Wage effects of having children on women’s wages in industrialised and

developing countries PhD student: Janna Besamusca

Supervisors: Prof.Dr. M. Keune, Prof.Dr. K. Tijdens & Dr. S. Steinmetz

WORK IN PROGRESS – DO NOT QUOTE

Introduction The labour market earnings of American and Western European women have attracted academic

curiosity and political activism alike since women started entering paid work in growing numbers in

the second half of the twentieth century in way that radically and lastingly changed it. Initially, most

attention went out to the weaker position of women relative to men’s, reflected in the structurally

lower wages and pay scales for female workers. Since the 1990s, however, scientists in advanced

capitalist economies have started to find that the pay gap between different groups of women may

be at least as sizeable, and potentially even larger, than that between women and men. In fact, the

lion’s share of the disadvantage may not be driven by direct discrimination anymore, but rather

indirectly by the gender way in which our societies are organised. In particular, there appear to be

major earnings differences between women facing substantial care responsibilities and those who do

not, showing evidence of a child penalty on wages.

Previous research has shown that mothers may be disadvantaged through processes of

discrimination, self-selection and adaptation. Employers have seen mothers as less productive, or at

least less committed to their careers (c.f. Correll, Bernard & Paik, 2007; Baum, 2002). Women who

are included to have children, however, may also self-select into jobs that are more family-friendly,

or may adapt to motherhood by prioritising the reconciliation of work and family responsibilities

after they give birth to the first child (Baum, 2002; Albrecht et.al, 1999). Several authors have indeed

found evidence of mothers’ lower wages compared to childless women in the US (Waldfogel, 1998,

1998; Budig & England, 2002), Sweden (Albrecht et al, 1999), Denmark (Datta Gupta et al, 2002;

Nielsen et al, 2004), Germany (Ondrich et al, 2003) and Canada (Phipps et al, 2001). Aisenbrey,

Evertsson & Grunow (2009) found a substantial child penalty in Sweden and Western Germany, as

did Gornick and Meyer (2004) for a number of highly industrialised countries.

Perhaps partly due to the tacit assumption that discrimination of subgroups of women like mothers

becomes prominent only after the elimination of blatant gender discrimination, research into the

effects of motherhood on wages has so far been focused on the examination of women in one or a

number of North American and Western European countries. As Besamusca et al (forthcoming)

show, care affects women’s labour market behaviour in developing countries as much as in

industrialised countries. However, by all accounts the child penalty is driven by culturally specific

mechanisms (c.f Aisenbrey, Evertsson and Grunow, 2009; Gangl & Ziefle, 2009). As Albrecht et al

(1999, p. 296) point out, extended periods of maternity leave are seen as signals of lower

productivity or lesser labour market commitment in the US, where take-up is relatively low, but not

so in Sweden, where take-up in near universal. Such signals, it would appear, might be very different

in developing countries where fertility rates are higher and the choice of becoming a mother is as

such unremarkable. Secondly, wives may often lack the luxury of (partially) withdrawing from the

labour market for the sake of motherhood.

In this article, I aim to expand the current knowledge by including countries that have so far been

excluded from this debate and by looking closer into the mechanisms that drive the wage differences

between mothers and childless women. I compare both industrialised and developing countries,

using two datasets covering 52 countries across the Americas, Europe, Africa and Asia. I look at

human capital and work place characteristics that may explain the distinct labour market positions of

women and with and without children, as well as the factors that affect the size of the penalty for

different groups of women. I firstly examine the mechanisms through which having children has

previously been found to affect women’s wages in industrialised countries. I then explore whether

the child penalty exists outside North America and Europe as well as the extent to which it can be

explained by mothers’ and childless women’s distinct labour market behaviour. Finally, I test whether

the postponement of motherhood and passing on of related care responsibilities can reduced the

negative effect of having children.

Theoretical background Early studies into women’s wages focused on their inferior earnings compared to men, quoting

discrimination as the primary mechanism through with this disadvantage came into existence. As

women’s position became more equal, in both law and practice, research has started focusing on

smaller niches or alternative mechanisms of disadvantage. Studies focused on the particular situation

of women whom emancipation had benefited to a lesser degree (ethnic minorities, lower social

classes; low education), the unfortunate effects of women’s occupational choices (female dominated

occupations, sectors and part-time) or the drag on wages of care responsibilities. As such

developments led research towards a focus on discrimination, self-elected disadvantage and

adaptation to the demands of family life, it became less self-evident to compare women to men and

more attractive to contrast one group of women to another much like it.

On care in particular, a body of literature reporting the lower wages of mothers compared to

childless women has started to develop since the late 1990s (c.f. Waldfogel, 1997, 1998; Budig &

England, 2001). The negative effect of having children, or child penalty, on women’s wages has been

studied in a number of industrialised countries and in a number of cases also from a comparative

perspective (c.f. Grunow, Hofmeister & Buchholz, 2006; Aisenbrey, Evertsson & Grunow, 2009; Gangl

& Ziefle, 2009). Studying non-Hispanic white women the United States, Budig and England (2001)

found a 5% wages penalty per child, while Waldfogel (1997) found a 4% penalty for the first child and

12% penalty for higher order births. Aisenbrey, Evertsson and Grunow (2009) confirm the existence

of child penalties in Germany, Sweden and the US, where Gangl & Ziefle (2009) do so for the Britain,

Germany and the UK. [Add more studies Denmark, Sweden, Germany, Canada]. One of the few

works on the child penalty in Latin America (Piras & Ripani, 2005) found inconsistent effects, failing

to reproduce the negative effect of children on wages in some countries while confirming it in others.

To the best of our knowledge, no studies exist that have reported the existence or absence of a child

penalty in Asia or Africa.

Most studies distinguish between what Anderson, Binder and Krause (2002, p. 354) would term a

“pure” and a “total” wage effect of children. The total child effect, here, is the often rather large

difference in average wages between women with and without children. Part of the gap is certainly

attributable to differences in treatment of mothers and childless women, often explained through

mechanisms of statistical discrimination by which employers expect mothers to be less productive

workers than childless women or men. In a laboratory experiment and audit study, Correll, Bernard

and Paik (2007) found that American employers attribute significantly lower recommended starting

salaries to mothers than to childless women with identical curricula. Discrimination, particularly in

the form of expectations of lower productivity, undoubtedly plays a role in explaining the child

penalty.

There are several choices that mothers, prospective mothers, and sometimes women in general

make, that are interpreted by employers as signals of the type of worker they are. Next to the crude

discrimination that classifies all mothers as worse employees that Correll et al (ibid) point to, subtler

signals have been identified to convey lower commitment or ambition to employers, such as

extended breaks or shorter hours (c.f. Baum, 2002). Prospective mothers may also self-select into

worse paid jobs, by choosing such professions and sectors as are most family friendly. Finally, they

may adapt to motherhood by changing jobs or reducing work load after having given birth.

The mechanisms of discrimination and self-selection, then, are in essence the choices of prospective

mothers’ in anticipation of care responsibilities and employers’ perception of those choices. A large

share of the wage difference between mothers and childless women can be explained by their

distinct positions in the labour market, i.e. the different occupations, sectors and career levels

associated with the labour market behaviour of women with and without children. First and

foremost, these characteristics include a set of human capital and workplace characteristics.

Women’s human capital refers mainly to their experience and skills in or as relates to the labour

market. This would include the differences in wages arising from women’s age differences, as wages

tend to rise over the life course, but also from tenure, education, occupations and time out of the

labour market. Budig and England (2001) find only very small effects of education and years of full

time and part time work experience on American mothers’ wages, whereas Waldfogel (1997) reports

years of tenure are associated with higher wages.

Measuring the effect of one and two or more children on non-hispanic white American mothers’

wages using in a cross sectional OLS regression, Anderson, Binder and Krause (2002, p. 356) report

that between 30 and 40 per cent of the child penalty is explained by education, experience and time

spent out of the labour market. They find that while more education is associated with higher

wages, highly educated women also suffer larger child penalties, whereas no effect of having children

is found for the least educated women in the sample (2002, pp. 355-356). They argue that the child

penalty results, in the first place, from mothers’ delayed career advancement due to time out of the

labour market or periods of fragile career commitment.

Time out of the labour market is often associated with a wage penalty. Breaks can be expected to

stall career advancement from a point of view of delayed promotions and slower accumulation of

tenure. Secondly, career interruptions have been seen as signals of limited productivity and labour

market commitment by employers (c.f. Baum, 2002; Albrecht et al, 1999; Anderson et al, 2002).

Thirdly, as Albrecht et al (Albrecht et al, 1999, p. 295) point out, prospective mothers may

“[anticipate] future work interruptions….[and thus they] choose (or are assigned to) jobs with less

potential for training and hence have flatter earnings-experience profiles”.

Aisenbrey, Evertsson and Grunow (2009, pp. 598-99) find negative effects of maternity related

career breaks on women’s wages in Germany Sweden and the US, although not to the same degree.

Using a longitudinal US dataset, Baum (2002, p. 29) also finds negative effects of both breaks and

decisions to have children, amounting to about two to three per cent per year or for the first child,

but notes that these effects are offset within a few year if women return to the same jobs they held

before their break. Gangl and Ziefle (2009) report that breaks and choices for mother-friendly jobs

explain most of the child penalty in the US and UK, but not in Germany. Lundberg and Rose (2000)

find that American mothers who do not experience a maternity related career break, do not suffer

from a child penalty, whereas those who temporarily withdraw from the labour market do.

Gangl and Ziefle (2009, p. 344) refer argue women with children may make further choices that make

them less “competitive” in the labour market, referring amongst others to a lower willingness to

commute or to work long hours. Several studies have indicated there is a trade-off between wages

and commuting time, suggesting that workers who are prepared to travel further for better jobs may

earn higher wages in return as well as that mothers may be less willing to do so. With a few

exceptions (c.f. Tijdens, year, on the specific dynamic of part-time work in the Netherlands) part-time

work has also been associated with lower hourly wages. Both Waldfogel (1997) and Budig and

England (2001) find negative effects of part-time work on wages, corroborating the story that part of

mothers’ lower wages can be explained by their choice to work shorter hours.

A range of studies on wages have shown an association between low paid sectors and occupations

and the share of women or mothers in those jobs. Mothers are less often found in higher status

occupations and supervisory positions, contributing to their lower average pay. [Add paragraph

horizontal & vertical segregation and maternity].

Mothers, then, are expected to have a worse labour market position than women without children

due to both statistical discrimination, lower acquired human capital and their tendency to work in

less prestigious but more family-friendly jobs. However, several studies have also indicated that not

all mothers may be negatively affected by having children to the same extent. Indeed, certain groups

of mothers may be expected to be able to weather the child wage effects much better depending on

their ability to reduce their caring responsibilities. Mothers who are able to time the childbirth and

pass on (some share of) the care tasks associated with raising children in such a way that it is less

intrusive to their career development, may be expected to undergo fewer negative consequences of

starting a family.

Timing of motherhood, including its postponement as is increasingly observed throughout the

industrialised world, may go a long way in mediating the negative effects of having children. As

discussed above, wages as a rule tend to increase over the life course and, as Mincer and Polacheck

(1974, 1978) famously pointed out, they do so most steeply at the beginning of the labour market

career. Several other authors have also pointed out that the benefits of tenure accumulate at a

decreasing rate, making it more advantageous to interrupt one’s career at a later rather than earlier

stage (for an extensive overview of the effects of breaks on wages, see Baum, 2002). Comparing the

gain in salaries for mothers who were early child bearers to late child bearers, Blackburn et al (1993),

argue that postponement of motherhood affects wages both because women who postpone have

more opportunities to accumulate human capital, as well as because those prone to postpone had

higher initial skills and this have higher wages throughout the life course. Postponing the first child to

a later age, as well as maximising the time between leaving full time education and motherhood

might thus reduce the child penalty by moving the impact to a flatter point on the mincer curve.

The provision of child care can improve the compatibility between family and career, albeit mainly

indirectly by allowing women to work more hours. Several authors have shown that countries where

child care coverage is higher have both higher labour force participation of women and a smaller

wage gap between mothers and childless women (c.f. Gornick & Meyer, 2004; Stryker, Eliason,

Tranby & Hamilton, 2011). Aisenbrey, Evertsson and Grunow (2009) show that mothers who make

use of childcare facilities, particularly if they live in countries with high coverage, are more likely to

return to the same or higher occupation positions as before childbirth. The presence of other adults

in the household could theoretically point towards a greater ability to share care tasks. Previous

research, however, has indicated that families are likely to revert to more traditional divisions of

labour once children are born. Budig and England (2001) showed that while married women earned

higher wages in general, married mothers experienced more severe penalties.

Hypotheses The aim of this article is to investigate whether a child penalty on women’s wages exists in a larger

set of countries that those previously studied, as well as to shine light on the factors explaining the

existence and size of the wage effect of having children in those countries. As the lion’s share of care

responsibilities falls to women in both industrialised and developing countries (c.f. [authors,

forthcoming]), it would stand to reason that women’s career advancement in impeded by having

children throughout the world and a wage effect can be expected outside the limited confines of

North American and Europe as well as within it. I thus hypothesise that:

H1: Having children has a negative effect on women’s wages in both industrialised and

developing countries.

As mothers and childless women are expected, and have been shown, to make different labour

market choices, part of the wage gap can be explained through differences in human capital between

women with and without children. Women without children are less likely to take career breaks and

will therefore, on average, have more labour market experience that mothers of the same age,

making them more competitive. Expecting motherhood to be disadvantageous both through a lag in

in career advancement from less experience, as well as from disadvantageous re-entry, I hypothesise

that both tenure and having a career break will affect women’s wages. In addition, mothers are

expected to choose more family-friendly occupations, sectors, firms, working hours and locations.

H2: Mothers’ lower human capital can explain a substantial part of the child penalty, through

positive effects of tenure and negative effects of breaks.

H3: Mothers’ tendency to work in more family-friendly work places can explain a substantial

part of the child penalty, through positive effects of firm size and hours on wages, negative

effects of a larger share of women in a firm.

Timing of childbirth and the ability to pass on some of the care responsibility can reduce the negative

effects of having children on women’s wages. Postponement of motherhood allows a stronger initial

commitment to one’s career; limiting the time taken away from work because of care can reduce the

negative effect on career advancement. I just hypothesise that:

H4: Mothers who are older and have more experience in the labour market at the time of the

birth of the first child, will experience smaller child penalties.

H5: Mothers who do not interrupt their labour market participation at the time of childbirth,

will experience smaller child penalties.

H6: Mothers whose children are enrolled in child care facilities will experience smaller child

penalties, whereas women living with partners will experience higher child penalties.

Operationalisation In this article, I aim to test whether the child penalty on hourly wages exists outside the limit number

of countries that has so far been studied, as well as to study the mechanisms by which mothers are

disadvantaged. In order to do so, I compare hourly wages of mothers to those of childless women

using stata’s xtmixed package for multilevel regression models. I use two datasets that are chosen

specifically for their inclusion of developing countries and whose results are compared to confirm the

robustness of our findings. Firstly, I use the 2013 online WageIndicator volunteer survey, which

contains information on wages and working conditions in Latin America (Argentina, Brazil, Mexico),

South Asia (India), Africa (South Africa), Western Europe (Belgium, Germany, Netherlands, Spain) and

Eastern Europe (Belarus, Russia, Slovakia, Ukraine). Secondly, I use the 2006-2013 WageIndicator

face to face surveys, which were held in Burundi, Cambodia, China, Costa Rica, Benin, El Salvador,

Ethiopia, Ghana, Guatemala, Guinea, Honduras, India, Indonesia, Kenya, Madagascar, Mozambique,

Nicaragua, Niger, Pakistan, Paraguay, Rwanda, Senegal, South Sudan, Togo, Uganda, Tanzania and

Zambia.

I measure the child penalty by introducing a variable for having children to measure its impact on the

dependent variable, logged gross hourly wages. The multilevel models are run on two different

measurement of having children. Firstly, the effect of having children or not is tested using a binary

variable; then the model are run again, contrasts women with one child, two children and three or

more children to women who are not mothers. I test the grand mean effects across the entire

sample, as well as country specific child penalties though the empirical Bayes estimates for a random

slope for the child variable. These models are run on the 2013 data from the WageIndicator online

volunteer survey using hierarchical two-level models and on the 2006-2013 face to face surveys using

cross-classified multilevel models. Note: I still have to test the models on the different dependent

variables and the f2f dataset, so those results are not yet here and these results are very preliminary.

In all models, I control for per capita GDP in order to filter out differences in wages arising from

different levels of economic development, as well as for age, in order to filter out wage differences

that arise from progression throughout the life course. I also interact GDP with the main explanatory

variable for having children, to estimate the relation between development and the child penalty.

Results may be biased if mothers and childless women differ in their inclination to enter the labour

market. Because both datasets contain samples of working women, I cannot introduce a Heckmann

selection and do, instead, introduce a main term and interaction with having children for female

labour force participation rates in a country. Female labour force participation rates are taken from

the ILO Estimates and Projections of the Economically Active Population (EAPEP) for 2013 and

contain information on female participation rates per five-year age category.

The child penalty is measures while subsequently introducing two sets of variables controlling for

human capital and work place characteristics that could potentially explain wage differences

between women independently of the condition of motherhood. As proxies for human capital, I

introduce women’s education, occupational status, tenure and past career breaks. Educational level

is measured as classified in UNESCO’s international standard classification (ISCED). We measure

occupational status according to Ganzeboom’s International Socio-Economic Index of Occupational

Status (ISEI); models using first digit ISCO codes produce the same results, without the advantage of

having a metric variable. Tenure is measured as years of labour market experience and career breaks

as a binary variable for ever having taken a career break. Commuting time is measure in minutes and

two dummies are introduced for respondents reporting that they hold a junior or a supervisory

position.

Work place characteristics I include are the percentage of women in a firm, firm size, contract hours

and sector. While measured on an ordinal scale, firm size is treated as an interval variable since the

introduction of each category shows an exactly linear effect. Contract hours are respondents’ self-

reported working hours as agreed in a written or verbal contract, explicitly excluding overtime. We

distinguish between four sectors, corresponding to the first digit NACE distinction: industry, trade,

commercial services and public sector.

In part three, I investigate which individual level characteristics moderate the effect of having

children that are left unexplained after controlling for human capital and work place characteristics.

These mediating variables are introduced as added effects to having children. Following Franzese &

Kam, main effects of the mediating variables are introduced where they are hypothesised to have a

direct effect on wages independent from motherhood, i.e. when they are expected to affect wages

of women without children as well as mothers’ wages, and left out when they do not.

I include the age of the mother’s age at first birth and the time between her labour market entry and

first birth. In addition to the previously introduced variable for career breaks, I include an interaction

term to distinguish child-related breaks from other breaks. To measure the potential of sharing care

responsibilities with other adults (either through family arrangements or paid facilities), the model

includes a variable for living with a partner. Additionally, a binary term is introduced that measures

where at least one child attends a kindergarten or other form of child care facility.

Results In total 46% of the 12,965 women in the sample are mothers. The share of women indicating they

have children increases steadily with age, from only 2% of under twenty years olds to nearly one in

eight women over fifty. As table 1 shows, the share of mothers in the youngest age categories is

highest in Latin American countries and Spain, while there are relatively few mothers over 50 years

old in those samples, suggesting many mothers may have dropped out of the (formal) labour market.

Table 1 Under 20 20 - 29 years 30 - 39 years 40 - 49 years 50 or older

Azerbaijan 0,07 0,22 0,68 0,80 0,82

Argentina 0,19 0,21 0,53 0,72 0,69

Belgium 0,00 0,17 0,60 0,86 0,81

Brazil 0,05 0,25 0,55 0,76 0,80

Belarus 0,11 0,39 0,79 0,90 0,94

Chile 0,38 0,32 0,51 0,89 0,78

Colombia 0,50 0,30 0,56 0,74 0,90

Czech Republic 0,09 0,18 0,62 0,86 0,93

Germany 0,06 0,08 0,42 0,71 0,80

India 0,00 0,13 0,55 0,78 0,90

Indonesia 0,04 0,19 0,66 0,72 0,90

Kazakhstan 0,11 0,36 0,78 0,86 0,89

Mexico 0,08 0,23 0,59 0,78 0,85

Netherlands 0,01 0,09 0,50 0,75 0,81

Russian Federation 0,06 0,23 0,72 0,86 0,92

Slovakia 0,05 0,12 0,65 0,82 0,94

South Africa 0,22 0,37 0,68 0,88 0,77

Spain 0,17 0,02 0,34 0,60 0,80

Ukraine 0,08 0,30 0,76 0,91 0,90

United Kingdom 0,00 0,10 0,45 0,73 0,76

Total 0,02 0,18 0,52 0,73 0,79

N 244 4839 3829 2381 1663

Part 1: Does the child penalty exist in developing countries too?

Wage Indicator Continuous Online Volunteer Survey (2013 data)

The webdata on women’s hourly wages is quite heavily clustered. As table 2 shows, a null model

indicating that as much as 40% of the variance is between countries rather than within them. The

models show that women’s wages increase with age, at a decreasing rate. Controlling for age alone,

mothers have 22% lower wages than women without children. Female labour force participation in

itself does not have an effect on wages, but it does moderate the child penalty in two ways.

Controlling for the female labour force participation rate in five-year age groups in order to control

for self-selection into employment, the child wage effect is reduced to 14%. The negative interaction

term indicates that the child penalty is larger in countries with higher female labour force

participation rates. When I estimate the effect of having children controlling for per capita GDP and

interacting that with the variable for having children, the country level variance is reduced to about

27% and the negative coefficient of having children indicates that women with children earn about

10% less than their childless counterparts of the same age and in countries at the same level of

economic development. The positive interaction term indicates that the child penalty is smaller in

countries with higher per capita GDP. Figure 1 indicates that a negative effect of having children on

hourly wages is estimated for all countries except Indonesia.

Table 2 nullmodel modelA1 modelA2 modelA3

Having children -0.217*** -0.141*** -0.103***

(0.036) (0.040) (0.029) Age 0.095*** 0.105*** 0.107*** (0.004) (0.006) (0.006)

Age squared -0.001*** -0.001*** -0.001*** (0.000) (0.000) (0.000)

FLPR (centred) 0.001 0.000 (0.001) (0.001)

Child * FLPR -0.005*** -0.005*** (0.001) (0.001) Per capita GDP (centred) 0.026*** (0.007)

Child * GDP 0.007*** (0.001) Constant 1.837*** 0.026 -0.140 -0.065 (0.133) (0.144) (0.164) (0.142) Var(constant) 0,35063832 0,01627704 0,01756231 0,00396599

Var(child) 0,31036694 0,30912795 0,16629366 var(residual) 0,49361471 0,45840601 0,45749012 0,45840601 Observations 14,043 14,043 14,043 14,043 Number of groups 20 20 20 20 ICC L1 0.41514 0.416 0.416 0.271

-2LL -15030 -14525 -14512 -14501 df 0 3 5 7

Note: WageIndicator 2013 Volunteer Websurvey. Standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

Part 2: Human capital and work place characteristics

Wage Indicator Continuous Online Volunteer Survey (2013 data)

When controlling for human capital, the negative effect of having children is reduced to 7%. There

are positive effects on wages of being higher educated and having a higher occupational status and

higher tenure. The fact that they reduce the effect of having children suggests that mothers on

average hold lower occupational status and tenure, confirming theories that argue motherhood

delays the accumulation of human capital. Most striking, is the large negative effect on wages of

having experienced a career break, which has an estimated negative effect of nearly 8% that appears

to have been captured in by the child variable in the previous models. Thus, the model1 indicates

that older, more experienced, highly educated women in high status occupations on average earn

higher wages and women with children and women who have spent time out of the labour market,

have lower average wages. Women in junior position have lower and those in supervisory position

have higher wages. The model also confirms the trade-off between wages and commuting time,

where those who travel farther for work earn higher average wages. Figure 2 shows that when

controlling for human capital variables, mothers earn lower wages than childless women in all

countries in the web sample.

Adding the control variables for work place characteristics (model2), the model estimates women

with children earn on average 8% less than women without children. The results show that women in

firms with a high share of female employees and working longer hours earn lower wages. I find

positive effects for working in larger firms. The effects are slightly reduced when tested in a model

with both the human capital and workplace covariates, but remain significant.

Controlling for both human capital and workplace characteristics, a 4.5% child penalty remains

unexplained. Half of the 22% total child penalty was explained in the previous section by taking

account of self-selection into employment and the level of economic development, where one

quarter was explained by the different labour market behaviour of women with and without

-.2 -.15 -.1 -.05 0

360. Indonesia398. Kazakhstan

724. Spain710. South Africa

152. Chile276. Germany

528. Netherlands203. Czech Republic

356. India76. Brazil

643. Russian Federation804. Ukraine56. Belgium

32. Argentina170. Colombia703. Slovakia112. Belarus

31. Azerbaijan484. Mexico

826. United Kingdom

Source: WageIndicator Global Dataset 2013Controlled for age, per capita GDP and FLPR

Figure 1: Country specific child wage effect

mean of betaA3 mean of loA3

mean of hiA3

children. The Figure 3 shows that when taking into account all human capital and work place

characteristics, a negative effect of having children is found in all countries.

(1) (2) (3)

Having children -0.068*** -0.077*** -0.045**

(0.025) (0.025) (0.020)

Age 0.061*** 0.112*** 0.073***

(0.007) (0.006) (0.006)

Age squared -0.001*** -0.001*** -0.001***

(0.000) (0.000) (0.000)

GDP/capita (per $1000) 0.029*** 0.024*** 0.026***

(0.006) (0.006) (0.006)

Child * GDP 0.007*** 0.006*** 0.007***

(0.001) (0.001) (0.001)

FLPR (centred) -0.000 0.002 0.001

(0.001) (0.001) (0.001)

Child * FLPR -0.003*** -0.008*** -0.006***

(0.001) (0.001) (0.001)

Had a career break -0.082*** -0.080***

(0.012) (0.011)

eduisced 0.009*** 0.008***

(0.001) (0.001)

iscoisei 0.008*** 0.008***

(0.000) (0.000)

Tenure 0.013*** 0.013***

(0.002) (0.002)

Tenure squared -0.000*** -0.000***

(0.000) (0.000)

Holds junior position -0.153*** -0.138***

(0.014) (0.013)

Supervisor 0.126*** 0.158***

(0.017) (0.016)

Commuting time (min) 0.027*** 0.027***

(0.004) (0.003)

Percentage female employees in firm -0.047*** -0.033***

(0.004) (0.004)

Firm size 0.050*** 0.039***

(0.002) (0.002)

Contract hours -0.019*** -0.020***

(0.001) (0.000)

Trade sector -0.090*** -0.047***

(0.017) (0.016)

Commercial services 0.074*** 0.006

(0.016) (0.016)

Public sector -0.024 -0.077***

(0.018) (0.018)

Constant -0.087 0.504*** 0.464***

(0.140) (0.136) (0.134)

Var(constant) 0,15505118 0,15320169 0,14427992

Var(child) 0,00212922 0,00255936 0,00036051

var(residual) 0,41561331 0,40171998 0,36421898

Observations 14,040 14,043 14,040

Number of groups 20 20 20

ICC L1 0.274 0.279 0.284

-2LL -13.818 -13.576 -12884

df 15 13 21

Note: WageIndicator 2013 Volunteer Websurvey. Standard errors in parentheses.

*** p<0.01, ** p<0.05, * p<0.1

-.15 -.1 -.05 0

276. Germany710. South Africa

360. Indonesia398. Kazakhstan

724. Spain152. Chile

528. Netherlands203. Czech Republic

356. India76. Brazil

170. Colombia643. Russian Federation

804. Ukraine32. Argentina703. Slovakia

484. Mexico112. Belarus56. Belgium

31. Azerbaijan826. United Kingdom

Source: WageIndicator Global Dataset 2013Controlled for age, per capita GDP, FLPR & human capital

Figure 2: Country specific child wage effect

mean of betaHC mean of loHC

mean of hiHC

-.06 -.04 -.02 0

276. Germany398. Kazakhstan

710. South Africa360. Indonesia

724. Spain203. Czech Republic

152. Chile703. Slovakia

643. Russian Federation356. India76. Brazil

170. Colombia32. Argentina

528. Netherlands112. Belarus56. Belgium

31. Azerbaijan484. Mexico804. Ukraine

826. United Kingdom

Source: WageIndicator Global Dataset 2013Controlled for age, per capita GDP, FLPR human capital & workplace.

Figure 3: Country specific child wage effect

mean of betaHW mean of loHW

mean of hiHW

Part 3: The size of the child penalty

Wage Indicator Continuous Online Volunteer Survey (2013 data)

When examining the factors that can explain why some mothers experience a child penalty and

others do not or do so to a lesser extent, controlling for all previous covariates, the negative effect of

having children persists. Models F1 through F5 show child penalties between 6% and 3%, where the

effect is no longer significant when controlling for living with a partner. Model F1 measures the

relation between the child penalty and postponement of childbirth, but does not find significant

effects. Model F2 contains an interaction between having children and having experiences a career

break and shows that while having any career break or having children both have a negative effect,

their combination is even more negative. The effect, however, is not significant. Women who live

with their partner earn higher wages, but they also experience larger child penalties. Mothers whose

children go to child care experience lower child penalties than those whose children do not, but this

effect is no longer significant in model F5, controlling for all mediators at the same time.

modelF1 modelF2 modelF3 modelF4 modelF5

Having children -0.060** -0.042* -0.029 -0.065*** -0.051*

(0.025) (0.023) (0.025) (0.023) (0.031)

Child*Age at 1st birth 0.001 0.000

(0.001) (0.001)

Child*pre-motherhood tenure -0.001 -0.001

(0.002) (0.002)

Child*break -0.005 -0.009

(0.021) (0.021)

Lives with partner 0.044*** 0.044***

(0.014) (0.014)

Child*Partner -0.042* -0.044*

(0.022) (0.022)

Child*Childcare 0.031* 0.027

(0.017) (0.018)

Constant 0.473*** 0.464*** 0.475*** 0.466*** 0.483***

(0.135) (0.134) (0.134) (0.134) (0.135)

Var(constant) 0,14399165 0,14456877 0,14399165 0,14399165 0,14370395

Var(child) 0,00057336 0,00036486 0,00040973 0,00045738 0,00061863

var(residual) 0,36421898 0,36421898 0,36421898 0,36421898 0,36349127

Observations 14,040 14,040 14,040 14,040 14,040

Number of groups 20 20 20 20 20

ICC L1 0.284 0.284 0.284 0.284 0.284

-2LL -12.883 -12.884 -12.879 -12.882 -12877

df 23 22 24 22 27

WageIndicator 2013 Volunteer Websurvey. Standard errors in parentheses

Controlled for all part 2 variables *** p<0.01, ** p<0.05, * p<0.1

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