New approach for defining multidimensional deprivation
Abstract
The authors propose a new measure of deprivation based on three dimensions for the
European Union. This paper argues that the proposed deprivation index both conceptually
and empiracally is able to capture deprivation more realistically than the existing
deprivation index. The proposed deprivation dimensions are based on joint decisions on
which substances are more important to ensure a good standard of living, regardless of
people's preferences and the capacity to meet living standards. Material deprivation is
typically indicator in EU-SILC that constructs the inability to afford some items considered
by individuals to be an essential to lead an accurate life.
Deprivation is a wider topic than poverty itself because the concept of deprivation includes
monetary, social exclusion, and living condition aspects which prevent people from
accessing their desired way of life. The indicators of the deprivation index differ from
country to country due to variations in political and social environments. The foundation
of the calculations used in this study is the SILC database provided by Eurostat and Turkish
statistical office. The suggested method can be used to create comprehensive perspective
of people living in deprivation.
Keywords: poverty, deprivation, multidimensional deprivation
1
INTRODUCTION
Methodologically, the Eurostat does not properly illustrate the European population living
conditions. The aim of this paper to identify significant items for a new method to measure
the deprivation index in three dimensions. Because, as it is agreed and published by
scientist which are described below in the literature. Deprivation is the outcome of a lack
of monetary resources. For that reason, in order to measure deprivation, it should be
considered more than one dimension. Current social scientists and researchers approach the
topic of deprivation and poverty by using a wider lens that focuses not only on one’s
economics, but also on one’s living conditions, housing and environment. Based on our
definition, using multidimensional approach will capture more people deprived within
European Union. Ideas about deprivation is one of the challenging, conceptualizing topics
for all scientists and policy makers. In this new improvement of the deprivation definition,
our approach will facilitate developing, implementing and assessing new and more
effective comparability studies among the countries. However, to focus on what really
matters for those countries, their populations and indeed, their households and individuals
who cannot afford minimal number of unmet fundamental needs. This paper analyzes
several factors including more indices of conditions for individuals rather than just general
deprivation measures additionally provides brief cross-country comparative analysis using
the EU-SILC and TUIK datasets.
The core of this paper is derived from of the famous nobel prize economist Amartya Sen
who clearly emphasized that the main bridge between development and freedom is poverty
as measured holistically related to deprivation of basic needs as opposed to univariably
related to level of income. There are several dimensions of well-being of individuals that
are not captured by income indicators. Sen mentions that the well-being of an individual is
best captured as an index of the individual’s behaviors (Sen, 1985). In his study, behaviors
are an expression of the state of a person and a reflection of what he or she can manage
based on their available resources. Therefore, well-being approach focuses on the varieties
of the resources available for the individual to select one of this option freely then exercise
it. Thus, living is approached as combination of many things “doings and beings” with
quality of life to be able to reach in terms of the capabilities to achieve to behave.
Multidimensional poverty measurement started in early 1980s, when the first studies were
published that analyzed poverty and social exclusion using non-financial indicators. The
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first scientists who attempted to analyze poverty were Peter Townsend in 1979, Joanna
Mack and Stewart Lansley in 1985 and Tim Callan, Brian Nolan and Christopher T.
Whelan in 1993.
In 1979, Townsend created a multidimensional deprivation index using sixty indicators that
reflect living conditions and provide information on food, clothing, health, entertainment,
household goods and consumer durables. Out of these sixty indicators he randomly chose
twelve of them. Townsend set cut-off of five out of twelve to identify the deprived people.
He created the multidimensional deprivation index with a simple breakdown of indicators
of goods and services. With this multidimensional deprivation indicator, Townsend wanted
to identify the level of income where the amount of deprivation increased enormously, orin
other words, where the living conditions were severely reduced. This income level was
labeled as the poverty threshold. His study was adopted by other researchers and inspired
the work on poverty and social exclusion in Europe. In particular, in 1985, Mack and
Lansley established another multidimensional poverty indicator.
They differentiated
between the main indicators, between compulsory and voluntary scarcity, and thought that
there was deprivation only when there is a lack of a good or service also a product was not
compulsory for individual or family’s choices. Mack and Lansley used thirty-five
indicators, selecting eighteen to create a deprivation index. With this breakdown indicator,
the population was classified as follows: all those deprived of the goods and services
included in the reduced eighteen indicator group were considered deprived. In this case,
Mack and Lansley used their multidimensional deprivation index to directly measure
deprivation.
In 1993, Callan, Nolan and Whelan conducted a study in which they aimed to deepen the
link between income and material living conditions. Living conditions were measured
directly using non-monetary indicators. The method used can be summarized as follows:
It began with a group of twenty-four indicators, and, using a factor method, the authors
examined whether the different conditions, goods and services considered in the indicators
were classified into different groups (clusters).
These clusters defined the possible
dimensions of material deprivation. When deprived of basic grouped goods, services or
living conditions, they regarded a person as poor (according to their multidimensional
deprivation criteria). It was not taken into consideration because it was considered that it
did not include actual needs or that the included needs were due to specific factors not
associated with general material deprivation definition. This study compared the
characteristics of poor groups of individuals using this deprivation index and the indicator
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collected when applying monetary poverty. The authors found out that many individuals
who were not classified as financially poor had material deprivation, they found some
individuals who were considered financially poor but did not have deprivation.
Later research efforts focused on developing a European multidimensional deprivation
index. Building upon the work of prior social scientists and researchers, the European
Statistical Office (Eurostat), the sub-group of indicators of the Social Assistance Council,
is developing a methodology for the creation of non-monetary indicators of deprivation.
Although these indicators are not intended to cover all areas of social exclusion, but they
provide information that supplements the information already provided by other social
exclusion indicators.
Eurostat published two reports on multidimensional material deprivation (2000 and 2003)
and an article in 2005. The official methodology to be adopted by Eurostat nowadays is
based on these two prior reports. Nowadays, Eurostat publishes material deprivation and
severe deprivation statistics based on the Statistics on Income and Living Conditions
survey. Anne-Catherine Guio has published a material deprivation study in 2005. This
study describes the conditions in a household, the availability of durable goods, delays in
payments and inability to meet basic material needs. Several elements used to detect
material deprivation, goods, services and material living conditions were taken as the main
indicators. Guio (2017) sets a new indicator based on thirteen items where seven
deprivation items relate to person’s household and six to the individual herself or himself.
Individual items are collected at the adult level for all persons in the household aged 16 or
above to allow for new indicators related to gender and age for those who live in the same
household.
The dimensions Guio (2017) used are as follows; Economic difficulties are defines as being
able to afford holidays away from home for at least one week a year, delays in mortgage,
rent, water, electricity payments, shopping paid for in instalments, being able to afford
meat, chicken or fish (or the vegetarian equivalent) at least every other day, being able to
maintain the dwelling at an adequate temperature during the cold months). Durable goods
are defined as colour TV, telephone. car for personal use). Dwelling (The existence of leaks,
damp in the walls, floors, ceilings or foundations or rotten, floors, window or door frames,
shortage of natural light in a room, bathroom or shower in the dwelling, toilet with running
water inside the dwelling for the household's exclusive use).
But later, Guio’s methodology has criticized by researchers. Bruder (2014) postulated in
her study that material deprivation should be modified with new indices. In Bruder’s study,
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she argues that some items should be replaced such as “having a mobile phone”. This item
should not be considered as a sign of deprivation because almost all people have a cell
phone within European Union. Boarini, and Mira d'Ercole (2006) studied data from OECD
countries with the goal to create suitable survey questions to measure comparative analysis
for more satisfactory deprivation analyses. The paper proposes a broad motion to
deprivation based on its objective and subjective components. They suggest that the scope
of the deprivation should be reconstructed from survey questioners in order identify those
people who need targeted social policies. Further analyses carried out out of non-European
countries by Bruder et al.
(2019) studied Turkish poverty to find exact causes of
deprivation in Turkey. Turkey has one of the highest rates of material deprivation (28.7%)
based on 2017 European measures. Another statistical method of multidimensional
measurement was created by Hungarian scientist Ottó Hajdu in 2007. The aim of his paper
was unique and focused on estimating the relationship between poverty, deprivation and
social exclusion without differentiating between society’s poor and non-poor.
The multidimensional poverty index continues to be adopted by many scientists. Recently,
Alkire (Alkire & Foster, 2015) created a multidimensional poverty index (MPI) for use in
studying African countries based on three dimensions; education, health and basic needs.
This MPI was adopted by the United Nations for use in reporting multidimensional poverty.
Indicators that are commonly used in the European Union allow comparisons across
various time periods. International comparisons do not require basic indicators to be the
same in all countries. It is enough that the aggregate key indicators (even if different in
each country) bring together the same information. However, if we want to use harmonized
data across Europe, the solution would be to use existing harmonized information and
therefore will include the same key indicators in all countries.
2
DATA/METHOD
This chapter documents and gives detailed account of the materials and methods used to
conduct the process for defining deprivation and the methodology for defining each
dimension. A critical lens is applied to the current standard processes of collecting and
defining deprivation in Europe considered normative in academic and social policy venues.
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Each dimension and their indices are examined after revieweing the available literature in
order to develop the methodology used in this study. Then, additional dimensions are added
which compare the results of an individual-level of the authors new definition of
deprivation for selected countries with an individual-based measure. The study utilizes two
main sets of data derived from the Statistics on Income and Living Conditions Survey. The
first data set for this study was provided by Eurostat and covers the years 2005 to 2017 and
the second Turkish data set was provided by the Turkish Statistical Institute (Tuik) and
covers the same timespan, 2005 to 2017. At the writing of this paper, 2005-2017 is the most
recent and available time periods for the data. Selected countries were utilized in this study
based on the data where there is high gap between years in terms of three dimensions.
In the next section, each dimension is described based on the main concepts and
methodology and how deprivation is interpreted. Lastly, different dimensions of
deprivation and the selection of each of them are proposed. Economic strain, living
condition, housing and environmental conditions are the basis for this study’s proposed
multidimensional deprivation index.
2.1
Economic Strain
In general, there are large cross-country differences based on items considered within the
indices of economic strain. The economic strain index is comprised of four items. The first
item refers to being able to afford a holiday away from home and captures the total
population of those who are incapable of paying for a yearly holiday. The second item
refers to the percentage of people in the total population who are unable to eat meat,
chicken, or fish (or the vegetarian equivalent) every two days. The third item refers to the
facing of unexpected financial expenses means the percentage of those are unable to face
unexpected financial expenses. The last item refers to overdue payables which means the
percentage of people in the total population who are not able to pay their debts (mortgages
or leases, invoices or lease purchases, inability to pay utilities).
For the last item on overdue payables, an additional dimension was added in order to
capture the subtle difference between the inability pay a debt for one month or more than
one month. This last item is measured by the following question in the EU-SILC data:
“Arrears on mortgage or rental payments, utility bills and other loan payments”
1. Yes (Once)
2. Yes (Twice or more)
6
3. No
4. There is no such kind of payment
People who are deprived in this example are those ones who answer second option (Yes,
(Twice or more)). Selection of this option is that those who could not pay just once would
not be deprived because, there would be other reason why they could not pay their
mortgages or other payments. Other indices are also selected based on worst cases where
people are facing financial difficulties twice or more.
These items are types of deprivation whose enforced experience involves exclusion from a
minimally acceptable way of life. Items on this dimension is relatively homogeneous.
Our economic strain formula is applied based Eurostat selection which is 33% of total
items.
Where:
DEco (dholiday + dmeat + dunexpected + dmorgage) > 2
Where:
dholiday = Capacity to afford paying for one-week annual holiday away from home
dmeat = Capacity to afford a meal with meat, chicken, fish (or vegetarian equivalent) every
second day
dunexpected = Capacity to face unexpected financial expenses
dmorgage = Arrears on mortgage or rental payments, utility bills and other loan payments
Based on our definition on economic strain, table 1 created in selected countries (Those
countries where data is missing in any years is excluded).
Table 1. Share of deprived population in Economic Strain (in %) in selected
countries
Country List
BG
2005
-
2009
71.5%
2013
79.2%
2017
70.0%
CZ
56.5%
50.3%
52.7%
35.5%
EE
70.0%
56.8%
59.6%
45.8%
HU
77.1%
82.5%
82.4%
52.6%
LT
80.5%
62.1%
66.0%
59.7%
7
LV
86.4%
81.2%
78.4%
67.8%
PL
79.3%
68.9%
68.7%
51.3%
RO
-
79.7%
78.8%
73.8%
SL
53.8%
52.4%
56.4%
46.0%
SK
77.2%
64.0%
59.7%
53.3%
TR
92.3%
99.4%
81.1%
63.9%
Source: Based on the SILC (EUROSTAT) and TUIK (note: all percentages are measured
with weighted cases)
The basic idea of economic strain is that individuals are not able to afford to pay their
mortgages, rents, utility bills and other expenses. The results reported in Table 1 shows the
changes in selected countries and how economic conditions items change over time. The
current literature defines deprivation as the consequence of income poverty where
individuals cannot afford a standard of living and are not able to maintain their basic needs.
The aim of Table 1 is to show how economic deprivation changes by year in selected
countries based on new proposed approach. From 2005 to 2017, the most significant change
in the economic conditions of the people has been observed in Turkey, where the economic
deprivation has decreased from 92.3% to 63.9%. Table 1 shows that the most financial
issues withing the EU were face by Romania (73.8%) and Bulgaria (70%) in 2017 where
individuals who could not afford two items out of four. Surprisingly, one fact noticed in
Turkey is that in 2009, 99.4% of the population faced financial difficulty.
Table 2. Share of individuals cannot afford economic strain items (in %) by
country in 2017
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Countries
dholiday
dmeat
dunexpected dmortgage
BG
53.4%
32.3%
53.9%
32.5%
CZ
25.1%
7.4%
27.4%
2.8%
EE
28.6%
5.5%
36.2%
6.9%
HU
47.8%
16.3%
30.3%
14.3%
LT
42.7%
16.6%
50.9%
7.9%
LV
39.1%
13.6%
59.9%
13.2%
PL
39.6%
7.1%
35.4%
10.5%
RO
65.2%
19.3%
52.0%
16.9%
SL
24.9%
6.9%
37.5%
14.3%
SK
42.9%
14.8%
34.1%
6.9%
TR
59.1%
32.8%
30.4%
25.7%
Source: Based on the SILC (EUROSTAT) and TUIK (note: all percentages are measured
with weighted cases)
Table 2 represents the share of individuals who cannot afford economic strain items (in %)
for selected countries in 2017. For those people who answered the questions declaring that
they were unable to go on holiday away from home the highest rates are observed in
Romania (65.2%) and Turkey (59.1). Tragically, people are not able to spend one-week
holiday away from home annually. Secondly, the highest share of individuals who were
interviewed answered that they could not afford to eat meat, chicken or fish were found in
Turkey (32.8%) and Bulgaria (32.3%). Thirdly, the highest share of the population who
could not afford unexpected payments are seen in Latvia (59.9%) and Bulgaria (53.9%),
which means that those people did not have saved money in their accounts to pay
unexpected payments. Lastly, the highest share of individuals who could not pay their
mortgages, rents, utility bills and other kind of payments during the past twelve months
was highest in Bulgaria (32.5%) and in Turkey (25.7%).
2.2
Living Condition
Living conditions can be measured a variety of ways through either a money metric method
or a basic needs method. The basic needs method considers whether an individual’s
expenditures fall into “minimum level” or “cannot afford” indices as shown below. Living
condition deprivation refers to a lack of goods and materials and to the lack of an
individual’s financial and material stability to live a decent life. This understanding leads
to an estimate of the amount of money required to maintain a minimum standard of living.
Satisfaction of basic needs refers to the ability to keep one’s home warm. Capacity to afford
basic leisure activities (having a washing machine and other home necesities.) refers to
items that, while not essential for physical survival, but critical for enjoying a decent quality
of life. Availability of consumer durables refers to items that are essential to perform every9
day life activities (having a car or having a computer). Living conditions relate to both the
interior and exterior physical characteristics of the dwelling (indoor flushing toilet, or
availability of shower, bath).
The availability of the EU-SILC dataset allows researchers and scientists to make crosscountry comparisons due to the fact the instrument has standard questions across countries.
However, to determine whether who is deprived who is not deprived depend on years that
questions were asked, in 2005 EU-SILC dataset living conditions questions about car,
dwelling, washing, bath or shower were in a binominal format (Yes, No) which has
limitations for participants. However, most refresh dataset of EU-SILC has improved.
In order to determine the deprivation statistic, those who are deprived were selected based
on those who chose the second option that they do not have a bath or shower, or they have
one, but it is shared. Critics on this item point to the fact that the EU-SILC questions do not
provide more information on the participants in terms of the availability of the dwelling or
if it is a shared dwelling with other households or individuals.
The same questions asked in 2017 “Do you have shower or bath in dwelling? “
1. Yes, for sole use of the household
2. Yes, shared
3. No
The reason why this is important is that the share of the population who used to answer
“No” in 2005 were not provided other options. But nowadays, the number of individuals
who are categorized as deprived has decreased due to the improvement of the questions.
The following items are considered in determining a living conditions formula based on a
percentage of the Eurostat (33%) of all items, whether an individual cannot afford two out
of seven items considered to be deprived.
Where:
DLiving (dwarm + dcomp + dcar + dtv + dwashing + dbath + dtoilet) > 2
Where:
dwarm = Ability to keep home adequately warm
dcomp = Do you have a computer?
dcar = Do you have a car?
dwashing = Do you have a washing machine?
dbath = Bath or shower in dwelling
dtoilet = Indoor flushing toilet for sole use of household
dtv = Do you have a TV?
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Based on our definition on living condition, table 3 created in selected countries (Those
countries where data is missing in any years is excluded).
Table 3. Share of deprived population in Living Conditions (in %) in selected countries
Country List
2005
2009
2013
2017
BG
-
49.1%
38.7%
33.7%
CZ
11.0%
6.1%
4.8%
3.1%
EE
31.1%
15.8%
11.7%
8.9%
HU
19.0%
-
14.6%
9.8%
LT
42.4%
27.7%
23.1%
-
LV
47.9%
29.5%
27.4%
17.9%
PL
29.8%
14.4%
8.8%
6.4%
RO
-
53.4%
42.7%
33.8%
SL
3.6%
3.1%
3.0%
2.9%
SK
20.0%
8.9%
6.7%
5.5%
TR
53.3%
44.8%
33.1%
20%
Source: Based on the SILC (EUROSTAT) and TUIK (note: all percentages are measured
with weighted cases)
Table 2 shows the share of deprived population in living conditions in selected countries.
The changes over time that living conditions of the individuals have been increased in the
selected countries. However, some countries such as; Romania, Bulgaria and Turkey could
not follow increasing changes over time. It is obvious that individuals live in Turkey
(20.0%), Romania (33.8%) and Bulgaria (33.7%) do not have a significant standard of
living where individuals cannot afford their basic needs and facing lack of basic needs of a
decent life. Surprisingly, countries for instance; Poland and Latvia had faced a significant
improvement in living conditions. Poland faces lack of having durable goods 29.8% in
2005, however it is only 6.4% in 2017. Decreasing changes are also detected in Latvia
(from 47.9% to 17.9%), Estonia (from 31.1% to 8.9%) and Slovakia (from 20.0% to 5.5%).
Table 4. Share of individuals who are not able to afford living conditions items (in %) by
country in 2017
Countries
dwarm
dtv
dwashing
dcar
dbath
dtoilet
dcomputer
BG
37.1%
1.6%
8.1%
20.2%
20.1%
26.6%
13.7%
11
CZ
3.3%
0.1%
0.2%
7.3%
0.6%
0.7%
2.7%
EE
3.2%
0.3%
1.1%
11.0%
9.1%
7.4%
3.2%
HU
6.8%
0.6%
0.7%
19.1%
3.5%
3.9%
8.1%
LT
29.4%
-
-
10.2%
13.0%
13.5%
6.2%
LV
9.9%
0.9%
3.6%
18.5%
13.4%
12.5%
7.8%
PL
6.5%
0.4%
0.5%
7.3%
4.3%
3.7%
3.1%
RO
11.3%
0.9%
7.8%
28.9%
27.6%
29.5%
14.0%
SL
4.2%
0.4%
0.2%
4.0%
0.6%
0.6%
3.6%
SK
4.1%
0.2%
0.6%
10.9%
1.9%
2.7%
4.5%
TR
19.4%
13.7%
0.4%
0.4%
0.9%
1.3%
4.3%
Source: Based on the SILC (EUROSTAT) and TUIK (note: all percentages are measured
with weighted cases)
Table 4 represents the changes in living conditions over time where participants are not
able to afford to maintain their basic living quality of life in 2017.
Among Baltic countries, lowest percentages of living condition are in Estonia in all living
items. Highest rate of those who cannot keep their home adequately warm is in Bulgaria
(37.1%), Lithuania (29.4%) and Turkey (19.4%). Out of selected selected countries,
Bulgaria faces the worst scenario in terms of ability of afford living items. People who
cannot afford a car for personal use is 20.2%, do not have bath in their dwelling is 20.1%
do not have toilet is 26.6% in Bulgaria.
2.3
Housing and Environmental Conditions
The aim of the housing and environmental conditions dimension is to measure “quality and
affordability” of the individual’s housing. Variables such as having a leaking roof, damp
walls, floors, foundation, or rot in the window frames or floor and problems with the
dwelling: too dark, not enough light explains the comprehensive picture of housing
conditions or families where they can or cannot afford to maintain leaking roof, walls,
floors. All items were considered after checking availability of data to make sure that the
data was available for all the selected countries in order to make a valid comparison. This
dimension focuses on the “quality of life” of households with respect to the environmental
conditions of crime, noise, and pollution. Crime refers to people declaring that "there is
crime or vandalism in the area where they live”. Noise and pollution refer to respondents
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declaring that "their accommodation suffers from neighborhood businesses and industries
or other environmental problem caused by traffic or industry”.
To arrange data to find those ones who are deprived due to one of these problems,
participants are given two options by EU-SILC questioner. The question about pollution is
asked;
Do you have pollution, grime or other environment problems?
1. Yes
2. No
Participants who answer “Yes” are categorized as deprived due to one of these
environmental problems.
The following items are considered to determine housing and environmental conditions
formula based on percentage of Eurostat (33%) of all items, whether an individual face
difficulties two out of five items considered to be deprived.
Where:
DHousing (ddark + dpoll + dleak + dcrime + dnoise) > 2
ddark = Problems with the dwelling: too dark, not enough light
dpoll = Pollution, grime or other environment problems
dleak = Leaking roof, damp walls, floors, foundation, or rot in window frames or floor
dcrime = Crime, violence or vandalism in the area
dnoise = Noise from neighbors or from the street
Based on our definition on housing and environmental conditions, table 5 created in
selected countries (Those countries where data is missing in any years is excluded)
Table 5. Share of deprived population in Housing and Environmental conditions (in %) in
selected countries
Country List
2005
2009
2013
2017
BG
-
26.4%
17.8%
17.9%
CZ
24.1%
20.9%
15.6%
11.7%
EE
27.4%
17.9%
12.8%
10.1%
HU
26.3%
15.8%
20.6%
16.6%
LT
23.7%
18.1%
16.0%
14.6%
LV
37.3%
32.6%
22.5%
19.8%
PL
25.9%
16.3%
12.5%
12.0%
RO
-
31.7%
23.2%
16.7%
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SL
21.8%
25.8%
17.3%
16.1%
SK
18.2%
20.4%
12.9%
10.2%
TR
49.1%
38.3%
32.0%
28.0%
Source: Based on the SILC (EUROSTAT) and TUIK (note: all percentages are measured
with weighted cases)
This table 5 shows in % that countries who has housing and environmental problems
between 2005 and 2017. These items describing the condition of the dwelling and
environmental problems which encompass noise, pollution, crime, shortage of space and
darkness of the dwelling. These items were weighted calculations-built percentages of
individuals who face two problems out of five. There is a significant change for most
countries from 2005 to 2017 increasing in quality of housing and environmental conditions:
Firstly, housing and environmental conditions in Latvia is decreased from 37.3% to 19.8%.
Secondly, quality of housing and environmental conditions is decreased from 49.1% to
28.0% in Turkey. On the other hand, countries who are less developed compared to
westerns countries such as Hungary is in better condition than western countries. It is
observed that quality of housing and environmental condition has decreased from 26.3% to
16.6%. But as a conclusion for housing and environmental condition dimension is those
countries where there is intensive industry or business have less quality of housing and
environmental conditions compared to those countries where there is less industry or
business have higher quality of housing and environmental conditions.
Table 6. Share of individuals experiencing poor housing and environmental items
(in %) by country in 2017
Countries
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ddark
dpoll
dleaking
dcrime
dnoise
BG
6.4%
14.4%
12.3%
24.0%
9.7%
CZ
3.0%
11.4%
7.7%
9.1%
13.7%
EE
4.3%
8.6%
14.0%
7.3%
8.3%
HU
7.9%
12.3%
23.9%
6.8%
10.8%
LT
5.9%
14.7%
15.2%
8.0%
12.7%
LV
8.8%
18.5%
22.9%
7.9%
14.4%
PL
4.6%
12.6%
12.0%
5.6%
12.8%
RO
4.3%
14.1%
10.5%
10.8%
18.9%
SL
4.5%
16.8%
22.5%
8.0%
13.7%
SK
2.8%
10.5%
6.5%
6.1%
12.7%
TR
18.4%
22.3%
35.7%
11.0%
15.3%
Source: Based on the SILC (EUROSTAT) and TUIK (note: all percentages are measured
with weighted cases)
Table 5 shows that each selected country has shown that population of different countries
who faces housing and environmental issues are shown by percentage for each item. Firstly,
in Turkey, those people have dark accommodation or do not have enough light in the house
is 18.4% while those people who has noise issue where they live is 15.3%, and surprisingly,
conditions of those houses where they have problem with leaking is 35.7% which is highest
rate in selected countries. Rest of the selected countries has performed with respected
signigicant changes over time.
3
CONCLUSION
This article is based on simple measures of deprivation built as the average of individuals
reporting different forms of deprivation. The author attempts create a new method to
explain deprivation. Utilizing data from the EU-SILC, the author expanded the number of
dimensions from one to three and applied these dimensions to selected countries. This paper
provides evidence and research on deprivation and has implications for both methodology
and policy. This article attempts to broaden the scope of deprivation by identifying survey
questions that may be the basis for a comparative assessment of the scope of deprivation in
different countries. However, this preliminary analysis is limited in several dimensions. It
is based on summary statistics rather than a more complex system of micro aspects
collections that would allow for the creation of multiple deprivations and overlap measures
between financial and non-financial deprivation. Taking the broader concept of
deprivation, the authors found that each item shows unique significant changes and
importance for different countries specifically in the economic strain dimension. In looking
at economic strain, the most problematic item was demonstrated for those people who
cannot afford going on a one-week holiday away from home in each country. In terms of
living conditions, the most problematic item as it relates to a consequence of the lack of
financial stability, was keeping the home adequately warm. Overally multidimensional
approach stands with limiatations. Deprivation remains as a complex phenomenon among
15
countries. Statistical tools and methods attempt to measure this reality that relies among
societies cannot be truly measured due to the aspect of the poverty arising in one’s country.
As a result, majority of the population found itself competing for survival, though they
were deeply wounded in the process.
4
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