Recession and Inequalities –
local findings
Gergely Fábián – Péter Takács
CONTENTS
1. Background and significance of the study
2. Recession, employment and economic activity
3. Incomes, income distribution, inequality
4. Social support system, social problems and benefit
5. Local measure of the quality of life - The FT Index
Summary
Local Organization of Social Services in Hungary
Crises – Reactions – Changes
Conference and Book launch
2012.11.15. Debrecen, DAB
1. Background and significance of the study
In 2008, the Bureau of Social Affairs of Municipal Government of Nyíregyháza Mayor’s Office and
the Department of Applied Social Sciences of the University of Debrecen, Faculty of Health
launched a series of research studies to examine the citizens’ living conditions and to present
and analyze the changes over time. This survey is based on national and international examples
and utilizes the methodology of household panel survey. The household panel survey collects
information on households in towns and their characteristics - changes are studied in the same
sample over time using the same questionnaires.
The household panel survey has used this standardized methodology both in the European Union
and Hungary:
European Community Household Panel (ECHP) - ran from 1994 to 2001 - was based on
a standardized questionnaire - interviewed the same sample population - 60,500 households –
topics including income, poverty, economic activity, and health. A renewal in the series of
surveys became necessary since much of the original survey population was lost to attrition
(moving out, death, other mobility problems). The original plans interviewing was stopped in
2001.
Statistics in Income and Living Conditions (EU-SILC) – continuation –under new title.
The EU-SILC basically provides two types of data:
- cross-sectional (referring to a period of time or a point in time) and
- longitudinal data (studying changes of the individuals in the sample followed over time at
annual intervals for 4 consecutive years).
TÁRKI’s survey Hungarian Household Panel (HHP) (later Household Monitor) - with same
methodology.
Nyíregyháza Household Panel (NHP) survey was based on national and international surveys.
It uses the questionnaires of ECHP, EU-SILC and HHP - therefore, local information
is comparable to that of Hungary as well as to other countries.
Methods
The final version of the questionnaire grouped the questions into comprehensive sections:
- Characteristics of the households (household composition, housing, income, etc.);
- Economy activities (employment characteristics);
- Health (health condition, long-term diseases);
- Social relationships (family and personal relationships, extensity, intensity);
- Elderly people (65 years of age and above);
- Support systems – social problems (characteristics of natural and built-out social safety
networks, allowances, opinion about the system of allowances and social care);
- The Bureau of Social Affairs (clients’ opinion);
- Biography (personal data about of the respondents).
In selecting a sample, the methodology of HHP was used.
Adults over 18 with permanent address in Nyíregyháza were placed into the sample pool.
The sample population was chosen in a randomized way from the database of the Central Office
for Public Administration and Electronic Public Service.
In the first round, a database of 2000 persons was chosen.
Later a database of 400 persons was added to provide the investigators with extra addresses
to supplement the original sample if someone was unwilling to answer the questions.
The representativeness was tested on the gender variable.
All together 1848 usable questionnaires were collected to be analyzed (4866 persons - 4%
of the total population of Nyíregyháza - such a large local population has not been studied
before).
The first wave was in 2008, while the second in 2010.
Sample - weighting
The representative sample may be varied, since the investigators, just like in any other panel
research, were instructed that the person most versed in household matters and most likely to
be able to answer the questions should be asked first, then followed by the questionnaires
asking information about persons.
In a significant part of the households women answered to questions about the household.
Table One
Table One: Characteristics of the sample
Gender from 2001
Census
Gender of the
citizens from sample
pool
Gender of participant
respondents
Men
46.8
46.7
38.9
Women
53.2
53.3
61.1
Similarly to any database
the confounding factors
may be corrected with
weighting by to match the
original incidence.
Table Two
Table Two: Characteristics of the sample – weighting
Gender
incidence
of the
citizens
(2001
Census)
Gender
incidence of
the citizens
(from the
sample)
Gender incidence of
the citizens (in the
primary database
after the interview)
Gender of
participants after
weighting
Men
46.8
46.7
38.9
46.8
Women
53.2
53.3
61.1
53.2
Information on households is shown on the basis of the unweighted primary database, since
the respondent’s personal characteristics cannot be regarded as relevant information. The unit of
analysis is not the person but the household itself. However, information on the individuals is
taken from the weighted database.
2. Results - Recession, employment and economic activity
70
60
66 63,7
56,754,5
54,954,5
50
49,9
44
40
30
42,142,2
20
10
0
EU-27
Hungary
Nyíregyháza
Chart One: Employment rate (%)
2008
2010
Northern Great
Plain
SzabolcsSzatmár-Bereg
(National and international data source: KSH, 2011a)
The recent economic recession has greatly affected manufacturing which has led to a decrease
in employment.
When asked ‘Are you working at the moment?’
54.9 percent of the respondents gave a positive answer in 2008 whereas 54.5 percent in 2010.
The employment rate is quite similar to the national one with its 54.5 percent among the 15-64
age group. The rate measured in the Nyíregyháza region exceeds the rate in the neighbouring
Northern Great Plain Region (Észak-Alföldi Régió) and Szabolcs-Szatmár-Bereg County. The region
had 44 percent, while 49.9 percent in 2008 and in the County it was 42.2 percent. The above
mentioned rates lag behind the EU27 average which is 63.7 percent. However, a decrease in
employment has been seen in the EU as well since 2008, when this rate was some 66 percent.
Hungary and Nyíregyháza are lagging behind with some 9.2 percent.
Chart Two: The rate of employment of the citizens by gender, 2008-2010 (%)
60,8
62
59
60
58
56
54
52,8
53
52
50
48
Women
Men
2008
2010
(Source: our own data)
As for men and women a significant difference can be seen in employment in both periods,
though a decrease is shown in the case of men. For women hardly any changes can be seen,
while among men some decrease can be seen which also reflects the national tendencies.
In the third quarter of 2010 the rate for women in Hungary was 51 percent, for men it was
61.2 percent. In the same period of 2008 the rate for women was also 51 percent while for
men it was 63.9 percent, some 3 percent decrease has occurred.
It can be explained, both locally and nationally, by the impact of economic recession on
industry leading to a great number of laid off; and the loss of jobs affecting losing men in
the first round. The difference in employment between men and women is rather significant.
Losing jobs also happened in towns, though the number of laid off people and the rate of
lagged behind other regions.
Chart Three: The number of laid off people between March and October 2008
(Source: GKI 2010)
This map shows the business sphere in regions of high economic activity suffered the biggest fall
in Hungary.
Large export-oriented manufacturing factories and their suppliers, set up within the last 10-15
years in the Northern-Western part of Trans-Danubia, found themselves in a critical
situation.
Naturally, it does not mean that towns of the north-east region, Debrecen or Nyíregyháza,
were not affected by difficulties, but to a lesser extent and the rate of unemployment is still
much lower than in other regions of the country.
Chart Four: The rate of unemployment in the Nyíregyháza small region, 2010, (%)
9,31
9,28
10
8
6,8
5,97
(Source: National
Employment Service,
2011)
6
4
2
0
2007
2008
2009
2010
The increase in unemployment in the small region shows the impact of economic recession,
since the rate increased between 2008 and 2009 and has stayed steady since then.
Chart Five: The rate of unemployment of small regions in Szabolcs-Szatmár-Bereg County, 2010, (%)
Nyíregyházi
9,31
Tiszavasvári
It can be concluded that
the employment situation
of Nyíregyháza region
became worse, the rate
of unemployment has
increased (from 6-7
percent to 9-10 percent),
though comparing it to
other regions the
situation is still better.
13,92
Kisvárdai
16,38
18,16
18,62
20,06
20,65
21,84
23,31
24,05
24,85
25,09
Záhonyi
Nagykállói
Ibrány-Nagyhalászi
Nyírbátori
Mátészalkai
Vásárosnaményi
Csengeri
Baktalórántházi
Fehérgyarmati
0
5
10
(Source: National Employment Service 2011)
15
20
25
30
Chart Six: The distribution of job holders of different sectors in the town, 2008-2010 (%)
66,1
80
67,3
60
28,4
40
7
5,3
20
25,6
0
Agriculture
Industry
2008
2010
Services
(Source: Own data)
Due to the recession some inner transformation of employment is also visible. The loss of jobs
in industry was compensated by the slight increase in agriculture and services, even though it
slowed down still did not decrease the number and rate of unemployed people, however, the
impact of the loss was buffered for a while.
Chart Seven: Employment rate with regard to education, Nyíregyháza, 2008-2010 (%)
University degree
73,6
College degree
68,6
73,1
81
Naturally, with regard to education significant
differences can be seen and from earlier
studies it widely accepted that the more
educated you are the more favourable
your employability. As a matter of fact,
some inner transformation can be seen in
this field, too.
57,6
54,4
Gram m ar school
Com prehensive
school
59,2
61,2
51,9
52,3
Vocational school
20,7
22,7
Prim ary school
0
10
Source: Own data
20
30
40
50
2008
2010
60
70
80
90
Employment rate and the education – reasons and consequences
These changes follow the national tendencies, since according to the Hungarian Central
Statistical Office (KSH) the number of employed people with college degree has decreased
nationally, while there is an increase among university degree holders.
The rate of employment for those with the lowest education lags behind all other groups.
As a matter of concern for those who have completed only 8 grades of primary school or
less is quite problematic, as it is written in the KHS report: “One explanation of the very
low employment rate in Hungary in comparison with the EU is the extremely bad employment
situation of people with low education. Only 27.2 percent of people with completed primary
education were employed in Hungary in 2008, while the EU27 average was as high as 48.1
percent. Some 63.3 percent of the 15-64 age-group with secondary professional educational
attainment worked in 2008 which lags behind the EU27 average with about 8 percent (71.3).
Although the employment rate of people with higher educational attainment (79.5 percent) is
closer to EU average, Hungary is the next to last in rank.” (KSH, 2011b).
About 10% of those employed in Nyíregyháza (2008), apart from the wage or salary from
their main job, had extra earnings from a second job. This rate rose to 13.4 percent in
2010. Though the difference is statistically not significant, it is worth focussing on this data
since (having known the data above might not be surprising) the number of men with a
second job exceeds that of women.
It also can be regarded as a ‘trait of the educated ones’ because it is typical to those having
higher educational attainment. The number of those with extra earnings (as well as
opportunities) is extremely low among people with low educational attainment who,
being unqualified, are often crowded out of this secondary job market.
3. Results - Incomes, income distribution, inequality
This survey, like other panel research studies, examined the characteristics and distribution
of the net household disposable income, but has no information on the gross income or
the ‘relation’ of gross and net incomes.
In 2008, the average net household income in Nyíregyháza was 177.000 HUF, the median
income 160.000, while in 2010 it was 184.000 HUF and the median remained steady. Though
there is a slight growth in the monthly net household income, the steadiness of median
already indicates the impact of the crisis, namely the ‘frozen’ wages or salaries. The increase
could not keep up with the inflation, thus a decrease in real income was about 7 percent.
The changes in income both in Hungary and Nyíregyháza show some income
polarization.
The proportion of poor and upper level groups increased at the expense of the middle class. A
2 percentage point rise in poverty was typical. In this sense one cannot talk about exclusive
impoverishment but rather a growth of income inequalities which resulted in growing
impoverishment of certain social classes, and weakening of the middle class, while the upper
level group saw income gains; thus the social polarization.
We can see it in next two slides.
We study the
Empirical estimate rates of income categories
Hungary 2007-2009, %
middle class
40
The categories:
wealthy,
upper-middle class,
middle class,
lower-middle class,
poor
36
35
31
upper-middle class
30
25
27
25
22 22
20
15
10
This chart shows data for
two years
(2007 and 2009)
in Hungary.
lower-middle class
poor
wealthy
7
10
8
12
The relative share
of rich and poor
is increasing.
This means polarization
in the population
in the country.
5
0
We can see the
elimination / depletion
of the middle-class.
Jómódúak
1,0
Felső-középréteg
2,0
Chart Eight
Source: Hungary: 2007, 2009, TÁRKI
Középréteg
- 5,0
2007
2009
Alsó-középréteg
0,0
Szegények
2,0
We can see it
by GINI index too.
Empirical estimate rates of income categories
Nyíregyháza, 2008-2010, %
middle class
35
32,8
upper-middle class
30
25,2
25
29,1
26,5
We can observe the
same in Nyíregyháza
In 2008 and 2010.
lower-middle class
28 27,6
Remark/Note:
Here we can see that
Nyíregyháza have
similar trends to the
country.
20
poor
15
wealthy
9,4
10
5
0
11,4
4,6 5,4
Felső-középréteg
Középréteg
0,8
1,3
- 3,7
Source: our survey
The relative share of rich
and poor is increasing.
We believe that this is
partly due to economic
crisis.
Jómódúak
Chart Nine
We can see the
elimination / depletion of
middle-class.
2008
2010
Alsó-középréteg
- 0,4
Szegények
2,0
4. Social support system, social problems and benefit
Chart Ten: Whose help the citizens can count on when solving their problems
– positive answers, 2008-2010 (%)
100
90
91,492,2
80
70
60,2
60
53
50
40
27,727,8
30
20
24,6
20,3
22,4
18,7
10
7,9 7,8
0
Family member
Friends
Acquaintances
2008
Office
2010
Social Serv ice
No help
(Source: Own Data)
Having known and analyzed some impacts of the crisis, the question arises whose support the
citizens can count on when solving their problems. Data and viewpoints concerning the natural
support systems, social services, and social benefits was obtained by asking the question of
whose help they can count on when solving their social problems.
Data has shown that citizens having social problems typically count on the help of family
members, followed by friends, acquaintances, then the elements of formal social safety
nets, such as the municipality, certain social services, and the amount of this help cannot be
neglected. Only a small number of people stated that no help was available.
The general opinion about social benefits - 2008
We applied the main component analysis; 4 factors were separated which, at the same
time, made for 64.2 percent of the proportion explained.
The first factor groups questions around what is labelled pro-benefits. Benefits are seen as a
necessary form of support which could be given more frequently. Respondents who answer
positively to this set of questions support benefits and totally refuse benefits to be stopped.
The second factor relates to “swindlers taking undue advantage of the system”.
Respondents who answer positively to this set of questions that not only people in need get
benefit support but too many individuals apply for benefits who are not in need and are
cheating the system and should be stopped.
The third factor related to the position that benefits should be provided “in kind” and not in
cash benefits. Respondents who answer positively to these questions, prefer that support be
provided in kind and not in cash money.
The fourth factor formed a grouping of statements that only those who are really in need
reveal their correct financial situation and that real need should be provided. Then cash money
could be given in larger amounts but only rarely.
Pro-benefit
Swindlers taking undue
advantage
Benefit in-kind
People in need
It is necessary to provide benefit
because it is the only way to solve
certain problems. (0.733)
Smaller sum of money, as benefit,
should be given but more frequently.
(0.708)
There is no need for providing
benefits they cannot solve the
problems. (-0.685)
Benefit is mainly applied
for by those who are not in
need. (0.801)
Lots of people don’t reveal
their real financial
situation to get benefit.
(0.752)
Those apply for benefits
who are really in need.
(-0.379)
Benefit in-kind would
be more necessary.
(0.843)
Cash benefit would be
more necessary.
(-0.693)
Only those are provided with
benefits who reveal their real
financial situation. (0.722)
Bigger sum of money, as
benefit, should be given but
more rarely. (0.641)
Only those apply for benefits
who reveal their real
financial situation. (0.600)
The general opinion about social benefits - 2010
Having known the general changes over time, the citizens’ changes in preferences in two
years’ time was also worth examining. The 2010 analysis was also carried out with main
component analysis, 4 factors were separated which made for 64.2 % of the variance
explained.
It is quite probable that due to the economic and financial crises (laid off people, rise in
unemployment, being in debts, people with mortgage, decrease in income, etc.) opinions
went through apparent changes in the last two years. The most important and significant
changes are the disappearance of two factors: the presence of swindlers and
preference of benefit in-kind. As a matter of fact, these factors did not really disappear,
they still exist but to a more modest extent. Basically all factors are in favour of the social
benefit system, and “being in need and entitled to benefits” was more often emphasized.
Opinions became restructured and more generalized which resulted in almost invisible
differences regarding the acceptation or rejection of a factor by a certain economic or social
class.
People in need
Pro-benefit One
Those apply for benefits who
are really in need (0.710)
Only those are provided with
benefits who reveal their real
financial situation. (0.683)
Benefit is mainly applied for
by those who are not in need
(-0.729)
Lots of people don’t reveal
their real financial situation
to get benefit. (-0.674)
It is necessary to provide
benefit because it is the only
way to solve certain
problems. (0.799)
Cash benefit would be more
necessary (0.409)
There is no need for
providing benefits they
cannot solve the problems.
(-0.697)
Pro-benefit Two
Cash benefit would be more
necessary. (0.788)
Bigger sum of money, as
benefit, should be given but
more rarely. (0.330)
Benefit in-kind would be
more necessary. (-0.844)
Pro-benefit Three
Smaller sum of money, as
benefit, should be given but
more frequently. (0.784)
Bigger sum of money, as
benefit, should be given but
more rarely. (-0.667)
5. Local measure
of the quality of life
Σ
The FT Index
„The term quality of life is used to
evaluate the general well-being of
individuals and societies.” - wikipedia
We present our local quality of life index:
Index Fábián-Takács – FT index
Questions of the quality of life have been
focused on developed societies at the end of the twentieth century.
The basic idea is: The main objective of the whole society should be to increase the human quality of
life, constantly.
http://myviewsdrift.blogspot.com/2010/04/quality-of-life.html
These require examination instruments and methods. So we can increase the objectivity of the
researches. We can classify quality of life indicators in the following ways.
A, Objective and Subjective indicators. Per capita GDP (Gross domestic product); Life expectancy; Healthy
Life Years; Personal satisfaction with the quality of life, with the health, with the economic status; etc.
B, Profession-specific approach. Main areas where the studies started are economics, sociology,
psychology, health sciences, etc.
Complex indicators were formed from these indicators.
Indicators that we developed are complex indicators, based on mainly sociology.
http://www.maps-inc.org/events/international-symposium-on-human-rights-and-quality-of-life-of-the-portuguese-speaking-communities-in-the-united-states-of-america-and-canada/
Methods
We started the development of our local quality of life indicator in 2010. Our base was a research
Nyíregyháza Household Panel (NHP) survey - the above mentioned.
We developed two models.
I. The first model is a simple aggregate model. 2008. 1. model: QLI_1. & 2010. 2. model: QLI_2.
This is the summary of the involved variables. The main results of this model is
to develop and fix a variable-set – 23 questions.
We used this variable-set in the second model.
II. The second model was based on the Rahman-model (see quality of life literature).
The Rahman-model uses eight groups of questions.
Our 23 questions can be classified in seven Rahman-categories.
We used principal component analysis (PCA) to establish the weight of the groups.
We develop complex indicators (QLI_1, …, QLI_4 = FT Indexes) with weighted sum.
2008. 3. model: QLI_3. & 2010. 4. model: QLI_4.
Remarks: The difference of the calculated weights are very small in the two years.
We present the four models and some results in the following slides – Contents:
2008. 1. model: QLI_1. - QLI_1. – ‘sub-area’ - QLI_1. – ‘rich’ - QLI_1. – ‘employment’ - QLI_1. – ‘language’ QLI_1. – ‘car’
2010. 2. model: QLI_2. – wrong way
2008. 3. model: QLI_3. - QLI_3. – ‘sub-area’
2010. 4. model: QLI_4. - QLI_4. – ‘sub-area’
QLI_3 and QLI_4. – ‘sub-area’ - QLI_3. and QLI_4. – ‘rich’ - QLI_3. and QLI_4. – ‘education’ - QLI_3. and
QLI_4. – ‘employment’ - QLI_3. and QLI_4. – ‘religion’
2008. 1. model: QLI_1
model summary
The research steps were the following:
-selection of 30 questions
-re-encoding - increasing human values
represent increasing points
-creating descriptive statistics
-exclude four variables - many missing
answers
-Factor Analysis - exclude three variables very different from the group
-index calculation: summation –
QLI_SUM_1 or QLI_1
We can see the descriptive statistics of
the index on the right.
We can see the histogram of the index
on the left.
The distribution of the QLI_1 variable is not
a normal distribution
Kolmogorov-Smirnov test p=0.000
and
Saphiro-Wilk test p=0.000.
The distribution is stretched to the right
so we can understand the lack of
normality.
Chart Eleven
Now comes further investigations in
relation to this index.
QLI_1. – ‘sub-area’
We can divide Nyíregyháza for
14 sub-area.
We investigated the average of the variable
QLI_1 in these sub-areas.
The Kruskal-Wallis test does not require
the normality of the variables.
The Kruskal-Wallis test indicates a
detectable difference (p=0.022).
The Kruskal-Wallis test uses rank numbers:
The first is „Sóstó” – rich area of
Nyíregyháza.
The last is „Huszártelep” – poor area of
Nyíregyháza.
Chart Twelve
QLI_1. – ‘rich’
We examined the perception of
individual and family rich and
the distribution of the QLI_1
index.
The results are shown in this
slide.
The categories:
wealthy,
upper-middle class,
middle class,
lower-middle class,
poor
We see, "the growing
assessment of economic
status" involves "increasing
quality of life".
The results of the statistical
analysis are the following:
A, ANOVA (Analysis of
Variance) – no difference –
p=0.279
B, Kruskal-Wallis test –
difference – p=0.000
Analysis B,
is the correct analysis
due to lack of normality.
Chart Thirteen
QLI_1. – ‘employment’
We investigate the
employment classification
in the same way.
The results are shown in this slide.
The results of the statistical analysis
are the following:
A, ANOVA (Analysis of Variance) –
no difference – p=0.547
B, Kruskal-Wallis test – difference –
p=0.011
Analysis B, is the correct analysis
due to lack of normality.
The „disability pensioners” show the
lowest quality of life.
The highest part is the „dependents,
supported by family”
Chart Fourteen
QLI_1. – ‘language’
We investigate the
„language knowledge”
the same way.
Those who speak foreign
languages has a higher
quality of life.
OR
The high quality of life
allows the language
learning
‘Which came first: the
chicken or the egg?’
t-test: p=0.025
Mann-Whitney-test:
p=0.000
Chart Fifteen
QLI_1. – ‘car’
We investigate the question
„Do you have a car?”
the same way.
Those who have a car have a
higher quality of life.
t-test:
p=0.006
Mann-Whitney-test:
p=0.000
Chart Sixteen
2010. 2. model: QLI_2
model summary
We develop a similar
model to the 2010 data.
The histogram of QLI_2
index is on the slide.
Since
the reduction in
number of elements
was too large
we have not continued
this way for the analysis
We developed a new
model
– the Principal
Component Analysis
(PCA) based model.
Chart Seventeen
Ø
2008. 3. model: QLI_3
model summary
We explained the steps of model development
previously.
so
here we discuss the descriptive statistics of
model (QLI_3 or FT Index).
We can see the descriptive statistics and the
histogram of the index in the slide.
The number of cases was 1675.
The average quality of life is 6.09.
The distribution of the QLI_3 variable is a normal
distribution.
Kolmogorov-Smirnov test p=0.200 and
Saphiro-Wilk test p=0.253
We can see the familiar bell-shaped curve in the
diagram. The results of this model are more
accurate.
Chart Eighteen
QLI_3. – ‘sub-area’
We investigated the average of the
variable QLI_3 in Nyíregyháza’ subareas.
We used analysis of variance
(ANOVA) to compare the averages.
The analysis shows that the
averages differ p=0.001
By the post-hoc analysis,
Huszártelep has a significantly lower
quality of life index.
2008. QLI_1
Chart Nineteen
2010. 4. model: QLI_4
model summary
The PCA-based model in 2010
has good properties,
just like in 2008.
The distribution of the QLI_4
variable is close to normal
distribution.
Kolmogorov-Smirnov test:
p=0.161
and
Saphiro-Wilk test:
p=0.023.
The number of missing cases
has grown highly.
This is a warning sign
concerning the following
sampling.
We will take care of sampling in
2012.
Chart Twenty
QLI_4. – ‘sub-area’
We investigated the
average of the variable
QLI_4 in Nyíregyháza’
sub-areas.
We used analysis of
variance (ANOVA) to
compare the averages.
The analysis shows that
the averages differ
p=0.037
By the post-hoc
analysis,
Huszártelep has a
significantly lower
quality of life index,
again.
Chart Twenty One
QLI_3 and QLI_4. – ‘sub-area’
We can see the second
(PCA-based) model
(QLI_3, QLI_4) on the
same slide:
We can observe an
increase of quality of
life (standardized) in
four parts of the city
(from 14).
The greatest reduction
is in the following
areas:
Jósaváros II.,
Huszártelep,
Bokortanyák,
Újtelekiszőlő.
We also examine the
underlying causes.
but
Chart Twenty Two
We think we should
pay attention to internal
migration,
in addition the
economic crisis.
QLI_3. and QLI_4. – ‘rich’
We compared the distribution of the perception of Individual and family rich
in the two years.
The quality of life of the poor (-0.19) and the rich (-0.2) is decreased.
The middle class has not changed fundamentally.
Quality of life in upper-middle class has increased.
0,8
The categories:
wealthy,
0,6
0,4
upper-middle class,
0,2
middle class,
0
Szegények
Alsó középréteg
Középréteg
Felső középréteg
-0,2
lower-middle class,
-0,4
poor
-0,6
Chart Twenty Three
2008
2010
Jómódúak
QLI_3. and QLI_4. – ‘education’
We investigated the relationship between „education” and „quality of life”.
We see, "the growing of personal education" involves "increasing quality of life".
We can observe small changes in the city:
The quality of life those have completed secondary education has grown.
0,6
grammar school
0,4
university
0,2
college
0
8 általános alatt
8 általános
Szakmunkásképző
Szakközépiskola
-0,2
vocational school
-0,4
-0,6
elementary school
-0,8
-1
-1,2
Chart Twenty Four
2008
2010
Gimnázium
Főiskola
Egyetem
QLI_3. and QLI_4. – ‘employment’
We examine the employment classification in the same way.
Here we can see even greater changes.
We can see significant reduction in quality of life in many layers.
0,6
employee
0,4
own business
on maternity leave
0,2
social benefits,
transfers
0
-0,2
Saját
vállalkozásában
dolgozik
Alkalmazott
GYES
Munkanélküli
unemployment
-0,4
-0,6
-0,8
-1
2008
Chart Twenty Five
2010
Szociális
transzferekből él
disability pension
Rokkant
nyugdíjas
QLI_3. and QLI_4. – ‘religion’
This figure presents the relationship "relation to religion" and "quality of life„.
Change in two years is very high.
The religious people's quality of life has increased.
We are researching the causes ...
0,5
0,4
the other believes
ateist ?
0,3
0,2
0,1
0
-0,1
-0,2
religious people
uncertainty in religion
Vallásos vagyok, Vallásos vagyok
az egyház
a magam módján
tanítását követem
Nem tudom
megmondani
-0,3
-0,4
Chart Twenty Six
2008
2010
Nem vagyok
vallásos
Más a
meggyőződésem
Summary
The impact of financial crises can unquestionably be measured even locally, in Nyíregyháza.
During the examined period, the number of unemployed people grew. During the second part
of the study the rate did not change, so the situation did not get worse and kind of stagnation
could be observed. Those who had lost their jobs before were still between jobs. Men apparently
were affected to a larger extent. The difference between the number of employed men and
women is still significant in Nyíregyháza. However, regarding employment and unemployment,
the situation is still much more favourable than in other small regions of SzabolcsSzatmár-Bereg County. In addition, the government’s and local government’s restrictive
measures resulted in a decrease in the number of people working in the public service.
The impact of financial crisis on the citizens’ income has been rather unfavourable. Frozen income
became a usual phenomenon, real income decreased by as much as 7 percent. The officially
measured poverty rate in Nyíregyháza is almost 14 percent, which is two points higher
than it was in 2008. All indices show a rise in income inequality, therefore not only
impoverishment but income polarization can also be observed, which means that two
tendencies exist parallel; impoverishment on the one hand and improvement of the well-off.
Polarization involves a declining standard of living for the middle-class, so as a result the
winners of the process have moved upwards while the losers have moved downwards.
On the basis of TARKI research, it is also worth mentioning that Nyíregyháza has followed the
national tendencies. Due to these changes the social benefit system has been
restructured. Though the number of clients turning for help to the Social Bureau has not
increased, more cash benefits were allocated than benefit in-kind.
In line with it the respondents’ opinion about on the system of social benefit has
apparently changed. The rationale for the formerly polarized opinions decreased, and less
people objected to the necessity of social benefits, though opinions on the method of benefit
provision diverted. On the other hand, people’s trust in official services, local government and
other services has increased, in addition more of them share the viewpoint that services are able
to help people in need.
The current studies demonstrate the utility of the new FT quality of life index.
This was the
Recession and Inequalities – local findings
- in Nyíregyháza, in 2008-2010
ever since
We have a lot of new
research questions
and
We have some small answers.
Thank you for your attention!