	Good health condition
	(1)	(2)
Divorced	−0.060	−0.031
	(0.057)	(0.045)
Divorced * female	0.000	0.035
	(0.077)	(0.060)
R-squared	0.034	0.004
N (individuals)	95	95
N (observations)	305	309

Source: CBS, The Longitudinal Survey, 2012–2017. Standard errors are presented in parentheses. Control variables include dummies for age above median (44+) and years of schooling above median (16+).

†p < 0.1. *p < .05. **p < .01. ***p <. 001.

As can be seen in Table 3, divorced men worked 7% less than married men. As for divorced women, they work 7% more than divorced men, but overall, they almost do not increase their labor force participation after divorce (an increase of only half a percent: −0.066 + 0.071). Divorced men also tend to work more at full-time positions, though this result is only marginally statistically significant. The estimate for women is negative and not statistically significant. As for other outcomes—labor force participation, considering oneself poor, and good health condition—we find no evidence of their association with divorce for either men or women. Given the limited sample size, we cannot rule out that the absence of significant effects for these outcomes reflects insufficient statistical power rather than a true null.

The Social Survey: OLS Model

Panel A of Table 4 presents the estimation results for the economic outcomes. We find that women report less satisfaction with their income than men (by 0.16 scale points), regardless of their marital status. This result is highly statistically significant. As for divorce, we find a strong and highly statistically significant association between divorce and women’s adjusted household income (a decline of 32%), while divorced men’s income is not affected. Note that this result is obtained after controlling for the number of children. Both divorced men and women report giving up food due to financial difficulties, but the magnitude for divorced women is twice as large (an increase of 0.10 scale points: 0.043 + 0.057). Also, divorce is negatively associated with satisfaction with economic situation for both men and women (a decline of 0.21 scale points). Here, also the decline is sharper for women (a total decline of 0.41 scale points: −0.206-0.207). Divorced women’s ability to cover their monthly expenses declines by 0.15 scale points, in addition to the overall association for divorced individuals of 0.13 scale points. We find no difference between married and divorced individuals in satisfaction with income from work and economic optimism.

Panel B presents the estimation results for the psychological outcomes. As for general gender differences, we find that women report higher levels of loneliness (by 0.15 scale points), stress (by 0.23 scale points), and depression (by 0.19 scale points), and lower ability to cope (by 0.05 scale points) compared to men, regardless of their marital status. Satisfaction with life does not seem to vary between men and women. As one may expect, divorce is associated with less satisfaction with life (a decrease of 0.18 scale points), higher levels of loneliness (by 0.45 scale points), depression (by 0.24 scale points), and lower coping ability (by 0.10 scale points) for both men and women. We find an association between divorce and women’s feeling of stress (an increase of 0.26 scale points above the overall divorce effect) (Table 4).

Table 4.

Gender and Divorce Effects on the Outcomes. The Social Survey

Panel A. Economic outcomes
	Log of adjusted net household income (monthly)	Gave up food due to financial difficulties	Satisfaction with income	Satisfaction with economic situation	Economic optimism	Coverage of monthly expenses
	(1)	(2)	(3)	(4)	(5)	(6)
Female	−0.032†	−0.012	−0.160***	−0.008	−0.017	−0.030
	(0.016)	(0.007)	(0.029)	(0.022)	(0.018)	(0.022)
Divorced	−0.038	0.043**	−0.066	−0.206***	0.005	−0.126**
	(0.043)	(0.020)	(0.076)	(0.059)	(0.049)	(0.058)
Divorced * female	−0.318***	0.057**	−0.033	−0.207**	−0.034	−0.145**
	(0.055)	(0.025)	(0.095)	(0.074)	(0.062)	(0.073)
R-squared	0.364	0.049	0.033	0.078	0.211	0.109
N	4,303	5,153	3,597	5,141	4,654	5,132

Panel B. Psychological outcomes
	Satisfaction with life	Feeling of loneliness	Feeling of stress	Feeling of depression	Coping with situation
	(1)	(2)	(3)	(4)	(5)
Female	0.022	0.152***	0.230***	0.191***	−0.047**
	(0.018)	(0.025)	(0.014)	(0.026)	(0.018)
Divorced	−0.181***	0.447***	0.025	0.241***	−0.101**
	(0.048)	(0.067)	(0.037)	(0.069)	(0.018)
Divorced * female	−0.063	0.023	0.263***	0.080	0.021
	(0.060)	(0.084)	(0.095)	(0.087)	(0.061)
R-squared	0.128	0.059	0.083	0.053	0.103
N	5,138	5,142	5,110	5,106	5,090

Source: CBS, The Social Survey, 2017. Standard errors are presented in parentheses. Control variables include number of children, dummies for age groups, dummies for categories of years of schooling, dummies for Arabs, ultra-Orthodox, and new immigrants from 1990 onwards.

†p < 0.1. *p < .05. **p < .01. ***p < .001.

Discussion and Conclusions

The findings of this study speak to three bodies of theory. First, they extend the marital specialization framework of Holden and Smock (1991) and Bröckel and Andreß (2015) by showing that the human capital deficits accumulated during marriage do not merely translate into income loss after divorce, but propagate further into subjective economic dissatisfaction and psychological stress. This transmission pathway—from objective economic disruption to subjective and psychological deterioration—is consistent with the family stress model (Conger et al., 1990), and our findings provide empirical support for it in a context where it has not previously been tested. Second, our results contribute to the debate opened by Leopold (2018), who found that in the medium term, gender differences in subjective well-being after divorce largely disappear while economic differences persist. Our cross-sectional evidence suggests that in the Israeli context, subjective economic dissatisfaction and stress remain elevated among divorced women even beyond the immediate post-divorce period, pointing to a more persistent penalty than Leopold’s German findings would predict. This difference is likely context-dependent: Israel’s combination of a large gender pay gap, strong familist norms, and limited institutional support for single mothers—features of what Esping-Andersen and Billari (2015) describe as a stalled gender revolution—may sustain both the material and psychological dimensions of the divorce penalty longer than in more egalitarian welfare state contexts. Third, and relatedly, our findings illustrate the theoretical value of examining post-divorce outcomes in societies where the gender revolution is incomplete. The persistence of both economic and subjective penalties for divorced women in Israel suggests that the benefits of women’s increased labor force participation have not been matched by the institutional and normative changes needed to protect them when marriages dissolve. We note that this mechanism is consistent with our findings but cannot be directly tested with available data, as discussed in the limitations section.

The purpose of this paper was to offer a holistic exploration of the effects of divorce on women and men. We showed that the effect of divorce on income does have a gender component: divorced women encounter a steep and persistent decline in household income compared to divorced men. Divorced women also report lower levels of satisfaction with their economic situation, lower ability to cover monthly expenses, and higher levels of stress. In contrast to women, divorced men face an increase in adjusted household income and tend to work less.

The findings of this paper support the three research hypotheses which were outlined above. First, men report having higher levels of satisfaction with income, as well as lower levels of various adverse non-economic aspects such as loneliness, stress and depression, regardless of divorce. These findings are consistent with H1. Second, the results show a decline in both economic and non-economic well-being measures for both divorced men and women, thus corroborating H2. Finally, the results show a decline in economic well-being measures for divorced women compared to divorced men, corroborating H3. It is important to note that non-economic well-being measures mostly do not exhibit a divorce gender gap, other than stress levels.

These results can be explained by the following mechanism: After divorce women usually become the primary caregivers for their children, while men usually leave the household. Therefore, adjusted household income decreases for women and increases for men. After leaving the household, men can afford to work less to sustain the same level of household income, or alternatively, they need to devote more time to their children as part of the divorce arrangements. The decline in women’s economic well-being after divorce leads to lower satisfaction with their economic situation, reduced ability to cover monthly expenses, and possibly to higher stress levels. This mechanism is also in line with the current literature.

In addition to our main research questions, we also answer several adjacent questions. Consistent with most other studies, we found that women in Israel have lower income levels and lower satisfaction with their personal income than men. Women are also more likely than men to experience feelings of loneliness, depression, and stress. We also find some negative impact of divorce, on both genders. Both divorced men and divorced women report higher levels of loneliness, depression, and dissatisfaction with life.

Several limitations of this study should be acknowledged. The longitudinal panel analysis provides within-person identification of change before and after divorce, making it potentially the most informative component of the study. However, the panel sample is relatively small which constrains statistical power, limits robustness, and raises concerns about generalizability. Furthermore, while our fixed-effects specification controls for time-invariant individual characteristics, we are unable to formally test the parallel trends assumption or provide event-study diagnostics given the sample size and the limited number of panel waves. Accordingly, all findings from the panel analysis should be interpreted as associational evidence of within-person change linked to divorce, rather than causal estimates. Two considerations partially temper these concerns. First, the panel findings are broadly consistent with results from the larger cross-sectional Social Survey, lending them additional credibility. Second, the two datasets serve distinct evidentiary roles: the cross-sectional data provide the broader and more generalizable portrait of post-divorce gender differences, while the panel data contribute within-person identification for a subset of economic outcomes.

A further limitation concerns the measurement of the mechanisms proposed in this study. We argue that the joint effect of income decline and increased employment burden—driven primarily by women’s role as the primary caregiver following divorce—underlies the subjective economic dissatisfaction and psychological distress we observe among divorced women. However, neither dataset contains direct measures of caregiving responsibilities, custody arrangements, or time use. We therefore cannot observe the caregiving burden directly, nor formally test the pathway through which it operates. The mechanism we propose is supported by indirect evidence—specifically, the divergence in household size between divorced women and men in our panel sample, and the pattern of increased employment among divorced women—and is consistent with both the marital specialization framework (Bröckel & Andreß, 2015; Holden & Smock, 1991) and prior empirical literature. Future research using data that include custody arrangements and time-use diaries would allow for a more direct test of this mechanism.

Beyond documenting gender differences across multiple outcome domains, the contribution of this study lies in integrating these domains into a coherent theoretical account. We show that the economic and psychological consequences of divorce for women are not independent phenomena but reflect a single underlying process: the exposure of marriage-specific human capital deficits and caregiving burdens in a context where institutional supports are insufficient to compensate for them. This account advances beyond descriptive documentation by connecting individual-level outcomes to macro-level conditions of gender inequality, and by identifying the mechanism—rather than merely the magnitude—of the divorce gender gap.

Taking the results of this paper to the policy arena is a difficult task. This is because of the difficulty in evaluating the overall desirability of marriage and divorce for men and women, and the difficulty in discerning whether government intervention can improve these outcomes. Thus, our suggestions should be treated with caution. Nevertheless, we offer here two possible policy implications of our findings, which are related. First, the decline in economic conditions of women after divorce may be mitigated by government support. Second, if such support is given, it is worthwhile to design policies which will offer pre-marriage counseling to individuals, in order to avoid the adverse effects of divorce.

While our research has examined both economic and non-economic dimensions of the divorce gender gap, future research is needed to further explore these dimensions. Our results suggest that many non-economic well-being aspects do not exhibit a gender divorce gap. However, we were only able to test a limited number of such aspects, leaving many other non-economic aspects unexplored. Another avenue for future research is in quantifying the effect of additional workload on the well-being of divorced women, and to what extent the mechanism found in this paper affects overall well-being.

Footnotes

ORCID iD

Yaniv Reingewertz

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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