Influence of Socio-Economic Factors on Fertility Behaviour.
A Case Study on Romania
Raluca Dana CAPLESCU
Ileana NICULESCU-ARON
Constanta MIHAESCU
Bucharest University of Economic Studies
Introduction
One of the focuses of demographic research in the present is the difference between the
intended and the actual number of children. Although for an overwhelming proportion of European
countries the average intended number of children has been for a long time around two (OECD,
2010; Testa, 2006, 2012), the actual average number of children is, in many cases, much lower.
According to EUROSTAT, only three countries had, in 2011, a total fertility rate above 2.0 (Ireland,
Iceland and France), while there were ten countries with a TFR of 1.36 and lower. Although the
TFR may be biased by postponement (Haragus, 2008; Sobotka, 2004), there is little doubt that
fertility levels are low in many European countries.
Based on the research done so far, a number of categories of factors that influence fertility, as
well as fertility intention, can be identified. Among them there are demographic and socioeconomic factors, the norms and values system, family system and kinship networks and
psychological.
There are several studies focusing on determinants of fertility that include factors of socioeconomic, demographic and cultural nature either directly, or through proxies (Caplescu, Mihaescu,
& Begu, 2013; Caplescu, 2011a, 2011b; Golovlyanitsina, 2007; Haragus & Oanes, 2009; Maleva &
Sinyavskaya, 2006; Mihaescu, Niculescu-Aron, & Caplescu, 2011; Zacharov, 2011). Generally, in
Romania people who live in rural areas are older, have a lower education level, tend to have more
traditionalist views and to be more religious. This implies a certain level of correlation between the
variables and it also means that the residence area may be used as proxy for cultural values, namely
degree of traditionalism and religiosity. Also, marriage is still an important factor in fertility
decisions the general opinion being that marriage should precede childbirth (Rotariu, 2005).
Since couples have the possibility to decide upon their fertility levels, this allows for the
analysis of readiness and desire to have children at various points of the life cycle. A theory which
may be used to study such factors is the Theory of Planned Behaviour (Ajzen & Fishbein, 1969;
Ajzen, 1991; Fishbein & Ajzen, 2010), used for underlining the link between beliefs and behaviour.
According to this theory, human behaviour is the result of the interaction between a person’s
behavioural, normative and control beliefs. In order to assess the impact of these three categories of
beliefs on behaviour, intention is measured as a function of attitude towards behaviour (as proxy for
behavioural beliefs), subjective norm (as proxy for normative beliefs) and perceived behavioural
control (as proxy for control beliefs). The chances that behaviour will be performed increase with a
more positive subjective norm and attitude towards the behaviour and a greater perceived
behavioural control.
Under these circumstances, the main questions raised are which factors increase the odds of
having children and what would determine a woman to have a child on the short term.
Data and Methods
The source of the data is the 2005 wave of the Romanian Generations and Gender Survey
(GGS), which is part of the Generations and Gender Progamme (GGP). The GGP aims to improve
the knowledge base for policy-making in the UNECE countries. The nationally representative
sample comprises respondents aged 18-74 years and it is designed as a panel of 3 waves by 3 years
(Vikat et al., 2006).
A sample of the national database was analysed in order to determine the factors that
influence the number of children on the one hand, and fertility intentions on the other hand. Due to
the fact that the demographic behaviour of retired women, as well as that of invalid and long term
sick ones is different, they were excluded from the sample. Moreover, women who were pregnant,
who had no sexual experience and those whose health (or their partner’s) did not allow them to
have children were also eliminated from the analysis. The resulting sample comprises 1851 female
respondents aged 18-44 years, all of whom are theoretically able to have children.
In order to determine what set of factors influences the number of children a woman has, the
multinomial logistic regression was performed. The category of reference chosen was ‘2 children’,
as this would allow the comparison to highlight the minimum requirements in order to have two
children. For determining the factors that would determine women’s intentions to have a child
during 2005 and 2008, the sample was analysed using binary logistic regression.
Socio-economic determinants of the actual number of children
Following the analysis, the significant results are presented Table 1. The model is well fitted
to the data and it has a correct classification rate of 54.8%. The low percentage of correct
classification for the category 3 or more children suggests that the variables used are not likely to be
important determinants for this category. In contrast, the percentages for the other three categories
are reasonably high.
Age of the respondent
Compared to respondents who had two children at the time of the interview, young women
are substantially more likely to be childless or to have one child. The risk of being childless
decreases as age increases. On the other hand, regardless of the age group they belong to, the
respondents are less likely to have three children than two, with odds of having two children
increasing as the woman is younger. This is in accordance with the tendency to postpone
childbearing reflected by the shift of the peak in the age-specific fertility rates from the 20-24 years
age group to the 25-29 years one. On the other hand, the results obtained support the affirmation
according to which the main cause of this decline is not so much an increase in the number of
childless women (in the sense that they remain childless until the end of their reproductive life), but
rather a decrease in higher parity births (Caplescu, 2011a; Ghetau, 1997; Haragus, 2008). Not only
are 3 and higher order births less likely to occur to women in the sample, regardless of their age, but
in case of younger women they are also more likely to have one child rather than two, while for
older women the odds are equal.
Marital status
The main conclusion to be drawn from the results regarding marital status is that a married
woman is most likely to have two children. Moreover, the fact that married women are less likely to
be childless underlines the relationship between marriage and fertility, which in Romania is still
rather traditional. To be more precise, despite an increase in extramarital fertility since the regime
change in 1989, the main component of fertility is still, to a large extent, the marital one (Haragus &
Oanes, 2009). According to official statistics provided by Eurostat, in 2012 extramarital fertility in
Romania was around 30%, lower rates being registered in the European Union only in Poland,
Malta and Lithuania.
Table 1
Odds-ratios of women to have zero, one or three children as compared to two children, depending
on their demo-socio-economic characteristics
Independent Variable
Age group
Marital status
Highest education attained
Type of settlement
Activity status
Number of
children*
No children
Demographic factors
18-24 years
124.086
25-29 years
24.385
30-34 years
8.479
35-39 year
2.083
40-44 years
.
married
.070
not married
.
Social factors
up to lower secondary
.060
upper secondary
.207
post secondary non-tertiary
.565
tertiary
.
urban
4.057
.
rural
Economic factors
employed
1.687
unemployed
.955
.
inactive
Exp(B)
1 child
3 or more children
4.324
2.800
1.747
1.085
.
.629
.
.068
.336
.653
.527
.
.604
.
.417
.515
1.488
.
2.070
.
14.010
5.486
5.934
.
.599
.
1.404
.899
.
.588
.919
.
*
The reference category is: 2 children.
The values in bold are significant at the 0.05 level and underlined values are significant at the 0.10 level.
Attained level of education
Women with lower secondary education or less are 14 times more likely to have three
children or more than two children and 16.7 times less likely to be childless. In contrast, for
education levels above secondary, the number of children does not significantly depend on the
education level. The same was also observed by Muresan and Hoem (2010). The general conclusion
that lower levels of education are related to higher fertility is conform with the theory regarding the
relationship between education level and fertility, according to which higher fertility is associated
with lower education level (Hoem, Neyer, & Andersson, 2006; Muresan, 2007; Rindfuss &
Brauner-Otto, 2008).
Possible explanations for this finding in the Romanian context are related to human capital
value, investment in the quality of children and the values of the mother. The depreciation of human
capital and its associated decrease in the labour market value of the woman makes more educated
women less prone to childbearing (Bloom, Canning, Fink, & Finlay, 2009). Moreover, the shift of
focus from the number of children to their quality, corresponding to an equivalent diminution of the
economic role of children, is more pronounced for more educated women than for those with lower
education. Last, but not least, most women with lower education levels live, and probably formed
their values system, in the rural area, while more educated women are more likely to be found in
urban areas, their values system being shaped by different influences. For these reasons, as Muresan
and Hoem also note (2010), they may regard childbearing as a burden, since it is associated with
different time-spending patterns, which may imply the need for more attention to household and
family-related issues. Also, the minimum child quality level of a more educated woman is
considerably higher than that of a less educated one and this requires greater resource allocation.
Type of settlement
The odds of a woman in the urban area to have less than two children are considerably high.
Conversely, it is 1.7 times less likely that she has three or more children. This result is not
surprising, given the more traditional values of women in rural areas, which accounts to a great
extent for the predominance of higher birth parities in these areas. Also, the time spending pattern in
the urban area differs from the one in the rural area. Moreover, there are increased opportunities and
higher living standards associated with living in urban areas, but also greater opportunity costs. All
these aspects partly account for the parity difference between women living in the two types of
residence areas.
Activity status
The logistic regression results show that there is no significant difference between inactive
and unemployed women, regardless of parity level. On the other hand, employed women are more
likely to be childless or have one child than to have two children.
As in the case of education level, the category of employed women is mostly composed of
women from the urban area, thus being under the influence of the above described factors.
Moreover, the existence of a ‘conflict’ between the status of employed and that of mother has a
negative impact on fertility levels of these women. The fact that the desired status on the labour
market requires time and resource allocation towards training and career development delays
marriage and transition to parenthood.
There is a large body of literature dealing with employment of women and fertility (Billari &
Kohler, 2004; Brewster & Rindfuss, 2000; Caplescu et al., 2013; Engelhardt, Kögel, & Prskawetz,
2004; Kögel, 2004; Matysiak & Vignoli, 2007) and the main conclusion to be drawn from it is that
in the more traditional contexts the impact of women labour market participation on fertility is
negative, which supports the findings of the present analysis.
The profile of women, according to their number of children
Based on the results obtained, it is possible to sketch the profiles of women who are most
likely to be childless, to have one child, two children or three and more, as well as to draw some
general conclusions regarding the influence of the analysed factors on fertility. The synthetic
profiles are presented in Table 2 below.
First, women with no children are most likely to be young, not married, with at least
secondary education living in urban areas and employed (or maybe still enrolled in education,
mostly at tertiary level). They are most likely postponing childbearing in order to attain financial
stability, a certain social status (including a stable relationship) and a solid career foundation. Also,
it is not likely that many of these women will remain childless, but they will have fewer children
and will tend to invest more in their quality.
The women who have given birth to one child by the time of the interview are not
significantly different from the childless ones. They are indeed a little older and most likely
married, but their socio-economic characteristics are the same. These women may have already
achieved the desired status or believe to be close enough to it. They are more secure with regard to
their job and their labour market status. This gives them a certain financial stability, which is also
generally doubled by the presence of a partner, also employed. It is possible that the household
income level of these respondents is higher than in the case of the first group.
Table 2.
Demo-socio-economic characteristics of women according to their number of children
Characteristic
No children
Age group
Marital status
18-29 years
not married
Education level
Type of settlement
Activity status
secondary, higher
urban
active
1 child
Demographic
18-29 years
married
Social
secondary, higher
urban
Economic
active
2 children
3 or more children
30-39 years
married
35-44 years
married
secondary
rural
secondary or less
rural
inactive
inactive
On the other hand, starting with second child parity, the characteristics are likely to be
significantly different from the first two groups. On the one hand, the respondents with two children
or more are mostly aged 30 years or more, live in the rural area and thus tend to be more traditional
oriented. Also, they are most likely inactive on the labour market, taking over the responsibility of
childrearing and household tasks, which also explains their generally lower education level. Among
these women, the ones with three children or more are likely to have the lowest education level and
to be older.
In conclusion, the demographic, social and economic characteristic analysed have influence
on the number of children a woman has, but to various degrees and in different ways. The
demographic characteristics tend to have an overall positive influence, a higher age and marriage
being associated with more children born to those women. Social characteristics have a generally
negative impact, with fertility decreasing with each further education level attained and being lower
for urban areas than for rural ones. Finally, the economic factor considered, namely status on the
labour market, suggests that fewer children are born to active women than to the inactive ones.
Moreover, the complex relationship between all these factors generates a multitude of combinations
leading to a diverse range of fertility levels.
The Theory of Planned behaviour as a framework for studying fertility intentions
Having studied the characteristics of women who have children, it is interesting to take the
analysis one step further and analyse intentions to have a child using the framework of the Theory
of Planned Behaviour (TPB).
The TPB is the most used framework in the category of behavioural models (Morgan &
Bachrach, 2011). It was developed by Fishbein and Ajzen in the 1970s under the name of Theory of
Reasoned Action (Barber, 2011). The main assumptions of the TPB are that intention is a strong
predictor of behaviour and intention may be assessed by evaluating general attitudes, beliefs and
preferences.
In demography, fertility is seen as the result of rationally taken decisions, based on the
assessment of costs and benefits. This, however, does not imply that rational behaviour in the sense
of economic rationality is required in order to work within the TPB framework (Ajzen, 2011;
Klobas, 2011; Liefbroer, 2011; Philipov, 2011). As both Ajzen (2011) and Philipov (2011) point
out, beliefs are subjectively held information, possibly even incomplete and/or biased, but the TPB
is not concerned with the process through which the individuals arrive at their beliefs, so whether
this is a rational process or not does not affect the results obtained. What matters is how these
beliefs shape the attitudes, norms and perception of behavioural control with which the TPB
operates, thus also the intention to perform the behaviour.
Moreover, the TPB seems to constitute a useful heuristic framework even if intention is not
considered, since the model would still encourage researchers to analyse behaviour with regard to
the influence of attitudes, norms and (perceived) behavioural control (Billari & Liefbroer, 2007;
Liefbroer, 2005, 2011).
The greater control individuals have on their fertility, ranging from effective contraceptive
methods to fertility treatments, combined with increasing social acceptance of choices regarding
fertility renders necessary the understanding of how decisions about childbearing are made (Klobas,
2011) and the impact these decisions have on fertility patterns. Under these circumstances, the
occurrence of an unintended birth is more likely due to ineffective actual control (Barber, 2011;
Philipov, 2011).
TPB gives best results with short term intentions, since they are stable, which is why they
allow for a more accurate estimation of their realisation. Also, unlike the long-term intentions, their
realisation may be assessed easier and it brings valuable information about contemporary
childbearing decision-making and its subsequent behaviour.
For example, using data from a two-wave panel in four countries, Spéder and Kapitány (2009,
2012) analysed childbearing intentions and their subsequent realisation and were able to classify the
respondents into three categories. The first category comprised people who intended to have a child
at the moment of the first wave and they gave birth to one until the second interview. They were
called ‘intentional parents’. A second category was formed by the ‘postponers’, namely those who
initially declared they intend to have a child in the two years following the first interview, failed to
do so and declared the same intention at the second wave as well. The last category was that of
‘abandoners’, who intended to have a child at the time of the interview or during the subsequent two
years, failed to translate their intention into behaviour and declared no such intention at the second
interview.
To have or not to have a child? Factors determining the intention to have a child on the short
term
The intention to have a child is influenced by a varied range of factors of demographic,
economic, social, psychological or cultural nature. Using the logistic regression these factors may
be analysed within the TPB framework in order to obtain the profile of women who are most likely
to intend to have a child on the short term (three years).
Besides the determinants in the three categories used for analysing fertility, four other
variables were added. First, the attitude a woman has towards her having a birth in the period
considered, her perception about the attitude of her significant others (partner, parents and friends),
which will be referred to as (subjective) norm, and the influence she perceives from external factors
(economic situation, health, availability of childcare etc.). These were categorised as psychological
factors. Secondly, her contraceptive behaviour, which was introduced as behavioural factor, its role
being to determine whether the behaviour of the woman is in accordance to her intention.
In order to see which factors and to what degree they contribute to the formation of short-term
childbearing intention, the data was analysed using logistic regression. The significant results are
presented in Table 3 below. The model is well fitted to the data and it has a correct classification
rate of 89.3%, with reasonably high percentages for each of the two categories.
Table 3.
Significant odds-ratios of women to intend to have a child in the near future depending on
demographic, social, economic, psychological and behavioural factors
Exp(B)
Demographic factors
Number of children (ref.=no children)
1 child
.163
2 children
.025
3 or more children
.094
Age group (ref. 18-24 years)
25-29 years
.929
30-34 years
.571
35-39 year
.178
40-44 years
.099
Psychological factors Exp(B)
Attitude (ref.=positive)
neutral
.274
negative
.019
Subjective norm (ref.=positive)
neutral
.205
negative
.054
Behavioural factors Exp(B)
Using contraception (ref.=no)
yes
.408
Values in bold are significant at the 0.05 level.
The first thing to be noted is that social and economic characteristics of the respondent have
no significant impact on her intention formation process, and neither does the perception of
respondents regarding the influence of external factors. Also, the marital status, which exerts an
important influence on the number of children, looses importance when it comes to intentions. As
mentioned earlier, it is important to make a distinction between intention and behaviour, both when
it comes to intention to obtain a certain outcome, such as having a child, and intention to behave in
a certain way in order to obtain the intended outcome. Further, the focus will be on the significant
results obtained.
Number of children
The odds of a woman intending to have a child decrease with the number of children she
already has. Thus, it is most likely that a childless woman intends to have a child, while women
who already gave birth once are 6.1 times less likely to intend to repeat the experience during the
three years following the interview (2005-2008). Given that the data indicate 1-2 children as a
norm, with a bias towards the lower end, it is not surprising that mostly women with no children are
the ones who intend to have one on the short term.
Age of the respondent
The second demographic factor that impacts fertility intentions is the age the respondent had
at the time of the interview. The odds that a respondent aged 35 years or more intends to have a
child in the near future are significantly smaller than those of a younger woman. Intentions of
women younger than 35 years do not seem to be significantly different, regardless of the age group
they belong to. Therefore, it may be assumed that voluntary childlessness is not spread among
women in Romania in 2005, women manifesting intentions of childbearing for the short term until
the age of 29, and to a lesser extent, even before 35 years. If women in the third group most likely
already have at least one child, women in the first age group are probably childless, while among
women in the second group are both women who have children, and women who do not. This
supports the 1-2 children norm assumption.
Attitude towards having a birth in the next 3 years
Intention to have a child in the short-term is strongly dependent on a positive attitude of the
woman towards her having a birth, as a woman with neutral attitude is 3.6 times less likely to
express an intention to have a child, while women who believe a birth in the near term will have a
negative impact on their lives are 53.6 times less likely to intend to obtain such an outcome. These
results underline the relationship between intentions and the process of their formation. However, it
is not the purpose of the present analysis to go into further details regarding this issue. Thus, it
suffices to say that, given the strong predictive power of intentions on behaviour (Golovlyanitsina,
2007; Liefbroer, 2005, 2011; Philipov, 2009, 2011; Spéder & Kapitány, 2009, 2012), the attitude a
woman has towards the impact a possible short term birth would have on her life is an important
factor in the decision making process.
Attitude of the significant others towards the woman having a birth in the next 3 years
The results obtained are similar to those for the woman’s own attitude, namely women most
likely to express an intention for short-term childbearing are those who perceive a positive attitude
from her significant others. In other words, if the woman feels she has the support of her partner,
her parents and her friends, she is likely to form an intention to have a child in the near future. Also,
is it also possible that a perception of positive norm exerts certain pressure on the woman, thus
leading to the same intention, but for different reasons. An interesting aspect to be noted here is
that, although subjective norm plays an important role in the intention formation process, it is much
less influential than the impact a woman believes birth will have on her life.
Use of contraception
As expected, women using contraceptive means are 2.5 times less likely to express an
intention of childbearing. However, aspects relating to planning of a birth, especially for issues
related to the type of contraception used, need to be considered here. There is a large share of
women who use contraception among those who declared intention of childbearing in the short
term. However, although the analysis did not focus on the type of contraception to which women
resort to, the database does allow for studying contraception from this perspective. As may be seen
in Figure 1, most women who are not using contraception want to have a child as soon as possible,
while among the others, the most frequently used methods are condoms and pills. With the
exception of oral contraception, all other methods allow for conception theoretically immediately
after stopping to use them (the safe period method and withdrawal even pose the risk of pregnancy
while using them).
Figure 1.
Distribution of women who intend to have a child by desire to have a child at the time of the
interview and contraceptive means used
other
wants baby now
withdrawal
not sure if wants baby now
intra-uterine device
does not want baby now
safe period method
12.8%
pills
13.3%
condom
17.1%
not contracepting
0.0%
7.6%
11.1%
16.7%
42.7%
10.0%
20.0%
16.0%
30.0%
40.0%
50.0%
60.0%
70.0%
Therefore, the fact that there are women in the sample who declared they intend to have a
child during the next 3 years and who use contraception, their current behaviour is not likely to have
a negative impact on acting towards having a child. In other words, the fact that these women were
resorting to contraception at the time of the interview does not hinder the odds that they will
transpose their intention into practice.
Profile of the respondents according to their intention to have a child in the short-term
Starting from the results obtained, the profile of women who intend to have a child in the 3
years following the interview may be drawn. Thus, the women most likely to express such an
intention are young, aged up to 35 years, but most likely in their 20s, and with no children. They
believe a birth will bring benefits to her life in the sense of enhancing her joy and the satisfaction
she gets from life, of improving the relationship with her partner and her parents, but also adding
value to her social status in a context where children are still valued. Furthermore, women intending
to have a child on the short term feel that they benefit from the support of her significant others,
thus being able to count on their help with the child, once it is born.
The relationship between their stated intention and their actual behaviour regarding
contraception does not suggest, in the case of women resorting to contraceptive means, an
incompatibility between the two. Moreover, it is less likely that they are resorting to such measures.
Final remarks
Qualitative studies made on the intention to have children indicate a strong detachment from
the childless model in more traditional countries, such as Poland (Matysiak & Mynarska, 2010;
Mishtal, 2009; Mynarska, 2009), while for countries more advanced on the path of the ‘Second
Demographic Transition’, the situation is different, but there are also various models (Brachet,
Letablier, & Salles, 2010; Salles, Rossier, & Brachet, 2010).
The results of the present analysis indicate that Romanian behaviour is closer to that in
Poland, rather than in the countries more advanced on the path of the Second Demographic
Transition. The only characteristic that has a significant impact both in the number of children, and
on the intention of a woman to have a child is the age group she belongs to. The results obtained for
both analyses are in accordance and support each other: younger women are more likely to express
childbearing intentions, while older women are more likely to have more children. This conclusion
is neither new, nor outstanding, but rather predictable and hardly requiring further explanations.
On the other hand, the differences between the sets of factors that have significant influence
on the number of children and on the intention to have a child may lead to important conclusions
regarding the pronatalist measures that could be taken in order to avoid significant damage to the
age structure of the population and irreversible population decline (Lutz, Skirbekk, & Testa, 2006).
Such areas should target promotion and stimulation of family as the key agent in the society and the
economy, while decreasing uncertainty. Also, the emerging trends regarding demographic
behaviour (postponement of marriage and childbearing, increasing time spent in education, greater
desire to have a career etc.) should not be fought, but integrated into the system through adaptation
and by finding solutions that would make them simulative, rather than negative factors.
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