Rising Inequalities of Income and Saving and Perception of Social Mobility
Ewa Gucwa-Lesny1 and Barbara Liberda2, University of Warsaw, Poland
Abstract
The aim of the paper is to show that under the conditions of increasing income and
wealth inequality in the transition countries, especially Baltic States and Poland, the mobility
of households between different income and saving groups has lead to their polarization with
regard to accumulation of assets and wealth.
Income mobility was particularly intensive in the first years of transition and
gradually diminished. The policy of minimizing the role of the state and the drive to comply as
quickly as possible with the requirements of the economic efficiency resulted in less solidarity
and social protection than in the old market economies of Western Europe. As public
institutions perform less efficiently as a result of limited funds, the development of human
capital depends more and more on the effort of the family and its accumulated wealth. The
results of research on savings motives show it clearly.
Subjective feelings reflect the reality. In the group of low income mobility Gini
coefficient proved to be significant factor affecting satisfaction with income. The perception
of the opportunities for social advancement has decreased with time and depends more on
level of education attained. In the same time the feeling of inequality in access to education
has increased.
The research is made on the basis of data from Polish Household Budget Surveys for
the years 1996-2000 and the data from Consortium of Household Panels for European
Socio-Economic Research (CHER). The data from Polish General Social Survey 2002 and
International Social Survey Program, Social Inequality III for the years 1992 and 1999 are
also used. The paper concerns mostly Poland but some comparisons with Hungary – member
of CHER and ISSP consortia – are discussed.
Introduction
1
Department of Economics and Institute for Social Studies, University of Warsaw.
E-mail e.gucwa-lesny@uw.edu.pl
2
Department of Economics, University of Warsaw. E-mail Barbara.Liberda@uw.edu.pl
In most of the Central and East European countries undergoing transition from
planned to the market economy, the process of differentiation of incomes and material and
social status of households and individuals has started. The income and wealth inequalities
had been increasing in the first period of the change of economic and social system, until
middle of the 1990s, and then either were kept at the same level or continued to increase until
now.
We analyzed this process at the micro-scale i.e. income mobility of individuals or
households between different income groups, on the basis of Polish nationally representative
household budget surveys for the years 1994-2005 (above 30 thousand households in one year
and around 100 thousand persons surveyed each year). We tried also to assess the probability
of the long term occurrence of inequality using true panels of the same sample of households
extracted from these surveys. True panels are rather rare and short in time span (3-5 years)
in Central and East European countries. The ones, examined in this paper (1-6 thousand
households; 3-5 years of duration) for Poland and Hungary were prepared for Consortium of
Household Panels for European Socio-Economic Research (CHER).
The perception of changes in economic and social situation was analyzed. Data
originated from Polish General Social Survey 2002 as well as International Social Survey
Program, Social Inequality III, for the years 1992 and 1999.
1. Overview of income inequalities in transition economies of Europe.
The overall picture of changes in income inequalities in the transition economies is
mixed. Figure 1 shows the Gini coefficients for household incomes in Central and East
European economies3. In Lithuania, Estonia and Bulgaria the inequalities were the highest
after the first transition period in 1994-1995. In Slovakia the inequalities have been rising
since 1993 and in Czech Republic they are held at a level of mid-1990s. The highest income
per person inequalities in 2005, as compared to previous periods, was in Latvia, Lithuania,
Estonia and Poland. Inequality in these four countries was higher than in all but one members
of European Union, Only in case of Portugal Gini coefficient was higher than in Baltic States
(Human Development Report 2006).
Other measures of inequality show similar tendencies. The ratios of incomes or
expenditures of the 9th decile to the 1st decile and of the 2nd to the 8th deciles of individuals
ranked by income levels are much higher in transition economies of Central and East Europe
than are such ratios in richer European economies. The same concerns quintile expenditure
share ratios, especially in Baltic States and in Poland. The exceptions are Czech Republic,
Slovakia, Hungary and Slovenia where the quintile ratios are lower than the average quintile
expenditure share ratio for European Union (25 countries).
Figure 1. Income inequality in European transition economies 1998-2005
3
The exact numbers for Gini coefficients differ slightly in calculations by particular authors depending on the
specific data source and breaks in data.
Gini coefficients for income per person
Slovenia
Slovak Republic
Romania
Poland
Lithuania
2005
Latvia
1993
1988
Hungary
Estonia
Czech Republic
Bulgaria
0
10
20
30
40
Source: 1988, 1993 World Bank, Milanovic, 1998, p. 41; * Hungary, Poland, Slovenia 1987;
Bulgaria,
Romania
1989;
**
Lithuania,
1994;
Estonia,
Latvia
1995
2005 Eurostat; calculations for Poland 2005 by Barbara Liberda; *** Bulgaria 2004.
2.Income dynamics
In an egalitarian country, rising income inequality creates serious social problems.
Big income dynamics creates hope for less fortunate people to improve their situation in future.
According to Hirschman’s tunnel effect theory, in developing countries, the growth of
income inequality causes a growth of satisfaction because people believe that someone else’s
success proves that there is also a possibility for them to become richer and their satisfaction
rises. Kalbarczyk (2006) studied the relation between subjective satisfaction with income and
income distribution using a Polish (1994-1996) and a British (1992-2000) panel survey.
According to expectations, she showed that the Hirschman’s theory can be confirmed on an
individual level for Poland (a country with a very volatile economic situation) but not for
England (a country with a stable income). However, the application of a new measure of
dynamics, namely, the difference between the growth rates of reference income4 and real
income suggested that an increase in the reference income carried positive information and
increased satisfaction on individual level, both in Poland and in England. It looks like
dynamics of income were essential for “tunnel effect” to occur.
We observed similar effect in sociological perspective. Since the beginning of
transformation average material situation of younger and middle-age group had been unfavorable
comparing to others. In the same time respondents of social surveys at this age (up to 40 years
4
Education level and age as well as the region and year determined the affiliation to the same reference group.
old), had tended to support socioeconomic changes (Słomczyński et al. 1996). The analysis of
income dynamics showed that despite low income position of this group as a whole, within it
more people advanced in their material situation than experienced degradation, so they had
rational hope in going into moving line in tunnel.
Figure 2 show the share of stable group - whose position on the decile income scale
did not change at all or changed very little, by one decile up or down, and the share of the
groups that advanced or experienced degradation by 2, 3, 4 or more deciles.
Figure 2. Income mobility of individuals between deciles of income (ranked by income per
person) in Poland in 1991-2000
70
60
50
40
30
20
10
1999/2000
1997/1998
1993/1994
1991/1992
0
,=-4
-3,00
-2,00
-1,0,+1
2
3
>=4
Prepared on the basis of data from four panels for the years 1991/92, 1993/94, 1995/97
1997/2000.
During most intense income mobility period (1993-1994) the ratio of stable group was
only 35, 7. The groups that advanced or experienced degradation by 4 or more deciles were
large in this period; their share was about 13 percent in both cases. Exceptional income
mobility did not last long. Later in the 1990s more persons were moving down than moving
up, leading to more inequality. The group that did not move outside of the two closed deciles
was kept large, from 55% to 70% of all persons in households in Poland. Only in 1997-2000
was mobility again similar on both sides of the income scale: in each deciles group the
probability of advancing and degradation was almost the same.
In Hungary mobility of households during 5 years of 1992-1996 was more pronounced
than in Poland. More than half of the population in the middle three quintiles changed quintile
between years and moved to one of the neighboring quintiles. Measured over time, mobility
has gone down. After five years under study more people stayed in the same income groups
than had done so at the beginning of the period. Inequality of households’ income rose
moderately (Galasi, 1998). Kolosi and Robert (2005, 51) bring data for vertical mobility by
income deciles from 2001 to 2003. The report indicates that over the period the very lowest
and the highest deciles saw the largest absolute increase of per capita income in relation to
average growth. The ratio of the highest to the lowest deciles rose again at the end of the
period in 2003. A vertical differentiation of the Hungarian society took place.
The general stabilisation of relative income distribution has resulted in the lowering
probability of advancement or degradation on income scale, although its dynamics is still
higher in Poland and in Hungary than in old EU countries (Gorecki, 1999). Up to 1998
income mobility has been asymmetric. On the advancement side, probability to move up has
been higher in lover deciles. On the degradation side, up to 1998, changes were sharper. To
keep one’s position in the higher decile group was very difficult.
Concerning relationship between subjective satisfaction with income and income
distribution discussed above, Kalbarczyk found Gini to be significant only for the subgroup
with low volatility of income. Within this group there were people who could not overcome
difficult barriers to material advancement and high level of inequality deepened their
frustration.
3.Saving inequality and wealth accumulation
The present process of economic and social polarization concerns more wealth
accumulation than earned incomes only. Investment in housing, durables, human capital in a
form of education and caring for health are the attributes of wealth besides earned income.
Unfortunately all these investment are relatively new and difficult to observe. Data describing
wealth accumulation are heavily underreported and underestimated as well as unbalanced
when aggregated across the groups of household. The macroeconomic data on financial
investment of household are also often unbalanced.
Household budget data have remained the most useful data to examine wealth
distribution. Study on saving behavior of households at different income levels surprisingly
shows that households report positive savings even if they value their income as hardly
sufficient for living and if their income is really low (Liberda 2007). People with higher
income in Poland save much more than is the average rate of saving. The top quintile group of
households saves more than one fourth of their income, three times the average. The lowest
quintile group reports negative average savings. Also a third decile had often negative saving
in the past. The household average saving rates were at a level of around 6% till 2000 and
only after 2001 they start growing to 9% of household income (Figure 3).
Figure 3: Households’ saving rate by decile groups of disposable income in 2005 in Poland
(median, in %)
30
25
20
15
10
5
0
-5
-10
1
2
3
4
5
6
7
8
9
10
Decile
-6,4
-0,8
3,6
6,5
9,3
10,6
13,6
14,8
18,6
27,8
Median
9,4
9,4
9,4
9,4
9,4
9,4
9,4
9,4
9,4
9,4
Source: calculations by Barbara Liberda based on Household Budget Surveys 2005, CSO,
Warsaw.
With such saving profiles a major part of total private households’ savings comes from
the fifth top quintile income group. In 2005 households from the top quintile created 3/4 of all
positive household savings. In 2000, which was a year of slow down of the economy, the
saving curve was even more skewed. The top quintile accounted for more than 80% of the
total household savings. Ten years earlier in 1995 the saving distribution was as skewed as in
2005.
The analysis of the household mobility between different classes of households ranked
by saving rates allows for estimating the long term households’ distribution with regard to
saving rates. It was done by applying Markov mobility matrices to the household budget
panel data of 3001 Polish households surveyed in the same month during four consecutive
years 1997-2000, for which last true panel of Polish households is available (Liberda,
Pęczkowski 2005).
The results (Table 1) show that during four consecutive years (1997-2000) more than
one third of households with very low negative saving rates had not left their class, but around
one fifth jumped into the group of highest saving rates. In a class of households with highest
saving rates of above 20% of the household disposable income half of the households kept
these high saving rates and around one fifth of this group reported negative savings after a
year.
The analysis of saving mobility serves as a basis to deduce on the probability of a
household to fall into one of the saving rates groups. The long term probability of falling into
the lowest saving rate group was around 0.2. The highest (0.3) was the probability to get into
a group that saved more than 20% of the household disposable income.
Table 1 Households’ mobility matrices subject to the saving rates, 1997-2000, Poland
(households ranked by saving rates)
Saving rates 1998
<-20% -20% - -5% -5% - 5% 5% - 20% 20%+
Saving
rates
1997
Total
<-20%
37
15
11
15
23
100.0
-20% - -5%
26
16
18
20
19
100.0
-5% - 5%
23
16
16
22
22
100.0
5% - 20%
15
13
19
24
30
100.0
20%+
12
8
10
19
51
100.0
21
13
14
20
33
100.0
Total
Saving rates 1999
<-20% -20% - -5% -5% - 5% 5% - 20% 20%+
Saving
rates
1998
Total
<-20%
36
15
11
20
18
100.0
-20% - -5%
25
21
15
21
19
100.0
-5% - 5%
19
18
15
26
23
100.0
5% - 20%
16
10
15
27
32
100.0
20%+
12
7
10
20
53
100.0
20
13
13
22
33
100.0
Total
Saving rates 2000
<-20% -20% - -5% -5% - 5% 5% - 20% 20%+
Saving
rates
1999
Total
<-20%
38
14
13
17
18
100.0
-20% - -5%
26
18
15
21
19
100.0
-5% - 5%
17
17
16
27
23
100.0
5% - 20%
15
14
14
30
28
100.0
20%+
19
9
10
23
48
100.0
20
13
13
24
31
100.0
Total
Source: Liberda, Pęczkowski, 2005, based on 3001 households’ panel from Household
Budget Surveys 1997-2000, CSO, Warsaw.
There is then a clear tendency towards polarization of households with regard to
saving rates. Such polarization indicates that the accumulation of assets by households is
highly unequal. The wealth of households in transition economies will be more and more
unequally distributed between individuals and households that build up their human capital
and material well-being after a collapse of the central planning economy.
4. Savings and investment in human capital
Building human capital on the basis of savings makes long term polarisation of wealth
very important for future social mobility.
Numerous public opinion research showed that precisely the changes that relate to
market economy – income differences, unemployment and economization of public services
- in particular education and health services are the most difficult to accept. However it is
also important to note that people’s ability to adapt to the new conditions has improved from
the very beginning of transition. Growing self-reliance and realism of aspirations were
observed (Gucwa-Lesny 1996), as well as a more self-directed orientation (Kohn and all
1997). Building human capital with one’s own effort is a good example of the growing selfreliance mentioned above. State desertion from social policy which would be active in fields
which are crucial in terms of success in the modern world leads to selective modernization,
concerning only individualized areas of life, and addressed only to some segments of Polish
society.
Half of Polish households save voluntarily around 7 % of their disposable income. The
households also invest in educating children and adults on average 2% of their disposable
income and next 5 % in health care of members of the household.
The profiles of spending for education display an interesting picture. The highest are
expenditures for education in the young age of 20-24 years and then in 30-44 years. The first
is the period of investing in the own education by heads of households. There is an
educational boom at the level of tertiary education in Poland. About half of total number of
students pays fees for their education, though, according to Polish constitution, the tertiary
education is financed by the state. The other very common educational expenditure is for
learning foreign languages and for different types of training, including the post diploma
studies.
Households spending for education account for one fourth of the government spending
for this purpose. If not the private investment in education, Polish society would not have
been well prepared for the competition within EU and on a world scale.
This investment is sizable in relation to a relatively low average income of Polish
households. Total spending of households for human capital is slightly higher than is the sum
of savings.
In one of previous research, based on the structure of expenditures for human capital
and the pattern of saving function according to the level of the household income (Figure 4),
Barbara Liberda (2005) claimed that investment in human capital of Polish households can be
treated as a luxury good.
Figure 4. The share of spendings for education and health care in
household income along with household saving rate in income deciles
groups
25
Percent of
income for
education
mean
20
15
10
Percent of
income for
health mean
5
0
1
2
3
4
5
6
7
-5
Household income decile group
8
9
10
Saving rate
median
-10
-15
Spending for health care are the highest in relation to income in the lowest four
income decile groups. Though they spend for health in nominal terms below the average level
of household health expenditures, this investment constitutes a heavy burden for these poorer
households. Often it is forced by the lack of health service for some social groups in poorer
regions. At the same time 40% of richest households spend for health care more than is the
household average, but in their case investment in health care is less a luxury.
As spending for education is mainly voluntary, the expenditures for health care is very
often forced by the limited access to the public health system (long queues, overcrowding of
hospitals, sometimes low quality of service due to a shortage of qualified staff or a lower
service staff). Households spending for health care are almost of the same size as the
government spending for this purpose.
.
5.Perception of falling social mobility
Subjective opinions about rising inequality of income and wealth were analyzed on the
basis of the results of International Social Survey Program, Social Inequality III, for the years
1992 and 1999. Within this period, East Europeans managed to adjust to market economy,
the economy itself was stabilized, financial crises were overcome, inflation decreased to
acceptable level etc. At the same time due to income and saving inequalities described in this
paper, we can expect accumulation of assets by higher income households, their better
adjustment to inefficient public services by replacing them privately. We anticipated growing
perception of strengthening social barriers.
The social mobility was studied at the beginning of transition. The results showed that
Polish society became again more open than under previous social system. The tendency to
“inherit” social position from parents has diminished. Current occupational status was
determined by the level of education and intellectual flexibility to a greater extent in 1992
than in 1978 (Slomczynski et al. 1996).
However the comparison of these beliefs with opinions expressed by respondents of
Survey discussed here show reversal of this trend at the end of twentieth century. In four
Eastern European Countries where International Social Survey Program was conducted in
1999 (issp@nsd.uib.no), the feeling of difficulties in overcoming social barriers has been
high. It increased between 1992 and 1999 in Poland and in Hungary. In other countries Czech Republic, Slovak Republic and Slovenia, comparisons in time are impossible due to
geographical and political changes which occurred in the analyzed period.
Two variables were analyzed—answer to the following questions: “How important is
coming from a wealthy family?” and “How important is to have connections?”
Both variables were measured on the 5 point scale: 1.Very important, 2.Important, 3.
Somewhat important, 4. Not important, 8. Can’t choose. As both variables are highly
correlated; the principal components analysis was used to reduce them into one component
(the loadings of both variables were equal) measured after normalization on a hundred (100)
points scale. The scale was constructed for each country separately. Higher values indicate
that chances to get ahead are available and that perceptions of an individual are independent
of one’s personal and family connections; the lower values indicate that people perceive
chances to get ahead as not available without these connections. The respective attitudes
are shown on the figure 5.
Figure 5.
Mean values of scale of the availability of social advancement in 1999.
(Chances to get ahead; 1- success determined by the wealth of the family
and personal connections, 100 – no influence of the above factors on getting ahead)
It is interesting to compare Figure 5 with Figure 1 (the value of Gini coefficients).
The higher inequality in the particular country observed the lower perception on the
availability for social advancement expressed by its citizens.
Figure 6 presents changes in respondents status compared with her/his father in Hungary and
in Poland. In both countries significant differences are observed between 1992 and 1999.
Figure 6. Changes in job status.
* Significant change between 1992 and 1999 at p<0.05, Source: Social Inequality III data.
Please think of your present job (or your last one if you don't have one now).
If you compare this job with the job your father had when you were [14/15/16],
would you say that the level or status of your job is (or was)...
100%
*
8*
4*
90%
80%
1*
6*
4*
18*
22*
31*
28*
70%
Much low er than your father's
26*
36*
60%
40%
Higher
44*
55*
Much higher than your father's
38*
30%
36*
20%
10%
0%
Low er
About Equal
50%
18*
8
11*
7
1992
1999
HUNGARY
1992
1999
POLAND
Last figure is a subjective comment to the analysis of saving and investment in
education presented above.
Figure 7.
Opinions about commercialization of education
Is it just or unjust – right or wrong – that people with higher incomes can...
Buy better education for their children than people with lower incomes?
100%
26*
80%
63*
Very unjust
60%
36*
Somewhat unjust
Neither nor
40%
Somewhat just
18*
20%
13
0%
14
Very just
15*
3*
3*
9*
HUNGARY
POLAND
* Significant change between Hungary and Poland at p<0.05
Source: Social Inequality III data.
The visible difference between opinions of Hungarians and Poles are interesting
because in Hungary diminishing influence of the level of education on the level of income
was observed in the nineties. Different studies conducted on panel data in the years 19941997 demonstrated similar results. Maybe lower level of inequality in Hungary makes its
citizens less prepared for commercialization of public services.
6. Conclusions
The analysis of changes of inequality in a transition economy together with the analysis of
income and savings mobility of individuals or households between different income groups
leads to the following conclusions.

The transformation process led to increasing income and social inequalities in all
transition European countries. This process was less acute for households in Hungary,
Czech and Slovakia. In Lithuania, Latvia, Estonia and Poland inequalities increased more

The income and saving mobility between different classes of households (ranked by
income or saving rates) allows for estimating the long term households’ distribution with
regard to income or saving rates.

The tendency towards polarization of households with regard to saving rates signals that
accumulation of assets by households is highly unequal and the wealth of households in
transition economies will be more and more unequally distributed.

Half of Polish households save voluntarily around 7 % of their disposable income. The
households also invest in educating children and adults on average 2% of their disposable
income and next 5 % in health care of members of the household. This investment is
sizable in relation to a relatively low average income of Polish households. Total spending
of households for human capital is slightly higher than is the sum of savings.

The analysis of the results of International Social Survey Program, Social Inequality III
show subjective perception of rising barriers to social advancement.
References
Galasi P. (1998). Income Inequality and Mobility in Hungary 1992-96, Innocenti Occasional
Papers, Economic and Social Policy Series No. 64.
Górecki B., (1999). Dynamika zarobków w krajach przechodzących transformację i w krajach
Unii Europejskiej, (Dynamics of Payment in Transition Countries and in EU), Ekonomista
No. 5, 635-645.
Gorniak, J., 2003. Poland. In: Mikhalev, V. (ed.). Inequality and Social Structure during
the Transition. Oxford, UK: Palgrave Macmilan.
Gucwa-Lesny, E. (1996). ‘Market Oriented Economy and the Polish Soul - Less Romantism,
More Realism’. In: G. Antonides, F. van Raaij and S. Maital (eds). Advances in Economic
Psychology. Chichester. UK: John Wiley and Sons, Ltd., 3-25.
Hirschman, A., (1973). The Changing Tolerance for Income Inequality in the Course of
Economic Development. Quarterly Journal of Economics, 87, 544-566.
Kalbarczyk, M., (2006). Badanie związku między subiektywna a obiektywna zamoznoscia
gospodarstw domowych (Research on the Relationship between Subjective and Objective
Households’ Wealth). Ekonomista,1 (75-87)
Kohn, M.L., Słomczyński, K.M., Janicka, K., Khamelenko, V., Mach, B.W., Paniotto,V.,
Zaborowski,W., Heyman, G.R. (1997). Social Structure and personality under Conditions of
Radical Social Change: A Comparative Analysis of Poland and Ukraine. American
Sociological Review, 62, 614-638.
Kolosi T., P. Robert (2005). Key Processes of Structural Transformation and Mobility in
Hungarian Society since the Fall of Communism, in: Social Report 2004, Budapest, TARKI,
47-71.
Liberda B., (2007). Income Preferences and Household Saving, Gospodarka Narodowa, No.
9; and IAREP/SABE Conference, Paris 2006.
Liberda B., M. Pęczkowski, (2005). Saving Mobility of Polish Households, Proceedings of a
conference on Comparative Economic Analysis of Households` Behavior (Old and New EU
Members), Warsaw University, 2005, Warsaw.
Liberda B., (2005). Inwestycje w kapitał ludzki a stopa oszczędzania gospodarstw domowych
(Human Capital Investment versus Household Saving Rate). Ekonomista 4, 421-447.
Milanovic, B., 1998. Income, Inequality and Poverty during the Transition from Planned to
Market Economy, World Bank.
Słomczyński K. M., Janicka K., Mach B. W., Zaborowski W. 1996. Struktura społeczna a
osobowość. Psychologiczne funkcjonowanie jednostki w warunkach zmiany społecznej
(Social Structure and Personality. Psychological Functioning of the Individual under
Conditions of Social Change. Polish Academy of Sciences. Warsaw.
Transition, the First Ten Years. 2002. World Bank.