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HOUSEHOLD ECONOMIC EXCLUSION AMONG DANISH CHILDRENEvaluating Independent and Joint Household Risk of Income Poverty and Parental Labor Market Exclusion over the Course of Childhood
STUDY PAPER 150 JUNE 2020
SIMONE NORLUND VERING JOHANSEN PETER FALLESENLAWRENCE M. BERGER MARIE LOUISE SCHULTZ-NIELSEN
Household Economic Exclusion among Danish Children: Evaluating Independent and Joint Household Risk of Income Poverty and Parental Labor Market Exclusion over the Course of Childhood
Study Paper No. 150
Published by:© The ROCKWOOL Foundation Research Unit
Address: The ROCKWOOL Foundation Research UnitNy Kongensgade 61472 Copenhagen, Denmark
Telephone +45 33 34 48 00E-mail: [email protected]://www.rockwoolfonden.dk/en
June 2020
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Household Economic Exclusion among Danish Children:
Evaluating Independent and Joint Household Risk of Income Poverty and Parental
Labor Market Exclusion over the Course of Childhood
Simone Norlund Vering Johansen
ROCKWOOL Foundation
Peter Fallesen+
Stockholm University
ROCKWOOL Foundation
Lawrence M. Berger
University of Wisconsin-Madison
Marie Louise Schultz-Nielsen
ROCKWOOL Foundation
*We are grateful to Jenn Laird, Rhema Vaithianathan, Niels Ploug, and Jens Bonke for
comments. Jarl Quitzau provided invaluable information on indicators. Previous versions
presented at the ROCKWOOL Foundation, University of Copenhagen, the PAA annual
meeting, and the Alpine Population conference. The study received funding from the
ROCKWOOL Foundation (grant 1167). Peter Fallesen would like to acknowledge additional
funding from the Swedish Research Council for Health, Working Life and Welfare (Forte
grant 2016-07099).
+Corresponding author: [email protected]. Stockholm University, Universitetsvägen
9F, SE-106 91 Stockholm, Sweden.
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Abstract
Low household income and social exclusion increase children’s risk for unsuccessful
transitions to adulthood. Yet, we know little about children’s cumulative risk of experiencing
poverty and parental labor market exclusion during childhood, and to what extent these
circumstances co-occur. Using synthetic cohort lifetables and administrative data, we estimate
annual separate and joint cumulative risks for experiencing living in a household with income
below the OECD poverty line (poverty) and living in a low-work intensity household (labor
market exclusion) for children born in Denmark from 2003-2018. Our results show that
similar children are identified by both indicators, with the largest overlap between the joint
indicator of both poverty and labor market exclusion (economic exclusion) and the income
poverty indicator. Further, considering estimates produced from poverty and labor market
exclusion measures, as well as from a combined measure, helps to demonstrate the role of
business cycle volatility in each—procyclical with respect to poverty and countercyclical with
respect labor market exclusion. Linking multiple indicators makes it easier to distinguish
long-term trends in the cumulative risk of childhood poverty and the impact of changes to
levels of welfare payments from short-term fluctuations caused by changes in income levels
due to variation in labor market tightness.
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Introduction
Exposure to economic exclusion (disadvantage) during childhood has, on average, detrimental
impacts on children’s development and later life opportunities (Dickerson and Popli 2016;
Hanson et al. 2013; Lesner 2018; Ryan et al. 2006; Sharkey and Elwert 2011). Even short
periods of deprivation can have lasting effects (e.g., Lesner 2018). Moreover, the unequal
distribution of economic exclusion risk across social groups and neighborhoods may
undermine social cohesion (e.g., Portes and Vickstrom 2011; Tolsma et al. 2009). Yet,
although international institutions and individual countries now publish annual estimates of
child poverty and social exclusion under various definitions, limited progress has been made
in understanding children’s cumulative risk of ever experiencing economic exclusion—and
different forms thereof—during childhood. Moreover, there has been limited research
documenting the extent to which particular measures of economic exclusion capture and
describe the same or different groups of children.
Distinct measures of economic exclusion produce very varying estimates of the size of
the affected population. Using the EU definition of risk of poverty or social exclusion, which
is defined as experiencing at least one of three conditions; at-risk of poverty, severely
materially deprived, or living in a household with very low work intensity, Eurostat finds that,
24.9 % of children between 0-17 years of age in the EU28 countries were at risk of
experiencing poverty or social exclusion in 2017 (Eurostat 2019). Comparatively, the OECD
(2019) finds that by their income-based poverty definition (household income below 50 % of
the national median), the EU28 countries, on average, saw 12.3 % of all children living in
poverty, with child poverty rates in the Nordic countries being lowest, at between 3.7%
(Denmark in 2016) to 9.3 % (Sweden in 2017). Across the 23 EU countries with updated child
poverty data1, the average OECD child poverty rate for 2016-2017 was 13.1%. Among US
1 Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland,
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children, 20.9 % live in OECD defined poverty, with a further 22 % living in households
close to the U.S. poverty threshold (Jiang et al. 2016). Yet, these cross-sectional statistics
provide insight only into the share of children who experience deprivation at a given point in
time; they do not provide evidence of the cumulative risk of ever experiencing it across
childhood. In addition, all measures of economic exclusion are not created equal (cf. Blank
2008; Smeeding 2017), and there exists a dearth of knowledge on the cooccurrence and
temporal dynamic of different poverty indicators across the early life course.
In this study, we estimate and compare the cumulative risk of a series of poverty
indicators across childhood (age 1-17) for Danish children for the period 2003-2018. Using
synthetic cohort lifetable methods and administrative population data, we estimate the
cumulative individual and joint risks for Danish children of living in a household with income
below the OECD defined poverty line (50 % of median household disposable income,
equivalized for family size and composition), which we refer to as income poverty, and low
work-intensity (average employment among the adults in the household being below 20 % of
full-time employment), which we refer to as labor market exclusion. The two indicators
capture income scarcity and exclusion from the labor market. Whereas only the first directly
reflects poverty, both represent marginalized household living conditions with low levels of
possibility for savings and high rates of economic exclusion. We estimate the annual
cumulative risk for the entire population of children born in Denmark, as well as conditional
on migration background. Previous work has demonstrated large ethnic/racial differences in
cumulative risk of experiencing childhood poverty (Rank and Hirschl 2001). In our study, we
distinguish between native Danes and (predominantly Nonwestern2) descendants of first-
generation immigrants to make a similar comparison.
Italy, Latvia, Lithuania, Luxembourg, Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, and
United Kingdom. 2 Nonwestern includes all countries except the EU28, Andorra, Iceland, Liechtenstein, Monaco, Norway, San
Marino, Switzerland, the Vatican State, USA, Canada, New Zealand, and Australia
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Examining both income poverty and labor market exclusion in a country such as
Denmark, with relatively generous social welfare benefits, including cash transfers, is
particularly important to understand multiple domains of disadvantaged in a wealthy country.
We show that although annual OECD child poverty rates are low by international standards,
approximately 11.5 % of children born in Denmark can expect to experience at least one year
of childhood in a household characterized by both income poverty and labor market
exclusion, with substantial heterogeneity across immigration background. Further, our
estimates indicate that, whereas the income poverty measure is sensitive to periods of rapid
changes in economic conditions combing it with the labor market exclusion measure tempers
the volatility observed in the poverty measure alone in times of rapid income change across
the population.
Our study extends the literature on childhood poverty in four ways. First, by estimating
the cumulative risk of childhood poverty and labor market exclusion for the full population in
Denmark, a country with one of the lowest levels of child poverty in the Western world, we
provide credible lower-bound estimates for the risk of ever experiencing childhood poverty
across the life course in wealthy societies. Second, by comparing the (joint and independent)
cumulative risk of economic exclusion across overlapping indicators thereof, we highlight
important pathways into first occurrence of poverty and/or labor market exclusion in
households with children present. Third, by combining the OECD poverty indicator with a
labor market exclusion indicator not directly based on household income, we demonstrate that
it is possible to disentangle cumulative risk of economic exclusion during childhood poverty
from volatility from business cycle effects on the overall income distribution. Finally, by
using synthetic cohorts, as opposed to birth cohorts, we can provide up-to-date estimates
without having to observe the same children from birth to age 18 in order to estimate their
cumulative risk of economic exclusion through age 18.
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In the next section, we discuss relevant previous work on the risk of ever experiencing
childhood poverty, as well as the strengths and limitations of current measures of economic
exclusion. We then present the Danish administrative data used in our analyses and describe
the synthetic lifetable method we use to estimate the cumulative risk. After presenting our
findings, we discuss their implications for understanding for economic exclusion from a life
course perspective and under varying definitions thereof.
Background
While there is a vast literature on child poverty throughout the world, largely due to data
limitations, there are few estimates of cumulative risk of ever experiencing childhood poverty
(see, e.g., Bradbury et al. 2009 for discussion on longitudinal data and child poverty). As a
notable exception, Rank and Hirschl (1999) provide evidence on US children’s risk of
experiencing poverty from age 1 to 17. Using data from the PSID and the US poverty line as
their poverty indicator, they estimated that 34 % of all US children would ever experience
poverty from ages 1-17, a share which far exceeded the risk of experiencing poverty at a given
point in time.
Studies on other types of adverse childhood experiences that predominantly occur in
disadvantaged households, such a parental incarceration (Wildeman 2009; Wildeman and
Andersen 2015), foster care placements (Fallesen et al. 2014; Magruder and Shaw 2008;
Wildeman and Emanuel 2014), and child maltreatment (Kim et al. 2017; Kim and Drake
2019; Sabol et al. 2004; Wildeman et al. 2014) have similarly found that far more children
ever experience such event than is suggested by annual rates. Thus, cumulative risk estimates
provide insight into the importance of considering childhood incidence (as opposed to solely
annual prevalence) when estimating rates of experiencing disadvantage. Further, comparing
annual and cumulative risk over time provides key insights into change or stability of
dynamics. For example, a declining cumulative risk of economic exclusion, coupled with a
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constant annual rate thereof, would imply that, over time, fewer children are experiencing
such disadvantage, but that those that experience them do so for longer periods.
Definitions and Measures of Economic Exclusion
Economic exclusion and poverty can be defined and measured in a substantial range of ways
(Blank 2008; No et al. 2018; Nolan and Ive 2012; Smeeding 2017). Whereas traditional
measures are predominantly based on income levels in either relative (position in a country’s
income distribution) or absolute (below an income threshold) terms, several now also consider
nonmonetary aspects of an individual’s or household’s ability to fully participate in
mainstream society. In this study, we assess economic exclusion via one indicator of (relative)
income poverty and one indicator of labor market exclusion (low parental labor market
participation, regardless of monetary income) and examine the extent to which these measures
identify overlapping populations and may inform each other. For income poverty, we rely on
the equivalized OECD poverty threshold (OECD 2019), which defines a household as being
poor if the equivalized disposable household income falls below 50 % of the annual national
median. We assess labor market exclusion via the Eurostat definition of low work intensity
(Ward and Ozdemir 2013), defined as average employment below 20 % of full-time
employment among all adults in the household age 18-59, who are capable of working
(excluding students younger than 25 from capable of working). We impose some additional
assumptions to the indicators that we describe in detail in the Data and Measures section.
These assumptions make our estimates slightly more conservative.
Income poverty
Broadly speaking, income-based poverty indicators take two forms: absolute and relative.
Poverty is typically captured at the household level. Absolute poverty implies falling below a
fixed income threshold, such as the US poverty line, which sets a cash income below three
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times the cost of a minimum food diet in 1963 (prices updated with the CPI) adjusted for
family size, the World Bank’s global “$1 a day” at PPP threshold3, and other minimum
budget or “basket of goods” type measures (see Bonke and Christensen 2016 for an example
of a minimum budget for Denmark). Relative measures define the poverty in comparison to
the income level of other members of society, or one’s place in the income distribution, most
often at the national level. The primary strengths of such relative measures are twofold. First,
they implicitly take different national contexts into account. Second, year-to-year comparisons
are easy to make without, for example, having to account for inflation or changes to “basket-
of-goods” composition.
Yet, relative measures may shift drastically if the upper half of the income distribution
shifts, either due to wage growth during periods of labor market tightness and economic
expansion, or population wide income decreases during economic retraction. Such business
cycle driven changes in relative poverty may cause fluctuations in the share of the population
found to experience relative poverty, such that the poverty rate rises during economic
expansions and declines during recessions. As such, increases in poverty may not be tightly
linked to changes in material scarcity (e.g., a household’s resources and purchasing power
may hold constant, but its poverty status may change because other households gained or lost
income), thereby posing a challenge to properly identifying ‘poor’ households in a way that
consistently reflects their own resources and changes therein (cf. Sen 1981).
Recent work has shown that the OECD poverty definition maps closely to a “basket-of-
goods style” minimum budget poverty threshold for Denmark (Bonke and Christensen 2016).
Bonke and Christensen (2016) calculate minimum budgets for a series of family types
conditional on number, age, and gender of household members. They then calculate
household budgets that encompass expenditures for housing, insurance, leisure, food,
3 Since its conception, this line has been moved from $1 dollar to $1.90.
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clothing, and other expenditure set at the minimum level for the family to be able to properly
sustain themselves (this minimum level is computed based on expert assessments of different
expenses). Using their method, they found in 2015 that 2.3 % of Danish children lived in a
household with income beneath the level to meet the minimum budget, whereas the OECD
definition found 2.5 % of children living below its poverty line. Thus, at least in the Danish
case, there appears to be clear point-in-time overlap at the macro-level between absolute and
relative poverty measures.
Labor market exclusion
Poverty is intrinsically linked to the absence of productive activities such unemployment,
which are often considered forms of social exclusion (see, e.g., Atkinson 1998; Bhalla and
Lapeyre 1999; Moller et al. 2003). As such, the European Union Statistics on Income and
Living Conditions (EU-SILC) jointly considers risk of poverty or social exclusion, using a
three-pronged approach that includes an indicator for low-work intensity (to capture labor
market exclusion), a measure of at risk of poverty, and a measure of material deprivation.
(Eurostat 2015). Unemployment and labor force inactivity are often a necessary although not
all-inclusive (Atkinson 1998; Moller et al. 2003; Sen 1992) cause of poverty for the working
age population. At the same time, social transfers serve to weaken the link between work
intensity and poverty status.
In this study, we rely on a well-defined and widely-used indicator of labor market
exclusion, the EU-SILC’s low-work intensity indicator [LWI] (Ward and Ozdemir 2013).4
The LWI indicator is defined as an average employment level below 20 % of full-time
employment among all adults age 18-59 capable of working in the household, excluding
students below age 25. The LWI indicator moves countercyclically with the business cycle:
4 Eurostat’s low work intensity is sometimes also referred to as very low work intensity, while the definition
remains the same. We term this low work intensity consistently.
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During recessions work intensity is low, during economic expansions, it is high. Given that
the employment rate varies across years more in absolute terms than does the poverty rate,
coupled with the fact that social welfare transfers help buffer some of the income effects of
unemployment and underemployment, the pure LWI rate is more volatile than the poverty
rate. Synthetic cohort estimates magnify such volatility. Moreover, in settings (such as
Denmark) with generous social transfers, low work intensity need not lead directly to income
poverty and material scarcity. Combining the OECD poverty indicator with the LWI indicator
diffuses the volatility that haunts both indicators on their own.
Multi-dimensional economic exclusion
Limitations in measures of both income poverty and labor market exclusion suggest benefits
to multi-dimensional measures of economic exclusion. Thus, in addition to analyses focusing
on separate components thereof, we also examine childhood prevalence of economic
exclusion as measured by a joint indicator of living in a household both with income below 50
of the median and with an employment level of less than 20 % of full-time labor force
attachment. This measure identifies households that have both low incomes (from earnings
and benefits) and low labor market participation (and thus earnings). As such, we refer to
simultaneously experiencing both of these conditions as being economically excluded.
Moreover, the joint indicator has an additional feature that makes it particularly useful for
calculating period-based measures of entrance rates: since the two individual indicators have
countervailing relations with the business cycle, the joint indicator makes estimates less
volatile to sudden business cycle driven changes in rates of relative poverty or labor market
participation alone.5
At the same time, reducing such volatility comes at a cost—in the combined measure,
5 Previous work has sought to combine income measured with another EU-SILC indicator, which captures
material deprivation through a battery of binary indicators (Alkire and Foster 2011; Nolan and Whelan 2010).
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households that are not experiencing low-work-intensity, but are experiencing income poverty
(and vice versa) are excluded. In other words, the continuously working poor are not counted
in such a measure; nor are those who are disconnected from the labor market but living above
poverty. It is important to recognize, however, that in the EU context income poverty is driven
more by under- and unemployment (Halleröd et al. 2015; Maitre et al. 2012; OECD 2009;
Ponthieux and Concialdi 2000), than by low wages among workers, which in a Western
context is more prevalent in the US (Ponthieux and Concialdi 2000; Thiede et al. 2015). Thus,
in the Danish setting, the former should not be a large concern. Further, we can empirically
examine the difference between estimates for the income poverty and joint measure to assess
the share of the working poor we fail to capture with the joint indicator. Likewise, we can
examine the difference between the joint indicator and the labor market exclusion indicator to
assess the share of labor market disconnected households with children that are not income
poor. This likely includes a substantial group of children whose parents receive social benefits
at levels that bring their family above the income poverty threshold; given Denmark’s
generous of social benefits, many such families will be excluded from the joint indicator of
economic exclusion.
Differences in Children’s Economic Exclusion Risk across Migration Background
Immigrants have higher risk of poor labor market attachment and low income. Thiede and
Brooks (Thiede and Brooks 2018) showed that, for the US, first and second generation
immigrant children have higher poverty rates when measured by both the official poverty
measure and the supplemental poverty measure. For Denmark, children of immigrant parents
have higher rates of risk of living in relative poverty (EU definition) and their parents have
lower levels of labor market attachment (Pedersen 2014). Further, immigrants are more
vulnerable during recessions (Barrett and Kelly 2012; Bonifazi and Marini 2014).As such,
cumulative risk estimates for children of immigrants may present a different levels of
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vulnerability to the business cycle. To examine potentially important heterogeneity by
immigrant status, we also present evidence on the cumulative risk of economic exclusion
across migration background.
Data and Measures
Data
We use population-wide administrative data (registry) containing information on all residents
in Denmark from 1986-2018. Each individual is assigned a unique personal identifier at birth,
which allows us to link information from different data sources. In addition, the data include
parental and family identifiers, through which family members can be linked, as well as
dwelling unit level residency information, allowing us to identify members of the same
household. These data further enable our analyses by holding vital information on household
income, labor market participation, and rich background characteristics.
Sample
Our sample consists of children born between 1985 and 2015, who appear for the first time in
the registry data the year following birth. Only children born in Denmark are included in the
study. This restriction is enforced by conditioning on social origin to be native Dane or
descendant of immigrants, as well as on the child being present in Denmark and counted by
Statistics Denmark with the age of 0 in the population register (BEF). We focus on children
age 1-17 from 1987-2018. Children, who turn 1 in 1987, turn 17 in 2003. Therefore, we
follow the children born from 1986 forward. However, we do not assess economic exclusion
status in the first year after birth to ensure that we are not counting families taking parental
leave as experiencing economic exclusion. Our outcomes are estimated from 2003-2018,
given that 2003 is the first year we are able to observe cohort children’s entire childhood, thus
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allowing construction of the first full synthetic cohort (described below) for which we have
reliable measures on all childhood incidences of economic exclusion across all ages. See
Appendix Table A1 to A4 for a depiction of the sample flow.
Measures
We estimate the cumulative individual and joint risk of economic exclusion for Danish
children using three measures. Income poverty is assessed by the OECD (relative) poverty
line, which defines poverty as having a household income below 50 % of the national
median.6 In practice, we use Statistics Denmark’s equivalized disposable household income
information, which follows the modified OECD equivalence scale. This assigns a weight of 1
to the first adult in the household, a weight of 0.5 to each additional household member age
15 or older, and a weight of 0.3 to each individual aged 0-14. We calculate the annual median
income using all households in Denmark and define income poverty to be household income
that falls below 50 % of this median.
We make several additional assumptions not included in the original measure, which in
turn makes our version slightly more conservative. First, we do not consider individuals who
are older than 24 but still living with their parent(s), individuals in a cohabiting relationship or
who have ever been married but also are living with their parent(s) (regardless of age), or
individuals living with both their own children and their parent(s) (regardless of age) as
members of their parent(s)’s household. Rather, we treat these individuals and their parent(s)
as living in separate households and determine poverty status for their and their parent(s)’s
households separately. Second, we define children living in dwelling units that include more
than 9 co-residing adults (which are likely to be institutional in nature), emancipated youth
(those under age 18 but living on their own), children with at least one self-employed resident
6 A table showing the income poverty thresholds can be found in Appendix Table A1.
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parent, and children with at least one resident parent7 who is a full-time student as being
nonpoor.8 Statistics Denmark also has developed a poverty indicator inspired by the OECD
indicator, but that also includes wealth. The indicator uses the same definition of disposable
income as the OECD, but also requires that wealth (excluded pension savings) is also below
the 50 % of the median of equivalized disposable household income. Appendix B reproduces
all main results using this indicator instead. Whereas it does slightly lower the cumulative risk
of income poverty, it does not lead to substantially different findings than our preferred and
more commonly used indicator.
Labor market exclusion is assessed using a modified version of Eurostat’s measure of
low work intensity. Eurostat’s definition includes households in which the working aged
adults (18-59), on average, worked less than 20 % of their (combined total) full-time
employment potential during the previous 12 months. Eurostat bases such categorization on
self-reported survey responses collected via the EU-SILC. We assess work intensity via
mandatory payments to the Danish retirement system (Arbejdsmarkedets Tillægspension
[ATP]), which are contributed by all wage earners in Denmark and are recorded in the
administrative data. ATP payments vary by hours worked per week. Full-time employment in
Denmark is considered 37 hours per week. Thus, we consider payments that correspond to
less than 20 % of full-time employment (7.4 hours per week) to represent labor market
exclusion. Notably, ATP payments are voluntary for self-employed individuals and therefore
cannot be used to accurately measure work intensity for this group.9 We therefore assume that
7 Parent is defined as ‘head of household’ or ‘partner/spouse to head of household.’ We have conducted a
robustness test, using only legal parents as opposed this broader definition of parents, which did not change our
results. These results are presented in Appendix Figure A1. 8 We conduct a robustness test, where we drop students and self-employed prior to the median calculation, which
does not change our results, which can be found in Appendix Figure A2. 9 Prior to 2011, ATP payments were calculated from annual information. From 2011 forward they were
calculated from monthly information. For the latter period, we use monthly measures of hours of paid work to
compute the share of the year that individuals were employed full time. There are a few years of overlap between
the annual and monthly data series, with which we have tested the comparability of the two and found extensive
overlap between the two measures. We do not believe the data discontinuity to be of concern.
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all self-employed individuals are working full time. Our labor market exclusion estimate will
be downwardly biased (conservative) to the extent that some self-employed workers work less
than 20 % of full-time status.
Consistent with the Eurostat categorization, we do not consider adults who undertake
studies as their primary activity to be experiencing low work intensity (labor market
exclusion). Rather, these adults are excluded from calculation of labor market exclusion,
which considers only resident adults who are not full-time students. Households in which all
resident adults are full-time students are not considered experiencing labor market exclusion.
In addition, because labor market exclusion is considered relevant only to prime working age
individuals (age 18-59), we define households in which children are living only with adults
over age 59 as being non-labor market excluded. Notably, because Denmark has the second
lowest old-age income poverty rate among OECD countries (OECD 2019), and given that less
than 3 % of Danish households with children include any adult age 60 or above10, this is not
likely to have much effect on our estimates.
Finally, consistent with our construction of income poverty, in determining labor
market exclusion we consider individuals living with their parents but over age 24, in a
cohabitation, having been married (ever) or with resident children of their own to be a
separate household from that of their parents. Likewise, we define children living in dwelling
units that include more than 9 co-residing adults and households composed only of children as
non-labor market excluded.
Economic exclusion is defined as experiencing both income poverty and labor market
exclusion in the same year. Households assumed to be either non-income poor or non-low
work intensity based on the assumptions describe above, will be categorized as not
experiencing economic exclusion under this measure. Notably, these assumptions should
10 Authors’ calculations using data from Statistics Denmark.
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result in our estimates being conservative or ‘lower bound’ estimates of the cumulative risk of
income poverty, labor market exclusion, and economic exclusion.
Analytic Strategy
We estimate the cumulative risk of ever experiencing household income poverty, labor market
exclusion, and economic exclusion during childhood using synthetic cohort life tables. Life-
table methods have traditionally been used to estimate mortality and life expectancy. Yet, they
can also be used to shed light on cumulative risk of other social experiences, such as the
probability of experiencing economic exclusion (e.g. Rank & Hirschl 1999). Specifically, we
calculate the cumulative risk of experiencing each measure of economic exclusion for the first
time in a given year for all Danish children between the age of 1 and 17. The cohorts are
‘synthetic’ in that we use observed age-specific risks of first occurrence of each form of
economic exclusion in a given year to estimate such risk across years, as opposed to tracking
individual birth cohorts over time.
Our analytic strategy rests on several assumptions. First, we assume no migration in or
out of the population of children. This assumption could be relaxed to allow for migration if
children who join or leave the population have the same risk of first entry into poverty as the
population of children in Denmark in that year. This is not plausible in a Danish context,
however, where immigration flows have been volatile during the 2003-2018 period of
analysis and in which the risk of poverty is not equally distributed across native Danes and
immigrants (see Caner and Pedersen 2019 for an example focusing on Turkish immigrants).
Therefore, we restrict our population to individuals present in Denmark in the year following
their birth, which is the first time they appear in the registry data. This further serves the
purpose of ensuring information throughout all of childhood. We further assume that all
children born in Denmark spend their entire childhood in the country, assuming away
emigration and childhood death. In addition, we set an age-correction (Ax) for the population
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at risk to 0.5, such that we assume the economic exclusion incident to occur, on average,
halfway between age intervals (years). Finally, we standardize number of births. Typically,
the annual number of births is set at 100,000, which is also the case in our study (Yusuf et al.
2014 p. 144f).
Two basic inputs are required for our calculations. The first key figure is the number of
children experiencing economic exclusion for the first time at any age in a given year (ix). The
second is the size of the population of children at risk of experiencing economic exclusion for
the first time, at any age in a given year, (Px).
𝑚𝑥 =𝑖𝑥
𝑃𝑥 (1)
𝑞𝑥 =𝑖𝑥
𝑃𝑥+0.5 𝑖𝑥 (2)
𝑝𝑥 = 1 − 𝑞𝑥 (3)
Based on these two inputs11, we calculate age-specific rates of experiencing economic
exclusion (mx) and combine them with the age-correction factor to reach a figure for the
probability of first entry into economic exclusion (qx) and, thereby, also the probability of not
having experienced economic exclusion yet (px). We will refer to the latter as ‘having
survived’ going forward. These probabilities are then applied to a synthetic cohort of 100,000
children at the age of 1 within each of the years in our analysis. For instance, the number of
children surviving (without experiencing economic exclusion) to age of 2 in 2005 is
calculated by multiplying the population of children aged 1 (100,000) by the age-specific
survival rate for 1-year-olds in 2005. This procedure provides the number of survivors at each
age (lx) and, by subtracting these, we calculate the number of children who did not survive
(dx), ergo the children who experienced their first entry into economic exclusion under a
11 Since children do not exit the administrative data population when they experience first entry into poverty (as
they would do in a life table of mortality), we cannot use the actual observed population of children. Instead, we
repeat the calculations of mx-lx and apply the calculated survival rate on the observed population to obtain our
observed population at risk table
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particular measure thereof, using the following equations:
𝑙𝑥+1 = 𝑙𝑥 ∗ 𝑝𝑥 (4)
𝑑𝑥 = 𝑙𝑥 − 𝑙𝑥+1 (5)
Where dx is cumulated over age and divided by the starting population of 100,000 children,
providing the cumulative risk estimates under each economic exclusion measure.
One advantage of using synthetic cohorts, as opposed to birth cohorts, is that we do not
have to wait for the children to grow up and become adults prior to estimating the cumulative
risk all the way up to the age of 18. However, the synthetic cohorts do not provide insight into
ongoing economic exclusion dynamics throughout the course of childhood for a given birth
cohort.12 Rather, they provide insight into the risk of a child experiencing economic exclusion
for the first time in a given year, conditioned on the age of the child.
In contrast, annual child economic exclusion rates alone capture many of the same
children year after year without providing evidence of first-time economic exclusion entries.
If, for instance, the annual rate of children experiencing economic exclusion is relatively
stable, but the cumulative risk is increasing over time, it would indicate that the average
duration of child economic exclusion is declining. The implication being that more children
are experiencing economic exclusion, but in shorter spells. Thus, considering both estimates
together provides insights on trends in both ever having experienced economic exclusion and
duration of economic exclusion experiences.
Results
Annual Prevalence and Cumulative Risk
We start by comparing the annual rate of children experiencing income poverty to the
12 We have also estimated the cumulative risks by looking at birth cohorts 1986-2000. The results can be found
in Appendix Figure A3.
19
cumulative risk of first poverty entry. Figure 113 presents the risk of experiencing income
poverty, in terms of annual rate (light grey line, left y-axis) and cumulative risk (dark grey
line, right y-axis). The cumulative risk estimates are considerably higher than the annual
share. While the annual share varies roughly between 1.5 and 3.5 %, the cumulative risk
estimates range from 12.5 to 22.5 % highlighting the substantial difference between the
proportion of children who experience income poverty in a given year versus at some point
during childhood.
The annual and cumulative rates follow the same general trend throughout the period
and exhibit similar growth from 2004-2008. Thereafter, however, cumulative risk undergoes a
steep drop compared to the annual rate, which is relatively stable. Consequently, a profound
spacing between the lines emerges and is sustained until the last year of the period. Together,
these trends imply that, compared to the years prior to the Great Recession, during and after
the Great Recession fewer children experienced income poverty for the first time, but the
average duration of time children spent in income poverty increased. In other words, that the
cumulative risk is declining while the annual rate is stable, indicates that fewer unique
children are contributing to the annual prevalence.
Figure 2 shows childhood risk of experiencing a labor market excluded household by
annual share (the light grey line, left y-axis) and cumulative risk (the dark grey line, right y-
axis). The cumulative risk estimates are approximately 3 times the size of the annual share
estimates. The latter range between 7 and 9.5 %; the former from 20 to 31.5 %. Both rates
follow the same trend throughout the period, which indicates a roughly unchanged duration of
time spent in a labor market excluded household, with the biggest differences in 2003-2004
and 2009-2010. In both cases, the cumulative risk rises faster than the annual share,
suggesting that the average duration of household labor market exclusion is decreasing, but
13 The estimates used to produce these figures shown are provided in Appendix Tables A1 to A4 and A6 to A7,
along with a stock table of economic exclusion in Table A8.
20
that more children are experiencing a period of labor market exclusion. The trend between the
lines is homogenized shortly after.
Synthetic Cohort Life Table Estimates of Risk of Economic Exclusion
We next focus specifically on the cumulative risk estimates. Figure 3 depicts cumulative risk
estimates for income poverty, labor market exclusion, and the combined measure of
simultaneously experiencing both (economic exclusion). Outside of the period surrounding
the Great Recession, we estimate that about 15 % of children will ever experience income
poverty. Yet, cumulative risk of income poverty increases dramatically during the period of
rapid wage growth in the aftermath of the recession, highlighting the volatility to business
cycles of relying on relative income-based measures to calculate cumulative risk of childhood
poverty, especially within a year. The income poverty peak in 2008 surely reflects a decrease
in resources for many households as a result of the recession. However, during the subsequent
economic boom and associated increase in median income, the growth in income poverty
likely reflects relative increases in income in the middle and upper segments of the
distribution rather than absolute declines in income at the bottom.
The household labor market exclusion estimates are relatively stable during the last part
of the period at approximately 26 %. Yet, they too are relatively unstable in the years prior to
and during the Great Recession, during which the unemployment rate is changing rapidly.
Considering the joint risk of economic exclusion—simultaneous income poverty and
household labor market exclusion—serves to reduce the influence of these countervailing
influences of larger economic trends relative to their influence in each of the separate
measures.
Several trends are apparent in Figure 3. First, combined economic exclusion risk
estimates are stable at around 11.5 % throughout the period, with only minor deviations. This
indicates that the combined measure is less influenced by business cycle instability than are
21
the independent indicators. In 2016-2018 (especially in 2017), however, overall economic
exclusion risk exhibits a steep increase, reaching a cumulative risk level of over 18 %. This
parallels a considerable increase in income poverty, but not labor market exclusion,
suggesting that factors beyond the overall economy may be at play. Indeed, the 2016 and
2017 increase in income poverty (and, thus, overall economic exclusion) likely reflects the
effect of a major social policy reform in Denmark which resulted in less generous social
welfare benefits. The 2017 peak is likely a result of a joint increase in inflow into income
poverty of new household, as well as households entering income poverty sooner than they
otherwise would have.14 Thus, while the economy remained strong, decreases in benefits
drove increases in income poverty and, thereby overall economic exclusion as those who
experienced labor market exclusion would also be more likely to experience income poverty.
Second, in the aftermath of the great recession (2012 forward), the joint indicator
captures 77 % of the children ever experiencing income poverty and approximately half of the
children ever experiencing a low work intensity household. The overlap reveals that most of
the children experiencing income poverty will also experience a low work intensity household
at the same time. However, 23 % of the children experiencing income poverty do not
experience a household with low work intensity simultaneously. An even larger group of
children (~50 %, averaged over 2012-2018) will experience a low work intensity household,
without at the same time experiencing the income poverty. This implies that households with
low work intensity do not necessarily experience economic scarcity, this group is likely to
include a rather large group of children, whose parents receive welfare benefits that bring
them above poverty. It thus suggests that many recipients of social assistance and
unemployment benefits in Denmark will not face income poverty, likely due to even the
14 In 2016, long-term social assistance recipients saw substantial cuts to their benefits. In 2015 newly arrived
immigrants and other individuals on social assistance, who had not spent the last 9 out of 10 years in Denmark,
started receiving lower benefits. Both reforms have been linked to increased levels of childhood poverty (The
Economic Council of the Labour Movement 2018).
22
lowest of those benefits, social assistance, tends to be at levels above the 50 5 of median
equivalized household income.
Finally, the cumulative joint risk estimates of about 11.5 % (on average) are
substantially larger than the annual share of both income poverty (Figure 1) and labor market
exclusion (Figure 2), despite that they include a more select group of children—only those
who simultaneously experience both. The estimates imply that approximately every 9th child
in Denmark can expect to experience economic exclusion during childhood. In short, a
substantial share of Danish children can expect to encounter economic exclusion at some
point. We next examine the temporal ordering of income poverty and household labor market
exclusion for children who experience both.
Temporal Ordering of First Experiences of Economic Exclusion
The children captured by our joint measure of economic exclusion experience, for the first
time, both the income poverty and household labor market exclusion during the same year of
childhood. In this section, we explore the timing of each form of economic exclusion for the
group of children that experience both at any point during childhood. Table 1 depicts the share
of first entries into each type of economic exclusion, where (1) income poverty occurs prior to
household labor market exclusion, (2) household labor market exclusion occurs prior to
income poverty, and (3) income poverty and household labor market exclusion occur
simultaneously (in the same year).
A key conclusion from Table 1 is that, if the economic exclusion indicators are not
experienced for the first time in the same year, it is more likely that a child will experience
household labor market exclusion prior to experiencing income poverty than vice versa. It is
also evident, that close to 40 % of the children who experience both income poverty and
household labor market exclusion during childhood will simultaneously experience both for
the first time in the same year. In other words, it is common that income poverty and
23
household labor market exclusion go hand in hand. Furthermore, when they do not occur in
the same year, that labor market exclusion tends to precede income poverty suggests that it
may be a route into income poverty.
Table 1 also provides information on the gap between the timing of first experience of
household labor market exclusion and income poverty, measured as the average number of
years between the first experience of each. If household labor market exclusion happens prior
to income poverty, the latter will occur, on average, 6.4 years later. On the other hand, if
income poverty is experienced first, the average gap is 3.9 years. In the next section, we
estimate the cumulative risk of experiencing childhood economic exclusion for at least two
consecutive years.
Cumulative Risk of at Least Two Consecutive Years of Economic Exclusion
As a robustness check, we estimate the cumulative risk that children spend at least two
consecutive years experiencing economic exclusion, using two-year demeaned indicators.
This entails that we count only first entries if a child experiences the relevant category of
economic exclusion in a given year and in the prior year as well. For this analysis, we also
include economic exclusion between birth and age 1 in order to estimate the risk at age 1,
given that capturing temporal economic exclusion in relation to parental leave is of lesser
concern for the two-year than single-year estimates.15
Figure 4 shows the cumulative risk of experiencing at least two consecutive years of
each indicator of economic exclusion during childhood. The trends somewhat resemble the
one-year estimates in Figure 3 for first year experiences of poverty (with the exception of the
one-year peak in labor market exclusion at the start of the Great Recession in 2008), however,
the levels differ. The risk of experiencing income poverty in a given year, outside of the
15 The average period of parental leave in Denmark is well below a year (www.statistikbanken.dk, table
SOCDAG10: Total Leave After Birth by Parental Leave Weeks and Average Amount of Days per Child).
24
period of the Great Recession and 2017, was approximately 15 % (Figure 3), while the risk of
two consecutive years of income poverty during this period was roughly 5% (Figure 4).
Similarly, risk levels for household labor market exclusion and overall economic exclusion
are lower when conditioning on a minimum of two years of exposure.16 However, whereas the
one year cumulative risk declined from 2017 to 2018, the two year exposure risk continued to
increase, indicating that a salient increase in the risk of longer period economic exclusion. In
the next section, we examine the age at which children are most likely to experience economic
exclusion for the first time, and whether the age-specific risk has changed over time across
our study period.
Age-Specific Risk of Economic Exclusion
Figure 5 shows the age-specific risk of overall economic exclusion (joint risk of
simultaneously experiencing both income poverty and household labor market exclusion) for
the first time during childhood for the synthetic cohorts in years 2006, 2010, 2014 and 2018.17
Overall, the cohorts follow the same general pattern, in which the age-specific risk of
first entry into poverty is highest at age 1 and trends downward thereafter, with only minor
deviations. The high level of economic exclusion at age 1 reflects that, for families already
experiencing economic exclusion prior to a given birth, the newborn child will be born into
economic exclusion. Furthermore, for some families that are not experiencing economic
exclusion prior to a birth, expanded household size, conditional on unchanged income, could
potentially push them into income poverty (which takes family size into account). In theory, if
we excluded age 1 and began our synthetic cohorts at age 2, instead, we would expect to see a
16 Appendix Table A9 shows the distribution of numbers of years in economic exclusion for the birth cohorts
born 1986-2000; 41 % of those who experienced economic exclusion did so for at least two years during
childhood. 17 Age-specific risk for experiencing income poverty and household economic exclusion alone are presented in
Appendix Figure A4 and A5, respectively. Age-specific risk for all synthetic cohorts from 2003-2018, for all
measures, can be found in Appendix Table A10 to A12.
25
similarly high level at age 2, due to the introduction of these families into the sample.
In addition, each cohort exhibits a peak in economic exclusion risk at age 15. However,
this simply reflects the construction of income poverty threshold which, following the OECD
standard, weights children over age 15 more heaving than younger children in the equalization
of household income. Finally, whereas synthetic age cohorts are, for the most part, spaced
closely together across years, there is a noticeable increase in the difference in risk between
the cohorts during ages 1-4 and ages 15-17. In the first case, the 2018 cohort faces greater risk
than the other cohorts. Consequently, the increase in the joint risk in 2016-2018 seem to
reflect an actual shift in the risk of encountering poverty, since it does not reflect the group of
children experiencing poverty sooner
Cumulative Risk of Economic Exclusion by Immigrant Background
Since we have limited our sample to include only children born in Denmark, the subgroups
we examine are native Danes and descendants of immigrants, the latter defined as children
born in Denmark to parents who both were not themselves born in Denmark. Figure 6 shows
the cumulative risks of income poverty, household labor market exclusion, and economic
exclusion for the two groups. The cumulative risk estimates are substantially higher for
descendants on each indicator. For example, in 2018, the risk of overall economic exclusion
among native Danes is around10 %, whereas it is above 40 % for descendants. The risk for
economic exclusion in 2017-18 is higher than the risk of low work intensity because, as
shown in Table 1, most households experience low work intensity for the first time several
years prior to experiencing income poverty. Further, the figure shows a substantial increase in
cumulative risk of income poverty and economic exclusion for descendants from 2003 to
2004. The increase coincided with welfare reforms that saw benefits for married couples on
social assistance with at least two children cut with 9 percent (Hansen and Schultz-Nielsen
2015) – immigrant families are highly overrepresented among married couples with two or
26
more children who rely on social assistance.
While the levels of each indicator differ across groups, the trend in household labor market
exclusion is similar for the two, whereas there is more variation between groups in terms of
income poverty and, thus, overall economic exclusion. As a robustness check we have
examined immigrant background combined with the two-year demeaned measures. The
cumulative risk estimates are, as expected, on a lower level, yet the trends are quite similar.
These results can be found in Appendix Figure A6. In addition, Appendix Table A9 shows the
distribution of numbers of actual years in economic exclusion for the 1986-2000 birth cohorts,
by immigration background. For these birth cohorts, children of migrants not only had higher
risk of ever experiencing economic exclusion, but those who did also experienced them for
more years during childhood.
Geographical Distribution of Economic Exclusion Risk
Finally, we explore temporal trends in the geographical distribution of poverty risk. Figure 7
depicts the cumulative risk of experiencing overall economic exclusion by municipality
during the child’s birth (first register) year, using a Tukey box plot.18 We have recoded
addresses such that all households align with the post-2007 merged municipalities. We see,
that the development in the distribution closely resembles the joint risk depicted in Figure 3.
The cumulative risk is relatively stable throughout the entire period, with a clear increase in
the final years. Additionally, we find only one outlier municipality below the adjacent values,
while we find several outliers above the adjacent values in all years. Several of these outliers
are the same in more than one year, further indicating, that households with children in some
municipalities are particularly and continuously vulnerable to economic exclusion. The
18 Box plots for income poverty and household labor market exclusion are shown in Appendix Figure A7 and
A7. A list of the codes that translates municipality number to municipality names can be found in Appendix
Table A13
27
outliers in the top of the distribution, combined with the lack of outliers below, entails that the
median is lower that the cumulative risk because there are extreme observations driving the
overall risk in Figure 3 upwards.
Discussion
This study employs Danish registry data and synthetic cohort lifetable methods to yield new
information about cumulative risk of childhood disadvantage—measured as experiencing
income poverty, household labor market exclusion, and simultaneous exposure to both
(economic exclusion)—over the course of childhood in Denmark. Notably, income poverty
and labor market exclusion comprise two of the indicators used in Eurostat’s measure of risk
of poverty or social exclusion (the third being severe material deprivation).19 This work
informs our understanding of the incidence and prevalence of income poverty and other forms
of childhood economic exclusion in Denmark, a wealthy country with generous social welfare
benefits and one of the lowest annual child poverty rates in the developed world. It also
provides information to inform the literature on measurement of poverty and economic
exclusion. Its key limitations are that we are unable to assess economic exclusion in the first
year of life (prior to age 1), that we are able only to include children born in Denmark in (and
must exclude immigrant children from) our analyses, and that our analyses assume no child
mortality or in- or out-migration of children. However, these limitations serve to downwardly
bias our estimates, making them conservative in nature.
Several key findings inform our understanding of childhood economic exclusion in
Denmark, with implications for other wealthy countries. First, when viewed in terms of
cumulative risk, many more Danish children experience economic exclusion at some point
during childhood than is apparent via annual estimates. Whereas annual rates of childhood
19 We do, however, use the OECD definition of poverty (50% of median equivalized disposable household
income), which is more stringent than Eurostat’s 60% definition.
28
income poverty and household labor market exclusion ranged from 1.5-3.5 % and 7.0-9.5 %,
respectively, across our observation years (2003-2018), on average, 11.5 % of children
simultaneously experience both income poverty and labor market exclusion at some point
during childhood. Moreover, 16 % of all Danish children experience income poverty and 26.5
% experience household labor market exclusion at some point during childhood.
Second, we find that household labor market exclusion during childhood is much more
common than childhood income poverty. This speaks to the strength of the Danish welfare
state at supporting labor market-disconnected families to live above income poverty. Indeed,
whereas the vast majority of children who experience income poverty also experience
household labor market exclusion, only about half of the children who experience household
labor market exclusion also experience income poverty. At the same time, we also find that a
large group of children (12 % across childhood during the 2003-2018 period of analysis)
experience both income poverty and household labor market exclusion. Among these
children, it is common for both to be experienced for the first time in the same year.
Moreover, when they are not simultaneously experienced, labor market exclusion tends to
precede income poverty suggesting that, even in a context of considerable welfare generosity,
labor market exclusion remains a key component of the path to income poverty.
Third, we find evidence suggesting that, at least with respect to income poverty, social
welfare transfers matter. Our estimates indicate a substantial increase in risk of income
poverty and, thus, overall economic exclusion (reaching a cumulative risk of more than 18 %
in 2017)—but not of labor market exclusion—in 2016-18. This trend came directly on the
heels of Danish welfare reforms that reduced benefit generosity. It suggests that, despite a
strong economy and relatively flat rate of labor market exclusion, income poverty (and
therefore overall economic exclusion) likely increased among those who were relying most
heavily on social welfare benefits (and less so on earnings), whose household incomes would
29
have declined most as a result of benefit cuts
Our findings also have implications to inform measurement of economic exclusion. To
begin with, while not surprising, our findings that cumulative risk estimates of childhood
economic exclusion far exceed annual estimates, highlight the importance of considering the
latter as well as the former in setting policy goals and designing policies and programs
intended to buffer the potentially adverse consequences throughout the life course of
experiencing childhood poverty. Comparing trends in cumulative and annual rates of
economic exclusion over time further provides evidence as to whether changes in annual rates
reflect changes in economic exclusion spell lengths versus changes in the proportions of
children who are first experiencing economic exclusion. In short, considering cumulative
childhood risk of economic exclusion, and trends therein over time, shines light on the fact
that many more children will experience economic exclusion than is implied by annual
estimates. We have also provided estimates conditional om migration background. Children
born in Denmark who descended from parents not born in Denmark had markedly higher risk
of experiencing household economic exclusion during childhood than had children of native-
born parents. Depending on year, the cumulative risk of economic exclusion was 1.5- to 3-
fold higher for descendants. In relative terms, these differences are comparable to racial
differences in cumulative poverty rate in the US (Rank and Hirschl, 1999), although absolute
poverty levels are higher in the US.
In addition, our analyses underscore the importance of considering other measures of
economic exclusion beyond simply relative income. Our income poverty estimates, which
rely on the OECD relative poverty threshold of equivalized household income less than 50 %
of the national median, make readily apparent a key limitation of such measures. Specifically,
we observe considerable increases in income poverty during years in which the Danish
economy was strong, and during which labor market exclusion was declining, and declines in
30
income poverty in some years in which the economy was weak and labor market exclusion
increasing. These fluctuations in income poverty risk likely reflect changes in median
household income (which tends to increase with a strong economy and decrease with a weak
economy), rather than changes in actual living standards (or purchasing power) of low-income
households. Our combined measure of economic exclusion, by including both income poverty
(which tends to be countercyclical with the business cycle when measured in relative terms)
and labor market exclusion (which tends to be cyclical with the business cycle), is less subject
to these counter-acting and non-intuitive fluctuations. Thus, we argue that the combined
measure presents a more accurate, more consistent, and more stable picture of economic
exclusion.
On the whole, this study offers important implications for improving assessment of
childhood economic exclusion risk and patterns thereof over time, and also for considering the
strengths and limitations of specific measures of economic exclusion in particular economic
contexts. Future work, however, is warranted to further understand cumulative poverty risk in
nations beyond Denmark, including those with more and less generous social welfare systems,
as well as the range of individual and societal factors that drive cumulative risk of childhood
poverty in particular contexts, and the extent to which such risk varies across demographic
subgroups within and across nations. Further, given the relatively large group children who
may ever expect to experience economic exclusion, additional research into the consequences
of childhood economic exclusion is warranted.
31
References
Alkire, S., & Foster, J. (2011). Counting and multidimensional poverty measurement. Journal
of Public Economics, 95(7–8), 476–487. doi:10.1016/j.jpubeco.2010.11.006
Atkinson, A. B. (1998). Social Exclusion, Poverty and Unemployment. Exclusion,
employment and opportunity, CASE paper No 4.
doi:papers2://publication/uuid/23323176-487F-4C15-96E4-FE8AF1D92A06
Barrett, A., & Kelly, E. (2012). The Impact of Ireland’s Recession on the Labour Market
Outcomes of its Immigrants. Eur J Population, 28, 91–111. doi:10.1007/s10680-011-
9249-7
Bhalla, A. S., & Lapeyre, F. (1999). Poverty and Exclusion in a Global World. Poverty and
Exclusion in a Global World. MacMillan. doi:10.1057/9780230005624
Blank, R. M. (2008). Presidential address: How to improve poverty measurement in the
United States. In Journal of Policy Analysis and Management (Vol. 27, pp. 233–254).
Wiley-Blackwell. doi:10.1002/pam.20323
Bonifazi, C., & Marini, C. (2014). The Impact of the Economic Crisis on Foreigners in the
Italian Labour Market. Journal of Ethnic and Migration Studies, 40(3), 493–511.
doi:10.1080/1369183X.2013.829710
Bonke, J., & Christensen, A. E. W. (2016). Minimumsbudget for forbrugsudgifter.
Copenhagen, DK: Syddansk Universitetsforlag. www.rff.dk. Accessed 7 September 2018
Bonke, J., & Christensen, A. E. W. (2017). Børn i familier med lave indkomster: Hvor mange,
hvor længe, hvem og hvorfor? Copenhagen, DK: Syddansk Universitetsforlag.
Bradbury, B., Jenkins, S. P., & Micklewright, J. (2009). Conceptual and measurement issues.
In The Dynamics of Child Poverty in Industrialised Countries (pp. 27–61).
doi:10.1017/cbo9780511522147.002
Caner, A., & Pedersen, P. J. (2019). Does Poverty Among Immigrants Adapt to Country of
32
Residence? Turks in Germany and Denmark. International Migration, 57(1), 264–280.
doi:10.1111/imig.12522
Dickerson, A., & Popli, G. K. (2016). Persistent poverty and children’s cognitive
development: Evidence from the UK Millennium Cohort Study. Journal of the Royal
Statistical Society. Series A: Statistics in Society, 179(2), 535–558.
doi:10.1111/rssa.12128
Eurostat. (2015). People at risk of poverty or social exclusion. EUROSTAT Statistics
Explained. https://ec.europa.eu/eurostat/statistics-
explained/index.php/People_at_risk_of_poverty_or_social_exclusion. Accessed 7
September 2018
Eurostat. (2019). Children at risk of poverty or social exclusion - Statistics Explained.
https://ec.europa.eu/eurostat/statistics-
explained/index.php?title=Children_at_risk_of_poverty_or_social_exclusion. Accessed 8
November 2019
Fallesen, P., Emanuel, N., & Wildeman, C. (2014). Cumulative risks of foster care placement
for Danish children. PLoS ONE, 9(10). doi:10.1371/journal.pone.0109207
Halleröd, B., Ekbrand, H., & Bengtsson, M. (2015). In-work poverty and labour market
trajectories: Poverty risks among the working population in 22 European countries.
Journal of European Social Policy, 25(5), 473–488. doi:10.1177/0958928715608794
Hansen, H., & Schultz-Nielsen, M. L. (2015). Kontanthjælpen gennem 25 år : modtagere,
regler, incitamenter og levevilkår fra 1987 til 2012. Copenhagen, DK: Gyldendal A/S.
Hanson, J. L., Hair, N., Shen, D. G., Shi, F., Gilmore, J. H., Wolfe, B. L., & Pollak, S. D.
(2013). Family poverty affects the rate of human infant brain growth. PLoS ONE, 8(12).
doi:10.1371/journal.pone.0080954
Jiang, Y., Ekono, M., & Skinner, C. (2016). Basic Facts about Low-income children:
33
Children under 18 years, 2014. doi:10.7916/D8JS9Q92
Kim, H., & Drake, B. (2019). Cumulative Prevalence of Onset and Recurrence of Child
Maltreatment Reports. Journal of the American Academy of Child & Adolescent
Psychiatry. doi:10.1016/J.JAAC.2019.02.015
Kim, H., Wildeman, C., Jonson-Reid, M., & Drake, B. (2017). Lifetime prevalence of
investigating child maltreatment among US children. American Journal of Public Health,
107(2), 274–280. doi:10.2105/AJPH.2016.303545
Lesner, R. V. (2018). The long-term effect of childhood poverty. Journal of Population
Economics, 31(3), 969–1004. doi:10.1007/s00148-017-0674-8
Magruder, J., & Shaw, T. V. (2008). Children ever in care: An examination of cumulative
disproportionality. Child Welfare, 87(2), 169–188.
https://www.researchgate.net/publication/23440539. Accessed 16 March 2019
Maitre, B., Nolan, B., & Whelan, C. T. (2012). Low Pay, In-Work Poverty And Economic
Vulnerability: A Comparative Analysis Using Eu-Silc. Manchester School.
doi:10.1111/j.1467-9957.2011.02230.x
Moller, S., Huber, E., Stephens, J. D., Bradley, D., & Nielsen, F. (2003). Determinants of
relative poverty in advanced capitalist democracies. American Sociological Review,
68(1), 22–51. doi:10.2307/3088901
No, I. Z. A. D. P., Jenkins, S. P., & Jenkins, S. P. (2018). DISCUSSION PAPER SERIES
Perspectives on Poverty in Europe Perspectives on Poverty in Europe, (12014).
www.iza.org. Accessed 7 January 2019
Nolan, B., & Ive, M. (2012). Economic Inequality, Poverty, and Social Exclusion. The Oxford
Handbook of Economic Inequality. doi:10.1093/oxfordhb/9780199606061.013.0013
Nolan, B., & Whelan, C. T. (2010). Using non-monetary deprivation indicators to analyze
poverty and social exclusion: Lessons from Europe? Journal of Policy Analysis and
34
Management. doi:10.1002/pam.20493
OECD. (2009). OECD Employment Outlook 2009. OECD. doi:10.1787/empl_outlook-2009-
en
OECD. (2019). Poverty rate - Inequality. doi:10.1787/0fe1315d-en
Pedersen, P. J. (2014). Fattigdom blandt indvandrere og deres børn. Samfundsøkonomen, (4),
37–43.
Ponthieux, S., & Concialdi, P. (2000). Low pay and poor workers: a comparative study of
France and the United States. Transfer: European Review of Labour and Research, 6(4),
650–672. doi:10.1177/102425890000600408
Portes, A., & Vickstrom, E. (2011). Diversity, Social Capital, and Cohesion.
doi:10.1146/annurev-soc-081309-150022
Rank, M. R., & Hirschl, T. A. (1999). The economic risk of childhood in America: Estimating
the probability of poverty across the formative years. Journal of Marriage and Family,
61(4), 1058–1067. doi:10.2307/354024
Rank, M. R., & Hirschl, T. A. (2001). Poverty across the Life Cycle: Evidence from the PSID.
Journal of Policy Analysis and Management, 20(4), 737–755. doi:10.1002/pam.1026
Ryan, R. M., Fauth, R. C., & Brooks-Gunn, J. (2006). Childhood Poverty: Implications for
School Readiness and Early Childhood Education. In Handbook of research on the
education of young children (pp. 323–346).
Sabol, W., Coulton, C., & Polousky, E. (2004). Measuring child maltreatment risk in
communities: a life table approach. Child Abuse & Neglect, 28(9), 967–983.
doi:10.1016/J.CHIABU.2004.03.014
Sen, A. (1981). Issues in the Measurement of Poverty. In Measurement in Public Choice (pp.
144–166). London: Palgrave Macmillan UK. doi:10.1007/978-1-349-05090-1_11
Sen, A. (1992). Inequality Reexamined. Oxford University Press.
35
doi:10.1093/0198289286.001.0001
Sharkey, P., & Elwert, F. (2011). The legacy of disadvantage: Multigenerational
neighborhood effects on cognitive ability. American journal of sociology, 116(6), 1934–
1981. doi:10.1016/j.asieco.2008.09.006.EAST
Smeeding, T. M. (2017). Poverty measurement. In D. Brady & L. M. Burton (Eds.), The
Oxford Handbook of the Social Science of Poverty (Vol. 1, pp. 21–46). New York, NY:
Oxford University Press. doi:10.1093/oxfordhb/9780199914050.001.0001
The Economic Council of the Labour Movement. (2018). Den stigende polarisering rammer
børnene. Tema: Fordeling & Levevilkår 2018. www.ae.dk. Accessed 5 December 2019
Thiede, B. C., & Brooks, M. M. (2018). Child poverty across immigrant generations in the
United States, 1993–2016: Evidence using the official and supplemental poverty
measures. doi:10.4054/DemRes.2018.39.40
Thiede, B. C., Lichter, D. T., & Sanders, S. R. (2015). America’s Working Poor. Work and
Occupations, 42(3), 267–312. doi:10.1177/0730888415573635
Tolsma, J., van der Meer, T., & Gesthuizen, M. (2009). The impact of neighbourhood and
municipality characteristics on social cohesion in the Netherlands. Acta Politica, 44(3),
286–313. doi:10.1057/ap.2009.6
Ward, T., & Ozdemir, E. (2013). Measuring low work intensity – an analysis of the indicator.
ImPRovE Working Papers. https://ideas.repec.org/p/hdl/improv/1309.html. Accessed 7
September 2018
Wildeman, C. (2009). Parental Imprisonment, the Prison Boom, and the Concentration of
Childhood Disadvantage. Demography, 46(2), 265–280. doi:10.1353/dem.0.0052
Wildeman, C., & Andersen, L. H. (2015). Cumulative risks of paternal and maternal
incarceration in Denmark and the United States. Demographic Research, 32(1), 1567–
1580. doi:10.4054/DemRes.2015.32.57
36
Wildeman, C., & Emanuel, N. (2014). Cumulative risks of foster care placement by age 18 for
U.S. children, 2000-2011. PLoS ONE, 9(3). doi:10.1371/journal.pone.0092785
Wildeman, C., Emanuel, N., Leventhal, J. M., Putnam-Hornstein, E., Waldfogel, J., & Lee, H.
(2014). The Prevalence of Confirmed Maltreatment Among US Children, 2004 to 2011.
JAMA Pediatrics, 168(8), 706. doi:10.1001/jamapediatrics.2014.410
Yusuf, F., Swanson, D. A., & Martins, J. M. (2014). Methods of demographic analysis.
Methods of Demographic Analysis. Springer. doi:10.1007/978-94-007-6784-3
37
Table 1. Temporal Ordering of the First Economic Exclusion Experiences
Frequency Percent
Gap (Average
# Years)
Only Children Experiencing Both
Income Poverty First 11759 8.73 3.91
Labor Market Exclusion First 70976 52.72 6.37
Both in Same Year 51900 38.54
Total 134635 100.00
Only Children Not Experiencing Both
Only Income Poverty 34420 17.24
Only Labor Market Excl. 165720 82.76
Total 199690 100.00
Note: The first 3 rows include only those children who experience both income poverty and household labor
market exclusion at some point during the part of childhood, we observe in our data. The last 2 rows include only
children, who do not experience both income poverty and labor market, but only one or the other. As with the
other outcomes, we focus on the 2003-2018 period of analysis. For the group of children, that experience both
income poverty and labor market exclusion, but not for the first time in the same year, the second indicator will
be the decisive one for having experienced (joint) economic exclusion (and will have happened in 2003 or later).
38
Figure 1. Risk of Experiencing Income Poverty Definition During Childhood (1-17)
Note: Recession years (with a negative GDP growth) are shaded. Income poverty is defined as household
income below 50 % of the Danish national median income in the relevant year.
39
Figure 2. Risk of Experiencing Household Labor Market Exclusion During Childhood (1-17)
Note: Recession years (with a negative GDP growth) are shaded. Household labor market exclusion is defined as
all working-aged adults (18-59) in the household, on average, working < 20 % of full-time employment.
40
Figure 3. Synthetic Cohort Estimates of the Cumulative Risk of Experiencing Income
Poverty, Household Labor Market Exclusion, and Economic Exclusion Across Childhood
(age 1-17)
Note: Recession years (with a negative GDP growth) are shaded. Income poverty is defined as having a
household income below 50 % of the income median. Household labor market exclusion is defined as all
working-aged adults (18-59) in the household, on average, working < 20 % of full-time employment. Economic
exclusion is defined as simultaneously experiencing both income poverty and household labor market exclusion.
41
Figure 4. Synthetic Cohort Estimates of the Cumulative Risk Income Poverty, Household
Labor Market Exclusion, and Economic Exclusion for at Least Two Consecutive Years
During Childhood (age 1-17)
Note: Recession years (with a negative GDP growth) are shaded. Income poverty is defined as having a
household income below 50 % of the income median. Household labor market exclusion is defined as all
working-aged adults (18-59) in the household, on average, working < 20 % of full-time employment.
Economic exclusion is defined as simultaneously experiencing both income poverty and household labor
market exclusion.
42
Figure 5. Age-Specific Risk of First Experiencing Overall Economic Exclusion for the
Synthetic Cohorts; 2006, 2010, 2014 and 2018
Note: Recession years (with a negative GDP growth) are shaded. OECD poverty is defined as having a
household income below 50 % of the income median. Economic exclusion is defined as simultaneously
experiencing both income poverty and household labor market exclusion.
43
Figure 6. Synthetic Cohort Estimates of the Cumulative Risk of Experiencing Income
Poverty, Household Labor Market Exclusion, and Economic Exclusion Across Childhood
(age 1-17), by Immigrant Background
Note: Recession years (with a negative GDP growth) are shaded. Income poverty is defined as having a
household income below 50 % of the income median. Household labor market exclusion is defined as all
working-aged adults (18-59) in the household, on average, working < 20 % of full-time employment. Economic
exclusion is defined as simultaneously experiencing both income poverty and household labor market exclusion.
44
Figure 7. Geographical Distribution of Synthetic Cohort Estimates of Cumulative Risk of
Experiencing Economic Exclusion Across Childhood (age 1-17), by Municipality in Birth
Year
Note: The figure is based upon 94 municipalities (93 in 2006). A table of municipalities and codes can be found
in Appendix table A10. Income poverty is defined as having a household income below 50 % of the income
median. Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on
average, working < 20 % of full-time employment. Economic exclusion is defined as simultaneously
experiencing both income poverty and household labor market exclusion.
45
Appendix A: Additional Tables and Figures
46
Table A1. Number of Children in Denmark Ages 1-17 for Years 1987-2018, Assuming No Mortality and No Migration
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1987 53703
1988 55243 53703
1989 56067 55243 53703
1990 58655 56067 55243 53703
1991 61061 58655 56067 55243 53703
1992 63284 61061 58655 56067 55243 53703
1993 64192 63284 61061 58655 56067 55243 53703
1994 67538 64192 63284 61061 58655 56067 55243 53703
1995 67257 67538 64192 63284 61061 58655 56067 55243 53703
1996 69576 67257 67538 64192 63284 61061 58655 56067 55243 53703
1997 69956 69576 67257 67538 64192 63284 61061 58655 56067 55243 53703
1998 67616 69956 69576 67257 67538 64192 63284 61061 58655 56067 55243 53703
1999 67506 67616 69956 69576 67257 67538 64192 63284 61061 58655 56067 55243 53703
2000 66067 67506 67616 69956 69576 67257 67538 64192 63284 61061 58655 56067 55243 53703
2001 66166 66067 67506 67616 69956 69576 67257 67538 64192 63284 61061 58655 56067 55243 53703
2002 66986 66166 66067 67506 67616 69956 69576 67257 67538 64192 63284 61061 58655 56067 55243 53703
2003 65341 66986 66166 66067 67506 67616 69956 69576 67257 67538 64192 63284 61061 58655 56067 55243 53703
2004 64096 65341 66986 66166 66067 67506 67616 69956 69576 67257 67538 64192 63284 61061 58655 56067 55243
2005 64644 64096 65341 66986 66166 66067 67506 67616 69956 69576 67257 67538 64192 63284 61061 58655 56067
2006 64608 64644 64096 65341 66986 66166 66067 67506 67616 69956 69576 67257 67538 64192 63284 61061 58655
2007 64349 64608 64644 64096 65341 66986 66166 66067 67506 67616 69956 69576 67257 67538 64192 63284 61061
2008 65042 64349 64608 64644 64096 65341 66986 66166 66067 67506 67616 69956 69576 67257 67538 64192 63284
2009 64228 65042 64349 64608 64644 64096 65341 66986 66166 66067 67506 67616 69956 69576 67257 67538 64192
2010 65068 64228 65042 64349 64608 64644 64096 65341 66986 66166 66067 67506 67616 69956 69576 67257 67538
2011 62983 65068 64228 65042 64349 64608 64644 64096 65341 66986 66166 66067 67506 67616 69956 69576 67257
2012 63533 62983 65068 64228 65042 64349 64608 64644 64096 65341 66986 66166 66067 67506 67616 69956 69576
2013 59103 63533 62983 65068 64228 65042 64349 64608 64644 64096 65341 66986 66166 66067 67506 67616 69956
2014 58047 59103 63533 62983 65068 64228 65042 64349 64608 64644 64096 65341 66986 66166 66067 67506 67616
2015 55954 58047 59103 63533 62983 65068 64228 65042 64349 64608 64644 64096 65341 66986 66166 66067 67506
2016 56895 55954 58047 59103 63533 62983 65068 64228 65042 64349 64608 64644 64096 65341 66986 66166 66067
47
2017 58293 56895 55954 58047 59103 63533 62983 65068 64228 65042 64349 64608 64644 64096 65341 66986 66166
2018 58293 56895 55954 58047 59103 63533 62983 65068 64228 65042 64349 64608 64644 64096 65341 66986
48
Table A2. Number of Children Ages 1-17 whose Household is Income Poor for the First Time for Years 1987-2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1987 1130
1988 1170 748
1989 1316 878 713
1990 1498 881 784 654
1991 1375 889 683 589 551
1992 1429 873 696 630 536 511
1993 1832 1101 869 744 634 594 521
1994 1049 715 533 502 488 402 415 388
1995 1197 782 625 583 534 485 434 375 355
1996 1342 782 679 621 523 499 433 427 387 309
1997 1357 793 744 663 597 517 461 421 372 342 305
1998 1436 842 773 661 601 564 453 464 396 327 334 269
1999 1317 840 719 627 603 487 500 462 419 363 329 282 253
2000 1387 866 800 718 711 588 639 547 451 415 383 368 298 268
2001 1595 894 796 757 730 638 649 591 542 461 441 406 322 259 449
2002 1292 788 682 626 577 520 488 500 431 418 346 295 260 210 304 229 2003 1241 781 731 621 539 507 493 481 443 422 360 336 290 243 380 259 180
2004 1551 1033 873 827 711 654 635 582 565 475 470 406 339 322 449 295 247
2005 1790 995 867 857 742 630 619 594 606 509 508 431 419 326 511 330 273
2006 1716 971 767 742 646 676 570 522 508 461 474 435 390 334 501 329 266
2007 1768 967 851 793 762 716 684 618 599 554 493 477 482 365 579 398 307
2008 1888 998 925 810 782 731 728 694 636 584 575 575 558 514 656 506 411
2009 1932 955 793 746 671 630 627 617 577 502 552 465 464 432 650 465 405
2010 2055 958 811 738 676 600 561 577 557 507 463 454 427 375 668 494 403
2011 2024 908 740 706 662 533 509 544 494 490 471 462 394 374 622 465 375
2012 1501 789 640 606 544 493 448 435 445 414 397 328 357 292 506 386 347
2013 1606 768 675 560 527 443 430 396 417 371 390 349 359 289 544 387 340
2014 1827 905 757 689 582 481 485 451 408 363 358 336 316 252 527 371 301
2015 1914 772 679 562 503 419 425 412 356 318 332 326 292 281 519 346 260
2016 2193 1130 816 705 595 507 478 476 423 419 342 365 323 292 609 423 385
2017 3413 1374 1068 890 740 682 602 596 551 507 455 425 425 411 859 587 477
2018 3336 1145 869 755 550 542 519 463 421 422 378 362 342 325 656 378 328
49
Note: Income poverty is defined as having a household income below 50 % of the income median.
50
Table A3. Number of Children Ages 1-17 who Resided in a Labor Force Excluded Household in Denmark for the First Time for Years
1987-2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1987 5068
1988 6279 2131
1989 7018 2261 1630
1990 7786 2379 1597 1212
1991 8299 2493 1688 1266 1032
1992 8750 2617 1671 1259 962 875
1993 9749 2777 1802 1394 1066 869 808
1994 9629 2590 1609 1258 962 774 682 621
1995 9374 2521 1536 1104 910 776 640 529 466
1996 9365 2305 1342 1047 773 679 538 471 409 390
1997 10146 2798 1909 1397 1118 847 787 648 563 517 493
1998 9551 1776 1346 1020 734 688 540 481 411 392 385 340
1999 8779 2005 1370 1066 877 633 606 542 454 398 328 325 334
2000 8792 1826 1411 1084 878 781 630 531 465 387 393 319 300 271
2001 8821 1800 1323 1025 882 767 671 560 488 410 366 337 277 281 264
2002 9113 2107 1583 1284 1015 863 795 709 590 544 443 399 383 349 305 313 2003 8844 2065 1629 1279 1003 906 777 774 660 513 520 449 423 391 356 350 362
2004 8657 2084 1626 1327 1004 921 863 698 681 590 527 507 418 362 395 378 356
2005 7940 1631 1317 1095 945 745 740 671 610 512 489 455 411 397 384 378 341
2006 7002 1440 1189 867 817 688 602 590 511 474 455 421 368 348 345 341 308
2007 6330 1313 1040 831 698 584 547 492 444 434 401 393 367 343 338 331 304
2008 5847 1254 1060 747 596 532 451 436 402 327 343 360 337 305 279 272 268
2009 7145 1952 1635 1226 933 823 660 677 605 517 534 537 460 464 509 443 432
2010 7211 1867 1552 1299 1058 899 741 696 598 623 561 582 490 492 566 508 470
2011 6715 1380 1226 1027 905 737 664 569 547 456 488 432 436 389 386 401 400
2012 6589 1653 1281 1012 918 794 658 682 562 494 528 451 452 429 434 406 396
2013 6661 1433 1300 986 880 719 712 635 549 484 452 425 429 388 406 413 384
2014 6515 1373 1150 977 774 672 625 555 555 460 469 374 386 403 363 379 361
2015 6888 1332 1103 850 767 644 530 521 444 445 425 370 329 339 351 367 339
2016 6843 1284 1051 824 689 615 529 483 447 404 387 369 356 300 311 320 328
2017 7141 1279 979 815 662 534 549 470 422 394 373 315 311 335 303 294 346
2018 6874 1377 992 757 555 498 479 452 394 405 385 359 339 331 281 324 310
51
Note: Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average, working < 20 % of full-time employment.
52
Table A4. Number of Children Age 1-7 Who Experienced Economic Exclusion for the First Time for Years 1987-2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1987 676
1988 724 478
1989 862 564 453
1990 1005 585 488 429
1991 1010 629 456 389 345
1992 1050 622 467 428 327 320
1993 1444 834 618 548 429 405 359
1994 779 498 358 348 309 271 261 240
1995 838 548 435 380 334 309 290 235 207
1996 982 565 499 423 364 333 274 269 237 196
1997 1075 607 571 485 438 353 324 284 247 231 207
1998 1125 648 565 474 430 404 323 324 266 224 219 169
1999 1026 647 532 439 423 324 338 300 254 223 197 169 157
2000 1099 662 615 529 506 420 446 368 284 245 251 230 192 156
2001 1264 697 600 566 510 436 450 405 351 312 263 260 201 148 278
2002 974 577 485 441 395 331 315 317 276 251 220 167 143 141 189 129 2003 931 593 522 460 390 340 314 321 266 274 222 220 171 155 219 176 119
2004 1313 845 721 666 573 496 476 432 402 346 328 290 223 217 293 190 164
2005 1442 757 682 664 549 479 463 442 435 350 362 299 256 232 337 220 178
2006 1359 691 556 507 439 449 373 356 331 310 296 279 233 193 317 210 147
2007 1304 628 553 507 481 449 417 356 348 293 279 267 238 204 310 234 164
2008 1285 579 520 421 367 358 351 335 278 251 238 264 232 230 297 215 188
2009 1420 671 543 491 452 379 417 396 349 285 297 255 250 232 390 253 204
2010 1603 747 600 560 491 410 402 414 386 338 321 299 267 262 451 325 244
2011 1513 624 514 505 468 383 361 360 317 304 309 289 232 218 403 317 240
2012 1099 574 454 440 384 358 290 289 295 292 287 218 244 188 346 275 215
2013 1246 570 524 413 391 333 304 302 301 265 290 264 271 207 409 286 248
2014 1428 733 624 544 466 387 380 366 316 273 276 265 255 196 397 288 243
2015 1490 614 537 421 387 322 309 300 272 252 245 240 206 231 401 272 194
2016 1776 917 649 549 486 370 364 348 332 292 261 272 237 204 477 318 271
2017 2802 1111 873 725 572 556 487 476 450 409 372 351 350 325 701 463 398
2018 2671 908 681 575 424 392 379 335 320 325 282 268 256 228 496 308 248
53
Note: Economic exclusion is defined as simultaneously experiencing both income poverty and household labor market exclusion. Income poverty is defined as having a
household income below 50 % of the income median. Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average,
working < 20 % of full-time employment.
54
Table A5. Income Poverty Thresholds in Our
Sample – Presented Raw and Deflated (with 2017
as the Base Year)
Year 50 % of Median 50 % of Median
(deflated)
1987 44433 82099
1988 46842 82806
1989 49208 83018
1990 50942 83740
1991 53047 85157
1992 54701 85996
1993 56003 86966
1994 59780 91012
1995 61833 92208
1996 63833 93222
1997 65763 93979
1998 68483 96097
1999 70549 96590
2000 72903 96983
2001 75383 97969
2002 78575 99706
2003 80886 100539
2004 85538 105106
2005 88079 106303
2006 90757 107494
2007 93074 108382
2008 95427 107469
2009 97892 108807
2010 104266 113279
2011 106042 112123
2012 107954 111463
2013 109975 112667
2014 112614 114716
2015 114265 115874
2016 116362 117693
2017 119445 119445
2018 122851 121889
Note: Income poverty is defined as having a household
income below 50 % of the income median. We calculate the
annual median using all households in Denmark.
55
Table A6. Number of Children Ages 1-17 whose Household Experienced Income Poverty for Years 1987-2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1987 1276 1063 978 961 1011 1007 1015 959 1011 927 955 982 918 812 1022 829 650
1988 1292 1184 1109 997 929 966 931 961 943 996 915 982 928 831 1105 919 727
1989 1470 1331 1222 1164 1041 1007 984 1010 993 1004 965 958 876 929 1187 951 803
1990 1672 1438 1354 1237 1122 1056 1029 1037 1051 1065 1046 1005 982 859 1290 1055 813
1991 1565 1436 1221 1173 1071 958 938 879 948 818 961 865 901 797 1084 987 804
1992 1652 1382 1290 1133 1086 1010 938 871 903 848 909 913 825 827 1123 957 859
1993 2064 1742 1500 1384 1208 1173 1089 1007 919 948 887 883 872 793 1208 1041 808
1994 1251 1180 1024 960 958 845 848 815 681 670 653 634 597 579 889 739 561
1995 1605 1359 1181 1101 1023 1003 892 851 802 726 657 619 589 537 887 727 570
1996 1639 1339 1325 1159 1065 1001 918 939 820 785 705 625 587 545 825 747 548
1997 1591 1321 1259 1166 1133 1026 942 906 853 792 754 688 581 535 801 681 564
1998 1636 1344 1321 1223 1132 1104 999 988 935 798 802 723 609 497 854 674 567
1999 1517 1369 1259 1202 1132 1008 1051 967 956 873 808 760 667 527 798 716 541
2000 1588 1391 1389 1281 1304 1222 1232 1172 1055 987 919 883 725 678 955 760 569
2001 1833 1443 1394 1441 1344 1295 1319 1230 1226 1088 1061 968 829 672 1120 846 638
2002 1503 1266 1153 1130 1118 989 1044 1042 908 916 810 733 706 565 786 654 502
2003 1446 1303 1311 1179 1085 1100 1034 1011 1006 968 913 843 745 624 920 717 557
2004 1750 1632 1491 1542 1366 1330 1327 1270 1241 1144 1140 1059 922 818 1152 925 754
2005 1961 1746 1690 1620 1568 1467 1407 1462 1445 1331 1276 1231 1206 961 1365 1091 857
2006 1931 1765 1586 1559 1398 1470 1326 1244 1251 1150 1167 1142 1016 927 1259 976 820
2007 1992 1793 1728 1708 1594 1533 1559 1419 1363 1368 1274 1223 1210 1013 1411 1123 916
2008 2098 1813 1823 1774 1680 1667 1612 1647 1488 1424 1422 1362 1333 1254 1549 1304 1135
2009 2169 1807 1683 1671 1687 1561 1583 1557 1589 1418 1426 1312 1345 1254 1723 1405 1220
2010 2264 1887 1820 1733 1702 1653 1580 1721 1570 1564 1419 1401 1349 1240 1793 1549 1329
2011 2221 1933 1732 1761 1644 1579 1584 1629 1667 1547 1587 1388 1331 1233 1825 1526 1310
2012 1696 1647 1546 1507 1493 1431 1366 1440 1432 1414 1339 1274 1214 1071 1659 1423 1210
2013 1810 1554 1554 1482 1399 1349 1312 1357 1391 1359 1369 1300 1290 1095 1673 1478 1264
2014 2017 1728 1586 1629 1575 1408 1465 1372 1403 1344 1390 1340 1317 1199 1784 1512 1324
2015 2126 1667 1609 1446 1486 1387 1358 1340 1247 1319 1248 1301 1277 1230 1821 1500 1255
2016 2424 2139 1809 1682 1609 1559 1538 1550 1501 1464 1404 1400 1365 1290 2110 1819 1601
2017 3665 2699 2437 2158 1949 1876 1884 1897 1863 1804 1776 1722 1757 1695 2764 2393 2119
56
2018 3521 3245 2484 2357 1929 1799 1790 1785 1779 1777 1714 1672 1633 1641 2545 2202 1931
Note: Income poverty is defined as having a household income below 50 % of the income median.
57
Table A7. Number of Children Ages 1-17 who Experienced Household Labor Market Exclusion for Years 1987-2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1987 5240 4090 3815 3662 3630 3566 3665 3603 3590 3388 3432 3797 3689 3687 4021 3864 3837
1988 6393 5212 4664 4225 3983 4012 3913 3907 3855 3879 3757 3733 4069 3994 4157 4341 4012
1989 7173 6112 5527 5004 4471 4337 4409 4134 4255 4193 4086 4062 4164 4513 4464 4657 4611
1990 7975 6691 6192 5466 5055 4593 4332 4466 4269 4413 4418 4335 4229 4372 4799 4721 4538
1991 8500 7321 6598 6144 5431 4966 4552 4299 4389 4295 4466 4489 4422 4477 4600 4986 4754
1992 8998 7690 7113 6580 6011 5381 4963 4437 4365 4545 4347 4529 4564 4464 4560 4782 4989
1993 9990 8317 7623 7348 6549 6039 5500 5036 4578 4523 4620 4529 4650 4809 4763 4862 4817
1994 9850 8915 7851 7331 6879 6171 5692 5205 4713 4300 4201 4252 4172 4375 4521 4520 4428
1995 9801 8955 8155 7247 6629 6277 5599 5126 4619 4220 3849 3896 3899 3880 4175 4213 4104
1996 9686 8742 7964 7249 6490 6043 5555 4973 4558 4205 3903 3575 3616 3746 3734 3975 3880
1997 10389 9362 8692 8062 7493 6605 6225 5657 5298 4838 4507 4123 3838 3895 4065 4048 4268
1998 9748 8274 7989 7428 6924 6494 5806 5419 4979 4632 4426 4019 3789 3542 3691 3830 3697
1999 8979 8449 7661 7312 6811 6370 6063 5453 5101 4706 4444 4113 3809 3665 3442 3548 3551
2000 9002 7659 7736 7070 6834 6394 6085 5711 5156 4822 4544 4311 3962 3748 3538 3447 3304
2001 9063 7526 6916 7003 6530 6275 5840 5672 5363 4770 4595 4329 4045 3825 3641 3474 3159
2002 9359 8162 7524 6965 6964 6473 6364 6055 5785 5552 4939 4748 4539 4254 3999 3797 3446
2003 9071 8113 7696 7198 6600 6570 6367 6262 5986 5690 5615 4975 4907 4615 4363 4131 3825
2004 8859 7975 7961 7807 7169 6683 6709 6363 6330 6047 5737 5710 5146 4970 4819 4515 4205
2005 8132 7188 7282 7247 7057 6573 6243 6303 5983 5999 5716 5548 5487 5054 4990 4782 4314
2006 7205 6195 6257 6280 6266 6149 5831 5535 5574 5343 5446 5151 5055 5025 4721 4654 4241
2007 6542 5347 5330 5322 5445 5569 5481 5179 4948 5018 4917 5004 4754 4765 4760 4494 4299
2008 6066 4848 4846 4804 4772 4928 4928 4978 4679 4424 4604 4532 4627 4457 4447 4454 4165
2009 7378 5935 5710 5498 5502 5408 5648 5674 5626 5302 5194 5222 5229 5301 5296 5126 5005
2010 7438 6530 6227 6021 5801 5845 5795 6102 6085 6093 5834 5568 5730 5646 5854 5819 5563
2011 6882 5753 5930 5703 5695 5502 5512 5502 5834 5824 5944 5660 5488 5610 5661 5748 5520
2012 6771 6100 5920 5956 5777 5789 5590 5775 5751 5977 6031 6071 5858 5759 5984 5891 5933
2013 6860 5883 6009 5908 5907 5711 5834 5728 5791 5839 6098 6165 6278 5997 5937 6159 5943
2014 6703 5790 5581 5839 5712 5759 5639 5750 5804 5770 5919 6163 6238 6340 6034 6070 6121
2015 7085 5607 5531 5395 5587 5524 5606 5484 5546 5671 5717 5831 6059 6238 6322 6011 5913
2016 7046 5802 5328 5191 5139 5330 5226 5388 5341 5483 5468 5572 5689 5888 6095 6228 5935
2017 7391 5639 5316 4925 4825 4752 5031 4898 5102 5074 5210 5211 5365 5496 5707 5933 6050
2018 7022 6041 5177 4995 4498 4433 4508 4706 4677 4962 4968 5088 5085 5309 5437 5673 5772
Note: Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average, working < 20 % of full-time employment.
58
Table A8. Number of Children Ages 1-17 Who Experienced Economic Exclusion for Years 1987-2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1987 798 607 533 530 525 506 498 462 487 431 437 467 434 372 535 390 317
1988 815 716 613 545 454 495 478 471 451 468 408 427 409 374 517 437 311
1989 985 827 759 637 569 546 519 520 521 466 476 472 428 430 593 493 406
1990 1150 941 839 765 648 571 568 600 560 579 516 507 508 443 679 539 425
1991 1168 984 797 741 666 588 526 476 542 456 562 464 491 440 616 568 439
1992 1249 965 864 727 659 610 567 481 506 507 489 491 467 427 628 570 483
1993 1646 1324 1085 991 822 764 697 656 556 588 553 537 511 472 759 653 478
1994 957 842 721 649 633 569 531 507 406 396 373 374 355 334 545 456 348
1995 1193 1007 827 751 667 649 580 548 497 435 383 372 360 318 555 464 344
1996 1241 1012 982 798 734 678 597 595 490 515 414 388 356 322 499 467 336
1997 1273 1014 950 851 806 712 640 582 566 512 479 431 362 326 534 426 351
1998 1290 1032 974 899 803 771 673 663 616 533 521 453 385 301 573 457 371
1999 1192 1034 945 842 806 682 713 631 612 545 515 461 416 325 535 461 353
2000 1266 1061 1071 955 933 879 877 797 692 651 611 598 464 444 632 509 378
2001 1461 1148 1053 1102 968 917 938 863 828 733 699 628 542 412 743 558 421
2002 1153 946 851 826 779 667 687 691 610 565 510 452 424 373 492 402 302
2003 1112 966 924 840 759 729 671 674 623 650 577 529 465 399 557 446 353
2004 1477 1320 1190 1213 1072 999 997 958 910 830 830 750 628 567 806 634 528
2005 1581 1382 1313 1271 1200 1137 1049 1112 1048 975 919 891 819 682 947 780 586
2006 1527 1320 1193 1130 985 1041 922 869 838 788 772 737 677 595 815 673 541
2007 1483 1249 1189 1174 1059 1006 1005 878 856 815 779 743 684 602 830 696 545
2008 1452 1146 1152 1091 998 971 899 936 788 737 752 719 672 627 846 679 585
2009 1603 1290 1146 1131 1123 1034 1048 985 989 840 840 768 789 700 1032 813 674
2010 1784 1437 1366 1257 1227 1151 1117 1217 1099 1071 954 902 873 823 1184 1001 828
2011 1656 1400 1243 1265 1143 1121 1099 1121 1136 1020 1084 905 846 786 1196 1020 851
2012 1244 1170 1083 1065 1050 974 948 1003 963 971 925 882 793 706 1105 973 822
2013 1405 1143 1152 1071 1014 971 918 992 972 945 965 930 932 767 1184 1060 887
2014 1571 1329 1212 1218 1176 1067 1068 1001 1011 963 1004 959 967 879 1276 1086 979
2015 1658 1253 1211 1061 1088 1030 1000 987 894 968 909 925 913 902 1343 1089 926
2016 1956 1664 1381 1240 1207 1130 1116 1118 1119 1043 1018 1002 965 916 1571 1329 1170
2017 3017 2095 1895 1658 1473 1441 1425 1429 1425 1367 1356 1326 1359 1272 2124 1832 1663
2018 2795 2500 1821 1754 1430 1288 1314 1275 1292 1325 1271 1237 1199 1216 1904 1660 1470
59
Note: Economic exclusion is defined as simultaneously experiencing both income poverty and household labor market exclusion. Income poverty is defined as having a
household income below 50 % of the income median. Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average,
working < 20 % of full-time employment.
60
Table A9. Distribution of the Number of Years in Economic Exclusion During Childhood (Age 1-17), for the Group of Children Experiencing at Least One
Year of Economic Exclusion, Birth Cohorts 1986-2001 (Who Can Be Followed Throughout Childhood)
Number of
Years
Frequency,
All
Percent,
All
Frequency,
Natives
Percent,
Natives
Frequency,
Descendants
Percent,
Descendants
1 56177 58.65 45117 64.59 11060 42.65
2 18866 19.70 13407 19.19 5459 21.05
3 9034 9.43 5712 8.18 3322 12.81
4 4671 4.88 2647 3.79 2024 7.80
5 2652 2.77 1295 1.85 1357 5.23
6 1708 1.78 759 1.09 949 3.66
7 998 1.04 388 0.56 610 2.35
8 609 0.64 206 0.29 403 1.55
9 414 0.43 144 0.21 270 1.04
10 227 0.24 61 0.09 166 0.64
11 172 0.18 41 0.06 131 0.51
12 97 0.10 26 0.04 71 0.27
13 60 0.06 18 0.03 42 0.16
14 45 0.05 9 0.01 36 0.14
15 23 0.02 8 0.01 15 0.06
16 19 0.02 7 0.01 12 0.05
17 11 0.01 5 0.01 6 0.02
Note: Income poverty is defined as having a household income below 50 % of the income median. Household labor market exclusion is defined as all working-aged adults (18-59) in the
household, on average, working < 20 % of full-time employment. Economic exclusion is defined as simultaneously experiencing both income poverty and household labor market exclusion.
The number of years is not confined to be consecutive.
61
Table A10. Age Specific Risks for Experiencing Income Poverty the First Time for Danish Children Aged 1-17, for Synthetic Cohorts 2003-
2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
2003 0.019 0.012 0.011 0.010 0.008 0.008 0.008 0.007 0.007 0.007 0.006 0.006 0.005 0.005 0.008 0.005 0.004
2004 0.024 0.016 0.013 0.013 0.011 0.010 0.010 0.009 0.009 0.008 0.008 0.007 0.006 0.006 0.009 0.006 0.005
2005 0.027 0.016 0.014 0.013 0.012 0.010 0.010 0.010 0.010 0.008 0.009 0.007 0.007 0.006 0.010 0.007 0.006
2006 0.026 0.015 0.012 0.012 0.010 0.011 0.009 0.008 0.008 0.007 0.008 0.007 0.007 0.006 0.009 0.006 0.005
2007 0.027 0.015 0.014 0.013 0.012 0.012 0.011 0.010 0.010 0.009 0.008 0.008 0.008 0.006 0.010 0.007 0.006
2008 0.029 0.016 0.015 0.013 0.013 0.012 0.012 0.012 0.011 0.010 0.010 0.009 0.009 0.009 0.011 0.009 0.008
2009 0.030 0.015 0.013 0.012 0.011 0.011 0.010 0.010 0.010 0.008 0.009 0.008 0.008 0.007 0.011 0.008 0.007
2010 0.031 0.015 0.013 0.012 0.011 0.010 0.010 0.010 0.009 0.009 0.008 0.008 0.007 0.006 0.011 0.009 0.007
2011 0.032 0.014 0.012 0.011 0.011 0.009 0.009 0.009 0.008 0.008 0.008 0.008 0.007 0.006 0.010 0.008 0.007
2012 0.023 0.013 0.010 0.010 0.009 0.008 0.007 0.007 0.008 0.007 0.007 0.005 0.006 0.005 0.008 0.006 0.006
2013 0.027 0.012 0.011 0.009 0.009 0.007 0.007 0.007 0.007 0.006 0.007 0.006 0.006 0.005 0.009 0.006 0.006
2014 0.031 0.016 0.012 0.012 0.010 0.008 0.008 0.008 0.007 0.006 0.006 0.006 0.005 0.004 0.009 0.006 0.005
2015 0.034 0.014 0.012 0.009 0.009 0.007 0.007 0.007 0.006 0.005 0.006 0.006 0.005 0.005 0.009 0.006 0.004
2016 0.038 0.021 0.015 0.013 0.010 0.009 0.008 0.008 0.007 0.007 0.006 0.006 0.006 0.005 0.011 0.007 0.007
2017 0.057 0.025 0.021 0.017 0.014 0.012 0.011 0.011 0.010 0.009 0.008 0.008 0.008 0.008 0.016 0.011 0.009
2018 0.053 0.021 0.016 0.015 0.010 0.010 0.009 0.008 0.007 0.008 0.007 0.007 0.006 0.006 0.012 0.007 0.006
Note: Income poverty is defined as having a household income below 50 % of the income median.
62
Table A11. Age-Specific Risks for Experiencing Household Labor Market Exclusion for the First Time for Danish Children Aged 1-17, for
Synthetic Cohorts 2003-2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
2003 0.127 0.035 0.029 0.023 0.018 0.017 0.014 0.014 0.013 0.010 0.011 0.009 0.009 0.009 0.009 0.009 0.009
2004 0.127 0.036 0.028 0.024 0.019 0.017 0.016 0.013 0.013 0.011 0.010 0.010 0.009 0.008 0.009 0.009 0.009
2005 0.116 0.028 0.023 0.019 0.017 0.014 0.013 0.012 0.011 0.009 0.009 0.009 0.008 0.008 0.008 0.008 0.008
2006 0.103 0.025 0.021 0.015 0.014 0.012 0.011 0.011 0.009 0.008 0.008 0.008 0.007 0.007 0.007 0.007 0.007
2007 0.094 0.022 0.018 0.015 0.012 0.010 0.010 0.009 0.008 0.008 0.007 0.007 0.007 0.006 0.007 0.007 0.006
2008 0.086 0.021 0.018 0.013 0.011 0.009 0.008 0.008 0.007 0.006 0.006 0.006 0.006 0.005 0.005 0.005 0.005
2009 0.105 0.033 0.029 0.022 0.017 0.016 0.012 0.013 0.011 0.010 0.010 0.010 0.009 0.009 0.010 0.009 0.009
2010 0.105 0.032 0.027 0.024 0.019 0.017 0.014 0.013 0.011 0.012 0.011 0.011 0.009 0.009 0.011 0.010 0.009
2011 0.101 0.023 0.021 0.018 0.016 0.014 0.012 0.011 0.010 0.008 0.009 0.008 0.008 0.007 0.007 0.007 0.008
2012 0.099 0.029 0.022 0.018 0.017 0.015 0.012 0.013 0.011 0.009 0.010 0.009 0.009 0.008 0.008 0.008 0.007
2013 0.107 0.025 0.023 0.018 0.016 0.013 0.013 0.012 0.010 0.009 0.009 0.008 0.008 0.008 0.008 0.008 0.007
2014 0.106 0.026 0.021 0.018 0.014 0.012 0.012 0.010 0.011 0.009 0.009 0.007 0.007 0.008 0.007 0.007 0.007
2015 0.116 0.026 0.021 0.016 0.014 0.012 0.010 0.010 0.009 0.009 0.008 0.007 0.006 0.006 0.007 0.007 0.007
2016 0.113 0.026 0.021 0.016 0.013 0.012 0.010 0.009 0.008 0.008 0.007 0.007 0.007 0.006 0.006 0.006 0.006
2017 0.115 0.025 0.020 0.016 0.013 0.010 0.011 0.009 0.008 0.008 0.007 0.006 0.006 0.007 0.006 0.006 0.007
2018 0.105 0.026 0.020 0.016 0.011 0.010 0.009 0.009 0.007 0.008 0.007 0.007 0.007 0.006 0.006 0.006 0.006
Note: Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average, working < 20 % of full-time employment.
63
Table A12. Age-Specific Risks for Experiencing Economic Exclusion for the First Time for Danish Children Aged 1-17, for Synthetic
Cohorts 2003-2018
Age
Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
2003 0.014 0.009 0.008 0.007 0.006 0.005 0.005 0.005 0.004 0.004 0.004 0.004 0.003 0.003 0.004 0.003 0.002
2004 0.020 0.013 0.011 0.010 0.009 0.008 0.008 0.007 0.006 0.006 0.005 0.005 0.004 0.004 0.006 0.004 0.003
2005 0.022 0.012 0.011 0.010 0.009 0.008 0.007 0.007 0.007 0.005 0.006 0.005 0.004 0.004 0.006 0.004 0.004
2006 0.021 0.011 0.009 0.008 0.007 0.007 0.006 0.006 0.005 0.005 0.005 0.005 0.004 0.003 0.006 0.004 0.003
2007 0.020 0.010 0.009 0.008 0.008 0.007 0.007 0.006 0.006 0.005 0.004 0.004 0.004 0.003 0.005 0.004 0.003
2008 0.020 0.009 0.008 0.007 0.006 0.006 0.006 0.005 0.004 0.004 0.004 0.004 0.004 0.004 0.005 0.004 0.003
2009 0.022 0.010 0.009 0.008 0.007 0.006 0.007 0.006 0.006 0.005 0.005 0.004 0.004 0.004 0.006 0.004 0.004
2010 0.024 0.012 0.010 0.009 0.008 0.007 0.007 0.007 0.006 0.006 0.005 0.005 0.004 0.004 0.007 0.005 0.004
2011 0.024 0.010 0.008 0.008 0.008 0.006 0.006 0.006 0.005 0.005 0.005 0.005 0.004 0.004 0.006 0.005 0.004
2012 0.017 0.009 0.007 0.007 0.006 0.006 0.005 0.005 0.005 0.005 0.005 0.004 0.004 0.003 0.006 0.004 0.003
2013 0.021 0.009 0.009 0.007 0.006 0.005 0.005 0.005 0.005 0.004 0.005 0.004 0.004 0.003 0.007 0.005 0.004
2014 0.024 0.013 0.010 0.009 0.008 0.006 0.006 0.006 0.005 0.005 0.005 0.004 0.004 0.003 0.007 0.005 0.004
2015 0.026 0.011 0.009 0.007 0.006 0.005 0.005 0.005 0.005 0.004 0.004 0.004 0.003 0.004 0.007 0.005 0.003
2016 0.031 0.017 0.012 0.010 0.008 0.006 0.006 0.006 0.006 0.005 0.004 0.005 0.004 0.003 0.008 0.005 0.005
2017 0.047 0.020 0.017 0.013 0.011 0.010 0.009 0.008 0.008 0.007 0.007 0.006 0.006 0.006 0.013 0.008 0.007
2018 0.042 0.016 0.013 0.011 0.008 0.007 0.007 0.006 0.005 0.006 0.005 0.005 0.004 0.004 0.009 0.005 0.004
Note: Economic exclusion is defined as simultaneously experiencing both income poverty and household labor market exclusion. Income poverty is defined as having a
household income below 50 % of the income median. Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average,
working < 20 % of full-time employment.
64
Table A13. Municipalities and Municipality Codes in Denmark
Code Municipality Code Municipality Code Municipality
101 København 316 Holbæk 607 Fredericia
147 Frederiksberg 320 Faxe 615 Horsens
151 Ballerup 326 Kalundborg 621 Kolding
153 Brøndby 329 Ringsted 630 Vejle
155 Dragør 330 Slagelse 657 Herning
157 Gentofte 336 Stevns 661 Holstebro
159 Gladsaxe 340 Sorø 665 Lemvig
161 Glostrup 350 Lejre 671 Struer
163 Herlev 360 Lolland 706 Syddjurs
165 Albertslund 370 Næstved 707 Norddjurs
167 Hvidovre 376 Guldborgsund 710 Favrskov
169 Høje-Taastrup 390 Vordingborg 727 Odder
173 Lyngby-Taarbæk 400 Bornholm 730 Randers
175 Rødovre 410 Middelfart 740 Silkeborg
183 Ishøj 411 Christiansø 741 Samsø
185 Tårnby 420 Assens 746 Skanderborg
187 Vallensbæk 430 Faaborg-Midtfyn 751 Aarhus
190 Furesø 440 Kerteminde 756 Ikast-Brande
201 Allerød 450 Nyborg 760 Ringkøbing-Skjern
210 Fredensborg 461 Odense 766 Hedensted
217 Helsingør 479 Svendborg 773 Morsø
219 Hillerød 480 Nordfyns 779 Skive
223 Hørsholm 482 Langeland 787 Thisted
230 Rudersdal 492 Ærø 791 Viborg
240 Egedal 510 Haderslev 810 Brønderslev
250 Frederikssund 530 Billund 813 Frederikshavn
253 Greve 540 Sønderborg 820 Vesthimmerlands
259 Køge 550 Tønder 825 Læsø
260 Halsnæs 561 Esbjerg 840 Rebild
265 Roskilde 563 Fanø 846 Mariagerfjord
269 Solrød 573 Varde 849 Jammerbugt
270 Gribskov 575 Vejen 851 Aalborg
306 Odsherred 580 Aabenraa 860 Hjørring
Note: From 2007 and forward, there are 98 municipalities in Denmark. ‘Christiansø’ has a special status, as it is not a
municipality itself, nor does it belong to another municipality, why it has its own code (411).
65
Fig A1. Synthetic Cohort Estimates of the Cumulative Risk of Experiencing Household Income
Poverty, Labor Market Exclusion, and Economic Exclusion Across Childhood (age 1-17) – Using
Legal Parents as Opposed to Household Adults in Terms of Income Poverty and Economic Exclusion
Note: Recession years (with a negative GDP growth) are shaded. Income poverty is defined as having a household income
below 50 % of the income median. Household labor market exclusion is defined as all working-aged adults (18-59) in the
household, on average, working < 20 % of full-time employment. Economic exclusion is defined as simultaneously
experiencing both income poverty and household labor market exclusion.
66
Fig A2. Synthetic Cohort Estimates of the Cumulative Risk of Experiencing Household Income
Poverty, Labor Market Exclusion, and Economic Exclusion Across Childhood (age 1-17) – Students
and Self-employed Households are Dropped Prior to Median Calculation of Income Poverty (and
Economic Exclusion).
Note: Recession years (with a negative GDP growth) are shaded. OECD poverty is defined as having a household income
below 50 % of the income median. Income poverty is defined as having a household income below 50 % of the income
median. Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average,
working < 20 % of full-time employment. Economic exclusion is defined as simultaneously experiencing both income
poverty and household labor market exclusion.
67
Fig A3. Birth Cohort Estimates of the Cumulative Risk of Experiencing Household Income Poverty,
Labor Market Exclusion, and Economic Exclusion Across Childhood (age 1-17.
Note: This figure is based upon birth cohorts born 1986-2000, who turn 17 from 2003-2018. The inputs are the number of
first entries into poverty for a given birth cohort (which can be obtained by summarizing numbers from the incidents
tables A2-A4). The population used to estimate the cumulative risks are the population from A1, where we assume no
mortality and no migration. The estimates are obtained by dividing the sum of first incidents for a given birth cohort and
indicator, from age 1-17, with the population size of the given birth cohort. Income poverty is defined as having a
household income below 50 % of the income median. Household labor market exclusion is defined as all working-aged
adults (18-59) in the household, on average, working < 20 % of full-time employment. Economic exclusion is defined as
simultaneously experiencing both income poverty and household labor market exclusion.
68
Fig A4. Age-Specific Risks for Experiencing Income Poverty for the First Time for Danish
Children Aged 1-17, for the Synthetic Cohorts; 2006, 2010, 2014 and 2018.
Note: Income poverty is defined as having a household income below 50 % of the income median.
69
Fig A5. Age-Specific Risks for Experiencing Household Labor Market Exclusion for the First Time
for Danish Children Aged 1-17, for the Synthetic Cohorts; 2006, 2010, 2014 and 2018.
Note: Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average,
working < 20 % of full-time employment.
70
Fig A6. Synthetic Cohort Estimates of the Cumulative Risk of Experiencing at Least Two Years in
Experiencing Household Income Poverty, Labor Market Exclusion, and Economic Exclusion Across
Childhood (age 1-17), by Immigrant Background.
Note: Recession years (with a negative GDP growth) are shaded. Income poverty is defined as having a household income
below 50 % of the income median. Household labor market exclusion is defined as all working-aged adults (18-59) in the
household, on average, working < 20 % of full-time employment. Economic exclusion is defined as simultaneously
experiencing both income poverty and household labor market exclusion.
71
Fig A7. The Geographical Distribution of Synthetic Cohort Estimates of the Cumulative Risk of
Experiencing Income Poverty Across Childhood (age 1-17), at the Birth Municipality Level.
Note: Income poverty is defined as having a household income below 50 % of the income median.
72
Fig A8. The Geographical Distribution of Synthetic Cohort Estimates of the Cumulative Risk of
Experiencing Household Labor Market Exclusion Across Childhood (age 1-17), at the Birth
Municipality Level.
Note: Household labor market exclusion is defined as all working-aged adults (18-59) in the household, on average,
working < 20 % of full-time employment.
73
Appendix B: Main Results using Statistics Denmark’s Alternative Income Poverty Definition
Fig B1.