Certain Aspects of Family Policy Incentives for Childbearing—A Hungarian Study with an International Outlook

Abstract

Decreasing trends in birth rates in developed countries during the past decades, which threaten the sustainability of their populations, raise concerns in the areas of employment and social security, among others. A decrease in willingness to bear children has been examined in the international literature from several (biological, socio-cultural, economic, and spatial, etc.) aspects. Among these, the question of the effectiveness of fiscal incentives has been raised, with arguments that these are positive, but not significant, to birth rates; our study also concludes this. In Hungary, from 2010 onwards, the government has introduced very high tax allowances for families and, from 2015, has provided direct subsidies for housing purposes, all within a framework of a new family policy regime. This paper presents an evaluation of family policy interventions (e.g., housing support, tax allowances, other child-raising benefits), with the conclusion that fiscal incentives cannot be effective by themselves; a sustainable level of birth rates can only be maintained, but not necessarily increased, with an optimal design of family policy incentives. By studying the Hungarian example of pro-birth policies there is shown to be a policy gap in housing subsidies.

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sustainability
Article
Certain Aspects of Family Policy Incentives for
Childbearing—A Hungarian Study with an
International Outlook
Judit Sági 1, * and Csaba Lentner 2, *
1Budapest Business School, University of Applied Sciences, H-1149 Budapest, Hungary
2National University of Public Service, H-1083 Budapest, Hungary
*Correspondence: Sagi.Judit@uni-bge.hu (J.S.); Lentner.Csaba@uni-nke.hu (C.L.);
Tel.: +36-30-2211408 (J.S.); +36-70-2877728 (C.L.)
Received: 7 September 2018; Accepted: 29 October 2018; Published: 31 October 2018


Abstract:
Decreasing trends in birth rates in developed countries during the past decades, which
threaten the sustainability of their populations, raise concerns in the areas of employment and
social security, among others. A decrease in willingness to bear children has been examined in the
international literature from several (biological, socio-cultural, economic, and spatial, etc.) aspects.
Among these, the question of the effectiveness of fiscal incentives has been raised, with arguments
that these are positive, but not significant, to birth rates; our study also concludes this. In Hungary,
from 2010 onwards, the government has introduced very high tax allowances for families and,
from 2015, has provided direct subsidies for housing purposes, all within a framework of a new
family policy regime. This paper presents an evaluation of family policy interventions (e.g., housing
support, tax allowances, other child-raising benefits), with the conclusion that fiscal incentives cannot
be effective by themselves; a sustainable level of birth rates can only be maintained, but not necessarily
increased, with an optimal design of family policy incentives. By studying the Hungarian example of
pro-birth policies there is shown to be a policy gap in housing subsidies.
Keywords:
family and home subsidies regime; birth rate trends; pro-birth fiscal incentives; Hungary
1. Introduction
Family patterns have changed substantially over the past 50 years, with the shift in mentality
about childbearing. The 1960s ended a long-lasting period called the “Golden Age of the Family”,
when marriages and childbearing were common at a young age, and the incidence of divorces and
non-traditional family forms was very low. At present, a wide variety of family forms co-exist [
1
],
marriage and parenthood have been delayed to more mature ages, or not entered at all, and marital
relationships have become less stable even among couples with children [
2
]. Statistically, in nearly
all European countries, fertility rates have declined well below the necessary level for population
replacement (replacement level fertility is 2.1 children per woman on average). These trends may raise
concerns over the sustainability of economic growth in low birth-rate countries [
3
]. This issue may
call for a modernization of family-support policies involving a broad spectrum of state interventions
related to many aspects of the lives of women, men, couples, parents, and children [
4
], as well as the
reconciling of work and family responsibilities [5].
This article aims to contribute substantially to the empirical literature on the effect that pro-birth
policies with tax related tools might exercise on fertility in the example of one of the Central European
countries, Hungary. In evaluating family policy interventions, the authors hypothesize that fiscal
incentives may improve birth rates, but not increase them enough to reach the desired sustainable level.
Sustainability 2018,10, 3976; doi:10.3390/su10113976 www.mdpi.com/journal/sustainability

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The paper is structured as follows. Section 2summarises the methodology of the study, which
was mainly composed of the literature review and the statistical methods related to the authors’ own
surveys. Section 3depicts the demographic trends of decreasing birth rates, and the causes behind
these trends, based upon the literature. Regarding the pro-birth fiscal incentives, the example of
the Hungarian family support regime has both the tax allowance and the home subsidy element, as
described in Section 4.1 of this study. Descriptions of data from the survey are provided in Section 4.2.
The conclusions (i.e., that the home setup support scheme positively influences young adults’ desire to
have children, but does not cause a significant change in actual childbearing) are included in Section 4.3.
Finally, Section 5provides a summary of the conclusions.
2. Methods
To illustrate the decreasing fertility rates across Europe, descriptive statistics have been employed,
i.e., time series of the total fertility rates, and data about changes in age structure. From these data,
the authors examined the income and housing determinants of childbearing, as pointed out in the
literature [6], and connected them to the use of fiscal policy incentives.
The Hungarian study shows how pro-birth incentives were added to the tax and housing matters
of families with children. Additionally, the authors examined whether the intentions of young people
reaching the age of peak fertility are potentially changed by the existence of the pro-birth housing
support scheme in Hungary. A first questionnaire-based survey carried out by the authors involved
1332 students in higher education. Then, in a repeated questionnaire in the first few months of 2018,
the authors asked 15,700 students studying at higher education in the 10 most prominent university
campuses across the country. To analyse the answers, descriptive statistics and the Chi-Square Test
of independence have been employed for the relationship between planned inhabitancy and the
inclination for having children. Statistically, Pearson Chi
2
is for testing if two categorical variables are
related; and a measure that does indicate the strength of the association is Cramer V. It is important
to note though, that the correlation coefficient is used for (nearly) linear stochastic relationships.
The Pearson Chi
2
is not suitable for describing the relationship between values on a more complex
function curve. This method converts metric variables to nominal variables to examine if a relationship
existed between housing costs and childbearing intentions.
3. Drives of Fertility
3.1. Decreasing Birth Rates and the Problems They Raise
Population trends in European countries are described by low (below replacement level) rates of
fertility, as a long-term result of socio-demographic trends that are examined below.
3.1.1. Trends in Total Fertility Rates
The most commonly used fertility indicator is the total fertility rate. In a specific year, it is defined
as the total number of children that would be born to each woman if she were to live to the end of her
child-bearing years and give birth to children in accordance with the prevailing age-specific fertility
rates. It is calculated by totalling the age-specific fertility rates as defined over five-year intervals [7].
This indicator is measured in children per woman and reached a value of 2.5 in 1960 for the EU
(28 countries) average, with a corresponding figure of 1.6 in 2015 [
8
]. (Hungary reached a total fertility
rate of 2.0 in 1960, with a figure of 1.5 in 2015, respectively. Figure 1shows the trends.) The reasons for
the dramatic decline in birth rates during the past few decades include postponed family formation
and childbearing and a decrease in desired family sizes. Current levels of fertility rates across Europe
do not ensure the replacement-level fertility of 2.1 children per woman on average [9].

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Figure 1. Fertility rates, total, children/woman, 1960–2016.
Childlessness also contributes to the decrease in average birth rates (the decline in fertility) in
these countries. It has been relatively low in Central and Eastern European countries in the past
century, but has increased among women born in the late 1960s and early 1970s. By comparison, in
Western European countries, the rate of childlessness climbed to 20% on average during the past
decades, then has stabilized at this level, but is likely to continue rising in Southern Europe, especially
in Italy and in Spain [10]. Women in southern Europe are on track to have the highest levels of
childlessness in Europe, at around 25% [11]. However, the trends in childlessness are difficult to
predict due to socio-cultural changes in behaviour.
3.1.2. The Problem of Aging Societies, as Reflected by the Population Pyramid
According to the United Nations Demographic and Social Statistics, the estimated percentage
for the European population at the age of 65 or above was 17.9 in 2016 [12]. Meanwhile, the percentage
of the population at the age of 14 or below was only 15.8. These figures are highlighted from the
perspective of welfare and social security issues, which result from the higher percentages of the
elderly [13]. Alongside the potentially weak family savings for old age, which are partly hindered by
legal constraints on investing in many countries [14,15], governments face the unsolved issue of
funding social security systems for the forthcoming decades [16,17].
Alongside the increase in the share of older persons in the total population, the proportion of
people of a working age in the European countries is shrinking while the relative number of those
retired is expanding [17]. The population pyramid, showing the age structure of the population by
sex, is transforming due to the above birth and population trends. The pyramid in general is a
graphical illustration about the distribution of various age groups for each gender in a geographical
area, such as the European Union, a country, or a region. It is also called the age structure diagram
or the age-sex pyramid, which for Hungary, displays a contracting shape (see Figure 2). Out of the
total 9,797,561 inhabitants, the portion of middle-age and elderly persons is higher than of younger
people, therefore, the population pyramid is depicting an aging population [19]. In particular, there
are relatively more persons at the ages of 60–65, and 37–42, which has resulted from a government
decree prohibiting abortions during the 1950s (from 1950 till 1956).
1.20
1.40
1.60
1.80
2.00
2.20
2.40
2.60
2.80
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
European Union (28 countries) Hungary
Figure 1. Fertility rates, total, children/woman, 1960–2016.
Childlessness also contributes to the decrease in average birth rates (the decline in fertility) in
these countries. It has been relatively low in Central and Eastern European countries in the past century,
but has increased among women born in the late 1960s and early 1970s. By comparison, in Western
European countries, the rate of childlessness climbed to 20% on average during the past decades,
then has stabilized at this level, but is likely to continue rising in Southern Europe, especially in Italy
and in Spain [
10
]. Women in southern Europe are on track to have the highest levels of childlessness
in Europe, at around 25% [
11
]. However, the trends in childlessness are difficult to predict due to
socio-cultural changes in behaviour.
3.1.2. The Problem of Aging Societies, as Reflected by the Population Pyramid
According to the United Nations Demographic and Social Statistics, the estimated percentage for
the European population at the age of 65 or above was 17.9 in 2016 [
12
]. Meanwhile, the percentage
of the population at the age of 14 or below was only 15.8. These figures are highlighted from the
perspective of welfare and social security issues, which result from the higher percentages of the
elderly [
13
]. Alongside the potentially weak family savings for old age, which are partly hindered
by legal constraints on investing in many countries [
14
,
15
], governments face the unsolved issue of
funding social security systems for the forthcoming decades [16,17].
Alongside the increase in the share of older persons in the total population, the proportion of
people of a working age in the European countries is shrinking while the relative number of those
retired is expanding [
18
]. The population pyramid, showing the age structure of the population
by sex, is transforming due to the above birth and population trends. The pyramid in general is a
graphical illustration about the distribution of various age groups for each gender in a geographical
area, such as the European Union, a country, or a region. It is also called the age structure diagram
or the age-sex pyramid, which for Hungary, displays a contracting shape (see Figure 2). Out of the
total 9,797,561 inhabitants, the portion of middle-age and elderly persons is higher than of younger
people, therefore, the population pyramid is depicting an aging population [
19
]. In particular, there
are relatively more persons at the ages of 60–65, and 37–42, which has resulted from a government
decree prohibiting abortions during the 1950s (from 1950 till 1956).

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Figure 2. Population number of Hungary by sex and age, 1 January 2017.
3.2. Causes behind the Low Levels of Birth Rates
Decreasing trends in fertility in the scientific literature are linked to biological, socio-cultural,
economic, and spatial factors. The review of them is summarized below.
The focus of the theories that explore the influence of fertility variables is unquestionably the
biological ability of a woman to have a child, which leads to conception, or even failure. The question
of how a marriage (family) provides a positive, supportive environment for childbearing has been
raised by many research studies [20,21]. It has been noted that age patterns of natural marital fertility
are not primarily affecting childbearing [22]. Instead, the frequency of sexual intercourse and birth
control/contraception, and the age patterns of natural marital fertility together are recognized as the
proximate determinants of fertility [23,24]. In the socio-cultural models of childbearing, the supply
of births is raised from the natural rate of fertility (defined as the potential number of births without
contraception and abortion), and is constrained by family planning, that is, the demand for births
[25,26].
During the period of the first demographic transition in the 19th and 20th centuries, fertility rates
decreased even though the proportion of people living in marriages increased (people got married at
younger ages, divorce rates were low, and re-marriage rates were high). Childbearing was common
in marriages; parents had their first child at a younger age, but typically did not have any further
children. The single-child family model became the norm in society, alongside family values, such as
household income, working and housing conditions, healthcare, and schooling [27].
The spread of contraception, the delayed marriage of women, and the deterioration of fertility
indicators characterized the second demographic transition period [28], which started after the
Second World War, and came into full swing with the sexual revolution of the 1960s. The proportion
of people living in marriages decreased, people got married later, divorce rates became high, and
remarriage rates were low. Although the proportion of unexpected pregnancies among teenagers
increased, fertility declined, mainly due to the postponement of childbearing [29]. Forms of non-
marital cohabitation have spread, and the proportion of children born out of wedlock jumped. Family
values were replaced by individual values, and male-female roles became more uniform [30].
The economic theories of fertility decline [31] have added the time and opportunity cost
variables, as well as the mother’s income and labour market participation [32] to the models of
childbearing. Within the economics of households, the available resources of labour, capital, and time
are allocated to childbearing as well, in accordance with its utility measures [33,34]. However, socio-
economic factors are added as explanatory variables to these models, admitting the positive feedback
of society in the birth of the first child and especially in the case of further childbirth [35,36].
Figure 2. Population number of Hungary by sex and age, 1 January 2017.
3.2. Causes behind the Low Levels of Birth Rates
Decreasing trends in fertility in the scientific literature are linked to biological, socio-cultural,
economic, and spatial factors. The review of them is summarized below.
The focus of the theories that explore the influence of fertility variables is unquestionably the
biological ability of a woman to have a child, which leads to conception, or even failure. The question
of how a marriage (family) provides a positive, supportive environment for childbearing has been
raised by many research studies [
20
,
21
]. It has been noted that age patterns of natural marital fertility
are not primarily affecting childbearing [
22
]. Instead, the frequency of sexual intercourse and birth
control/contraception, and the age patterns of natural marital fertility together are recognized as the
proximate determinants of fertility [
23
,
24
]. In the socio-cultural models of childbearing, the supply
of births is raised from the natural rate of fertility (defined as the potential number of births without
contraception and abortion), and is constrained by family planning, that is, the demand for births [
25
,
26].
During the period of the first demographic transition in the 19th and 20th centuries, fertility rates
decreased even though the proportion of people living in marriages increased (people got married at
younger ages, divorce rates were low, and re-marriage rates were high). Childbearing was common
in marriages; parents had their first child at a younger age, but typically did not have any further
children. The single-child family model became the norm in society, alongside family values, such as
household income, working and housing conditions, healthcare, and schooling [27].
The spread of contraception, the delayed marriage of women, and the deterioration of fertility
indicators characterized the second demographic transition period [
28
], which started after the Second
World War, and came into full swing with the sexual revolution of the 1960s. The proportion of people
living in marriages decreased, people got married later, divorce rates became high, and remarriage rates
were low. Although the proportion of unexpected pregnancies among teenagers increased, fertility
declined, mainly due to the postponement of childbearing [
29
]. Forms of non-marital cohabitation
have spread, and the proportion of children born out of wedlock jumped. Family values were replaced
by individual values, and male-female roles became more uniform [30].
The economic theories of fertility decline [
31
] have added the time and opportunity cost variables,
as well as the mother’s income and labour market participation [
32
] to the models of childbearing.
Within the economics of households, the available resources of labour, capital, and time are allocated to
childbearing as well, in accordance with its utility measures [
33
,
34
]. However, socio-economic factors
are added as explanatory variables to these models, admitting the positive feedback of society in the
birth of the first child and especially in the case of further childbirth [35,36].

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In today’s literature on fertility, studies focus on regional factors, revealing the fact that in the
suburban districts of cities and, especially, in rural areas, fertility rates are higher [
37
,
38
]. In this
context, the living area (green residential areas, playground, nursery and kindergarten, medical
services) influences the parents’ decision on childbearing, and childbearing on their selection of
home [
39
]. The spatial differences may have a considerable effect on childbirths, especially in the case
of the second and the third child [40].
4. Pro-Birth Fiscal Incentives: Policy Design and Perception
The governmental policy responses differ across European countries, and, more importantly,
throughout time. There is a dynamic pattern to how these countries design their family policy
instruments, and how fast they respond to the decrease in fertility rates. After the demographic
tendencies had been traced, most of the EU countries introduced active family policy measures to
initiate childbearing and provide financial help for child raising.
In a narrow sense, these family policies can be interpreted as the total set of government subsidies
and services with the purpose of supporting families who raise children. These tools perform as
exogenous variables when decisions are made on childbearing or postponement, in relation to changes
in the cost of childrearing [
41
]. In this respect, the cash subsidies and housing supports represent direct
forms of policy tools, and the tax allowance is an indirect form.
Alongside the increase of a household’s disposable income, the willingness to have children
can be depicted by a U-shape curve [
42
]. This means that in lower income levels, the direct policy
incentives exercise a welfare effect on the household, possibly resulting in not having or postponing
to have a second or an additional child. In contrast to this, in higher income level households, the
indirect policy tools have a positive feedback on subsequent births. In general, pro-birth policies have
no measurable effect on childlessness, but a minor (significant) effect on the number of children borne
by maternal women [43].
The latest figures show that family incentives are substantial in most EU countries, as households
with children have a lower net personal average tax rate than the same household type without
children, and the difference is considerably more pronounced for a single worker at a lower level of
wage income [
44
]. These fiscal incentives are supplemented by different sources of parental support,
aimed at enhancing parenting skills and practices to address children’s physical, emotional, and social
needs [45].
4.1. Hungarian Policy
The GDP per capita in Purchasing Power Standards (PPS) in Hungary was HUF 6,297,920
(EUR 19,681) in 2016 [
46
]. The minimum regional average in the country was HUF 4,000,000
(EUR 12,500), and the maximum was HUF 9,536,000 (EUR 29,800) [
47
]. Based on these figures,
the budgetary subsidies exercise a substantial impact on families’ income.
On 1 January 2011, a new family tax regime was introduced in Hungary [
48
]. The essence of this
regime has common roots with Western European regimes and applies tax allowances. In contrast to
tax credits, tax allowances reduce the consolidated tax base of the taxable principal wage earner on
a monthly basis. The amount of the benefit depends on the number of dependent children.
The amount of the family tax allowance increased substantially in 2011: Families raising one or
two children enjoyed a monthly benefit of HUF 62,500 (approx. EUR 200) per child, while families
with three children could retain a monthly sum of HUF 206,250. The benefit considerably reduced
families’ tax burden: Compared to 2010, the net (after-tax) income of an average family with children
increased by 10–20% and the majority of families with multiple children were totally exempt from
personal income tax payments in 2011.
In 2012, the family tax allowance did not change compared to the previous year. However,
the amount of payable tax decreased due to changes in the calculation of the tax base. This tax
reduction mainly affected families with one or two children, and high-income families with more

Sustainability 2018,10, 3976 6 of 16
children. To ensure fairness, a reduction was required in the differences between the respective family
allowances in the personal income tax regime in 2015. Since 2016, the tax benefit for families with two
children has increased. As the allowance, which reduces the consolidated tax base, is increasing year
by year, disposable income has grown by HUF 20,000 per child by 2018. This tax allowance is also
granted to pregnant mothers from the 91st day of pregnancy until the birth of the child.
By 2013, the fiscal budget position had stabilized, and Hungary became exempt from the excess
deficit procedure as the fiscal deficit had decreased below 3% of the GDP. With the continuous increase
of GDP [49], the government could implement much larger amounts of further family incentives.
In 2015, the family social contribution allowance was added to the family tax allowance. This is
granted if the consolidated tax base is eligible only for a part of the family allowance. While the family
tax allowance reduces the tax base and the tax liability, the social contribution allowance reduces the
payable social contribution. Eligibility for family allowances does not alter social security benefits
(pension, healthcare, transfers, etc.) nor the amount of benefits of the insured person. The extension of
the benefit to individual contributions mainly affects families with three or more children and single
parents with two children.
Changes in family benefits since 1 January 2016 include a decrease in the personal income
tax rate from 16 to 15%, and an increase in the childcare allowance for families with two children.
Since 1 January 2017, the personal income tax rate has remained at 15%, and the rate of social security
contributions at 18.5% (calculated as a total of contributions to the pension fund at 10%, to healthcare
at 7%, and to the labour market fund at 1.5%).
In 2017, the family tax allowance was HUF 66,670 per month for families raising one child (this
sum reduces the personal income tax payable by HUF 10,000). The tax allowance is HUF 100,000 per
month per child in the case of two dependent children, and this sum is equal to a HUF 15,000 per
child decrease in the tax payable. Finally, the tax allowance is HUF 220,000 per month per child in the
case of a minimum three dependent children, which reduces the tax payable by HUF 33,000 per child.
Consequently, the personal income tax regime grants proportionally more benefit to families raising
two, three, or more children. Moreover, from 2017, family benefits have been extended to the spouses’
close relatives if they live in the same household.
Besides the wide range of tax benefits, child-related housing subsidies were introduced in 2015.
The authors proved in a former study [
50
] that in addition to tax benefits, housing subsidies may also
positively influence childbearing, and for that reason, they provided an overview of the housing market
trends since the turn of the millennium. This is confirmed by an increase in the number of applications
and contracts for housing: Between July 2015 and September 2017, 59,042 applications were approved
for family and housing subsidies and for interest subsidies in a total of HUF 161,991 million. Up to
30 September 2017, 42,443 contracts were signed in a total amount of HUF 131,064 million.
In 2016, approximately one-third (31%) of the applications included commitments to having
a child in the near future (the requirement is that at least one of the spouses must be younger than
40; in most cases, this condition is met by the mother). The remaining two-thirds of the applications
referred to children already born, up to the age of 25 (mostly by couples under the age of 50).
Data are available for the year, 2016, for the types of subsidies (for the first, second, or third child).
Of the contracts for housing subsidies signed in 2016, 69% of them referred to children already born,
and 31% to planned children. Regarding the latter figure, it is worth mentioning that the percentage
is lower (29%) in the case of newly built flats, and is higher (33%) in the case of resold flats. The
ratio of commitments to have additional children is the lowest (24%) in applications for HUF 10
million to subsidize new homes, with 62% committed to having one child, 26% two children, and
12% three children. Considering the resold flats, 58% of the beneficiaries made commitments for one
child, and 42% for two or more children in their applications for housing subsidies. Altogether, about
7000 of the contracting families have made a commitment to have about 10,000 children in the near
future; this figure totals approximately 8000 families with 11–12,000 children for 2016. In summary,
each family has committed to have an average 1.4 children within a six-year period.

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The budgeted figures for family subsidies were HUF 277.0 billion (approx. EUR 870 million)
and HUF 316.0 billion (approx. EUR 1000 million) in 2017 and 2018, respectively. These figures also
include marital allowances, withdrawn in the amount of HUF 0.5 billion and 2.2 billion in 2015 and
2016, respectively, which are predicted to have grown in the years, 2017 and 2018. Increases in subsidy
disbursements correlates with the increased tax allowances for families with two children (HUF 20,000
per month per child in 2015, HUF 25,000 in 2016, HUF 30,000 in 2017, HUF 35,000 in 2018, and HUF
40,000 in 2019, and so on). This means that subsidies for families with two children increased by
approximately one-third (31%), amounting to HUF 23 billion, from 2015 to 2016. Further growth in
family subsidies might also be expected for 2019.
4.2. Data Collection
To evaluate the long-term impact of the family and home subsidies regime on the change of the
willingness to have children among young adults, the authors conducted their own questionnaire
interviews among university students in Hungary. This survey took place in 2016 for the first time,
when 1332 students responded to the questionnaire. Then, in a repeated series of interviews in 2018,
15,700 university students took part (Table 1). Out of the total of 15,700 responders, 40% were men,
and 60% were women. In the first survey, students from one university in the capital city and one in
a provincial city participated by filling in the questionnaire; whilst the repeated survey was extended
to the 12 largest university campuses in Hungary. These 12 campuses have 174,338 full-time students
altogether (as of 2018), which account for 86.2% of the 202,300 full-time university students in Hungary.
The survey was also representative of the population of tertiary-educated young adults with potentially
high incomes (they account for 23.7% of the total population of their age group).
The first part of the questionnaire asked the gender, age, place of residence, number of siblings,
and housing situation of respondents, as well as their job experiences, to learn about some of their
demographic characteristics. To discover how respondents think about the incentive effect of family
and home subsidies on the willingness to have children, two main questions were asked: “Do you
think that the new home setup support measures will increase your desire to have children?” and
“To what extent can the currently implemented home setup scheme contribute to the acquisition or
development of the housing you expected to have?”
4.3. Results and Discussion
The authors empirically surveyed whether the subsidies alter the desire to have children among
young adults. Results from the first questionnaire survey showed that according to 73.4% of the
respondents, housing subsidies improve their willingness to have children; however, only 36.7%
answered that they would want to have more children if the subsidies remained in place. It was
concluded that housing subsidies do give a stimulus to childbearing.
The extended survey included the 20 most prominent university campuses across the country,
totalling approximately 7.8% of the total number of higher education students in Hungary. Forty five
percent of the respondents study in the capital, the rest of them study in the provinces, which represents
the geographical distribution of the Hungarian universities. The questionnaire asked if the extension
of the family and home subsidizing regime, together with the publicity it had gained, had substantially
changed the willingness to have children among this population. Statistical methods used in the
research were: Descriptive statistics, cross tabulation, and hypothesis analysis.
The results confirmed that 75% of these young adults consider the pro-birth fiscal incentives
to be useful for raising children (Table 2). However, only 20.9% (a significantly lower proportion of
respondents than in the previous survey) answered that if the subsidies remained they would want to
have more children and benefit from the home subsidy (Table 3).

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Table 1. Responders in the surveys, by university.
Name of the University (in Alphabetical Order) Location NUTS of the Location No. of Students No. of Respondents in
the First Survey
No. of Respondents in
the Repeated Survey
1. Budapest Business School Budapest, Zalaegerszeg HU101
HU223 11,316 902 1019
2. Budapest Corvinus University Budapest HU101 10,227 921
3. Budapest University of Technology and Economics Budapest HU101 19,400 1747
4. Eötvös Loránd University Budapest, Szombathely HU101
HU222 23,267 2095
5. Eszterházy Károly University Eger HU312 3554 320
6. National University of Public Service Budapest HU101 2813 253
7. Neumann János University Kecskemét HU331 2195 198
8. Óbuda University Budapest HU101 7657 690
9. Pannon University Veszprém HU213 4257 383
10. Semmelweis University Budapest HU101 9200 829
11. Szent István University Gödöll˝o HU102 7755 698
12. Széchenyi István University Gy˝or HU221 7774 430 700
13. University of Debrecen Debrecen HU321 21,089 1899
14. University of Kaposvár Kaposvár HU232 1570 141
15. University of Miskolc Miskolc HU311 5965 537
16. University of Nyíregyháza Nyíregyháza HU323 1613 145
17. University of Pécs Pécs HU231 15,679 1412
18. University of Physical Education Budapest HU101 1170 105
19. University of Sopron Sopron HU221 1660 149
20. University of Szeged Szeged HU333 17,347 1562
Total 174,338 1332 15,700

Sustainability 2018,10, 3976 9 of 16
Table 2. Perception of the pro-birth fiscal incentives in raising children: Usefulness of the incentives.
University Affirmation (%) Affirmation among
Men (%)
Affirmation among
Women (%)
1. Budapest Business School 75.3 74.7 75.7
2. Budapest Corvinus University 72.1 71.8 72.3
3. Budapest University of Technology and Economics 74.7 74.7 74.7
4. Eötvös Loránd University 73.9 72.4 74.9
5. Eszterházy Károly University 78.3 77.6 78.8
6. National University of Public Service 76.0 76.2 75.9
7. Neumann János University 75.9 71.1 79.1
8. Óbuda University 70.7 70.3 71.0
9. Pannon University 76.1 73.1 78.1
10. Semmelweis University 70.5 62.3 76.0
11. Széchenyi István University 73.8 70.8 75.8
12. Szent István University 78.3 77.6 78.8
13. University of Debrecen 73.5 72.9 73.9
14. University of Kaposvár 77.0 76.0 77.7
15. University of Miskolc 77.8 76.3 78.8
16. University of Nyíregyháza 77.4 74.4 79.4
17. University of Pécs 75.2 68.8 79.5
18. University of Physical Education 74.0 71.6 75.6
19. University of Sopron 77.0 74.5 78.7
20. University of Szeged 76.0 75.6 76.3
mean 75.0 72.8 75.9
dev 0.02049 0.03347 0.02258
Table 3.
Perception of the pro-birth fiscal incentives in raising children: Inclination to benefit from
the incentives.
University Affirmation (%) Affirmation among
Men (%)
Affirmation among
Women (%)
1. Budapest Business School 20.3 18.7 21.4
2. Budapest Corvinus University 19.9 19.6 20.1
3. Budapest University of Technology and Economics 20.4 19.5 21.0
4. Eötvös Loránd University 20.8 17.5 23.0
5. Eszterházy Károly University 20.1 19.2 20.7
6. National University of Public Service 22.0 20.8 22.8
7. Neumann János University 21.7 20.1 22.8
8. Óbuda University 22.0 18.9 24.1
9. Pannon University 21.8 20.0 23.0
10. Semmelweis University 21.7 20.5 22.5
11. Széchenyi István University 22.9 20.1 24.8
12. Szent István University 21.0 20.3 21.5
13. University of Debrecen 22.2 21.0 23.0
14. University of Kaposvár 19.5 19.7 19.4
15. University of Miskolc 21.1 20.7 21.4
16. University of Nyíregyháza 19.0 18.3 19.5
17. University of Pécs 21.0 20.7 21.2
18. University of Physical Education 22.3 20.8 23.3
19. University of Sopron 21.9 20.9 22.6
20. University of Szeged 22.5 22.1 22.8
mean 20.9 19.8 21.9
dev 0.01032 0.01317 0.01321
The results confirm the relatively high prevalence of the intention not to have or to postpone
having children, with the main reasons being difficulties in finding the appropriate partner/spouse
(40%) and the insufficient supply of child-raising benefits (pre-schooling, medical care, etc.; 38%).
Moreover, only two thirds of them intend to settle down in their home country of Hungary.
Housing prices vary across the country. In order to depict the significance of the home settlement
support, the authors considered the price levels of the locations where the university students
plan to settle down. Based on local real estate prices, these categories were set: Low-cost housing
around
€
0–625/sqm (e.g., Békéscsaba, Eger, Miskolc, Szolnok); low to middle cost housing around
€
625–1100/sqm (e.g., Debrecen, Kecskemét, Pécs, Szeged); middle to high cost housing around
€
1100–1400/sqm (e.g., Gy˝or, Kaposvár, Veszprém); and high cost housing above
€
1400/sqm (Budapest).
The heat map of Hungary by housing prices is shown in Figure 3. The authors examined the

Sustainability 2018,10, 3976 10 of 16
relationship between the price level of the planned place of settlement and the inclination to benefit
from the home settlement support (the results are shown in Figure 4).
Sustainability 2018, 10, x FOR PEER REVIEW 10 of 16
mean 20.9 19.8 21.9
dev 0.01032 0.01317 0.01321
The results confirm the relatively high prevalence of the intention not to have or to postpone
having children, with the main reasons being difficulties in finding the appropriate partner/spouse
(40%) and the insufficient supply of child-raising benefits (pre-schooling, medical care, etc.; 38%).
Moreover, only two thirds of them intend to settle down in their home country of Hungary.
Housing prices vary across the country. In order to depict the significance of the home settlement
support, the authors considered the price levels of the locations where the university students plan
to settle down. Based on local real estate prices, these categories were set: Low-cost housing around
€0–625/sqm (e.g., Békéscsaba, Eger, Miskolc, Szolnok); low to middle cost housing around €625–
1100/sqm (e.g., Debrecen, Kecskemét, Pécs, Szeged); middle to high cost housing around €1100–
1400/sqm (e.g., Győr, Kaposvár, Veszprém); and high cost housing above €1400/sqm (Budapest). The
heat map of Hungary by housing prices is shown in Figure 3. The authors examined the relationship
between the price level of the planned place of settlement and the inclination to benefit from the home
settlement support (the results are shown in Figure 4).
Figure 3. The heat map of Hungary by the real estate prices. Major industrial centres are marked by
black circles, touristic areas by brown ones, regions near to the border (close to Vienna and Bratislava)
by pink ones, and developing regions by white ones.
Figure 3.
The heat map of Hungary by the real estate prices. Major industrial centres are marked by
black circles, touristic areas by brown ones, regions near to the border (close to Vienna and Bratislava)
by pink ones, and developing regions by white ones.
Sustainability 2018, 10, x FOR PEER REVIEW 11 of 16
Figure 4. Planned inhabitancy and the inclination for childbearing, displayed by bar chart. Source:
SPSS output.
The results show that housing subsidies are perceived as beneficial among those respondents
who plan to settle down in low or low to middle price locations after graduation. In contrast, those
who plan to purchase housing in more costly locations do not intend to benefit from the housing
subsidies.
The cross-table for the planned location of settlement confirms that the respondents are more
likely to benefit from home settlement subsidies in less developed regions, where they can
presumably afford housing (Table 4).
Table 4. Planned inhabitancy and the inclination for having children, cross-table and analysis from
SPSS output.
Chi-Squared Tests
Value df Asymp. Sig. (2-Sided)
Pearson Chi-Square 8015.757 a 3 0.000
Likelihood Ratio 7615.754 3 0.000
Linear-by-Linear Association 7491.397 1 0.000
N of Valid Cases 15692
a 0 cells (0.0%) have expected count less than 5. The minimum expected count is 244.56.
The analysis verified that a correlation exists between the housing price level of the planned
inhabitancy and the respondents’ inclination for benefitting from the housing child subsidy. The null
hypothesis for a chi-square independence test is that two categorical variables are independent in
some population. In our calculations, the Pearson Chi2 test is less than 5% (the significance level
marked in social sciences); and, based on the expected values, the test was proved to be reliable.
Results from the Chi2 test were confirmed by the likelihood ratio and the significance level of the
linear by linear association. Statistically, Cramer V is a number between 0 and 1 that indicates how
strongly two categorical variables are associated. Regarding the strength of the relationship as
measured by the Cramer V (Cramer V= 0.613 p = 0.00%), in our case, there is a middle to strong
Figure 4.
Planned inhabitancy and the inclination for childbearing, displayed by bar chart. Source:
SPSS output.
The results show that housing subsidies are perceived as beneficial among those respondents who
plan to settle down in low or low to middle price locations after graduation. In contrast, those who
plan to purchase housing in more costly locations do not intend to benefit from the housing subsidies.

Sustainability 2018,10, 3976 11 of 16
The cross-table for the planned location of settlement confirms that the respondents are more
likely to benefit from home settlement subsidies in less developed regions, where they can presumably
afford housing (Table 4).
Table 4.
Planned inhabitancy and the inclination for having children, cross-table and analysis from
SPSS output.
Chi-Squared Tests
Value df Asymp. Sig. (2-Sided)
Pearson Chi-Square 8015.757 a3 0.000
Likelihood Ratio 7615.754 3 0.000
Linear-by-Linear
Association 7491.397 1 0.000
N of Valid Cases 15692
a0 cells (0.0%) have expected count less than 5. The minimum expected count is 244.56.
The analysis verified that a correlation exists between the housing price level of the planned
inhabitancy and the respondents’ inclination for benefitting from the housing child subsidy. The null
hypothesis for a chi-square independence test is that two categorical variables are independent in some
population. In our calculations, the Pearson Chi
2
test is less than 5% (the significance level marked in
social sciences); and, based on the expected values, the test was proved to be reliable. Results from
the Chi
2
test were confirmed by the likelihood ratio and the significance level of the linear by linear
association. Statistically, Cramer V is a number between 0 and 1 that indicates how strongly two
categorical variables are associated. Regarding the strength of the relationship as measured by the
Cramer V (Cramer V= 0.613 p= 0.00%), in our case, there is a middle to strong relationship between the
two variables, i.e., the price levels of the planned inhabitancy and the inclination for having children
(and, consequently, benefit from the governmental subsidy).
The statistical analysis led to the conclusion that young adults who plan to settle down in lower
housing cost locations, where they are able to have a home without bank debts, are those who wish to
benefit from the home settlement subsidising regime. From this aspect, the home settlement subsidy is
not attractive for young adults who plan to live in the more popular, higher-priced locations (e.g., in the
capital city or near to other developed industrial areas).
The results also imply that the amount of the housing subsidies is not sufficiently high to
encourage having children, especially given the fact that these young adults will seek employment
and accommodation in the more developed larger cities, where housing is becoming more and more
expensive (see Figure 5). Housing prices became volatile during the past few years in Hungary [
51
],
with the current boom destroying the effects of the housing benefits, not just in the capital (Budapest),
but also in provincial towns.
According to the national statistics, housing subsidies have had an inflationary effect on the
housing market in that housing prices have grown by approximately 4.5–5.1% per year on average,
as a result of the regulatory changes [
52
]. This contradictory effect partly destroyed the intended
purpose of the governmental policy, i.e., to ease the housing conditions of families.
Among university locations, Budapest, Gödöll˝o, Gy˝or, Kaposvár, Sopron, Szombathely, and
Veszprém Zalaegerszeg are the most popular ones, with two or three times higher housing prices than
Miskolc or Nyíregyháza. The former locations are characterised by significantly higher GDP/capita
figures, as they offer more job opportunities at multinational companies (e.g., Budapest: Shared service
centres, banks, audit companies; Gy˝or: Audi; Kecskemét: Mercedes Benz, County of Vas: GE Opel,
etc.). The housing prices are also significantly higher in the former locations, due to the increased
demand there (Table 5).

Sustainability 2018,10, 3976 12 of 16
Sustainability 2018, 10, x FOR PEER REVIEW 12 of 16
relationship between the two variables, i.e., the price levels of the planned inhabitancy and the
inclination for having children (and, consequently, benefit from the governmental subsidy).
The statistical analysis led to the conclusion that young adults who plan to settle down in lower
housing cost locations, where they are able to have a home without bank debts, are those who wish
to benefit from the home settlement subsidising regime. From this aspect, the home settlement
subsidy is not attractive for young adults who plan to live in the more popular, higher-priced
locations (e.g., in the capital city or near to other developed industrial areas).
The results also imply that the amount of the housing subsidies is not sufficiently high to
encourage having children, especially given the fact that these young adults will seek employment
and accommodation in the more developed larger cities, where housing is becoming more and more
expensive (see Figure 5). Housing prices became volatile during the past few years in Hungary [51],
with the current boom destroying the effects of the housing benefits, not just in the capital (Budapest),
but also in provincial towns.
Figure 5. House price index—annual data (2015 = 100).
According to the national statistics, housing subsidies have had an inflationary effect on the
housing market in that housing prices have grown by approximately 4.5–5.1% per year on average,
as a result of the regulatory changes [52]. This contradictory effect partly destroyed the intended
purpose of the governmental policy, i.e., to ease the housing conditions of families.
Among university locations, Budapest, Gödöllő, Győr, Kaposvár, Sopron, Szombathely, and
Veszprém Zalaegerszeg are the most popular ones, with two or three times higher housing prices
than Miskolc or Nyíregyháza. The former locations are characterised by significantly higher
GDP/capita figures, as they offer more job opportunities at multinational companies (e.g., Budapest:
Shared service centres, banks, audit companies; Győr: Audi; Kecskemét: Mercedes Benz, County of
Vas: GE Opel, etc.). The housing prices are also significantly higher in the former locations, due to
the increased demand there (Table 5).
Table 5. GDP/capita and housing prices at the locations of the universities.
NUTS 3 University GDP/Capita (PPS) in Percentage
of the EU Average, as of 2016
Avg. Housing Price per Square
Metre (in EUR)
1 EUR = 320 HUF
HU101 1, 2, 3, 4, 6, 8, 10, 18 136 1970
HU102 11 54 873
HU213 9 51 1014
80.00
85.00
90.00
95.00
100.00
105.00
110.00
115.00
120.00
125.00
2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
European Union Hungary
Figure 5. House price index—annual data (2015 = 100).
Table 5. GDP/capita and housing prices at the locations of the universities.
NUTS 3 University GDP/Capita (PPS) in Percentage
of the EU Average, as of 2016
Avg. Housing Price per Square Metre (in EUR)
1 EUR = 320 HUF
HU101 1, 2, 3, 4, 6, 8, 10, 18 136 1970
HU102 11 54 873
HU213 9 51 1014
HU221 12, 19 92 1022
HU222 4 67 758
HU223 1 51 691
HU231 17 44 722
HU232 14 41 1084
HU311 15 47 541
HU321 13 47 944
HU323 16 38 651
HU331 7 51 837
HU333 20 51 877
The results suggest that the governmental home settlement subsidies provide greater support for
young adults who plan to live and work in the less developed locations in the country. As most of the
young adults prefer to live and work in the more popular sub-regions, where the housing costs tend to
be high, the home settlement subsidies have less impact on their childbearing decisions.
5. Conclusions
As this study has shown, the decrease in childbearing and the below-replacement fertility rates
across Europe, together with the aging of the populations, have raised concerns about the financial
sustainability of the social security systems in these countries [
53
]. States are reacting to declining
fertilities by applying tax-related types of pro-birth policies, and by targeting marriage, child-raising,
and the re-entrance of women to the labour market. Fiscal expenditures are being phased into the
personal income tax regimes, and are being supplemented by parental support [54].
In the case of Hungary, the low fertility rates are attributable to changing family formation
patterns, more years spent in education, and the transformation of family models and life concerns.
The uncertainty of youth employment and the difficulty of housing opportunities appear as principal
economic factors. For this reason, the authors argue that pro-birth fiscal incentives should also
include tax allowances (income channel) and housing support (accommodation channel). The
Hungarian model embraces both of these legs, with a considerable amount of government expenditure.
This argument is the novelty of this study, since the corresponding literature mentions cash-benefit

Sustainability 2018,10, 3976 13 of 16
policies, tax policies, and maternity leave systems as the only supporting policy elements for
subsidizing families [55,56], but does not include housing support.
The authors’ surveys among young adults in higher education confirmed that low rates of fertility
are likely to remain in Hungary. Pro-birth tax incentives are perceived as fiscal stimulus for these
high-income, or potentially high-income, young adults, but—as the relevant literature concludes—this
has not changed their willingness to have children (or to have children earlier). Housing incentives
have not fulfilled their intended purpose either. The results of the authors’ own questionnaire imply
that among full-time university students between the age of 18 and 27 who are planning to set up their
own family with children, the inclination to benefit from the home settlement support highly depends
on the price level of the housing. In the more popular locations, housing prices are high enough to
discourage young adults from drawing the housing benefits (for example, in Budapest, the amount of
the housing subsidy is fully absorbed by the high housing prices).
Government intervention through the housing support system has solely influenced the demand
side of the housing market in Hungary, without regulating the supply side of them, which has
resulted in an unwanted further increase in housing prices. The authors regard this regulatory gap
in the housing market as an obstacle to encouraging families to have more children, preferably at
an earlier age.
The authors also argue that the long-term unfavourable consequences of low fertility cannot be
fully mitigated by pro-birth policies. Fiscal incentives cannot be effective on their own; a sustainable
level of birth rates can only be maintained, but not necessarily increased, with an optimal design of
family policy incentives.
Finally, the authors noted that their survey was conducted on tertiary-educated young adults in
Hungary. However, recent studies in the literature [
57
] suggest that a positive association between
women’s level of education and lifetime fertility intentions exists also on a more general country level.
The authors see opportunities in further research in this field.
Author Contributions:
The authors developed the idea for this paper together. J.S. conceptualized the analysis
and wrote the paper. C.L. contributed substantially to the analysis of results and with overall guidance of the
project. (Conceptualization, J.S.; Formal analysis, J.S. and C.L.; Writing—original draft, J.S.; Writing—review &
editing, C.L.)
Funding:
This study was funded by the Hungarian National Bank through C.L.’s participation in the PADA
Leader Expert Program.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; and in the decision to
publish the results.
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