The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland

Abstract

This contribution investigates the link between female labour force participation and household income inequality using data from the Swiss Household Panel (2000-2014). Through index decomposition analyses, we find that female labour force participation has slightly attenuated household income inequality over time. Women’s entry into the labour market, higher work percentages within part-time work - but not the shift from part-time to full-time work - and the weak correlation in partner’s earnings have contributed to this effect.

Full text

DOI 10.1515/sjs-2017-0006
© 2017. This work is licensed under the Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Swiss Journal of Sociology, 43 (1), 2017, 115–135
The Impact of Female Labour Force Participation on Household
Income Inequality in Switzerland1
Ursina Kuhn* and Laura Ravazzini*/**
Abstract: is contribution investigates the link between female labour force participation
and household income inequality using data from the Swiss Household Panel (2000–2014).
rough index decomposition analyses, we nd that female labour force participation has
slightly attenuated household income inequality over time. Women’s entry into the labour
market, higher work percentages within part-time work – but not the shift from part-time to
full-time work – and the weak correlation in partner’s earnings have contributed to this eect.
Keywords: female labour force participation, income inequality, part-time work, index de-
composition, household types
Erwerbstätigkeit der Frauen und Ungleichheit der Haushaltseinkommen in der Schweiz
Zusammenfassung: Dieser Beitrag untersucht den Zusammenhang zwischen der Erwerbs-
beteiligung der Frauen und der Ungleichheit der Haushaltseinkommen anhand der Daten
des Schweizer Haushalt-Panels (2000–2014). Eine Zerlegung von Ungleichheitsindizes
zeigt einen ausgleichenden Einuss der steigenden Frauenerwerbstätigkeit auf die Einkom-
mensverteilung. Der Eintritt in den Arbeitsmarkt, höhere Teilzeit-Arbeitspensen, aber nicht
der Wechsel von Teilzeit zu Vollzeit, sowie die schwache Korrelation zwischen den Löhnen
der Partner sind für diesen Eekt verantwortlich.
Schlüsselwörter: Erwerbsbeteiligung von Frauen, Einkommensungleichheit, Teilzeitbeschäf-
tigung, Indexzerlegung, Haushaltstypen
Participation des femmes au marché du travail et inégalité de revenu des ménages
en Suisse
Résumé : Cet article traite du lien entre le taux d’activité des femmes et l’inégalité de revenu
des ménages à partir des données du Panel suisse de ménages (2000–2014). Une analyse de
décomposition de mesures d’inégalité montre que l’augmentation du taux d’activité des femmes
a tendance à réduire cette inégalité. Les causes principales en sont l’entrée des femmes sur
le marché de travail, l’augmentation des taux d’occupation du travail à temps partiel – mais
non pas le passage du travail à temps partiel au travail à plein temps – et la faible corrélation
des revenus entre partenaires.
Mots-clés : participation des femmes au marché du travail, inégalité de revenu, emploi à temps
partiel, décomposition d’indices, types de ménage
* Swiss Centre of Expertise in the Social Sciences (FORS), University of Lausanne, CH-1015
Lausanne, ursina.kuhn@fors.unil.ch.
** University of Neuchâtel, CH-2000 Neuchâtel, laura.ravazzini@unine.ch.
1 is contribution is based on the project “Income and wealth inequality, deprivation and wellbe-
ing in Switzerland, 1990–2013,” nanced by the Swiss National Science Foundation (project
100017_143320). is study was realised using the data collected by the Swiss Household Panel
(SHP), which is based at FORS; the SHP is nanced by the Swiss National Science Foundation.
We would like to address special thanks to the anonymous reviewers for their careful reading of our
manuscript and for their highly appreciated comments and suggestions, which have signicantly
improved the quality of this publication.
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116 Ursina Kuhn and Laura Ravazzini
1 Introduction
e growth of female employment is one of the major socio-economic changes in
most societies. A changed division of labour within couples, evolving social norms,
technological changes and the expansion of education are drivers of this transition
from unpaid housework to paid work. e increasing income earned by women has
consequences for household income. Household income includes all income sources
by all household members and takes into account the sharing of resources among
household members. Because it illustrates the economic well-being of individuals,
household income inequality is a key inequality measure. Female employment boosts
the level of household income, but the eect on its distribution is not a priori clear.
Whether more female employment is good or bad for household income
inequality depends on which women work more. If it is mostly women in low-
income households who work, inequality should decrease, whereas if it is mostly
women in high-income households who increase their working hours, inequality
should increase. Although most recent contributions nd egalitarian eects at the
household level, previous empirical analyses have shown mixed results.
In Switzerland, the link between female labour force participation and house-
hold income inequality has not been investigated so far. Considering that comparative
analyses stress the importance of the activity rate for household income inequality
(Pasqua 2008; Kollmeyer 2012), Switzerland presents an interesting case study.
e participation rate is high and part-time work is more common among women
than in any other OECD country (OECD StatExtract 2015).2 In parallel to the
rise of the activity rate from 68% in 1991 to 79% in 2014, the typical household
structure has gradually changed from a 1–0 type (men working full-time, women
not working) to a 1–0.5 type (men working full-time, women working part-time)
(Bühler et al. 2002). Another important characteristic of Switzerland is that, unlike
in many other countries, its household income inequality has remained at the same
level since 2000 (SFSO 2014; Suter et al. 2016) and is now below the European
average (Eurostat 2015). erefore, our research question is whether high and ris-
ing female employment has contributed to keeping household income inequality
in Switzerland relatively low.
Apart from adding evidence for Switzerland, this article contributes to a better
understanding of the impact of part-time work on household income inequality.
Although some studies consider part-time work to be a driver of household income in-
equality (Esping-Andersen 2009; OECD 2013), this aspect has never been empirically
addressed in detail. Typically, studies look at how earners and non-earners are grouped
in households, but they do not distinguish between dierent work percentages.
2 In 2014, 59.2% of active women in Switzerland worked part-time, followed closely by the Neth-
erlands, with 57.9%. Part-time percentages are computed according to national denitions. e
intensity of part-time work is similar for women of dierent age groups.
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 117
In this contribution, we rst discuss the dierent potential channels through
which female employment aects household income inequality. After a brief lit-
erature review, we discuss methods and data from the Swiss Household Panel (2000
to 2014). To measure inequality in income distribution, we use the eil index
and the Coecient of Variation. Inequality decompositions and counterfactual
simulations serve as the main methodological tools. Our main results suggest that
women’s stronger labour force participation has contributed to keeping household
income inequality relatively low in Switzerland.
2 Theory
Household income inequality is determined by many dierent factors (see e. g.
Jenkins 1995; OECD 2015), of which we discuss only those related to labour force
participation. e main dependent variable of our analysis, household income
inequality, includes labour income from employment and self-employment, asset
income, private and public transfers and imputed rent. Since we are not interested
in the eects of the tax system, we do not include direct taxes.
Figure 1 illustrates the dierent channels through which increasing female
employment may inuence household income inequality. We distinguish between
eects from changes in the household composition (e. g. more single households)
and eects from changing working patterns within households (e. g. household
labour supply). Earnings inequality at the individual level is determined by labour
force participation, by the variation in working hours and hourly wages and by the
relation between working hours and hourly wages. e correlation of earnings be-
tween members of the same household and the correlation between income sources
play an additional role.
Looking at the dierent channels of Figure 1, we can formulate some expec-
tations on how the rise in female labour force participation in Switzerland aects
household income inequality. Table 1 summarises these hypotheses. First, if more
women work, there are fewer women with no working hours (and thus zero earn-
ings), which means that inequality in working hours among all working-age women
shrinks (H1a). Second, the eect on the variation of hours depends on whether
women with a relatively low work percentage or with a relatively high work per-
centage increase their hours. Because working hours are limited at the top (we do
not take into account overtime here), we expect that rising work percentages bring
a lower heterogeneity in hours (H1b). e lower variation in working hours (H1a
and H1b) would clearly have an equalising eect on earnings and household income.
e equalising eect from the variation in working hours might be amplied
or mitigated by a positive or negative correlation between hours and hourly wages.
ere are two reasons to expect a positive correlation in Switzerland (H2), which
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118 Ursina Kuhn and Laura Ravazzini
partially osets the equalising eect of H1b. First, part-time work might be worse
paid than full-time work. Such a part-time penalty is the reason that the OECD
(2013) sees part-time work as a potential driver of income inequality. Second,
positive wage elasticities in labour supply models suggest that the wage potential
positively aects working hours (Gern and Leu 2007).
After having discussed the eects on individual earnings inequality, we now
turn to the household level. e role of the correlation between the dierent income
sources is a rather complex issue. With the working patterns of women and men
becoming more similar, we expect that the earnings of women and men should
increasingly resemble each other over time. Consequently, the correlation between
men’s and women’s earnings should become more positive (H3a). However, the
correlation between income sources does not only reect the similarity in working
hours, but also the household structure (e. g. the share of single households), the
similarity in wage levels between partners (e. g. due to assortative mating) and the
relationship between the labour supply and partners’ earnings. If it is mostly women
with high-earning partners who increase their working hours, household income
inequality will increase, whereas if it is mostly women with low-earning partners who
increase their working hours, inequality will decrease. In Switzerland, the female
labour supply depends negatively on the wage level of their partners (Gern and
Leu 2007). Other studies show that, due to the tax system and income-dependent
child-care costs, high work percentages are particularly unattractive for women
with children and a high-earning partner (Bütler and Ruesch 2009; Schwegler et al.
2012). We therefore expect that women with high-earning husbands have increased
their working hours to a smaller extent than women with low-earning husbands.
Consequently, the correlation between couples’ earnings should have become less
positive over time (H3b). e two hypotheses 3a and 3b point in dierent direc-
Figure 1 Determinants of household income inequality
Working
hours
Hourly
wages
Earnings
inequality of
working
individuals
Earnings
inequality of
all individuals
Household
earnings
inequality
Household
income
inequality
Other income
sources
Inactive
individuals
Household composition and
correlation of individual earnings
within the household
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 119
tions and might oset each other. Overall, ndings from various countries suggest
that the correlation between female earnings and other income components has
increased over time and has therefore had a disequalising eect on household income
inequality (Karoly and Burtless 1995; Schwartz 2010).
A straightforward impact of higher female labour supply is that women’s earn-
ings contribute more strongly to total household income. If women’s earnings are
more equally distributed than other income sources, more female earnings reduce
household income inequality. Considering that capital income (Piketty 2014) is
highly unequal and that pensions and social transfers are unequally distributed among
the working-age population (because only a small share of households receives these
incomes) we expect this to be the case. erefore, we expect a further equalising
impact of female labour force participation on household income inequality (H4).
Table 1 Hypotheses on the impact of increasing female labour force
participation on household income inequality
Type of change Reason Effect on household
income inequality
H1a All women: Variation in working
hours decreases over time
More women work: Fewer inactive
women with zero earnings
Equalising
H1b Working women: Variation in
working hours decreases over
time
Women increase their working hours,
fewer women with low work percent-
ages
Equalising
H2 Working women: Positive
correlation hours-wage level
Positive own-wage elasticity, part-time
penalty
Disequalising
H3a Household: Correlation of
partners’ earnings more positive
over time
Partners have more similar working
hours
Disequalising
H3b Household: Correlation of
partners’ earnings less positive
over time
Women with high-earning partners
increase their working hours less
Equalising
H4 Household: inequality in income
sources: Women’s earnings
become more relevant for
household income
Earnings are more equally distributed
than income from other sources (as-
sets, transfers, pensions)
Equalising
H5a Household structure: More single
households
Women in single households work
more than women in couple house-
holds, no pooling of household income
Disequalising
H5b Household structure: More single-
mother households
Single mothers work more than moth-
ers living with their partner, no pooling
of household income, generally low
income levels
Disequalising
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120 Ursina Kuhn and Laura Ravazzini
Our last hypothesis concerns the household composition. Because women
living in single households tend to work more than women living in couple house-
holds, we can see the rising number of single households as a cause of rising female
labour force participation. Because single households tend to be more unequal than
larger households (there is no pooling or redistribution of income among house-
hold members), a greater number of single households amplies household income
inequality (H5a). is seems likely to be true in the Swiss context. Although it is
not focused on female labour force participation, the research conducted by Ernst
et al. (2000) on Switzerland shows that inequality among dual-earner households
was clearly lower than among single-earner households. e same reasoning applies
to single mothers, who also tend to work more than mothers living with a partner.
Moreover, single mothers tend to have particularly low household income and a
high variation in earnings, which reinforces this disequalising eect (H5b). is is
conrmed by studies in many developed countries, where single parenthood con-
tributes to income inequality (Western et al. 2008; Kollmeyer 2012).
Notwithstanding the multitude of our hypotheses, there might be other potential
impacts of female labour force participation on household income inequality, for ex-
ample on inequality in hourly wages. Our discussion has not taken into account other
changes occurring over time, such as changes in the tax system, business cycles or changes
in the industrial structure or the unemployment rate. We also neglect the possible eects
of more male part-time work as a result of a changed division of labour within couples.3
3 Literature review
Although the issue of female earnings has received considerable attention in the
literature on income inequality, contributions have so far focused on few countries.
While there is extensive evidence for the USA (Cancian and Reed 1999; Daly and
Valletta 2006; Pencavel 2006; Larrimore 2014), there is scarce empirical research for
European countries (exceptions are Breen and Salazar (2010) on the UK and Del
Boca and Pasqua (2003) on Italy). is is surprising, considering that comparative
studies show large dierences between countries (Cancian and Schoeni 1998; Esping-
Andersen 2007; Pasqua 2008; Harkness 2013). Previous ndings in the literature
show that women’s entry into the labour market contributes to lower household
income inequality. e few studies that report the opposite eect were mostly pub-
lished more than 20 years ago (Ryscavage et al. 1992; Karoly and Burtless 1995).
An important drawback of comparative studies is that they do not involve an
analysis over time. Rather, they test whether observed income inequality is higher
or lower compared to a situation where no women work. Such approaches cannot
3 We have tested these eects, but we found that the increase in male part-time work is marginal
and not relevant for household income inequality.
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 121
show the eect of other changes in female employment, most importantly when
part-time working women increase their working hours. e same limitation applies
to aggregate-level analyses that link female employment rates to income inequal-
ity (e. g. Kollmeyer 2012). To nd the eect of an increase in female labour force
participation over time, data on dierent time points is required.
e study by Breen and Salazar (2010) on the UK was one of the rst to also
include single households. is is important not only for the purpose of drawing
inferences about the (working-age) population, but also to take the relationship
between having a partner and the labour supply into account. eir study looks not
only at female labour force participation, but also at assortative mating and, most
importantly, educational expansion. eir results show that these aspects have hardly
contributed to the increasing income inequality between households that, in the case
of the UK, was driven by the rise in unemployment among the male population.
More recently, Larrimore (2014) has disentangled the dierent drivers of in-
come inequality in the United States using shift-share decomposition of inequality
indices for the 1980s, 1990s and 2000s by employment status, marriage rate and
the correlation of spouses’ earnings. is last aspect was a main driver of the steep
rise in inequality in the 1990s, whereas a rise in female earnings inequality and the
unemployment rate made inequality slowly increase in the 2000s. Female employ-
ment moderated income inequality growth in the 2000s, but was unable to reduce
the growth in inequality in more recent years.
Following Breen and Salazar (2010) and Larrimore (2014), this paper includes
dierent household types according to the cohabitation and employment status of
all their members and, in addition, distinguishes between dierent work percent-
ages. While we acknowledge the interrelatedness of education, assortative mating
and employment, as illustrated by Blossfeld and Buchholz (2009), we do not go
into the dierent causes of female labour force participation, but concentrate on
the consequences in terms of household income inequality.
4 Data and methods
4.1 Data and operationalisation
We use data from the Swiss Household Panel (SHP) covering the years 2000 to
2014. Because the SHP includes the income and work percentages of all individuals
in the household, it is well suited for our purpose. Although we analysed the data
for all years, we present here results for only 2000, 2004, 2009 and 2014, as female
labour participation did not change abruptly from one year to another.4
4 We selected the years in order to include the rst and last available year in the SHP (2000, 2014)
and similar time intervals in-between. In the few cases where our results varied between the years,
we state this explicitly in the text.
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122 Ursina Kuhn and Laura Ravazzini
We focus on individuals of working age and do not limit the analysis to
households composed of couples. We include all households where the head is
between 25 and 64 years old (n in 2000 = 3589, in 2004 = 4307, in 2009 = 3261, in
2014 = 5186). e reason for this age range is that by the age of 25, most individu-
als have nished their education and by the age of 65, most are retired. e main
income earner within the household has been designated as the household head.
e units of analysis are individuals and weights are used to correct for sample
selection and non-response. Household income has been deated using the 2005
consumer price index and adjusted for household size using the modied OECD
scale, which assigns a weight of 1 to the rst adult, 0.5 to each additional adult
(14 years and older) and 0.3 to each child. We top-coded extremely high values
(income above the 99.75 percentile), as these outliers strongly inuence inequality
measures, in particular the coecient of variation, which is sensitive to high income
(Salverda et al. 2009).
For yearly income in the SHP, we use variables provided from the SHP-CNEF
le.5 Hourly wages have been computed at the basis of monthly wages and weekly
working hours and are top-coded at 10 times the median wage. e measurement
of part-time work is crucial for our analysis. In line with denitions by the Inter-
national Labour Organization (ILO) and the Swiss Federal Statistical Oce, we
consider individuals working at least six hours per week as active, and individuals
working at least 36 hours a week as full-time workers. For some analyses, we further
distinguish between small part-time work (6–19 hours) and higher part-time work
(20–35 hours).6 We are aware that the categorisation of working hours into three (or
four) groups has consequences on the results (although not on the main ndings).
However, considering that previous studies only identied two categories (working
vs not working) and did not consider heterogeneity in working hours among active
individuals, we think that our approach is already revealing.
4.2 Decomposition methods
e empirical aim of this article is to test how the recent rise in female employment
has aected household income inequality. We use dierent decomposition methods
and counterfactual distributions. Some of the hypotheses presented in Section 2
will be addressed by descriptive statistics.
5 Details of income imputation are available from the SHP documentation.
6 To distinguish work intensities, we have considered weekly working hours (usual hours and
contractual hours), work percentages and occupational status from the grid questionnaire. Indi-
viduals with yearly earnings below CHF 12 000 are considered inactive, while full-time working
individuals have yearly earnings of at least CHF 36 000. Further details can be obtained from
the authors upon request.
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 123
4.2.1 Factor decomposition
Factor decompositions separate household income into dierent additive income
components. In our analysis, we consider three factors: female labour income (f),
male labour income (m) and other income sources (ot).
YY YY
fmot
=++
In line with previous studies, we chose the coecient of variation (CV) as the in-
equality index due to its easy decomposability. e values of the CV are positive
but not limited at the top and are comparable across groups and time points. e
CV can be decomposed into three elements (Shorrocks 1982): the inequality in each
factor (CVk for factor k), the correlation between a pair of income components (p),
and the share of each component in the total income of the household (for factor
k). Decomposing the CV for our three income components gives:
CV SCVSCV SCVSSCVCV
ymmffototmfmfmf
22222222=+++ +
ρ
,22
2
ρ
ρ
motmot
mo
t
fotfot f
SSCV CV
SSCV CV
,
,
+oot
Increased female labour force participation inuences income inequality in three
dierent ways: inequality in female earnings (CVf), women’s share of total household
income (Sf) and the correlation of women’s earnings with men’s earnings (pm,f) and
with other income components (pot,f). A common misconception regarding the impact
of female labour force participation on household income is to draw conclusions
about the general eect from just one of these components. Several contributions
that have found a disequalising eect of women’s labour force participation indeed
suer from these methodological problems. For example, higher inequality in
women’s earnings compared to men’s earnings or the increased correlation between
spouses’ earnings over time are not sucient to explain the disequalising eect of
female employment.
Shift-share analysis can isolate the eect of female labour force participation
on inequality by varying one or several of the components of the decomposition.
To assess the impact over time using two time points (t, t+1), we compute inequal-
ity under the assumption that only some elements of the CV have changed to t+1
values, but the other elements have remained at their previous levels (t).
4.2.2 Decomposition by population groups
An alternative approach is to compare inequality in dierent household types, typi-
cally distinguishing between dual-earner couples, male- and female-breadwinner
couples, and non-working couples (Pasqua 2008; Harkness 2013). is approach
is complementary to factor decompositions, which cannot separate the eects due
to changes in the household composition (e. g. more single women or more single
mothers) from eects due to changes within groups. For example, single-men
households and households with a non-working wife are treated in the same way in
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124 Ursina Kuhn and Laura Ravazzini
factor decompositions because both are households with zero female labour income.7
Similarly, factor decompositions cannot explicitly distinguish between full-time
and part-time work. e main disadvantage of decompositions by groups is that
discrete groups are necessary.
e decomposition of inequality by groups can tell us to what extent inequal-
ity varies due to changes in the proportion of individuals in each group, changes
in within-group inequality and changes in inequality between the dierent groups.
Moreover, we are able to compare part-time and full-time work using a counterfac-
tual analysis. We use the eil index, which can be expressed as the weighted sum
of inequality between groups plus inequality within each level:
T
n
x
x
x
xpx
x
x
xpx
x
i
i
N
i
j
J
j
JJ
j
j
=



=



+
∑∑
1ln ln
jj
J
j
T
∑
where n is the total number of individuals i, xi the individual earnings and
x
mean
earnings, j represents a group, pj is the proportion of people in group j and
x
J the
mean income of the group. Tj is the eil within the group j and it takes the form of:
T
n
x
x
x
x
j
ij
J
ij
J
i
n
=




=
∑
1
1
||
ln
where n is the number of people in the jth group and xi|j is the individual wage of
individual i in group j. One drawback of the eil index and of all other inequality
measures based on the logarithm is that zeroes lead to the index being undened.
Households with no income are, therefore, excluded. is is unproblematic in our
case because there are virtually no households with zero total household income.
5 Results
5.1 Individual earnings
We rst focus on individual earnings to distinguish the evolution of women’s work-
ing hours from changes in hourly wages. Table 2 presents descriptive statistics to
assess individual-level hypotheses H1 and H2.8 First, we look at the evolution of
working types. e share of non-working women has declined from 38% in 2000
7 is has to be taken into account when results from factor decompositions are interpreted. To
test hypotheses 3a and 3b, which focus on couples, we will additionally report correlations for
couple households. Moreover, our results show relatively stable percentages of single households
over time. It is therefore unlikely that changes in the household composition explain changes
over time.
8 We opted for simple descriptive accounts rather than for a more formal decomposition into hourly
wage, working hours and correlations for two reasons. e rst is that the decomposition requires
a logarithmic transformation, which we nd inappropriate for working hours. e second is that
the decomposition relies on the coecient of variation, which is highly sensitive to outliers.
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 125
to 20% in 2014. In addition, active women have increased their work percentage
and full-time work has risen from 26% of all women in 2000 to 35% in 2014.
Similarly, the share of higher part-time work (21–35 hours per week) has increased
from 22% to 32%, while fewer women have a low percentage (from 14.2 to 12.9).
Another indication that part-time working women have intensied their labour
supply is the shrinking variation in hours worked (standard deviation declined from
12.6 in 2000 to 11.4 in 2014). We thus nd that both entry into the labour market
and shifts within active women (as expected in H1a and H1b) are responsible for
Table 2 Descriptive statistics on women’s working hours, hourly wages and
yearly earnings, 2000, 2004, 2009 and 2014
Women 2000 SD 2004 SD 2009 SD 2014 SD
Working type (in %)
0–5 hours 38.4 28.6 21.4 19.9
6–19 hours 14.2 15.5 15.6 12.9
20–35 hours 21.6 26.5 32.7 32.0
36+ hours 25.8 29.4 30.3 35.2
total 100 100 100 100
N2928 3192 2580 3973
Working hours (weekly)
working women: mean 29.4 (12.6) 29.8 (12.2) 29.9 (11.9) 31.3 (11.4)
all women (inc. inactive):
mean
18.3 (17.3) 21.5 (16.8) 23.6 (16.1) 25.2 (16.1)
N2928 3192 2580 3973
Hourly wage
6–19 hours: mean 39.1 (30.2) 32.6 (21.4) 34.5 (22.1) 35.5 (24.9)
20–35 hours: mean 36.0 (17.4) 33.0 (12.9) 35.5 (15.6) 35.4 (14.3)
36+ hours: mean 33.1 (12.3) 33.1 (12.4) 34.6 (14.9) 34.2 (13.6)
theil index 0.121 (0.009) 0.104 (0.008) 0.104 (0.009) 0.107 (0.009)
correlation hours-wage −0.12 −0.05 −0.02 −0.09
N1599 1913 1760 2664
Yearly earnings
all (incl. inactive): Theil
index
0.252 (0.016) 0.280 (0.009) 0.258 (0.011) 0.236 (0.009)
working: Theil index 0.190 (0.015) 0.194 (0.007) 0.180 (0.009) 0.187 (0.008)
N3416 4062 3119 4929
Notes: Women between 25 and 64 years of age. Standard deviation (sd) in parenthesis. Working hours have
been top-coded at 45 hours. Hourly wages have been deflated using 2005 as the base year. Yearly earnings
include imputed values provided in the CNEF-File of the SHP.
Source: SHP 2000–2014, own calculations.
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126 Ursina Kuhn and Laura Ravazzini
the decreasing variation of working hours and have contributed to lower earnings
inequality at the individual level.
e next step is the link between working hours and the wage level. Table 2
shows similar hourly wage levels for smaller part-time, higher part-time and full-
time work. Although we cannot formally test whether there is a part-time penalty
with these descriptive statistics, results illustrate that part-time work is not restricted
to low-qualied jobs in Switzerland.9 Accordingly, there is no correlation between
hourly wage and working hours, which means that the channel proposed in H2
does not seem relevant for Switzerland.10 Summing up our ndings on women’s
earnings inequality (H1, H2), we see that rising female labour force participation
has clearly reduced women’s earnings inequality.
5.2 Household income
5.2.1 Income sources
We now switch to the household level to test our remaining hypotheses (H3–H5).
Before addressing the hypotheses, we rst discuss the inequality decomposition by
income source (men’s earnings, women’s earnings and other income components)
as presented in Table 3.
Total household inequality seems to have slightly decreased since 2000 (both
signicant for eil and CV), which is in line with ocial statistics on income
inequality (SFSO 2014). Looking separately at the trends of the three income
sources, we notice that inequality in men’s earnings has remained constant over
time, whereas women’s earnings and other household income have become more
equally distributed.11 From the analysis at the individual level, we know that the
decline in women’s earnings can be uniquely attributed to the variation in working
hours rather than to the distribution of the wage level, as the latter has remained
stable.12 e analysis at the individual level has also shown that both entry into the
labour market and increasing work percentages have contributed to this equalising
eect. In addition, the higher earnings inequality among women compared to men
(1.12 vs 0.78 in 2014) can be explained by their higher variation in working hours
9 Further conrmation is provided by decomposition of the eil index by work type, where the
distinction between small part-time, high part-time and full-time explains less than 0.3% of wage
inequality.
10 Although the years shown in Table 2 suggest a negative correlation, the coecient is positive in
other years. Distinguishing wage quintiles, we nd that women in the middle part of the wage
distribution (3rd and 4th quintiles) work slightly more than women with lower or higher wages.
11 A more detailed analysis of other income shows that income inequality has decreased for private
transfers, public transfers and, to a lesser extent, imputed rent. Inequality in asset income and
social security pensions show no clear trend.
12 Although a more detailed analysis on wage inequality is beyond the scope of this article, we want
to point to the role of the data sources. While population surveys such as the SHP and the Swiss
Labour Force Survey suggest a rather stable wage inequality, the Swiss Earnings Structure Survey
shows increasing inequality in hourly wages because it covers very high wages (Suter et al. 2016).
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 127
rather than by a higher variation in wage levels. Comparing all income sources, we
notice that inequality in each separate income source is higher than inequality in
household income, reecting the strong equalising eect of aggregation and income
pooling at the household level.13
Turning to the correlation between income factors in Table 3, we see that
men’s earnings are negatively related to women’s earnings (−0.16 in 2000 and −0.18
in 2014). Furthermore, the correlation shows no time trend. e negativity can
be explained by the fact that the sample includes not only couples, but also single
households and other household members (e. g. children and parents, brothers and
sisters, atmates). To be able to test H3a and H3b (referring to the correlation
between partners), Table 3 also provides the correlation for couples in which both
partners are between 25 and 64 years old. ese coecients are very close to zero
and do not show any time trend. Overall, we can say that neither H3a (which
predicted a more positive correlation over time) nor H3b (which predicted a less
positive correlation over time) is supported. is is truly a dierent nding from
those reported in other studies (Cancian and Reed 1999; Schwartz 2010; Harkness
2013),14 which show positive and strengthening correlations between spouses’ earn-
13 As a robustness check, we have performed as far as possible the same analysis with data from the
Swiss Labour Force Survey, which has the advantages of dating back to 1991, providing larger
sample sizes and fresh samples every year. Because of serious shortcomings in the data (e. g. only
one person per household was interviewed and large measurement errors in household income),
we just mention that the equalising eect of increasing female labour force participation was also
observed during the 1990s, and that the evolution since 2000 is comparable to results in the SHP.
14 For example, replicating the sample selection in Harkness’s study, we nd more strongly negative
coecients than in any other country. For all households (including non-couple households)
Table 3 Decomposition of household income inequality by income source
Coefficient of variation Income share
(in %, total = 100%)
Correlation
total men women other working
women
men women other women/
men
women/
other
men/
other
women/
men couple
2000 0.572 0.734 1.313 2.581 0.983 66.3 24.9 8.8 −0.16 0.00 −0.09 0.00
(0.011) (0.012) (0.025) (0.012) (0.021)
2004 0.582 0.789 1.279 2.162 0.980 62.8 26.4 10.9 −0.17 −0.02 −0.09 0.02
(0.013) (0.016) (0.032) (0.016) (0.028)
2009 0.507 0.740 1.141 1.818 0.909 59.9 29.7 10.4 −0.19 −0.02 −0.18 0.00
(0.011) (0.015) (0.027) (0.071) (0.024)
2014 0.528 0.775 1.123 1.655 0.864 59.6 28.6 11.8 −0.18 −0.04 −0.09 0.03
(0.011) (0.016) (0.021) (0.046) (0.018)
Notes: Standard errors of the coefficients of variation are included in parenthesis. For correlation of couples, couples where
both partners are between 25 and 64 have been selected. n of households: 3589 (2000), 4307 (2004), 3261 (2009) and
5186 (2014).
Source: SHP 2000–2014.
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128 Ursina Kuhn and Laura Ravazzini
ings over time. To understand which women increased their working hours, Figure
2 shows women’s working hours by the earnings quintile of their partner. We see
that women’s working hours clearly decline with the wage level of their partner. In
2014, women with partners in the highest quintile worked six hours less per week
than women with partners in the lowest quintile.15 is dierence has remained
constant since 2000 because women in all quintiles have increased their working
hours in a similar way. Interestingly, such a clear pattern is no longer observed in
other countries (OECD 2015). e explanation of the negative relation between
women’s working hours and partner’s wages deserves further analysis for future studies.
Coming back to the decomposition of household income inequality by in-
come component, we now address H4. Table 3 reveals that men’s earnings are still
the correlation coecient in Switzerland amounts to −0.15 (for 2005), which is clearly below
estimates for any other country (the lowest in Harkness’s study is Luxemburg, with −0.03). Se-
lecting couples only, the correlation in Switzerland is 0.04 (in 2005), while the other countries
show correlations from 0.11 in Germany to 0.36 in Finland.
15 Women with partners in the highest quintile are older (46 years on average,) than women with
partners in the lowest earnings quintile (39 years on average). In contrast, having young chil-
dren is not related to the partner’s wage level. e negative relation between working hours and
partner’s wages holds both for participation and the working hours of active women.
Figure 2 Weekly working hours of women by wage quintile of their partner
for 2000 and 2014
0
5
10
15
20
25
30
54321
20.4
25.6
17.1
22.1
17.1
25.2
15.1
20.7
14.2
19.8
Wage quintile of partner
Paid working hours per week
2014
2000
Notes: All women 25–64 years of age living with their partner (including inactive); working hours top-coded
at 45 hours/week; n: 1410 in 2000, 2178 in 2014.
Source: SHP 2000 and 2014.
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 129
the most important income component, accounting for 66.3% of total household
income in 2000 and 59.6% in 2014. In parallel, although this share has stagnated
since 2009, the contribution of women’s earnings to household income has grown
from 24.9% in 2000 to 28.6% in 2014. Whether this change is equalising remains
an open question because women’s earnings inequality is lower than inequality in
other income sources, but higher than inequality in men’s earnings. In order to
properly test H4 (eect of higher contribution of female earnings on household
income), we conduct a shift-share analysis (Table 4), which also tests the overall
eect of increased female labour force participation on household income inequal-
ity. Because the selection of the years inuences the results, we show the eect for
three dierent time intervals. e rst row shows the CV in t0, the second row
shows the CV assuming that only inequality in women’s earnings (CVf) increases
to t1 level, keeping factor shares, inequality in other factors and correlations among
factors constant as in t0. In this scenario, inequality declines by 3.4% from 2000
to 2014. If we adjust the correlation between female earnings and other income
sources (men’s earnings and other income) to their 2014 values (counterfactual 4),
we nd that the CV is 2.3% lower than in 2000. In counterfactual 5, we change all
the income shares to their 2014 values. is change increases inequality by 3.7%,
which is due to the higher importance of (highly unequal) income of other sources
for household income. If we change only the share of female earnings while keeping
Table 4 Counterfactual distribution of household income for changes
between 2000 and 2014 (coefficient of variation)
2000–2014 2000–2009 2004–2014
CV change
since t0
CV change
since t0
CV change
since t0
Coefficient of variation (CV) t0 0.572 0.572 0.582
(1) women’s inequality to t1 0.552 −3.4% 0.554 −11.2% 0.564 −2.9%
(2) men’s inequality to t1 0.592 3.5% 0.574 −3.1% 0.575 −1.1%
(3) inequality in other income to t1 0.551 −3.6% 0.554 0.5% 0.567 −2.5%
(4) correlation of female income to t1 0.559 −2.3% 0.559 −3.1% 0.569 −2.1%
(5) all income shares to t1 0.593 3.7% 0.587 −2.3% 0.584 0.4%
(6) share of female earnings to t1 0.575 0.6% 0.577 2.6% 0.582 0.1%
(7) all women’s values to t1 0.535 −6.3% 0.537 −6.0% 0.550 −5.5%
Coefficient of variation t1 0.529 −7.5% 0.507 −11.2% 0.529 −9.1%
Change t1–t0 explained by women’s
labour force participation
84.0% 53.7% 60.1%
Source: SHP 2000–2014.
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130 Ursina Kuhn and Laura Ravazzini
the other factors constant (counterfactual 6),16 the CV changes by less than 1%,
which is against our expectations for H5.
Most importantly, Table 4 shows the inequality level assuming that only
elements associated with women’s labour force participation changed (correlation,
women’s share, inequality in women’s earnings), while men’s earnings and other
household income remained constant. For the period 2000–2014, we nd that
household income inequality declines from 0.57 to 0.53 (−7.5%). is amounts
to 84% of the real decrease in income inequality between 2000 and 2014 that can
be attributed to female labour force participation. If other years are chosen, how-
ever, female labour force participation explains only 54% of the change between
2000 and 2009 and 60% of the change between 2004 and 2014. is shows that
rising female earnings have contributed to the small decline in household income
inequality in Switzerland.
5.2.2 Household types
e decomposition by factor shares comes with some limitations, as it can neither
show the eect of part-time work nor address the eects of changing household
structure. erefore, we conduct decompositions by household types as described
in the methodological part. We distinguish ten groups: male-breadwinner couples
(1), female-breadwinner couples (2), couples where the man works full-time and
the woman part-time (3), couples where the woman works full-time and the man
part-time (4), full-time working couples (5), and couples where both either work
part-time or do not work (6), single women (7), single men (8), single mothers (9)
and other households (10), which consist mostly of couples living with children
who contribute to household income.17
Results are presented in Table 5. If not stated otherwise, the discussed changes
are signicant at the 95% condence level. e ten household types explain 15.7%
of total inequality in 2000 and almost the same share (15.1%) in 2014. Most of the
inequality is thus within groups. We rst address the role of single and single-mother
households to test H5. e share of single women has remained relatively stable,
which means that H5a can be rejected.18 Interestingly, more households composed
by single women would not even have increased household income inequality be-
cause the income level of and inequality in this group are close to the population
averages. e situation is slightly dierent for single men, who show a high average
income (ca 23% above the population average) and high (within) inequality level in
16 We divided income shares from men’s earnings and other earnings in 2000 by 0.95 (100-women’s
share in 2014)/(100-women’s share in 2000), so that the income shares of the counterfactual
distribution add up to 100%.
17 Couples whose children are younger than 18 years old or earn less than CHF 24 000 per year are
considered couple households.
18 Although Table 5 suggests an increasing share of single men, a closer examination reveals that
this evolution is due to weights provided by the SHP. We choose nevertheless to use weighted
data because unweighted data bring other biases.
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 131
2014. In contrast, single-mother households have the lowest average income of all
household types and a high level of within-group inequality. Given that the share
of single mothers has decreased over time, this socio-demographic aspect have not
aected inequality (H5b).
After testing the eect of the household composition, we look more closely
at couple households. Most importantly, the share of male-breadwinner couples
has declined from 31.8% of all working-age households in 2000 to only 19.1% in
2014, whereas the share of full-time working men and part-time working women
increased from 26.8% to 30.1%. Full-time working couples have also become more
common (6.9% in 2000, 9.2% in 2014), whereas couples with a main female earner
remained marginal. It is interesting to compare the inequality and income levels
within these household types. Single-breadwinner households are more unequal
than dual-earner households (the dierence is signicant in 2014, but it just misses
the signicance level in 2000) and have a low average household income (83% and
79% of average income). e abandonment of the male-breadwinner model thus
contributes to a more equal distribution of household income. Turning to the
comparison of part-time and full-time working women, we see that the inequality
within groups is lower when both partners work full-time, probably reecting the
heterogeneity of working hours among part-time working women. Because full-
Table 5 Decomposition of household income inequality by household types
in 2000 and 2014
Share
2000
Share
2014
Income
2000
Income
2014
Theil
2000
Theil
2014
Couple: male breadwinner 31.8% 19.1% 0.831 0.791 0.144 0.134
Couple: female breadwinner 2.6% 3.5% 0.692 0.846 0.268 0.129
Couple: man full-, woman part-time 26.8% 30.1% 1.113 1.051 0.118 0.084
Couple: woman full-, man part-time 1.1% 1.9% 1.036 1.192 0.055 0.086
Couple: both full-time 6.9% 9.2% 1.553 1.421 0.080 0.069
Couple: both part-time or inactive 6.2% 7.8% 0.668 0.768 0.227 0.157
Single women 4.2% 4.3% 0.994 0.928 0.136 0.114
Single man 3.6% 4.7% 1.230 1.224 0.105 0.162
Single mother 4.4% 3.6% 0.673 0.709 0.128 0.145
Other households (other earners
than couple)
12.5% 15.8% 1.170 1.055 0.091 0.088
Overall 100.0% 100.0% 1.000 1.000 0.149 0.122
% between household types 15.7% 15.1%
Notes: Income refers to the ratio of mean income of each household type to the population mean income.
n of households: 3589 (2000) and 5186 (2014).
Source: SHP 2000 and 2014.
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132 Ursina Kuhn and Laura Ravazzini
time working couples have high incomes (1.55 times the average income in 2000
and 1.42 times the average income in 2014), the eect of a switch from part-time
to full-time work on income inequality remains ambiguous and requires additional
analysis, which we present below. Turning to low work-intense couple households,
we notice that their inequality appears to be quite high. is is probably because
the reasons for low participation in the labour market vary considerably (e. g. from
income-rich households whose members do not need to work to unskilled household
members excluded from the labour market).19
In order to properly estimate the equalising potential of more working
women and to compare part-time and full-time work, we have computed a coun-
terfactual analysis with the eil index in 2000 and 2014 (Table 6). A limitation
of this approach is that selection eects are not taken into account. For example,
the counterfactual assumes that inactive women would have similar earnings as
women already working. In the rst counterfactual, we simulate that all inactive
partnered women enter the labour market as part-time workers, which means that
all 1–0 type households (group 1) switch to the 1–0.5 type (group 3) keeping other
proportions, within-group inequality and mean earnings constant. e eil index
in this scenario declines by 10.7% in 2000 and by 11.7% in 2014. In the second
counterfactual, we simulate that all part-time working women living with a partner
switch to full-time, which means that all 1–0.5 type households (group 3) switch to
the 1–1 type (group 5) assuming that other elements remain constant. is shows
that more full-time work relative to part-time work has little impact on household
income inequality (3.6% in 2000, 5.0% in 2014). Nevertheless, the eect points
to more income inequality.20
19 We have also carried out a decomposition of the inequality change proposed by Mookherjee and
Shorrocks (1982) for the MLD (mean log deviation). e MLD of household income declined
from 0.156 in 2000 to 0.125 in 2014. We can attribute 75% of this decline to inequality within
groups, 21% to changes in relative incomes and only 4% to changes in the proportions.
20 Taking account of the fact that part-time working women tend to have higher earning partners
than full-time working women (Figure 2), the adverse eect of more full-time work on inequality
is likely to be underestimated in the counterfactuals in Table 6.
Table 6 Counterfactual analysis by household type (Theil index)
Counterfactual analysis
2000 In % 2014 In %
Theil index 0.149 0.122
1–0 hh. switch to 1–0.5 hh. 0.133 −10.7% 0.107 −11.7%
1–0.5 hh. switch to 1–1 hh. 0.154 3.6% 0.128 5.0%
Notes: 1–0 hh. indicates male-breadwinner households; 1–0.5 hh. indicates households where men work
full-time and women work part-time and 1–1 hh. indicates household where both partners work full-time.
Source: SHP 2000 and 2014.
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The Impact of Female Labour Force Participation on Household Income Inequality in Switzerland 133
6 Conclusion
is study is a contribution to the growing literature addressing the consequences
of demographic changes on household income inequality. While many studies
have focused on the rising share of single households, we nd that the most striking
changes in household types in Switzerland have occurred within couples, as dual-
earning couples have replaced the dominant male-breadwinner family. Our analysis
has shown that this evolution has kept household income inequality relatively low
in Switzerland. Moreover, the small decline in inequality levels observed since 2000
can mainly be attributed to increasing female labour force participation.
Among the dierent channels linking female earnings and household income
inequality, the homogenisation of women’s working hours is the most important.
Both women who enter the labour market and part-time working women who aug-
ment their work percentage have contributed to the lower variation of working hours,
which translates into lower household income inequality. In contrast, potentially
osetting factors, such as a part-time wage penalty or an increasing correlation of
partners’ earnings, are not relevant for this country. Women over the entire income
distribution have increased their participation and working hours to a similar extent.
e very weak correlation of partners’ earnings in Switzerland is striking in
comparison to studies on other countries that report positive and strengthening cor-
relations between partners’ earnings. One of the reasons for this Swiss particularity
is that women with high-earning partners work less than women with low-earning
partners. e tax system, progressive child-care costs, attitudes, the gender pay
gap and weak assortative mating could be potential explanations, that need to be
addressed in future studies.
While there is extensive evidence that women’s entry into the labour market
reduces household income inequality, the dierences between part-time and full-time
work with respect to household inequality have been neglected by previous stud-
ies. Even though our analysis shows clear equalising eects of female labour force
participation in general, we nd that switching from part-time to full-time work has
little impact on income inequality, and that this impact even points towards more
household income inequality. Comparative studies are needed to test whether this
result is particular to Switzerland. About half of working-age women work part-time
(between 6 and 35 hours per week), and most of them work more than 50%. e
average hourly wages of full-time working women and of women with small and
high part-time percentages are very close. is means that, in Switzerland, part-
time work contributes to income inequality only through the variation in working
hours and not through the variation in hourly wages.
While our analysis shows clear equalising eects of female labour force participa-
tion up to 2014, the scope for future eects is limited. Considering the high activity
rate, the potential of labour-market entry is limited. Furthermore, an increase in
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134 Ursina Kuhn and Laura Ravazzini
full-time work relative to part-time work is not a means to lower household income
inequality further in Switzerland. However, women who increase their working hours
from small work percentages could be benecial for household income inequality.
Our ndings are more than a conrmation of previous studies. e Swiss case
shows that increased female labour force participation is equalising even in a context
of high female labour force participation. Another important result is that from
the perspective of household income inequality, part-time work is not detrimental,
but rather benecial. We can conclude by saying that high female labour force
participation has not come at the price of higher income inequality.
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Sous la direction de Jean-Marie Le Goff et René Levy
Devenir parents, devenir inégaux
Transition à la parentalité
et inégalités de genre
Devenir parent, donc la transition à la parentalité,
marque les parcours de vie par une multitude de
changements touchant autant les partenaires que
leur couple : transformation de la division du travail,
reconfiguration du réseau social, ajustements identi-
taires… Souvent, ces changements rapprochent l’or-
ganisation du couple des rôles traditionnels de père
et de mère, modèle qui inclut également les inégali-
tés de genre. Le présent ouvrage vise à comprendre
les mécanismes sociaux à l’œuvre dans la manifesta-
tion des inégalités entre les hommes et les femmes
au moment de la naissance de leur premier enfant
dans le contexte social et institutionnel de la Suisse.
Le livre présente les résultats d’un projet interdisci-
plinaire regroupant des psychologues, psychologues
sociaux, sociologues et démographes. L’étude a été
réalisée en Suisse romande, associant matériaux
quantitatifs et qualitatifs sur la transition à la parenta-
lité et relevés en trois vagues autour de la naissance
d’un premier enfant.
Jean-Marie Le Goff est démographe, maitre d’enseignement et de recherche à l’Université de
Lausanne et chercheur associé au NCCR Lives. Il a participé à l’élaboration du projet devenir
parent et de l’enquête Devenir parent, puis a été chef de projet de la collecte des données de
cette enquête.
René Levy est sociologue (inégalités sociales, rapports sociaux de sexe, parcours de vie), pro-
fesseur émérite à l’Université de Lausanne, ancien directeur du centre Pavie. Il a dirigé le projet
Devenir parent.
Questions de genre
ISBN 978-2-88351-071-5, 352 pages, Fr. 48.— / Euro 43.—
www.editions-seismo.ch info@editions-seismo.ch
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