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Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
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by Dragana Radevic* and Kathleen Beegle**
*Center for Entrepreneurships and Economic Development (CEED), Program Director,
Podgorica, Montenegro
**Development Research Group, World Bank, Washington, DC
This study is a background paper for the Serbia and Montenegro Poverty Assessment. We express our
sincere appreciation to the households in Montenegro who generously participated in the Household Survey.
We also thank the entire Household Survey team consisted of members of Institute for Strategic Studies and
Prognoses (ISSP), Podgorica, Montenegro for their efforts in collecting timely and crucial data. We are
grateful to Petar Ivanovic and Ruslan Yemtsov for valuable comments and support. The findings and
opinions expressed in this paper are those of the authors and should not be attributed to their institutions.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 1
TABLE OF CONTENTS
Tables and Graphs 2
Executive Summary 3
An Economy in Transition: Reforms and Challenges 3
How many poor? 3
Who are the poor? 5
Outlook for the future 6
Next Steps 7
I. Introduction 8
II. Poverty in Montenegro 11
The Study of Poverty in Montenegro 11
Consumption Poverty 12
Other Poverty Indicators 15
III. Inequality 18
IV. Poverty Profile 20
V. Factors Influencing Poverty in Montenegro 22
VI. Sources of support for households 25
Income Sources 25
Pensions 27
Social Transfers 29
Social protection and poverty 32
Private Transfers 33
VII. Conclusions 34
REFERENCES 36
ANNEX 1: Overview of Montenegro Household Survey Data 38
Background of the Project 38
Survey Rounds and Questionnaire Content 38
Sample and Data Collection 40
Dissemination, Feedback and Coordination 40
ANNEX 2: Welfare measure: household consumption and expenditures 42
Valuation of Housing 42
Adjusting for Regional Price Differences 43
Total Household Consumption 44
Adult equivalence scales 44
Sensitivity to Equivalence Scales 46
ANNEX 3: Poverty Line 49
Food poverty line 50
Comparing Food Baskets 52
Total Poverty Line 53
ANNEX 4: Poverty and Inequality Measures 53
Poverty measures 53
Inequality measures 54
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
2
TABLES AND GRAPHS
Table 1 Poverty in 2002 (Percent of Population) 4
Table 2 Poverty According to the Employment of Household Head in 2002 6
Table 3 Poverty Rates 13
Table 4 Alternative measures of consumption poverty 14
Table 5 Multidimensional Poverty Indicators 16
Table 6 Comparison of Consumption Inequality 19
Table 7 Poverty profile: Poverty Rates by Group 21
Table 8 Regression of Log Consumption per capita on Household Characteristics 24
Table 9 Income Sources for Households (percent of households with any income from
source)
26
Table 10 Composition of Household Income (mean in Euros) 26
Table 11 Percent of Individuals in Households Receiving Pension Income 28
Table 12 Household Pension Income as a Percent of Total Expenditures,
conditional on receiving support
28
Table 13 Percent of Individuals in Households Receiving Social Assistance,
Unemployment Benefits or Scholarship
31
Table 14 Social Transfers (CA, FMS, Other Social Assistance)
as a Percent of Total Expenditures, conditional on receiving
31
Table 15 Why Has Household not applied for Family Material Support 31
Table 16 Receipt of income from social programs 32
Table 17 Percent of Individuals in Households Receiving Private Transfers 33
Table 18 Private Transfers as a Percent of Total Expenditures conditional on receiving 34
Table A 1.1 ISSP Montenegro Household Survey 39
Table A 1.2 Samples in ISSP Household Survey Rounds 1-6 41
Table A 2.1 Non-food expenditure categories, ISSP Household Survey 43
Table A 2.2 Regional prices indices 43
Table A 2.3 Monthly household consumption and expenditures (Euros per month) 44
Table A 2.4 Estimates for Equivalence Scales Using Engel’s Method 46
Table A 3.1 Minimum Food Basket 50
Table A 3.2 Share of Food Basket Calories by Food Groups 53
Graph 1 Deprivation among Households 5
Graph 2 Gross Domestic Product per capita (US$) 8
Graph 3 Labor Force Participation and ILO Unemployment Rates (1995-2002) 10
Graph 4 Household Expenditure Patterns 14
Graph 5 Poverty Incidence Curve 15
Graph 6 Cumulative Distribution of Per Capita Expenditure by Region, 2002 15
Graph 7 Lorenz curve 19
Graph 8 Poverty rate of population in North relative to population in South and Center:
observed and simulated
23
Graph 9 Composition of Household Income (Share of total income by expenditure
groups)
26
Graph 10 Incidence of Pensions 29
Graph 11 Distribution of Social Protection Budget 30
Graph 12 Change in poverty without social protection programs for national populations 32
Graph 2.1 Poverty Rates Using Alternative Scales (fixed poverty at 20%) 47
Graph 2.2 Share of the Poor Using Alternative Scales (fixed poverty at 20%) 48
Graph 4.1 Lorenz Curve 55
Box 1 Poverty where No One Wants to Notice It: “Unofficial” Roma Settlement in
Montenegro
17
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 3
EXECUTIVE SUMMARY
An Economy in Transition: Reforms and Challenges
The Montenegrin economy has been marked by internal and external political and economic shocks
in the last decade. In recent years, Montenegro has undertaken an ambitious program of wide-
reaching economic reforms in an effort to promote growth and raise living standards. Still,
additional reforms are needed, for example, to confront a large public sector wage bill, heavy
dependence on donor assistance, and inefficiencies in state-owned enterprises. The uneven progress
in reforms is reflected in rather ambiguous macroeconomic performance: while GDP has been
slowly recovering since 1999 to about two percent growth during the last two years, employment
indicators do not reflect the positive gains to GDP.
Unfortunately, many new policies are being implemented with little information available about the
numbers and characteristics of the poor, let alone with an evaluation of the subsequent impact of
reforms for the poor. Moreover, efforts to reduce poverty and raising living standards are made
more difficult by the high expectations of the population for the economic reforms. Recognizing the
need for rigorous planning for poverty reduction activities and monitoring, Serbia and Montenegro
completed an Interim Poverty Reduction Strategy Paper (I-PRSP) in July 2002. The full PRSP is in
the drafting process in Montenegro. By analyzing the timely data on poverty and building on
previous analysis, this paper will supply critical information to the PRSP process.
This study provides an overview of the profile of poverty and living standards in Montenegro
using the most recent and best data available. The results show that the very dismal perceptions
of poverty are far from reality. On the other hand, it also highlights that it is important to
evaluate the potential impact of economics reforms on the poorest in Montenegro who remain
vulnerable to changes in the economic environment. By presenting an array of important results,
this document serves as a platform for important discussions in Montenegro on poverty
reduction strategies and efforts to monitor progress in their implementation.
How many poor?
Using the most recent and probably best survey data on living standards available for Montenegro,
applying strict definitions of household welfare, and establishing a poverty threshold, this study
finds that there are not a large number of people living in absolute poverty. Around 10 percent of
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
4
the population live in absolute material poverty. Poverty is not deep; the total poverty gap is
around 1 percent of GDP. Extreme poverty has been largely eradicated, though it is important
to recognize that pockets of it probably exists among subpopulations that are difficult to capture in a
household survey (especially the Roma and IDPs).
Although the poverty rate is low and poverty is shallow, poverty estimates are sensitive to the
poverty threshold. More than one third of the population is classified as economically
vulnerable, living below 150% of the poverty threshold. Raising the poverty line by 20 percent
doubles the poverty rate. Thus, living just above the poverty line, a significant share of the
population are vulnerable in the sense that they are vulnerable to any economy-wide fluctuation,
downturn, or personals income shock. A positive income shock (perhaps those associated with
growth and good policies, for example) would be associated with more-than-proportional declines
in poverty; negative shocks (such as recession) would lead to more-than-proportional increases in
poverty.
Table 1. Poverty in 2002 (Percent of Population)
Food
Poverty
Absolute
(baseline)
Economically
Vulnerable or Poor
4.0 9.4 36.4
Source: ISSP Household Survey 5 and 6. Food poverty is defined as a situation when the food
expenditures of a household are below the cost of the minimum food basket (41 Euros per month per person).
Absolute poverty is defined as total consumption below the cost of the full minimum subsistence basket, or
poverty line (107 Euros per month) and economies vulnerability line is set at the level 50 percent above the
poverty line. See Text for details.
Consumption poverty is only part of the story. Also, there is poverty in other dimensions besides
consumption, including poverty related to employment, housing, and health. About one in five
adults is not working but is ready to work if a job opportunity was available (employment poor);
two-fifths of all households have at least one household member who is employment poor. About
13 percent of the population resides in dwellings without piped water or a bathroom. About 6
percent of the population had an illness or injury that prevented normal activities. Nevertheless,
consistent with the lack of extreme consumption poverty, few people suffer several deprivations
simultaneously (Figure 1).
Inequality indicators are within the range of other economies in the region, but inequality that
stresses the relative position of the poor to the richest households (the 90/10 decile ratio) indicates
somewhat high inequality.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 5
Figure 1: Deprivation among Households
0 deprivations
46%
1 deprivation
38%
2 deprivations
13%
3-5
deprivations
3%
Source: ISSP Household Survey 5 and 6. Notes: See Table 3 in Text for
complete definitions. Deprivations include: consumption poverty, any
employment poverty among adults in household, health poverty, housing
p
overty in dwelling size, and lack of a telephone.
Who are the poor?
Interesting patterns merge in looking at the profile of the poor in Montenegro. The poor spend the
largest share of their expenditure on food. Housing is the second largest component in expenditure.
Large households are more likely to be poor, although they contribute a small share to the total
population of poor since average household size is small.
There is a strong regional aspect to poverty; poverty is highest among households in the Northern
region. It is striking that a country as compact as Montenegro had 1:2 differences in poverty rates
between the poorest and the richest regions. While basic characteristics, such as the level of
education, employment and the demographic structure, explain some of the regional differences,
strong disparities remain even after controlling for these background characteristics using
multivariate analysis. That is, regional differences cannot fully be accounted for by the education,
employment, demographic, and other household factors that differ across region. There are other,
general factors that make certain localities poor.
Employment opportunities matter; employment characteristics of household members, including
their human capital (education attainment), are strong determinants of living standards. Households
with working adults have higher consumption levels; inactivity and joblessness are strongly
correlated with poverty. At the same time, poverty exists in many households where the household
head is employed who make up fully two-fifths of poor households.
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
6
Table 2: Poverty According to the Employment of Household Head in 2002
Poor, % of
population in a group
Share in the
population
Share among
the poor
Poverty
depth
Poverty
severity
Not employed and not retired 18.6 9.8 19.3 3.0 0.8
Employed 6.5 62.4 43.5 0.9 0.2
Retired and not employed 12.1 27.8 37.2 1.6 0.3
Total 9.4 100 100 1.3 0.3
Source: ISSP Household Survey 5 and 6. Employed is defined as having worked for income in the last week or having a regular job
but not worked last week (vacation, sick, etc..); “retired” are those who are not employed and self-identify and report being retired as
their main activity; “not employed” are all others.
By protecting households against poverty, social insurance plays an important poverty alleviation
role. As a source of income for the poor, pensions are important, with old-age and disability
income being the dominant categories. Unemployment benefit, on the other hand, is received by a
very small percent of households. While the poor are more likely to receive social assistance, levels
of assistance (prevalence and amounts) are low and generally too low to have much impact of living
standards.
Outlook for the future
In the area of monitoring, it is necessary to establish clear guidelines for monitoring poverty
over time in a consistent and comparable way. A key action will require building consensus around
official poverty line and the poverty measurement methodology. Moreover, establishing both the
core indicators that will be monitored over time and the targets for these indicators requires careful
consideration. In the analysis of poverty, this document highlights the need for additional
analysis, including, among other areas, (i) forecasting the impact of pension reforms on the poor,
(ii) assessing the targeting and efficiency of the social programs, (iii) understanding constraints to
rural incomes, (iv) building a proper knowledge base to link the environmental issues and poverty,
and (v) simulating distributional effects of growth forecasts.
Proper monitoring and evaluation of living standards should be a priority task of the government.
However, without good data, policies will be misguided or not guided at all. This paper highlights
the need for timely, high-quality, accessible data to facilitate this task. Implementation of regular
household surveys that allow accurate monitoring of poverty will be therefore essential part of the
strategy. The data for poverty analysis in this assessment and in the PRSP come largely from
externally funded surveys implemented by NGO (Institute for Strategic Studies and Prognoses
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 7
(ISSP)), which showed its professionalism, expertise and flexibility to introduce in short period of
time international standards in all phases of undertaking the Household Survey.
But Montenegro still faces the challenge of developing a statistical system that can collect, process,
analyze, and disseminate information on living standards. The next step in this effort could be
coordinating the data collection efforts at ISSP with the on-going official household budget surveys
at MONSTAT to more fully develop data systems for poverty monitoring. Meanwhile, since the
regular data collection is a necessity and keeping in mind that Government of Montenegro adopted
Law on private sector participation in public services delivering, it is suggested to continue
cooperation with the NGO sector while capacities of MONSTAT are developed.
Political instability has also been an important factor affecting poverty: refugees and IDPs, in
particular. The lack of information in this assessment on the living standards of Roma,
refugees, and IDPs (groups that are notoriously difficult to sample and survey) warrants attention.
For example, it is likely that Roma households suffer much more extreme poverty than is captured
in existing household survey samples. The follow up research and data collection effort should
focus on these groups to complement the existing data on poverty among the main population strata.
Next steps
The work to follow from this assessment, therefore, is multifaceted. It will include:
• Collaboration with MONSTAT in the development of staff skills through upcoming ISSP
surveys
• A special household survey on Roma and IDPs conducted by ISSP in summer 2003 with
support and technical advice from the World Bank and United Nation Development
Programme, Liaison Office in Podgorica, Montenegro
• Expanding coverage of the ISSP household survey for analysis of issues related to
environmental analyses
• Developing the ISSP household survey questionnaire for analysis of the implications of
enterprise restructuring on labor markets and poverty.
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
8
I. INTRODUCTION
In last ten years, the Montenegrin economy has undergone rapid economic transformation. Since
the economic and political collapse of Yugoslavia, the Republic of Montenegro has suffered a loss
of 57% of the economic power it had in 1989 (Figure 2). GDP has been slowly recovering since
1999 to about two percent growth during the last two years. The transition has been marked by
internal and external political and economic shocks, leading to a deep and sharp decline in output,
hyperinflation, a rise in official unemployment, and a growing informal sector (“gray” economy).
In January 2002 Montenegro introduced EURO as official currency. Consequently, the
Montenegrin economy experienced “€ inflation”, characteristic for European countries that adopted
the new currency.
Figure 2: Gross Domestic Product per capita (US$)
0.0
300.0
600.0
900.0
1,200.0
1,500.0
1,800.0
2,100.0
2,400.0
2,700.0
3,000.0
3,300.0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Source: Institute for Strategic Studies and Prognoses (ISSP)
Currently, Montenegro is part of the Union of Serbia and Montenegro (SAM), which share a joint
Parliament, Presidency, and Council of Ministers. The union Parliament elects the President of the
union, who is responsible for proposing the Council of Ministers and directs its work. The union
Council of Ministers has five departments: foreign affairs, defense, international economic
relations, internal economic relations, and protection of human and minority rights. These common
functions in SAM will be jointly financed, in proportion to each republics contribution in GDP.
While these two republics have some joint institutions, they operate separate economic, fiscal, and
monetary policies.
Shortly following the 1999 elections, Montenegro implemented an array of economic reforms,
generally begun earlier than in Serbia.1 These initial reforms included efforts to stabilize prices, to
reduce fiscal deficits, and to eliminate trade distortions. Inflation fell from over 100 percent per
annum in 1999 to 24 percent in 2001 after the introduction of the Deutsche Mark as legal tender.
With increases in the administered prices in the energy sector, price distortions were reduced while
at the same time improving the financial position of the state-owned power company EPCG. Strict
1 Material in this section was drawn from ISSP (2003) and World Bank (2003).
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 9
limits on lending introduced in 1999, including a 100 percent reserve requirement against enterprise
deposits, helped to stabilize the banking system. In 2000 custom tariff structure was simplified and
the average tariff rate was reduced to less than 3 percent.
Reforms accelerated in 2001 with initiation of important reforms in public financial management.
On the revenue side, recent legislation should expand of the revenue base by reducing tax evasion
improved tax administration and collection. In April 2003, Government further boosted the
collection of indirect taxes by introducing a VAT. There are also new initiatives to improve the
targeting of social assistance and child allowances to the poorest households. Price distortions
continue to be addressed; there has been full liberalization of the prices of basic food items.
In the financial sector, efforts are underway to establish a sound banking system and to define the
core central bank functions. Despite the large increase in total deposits observed since the
conversion to the Euro, there remains a high level of distrust of the public towards the banking
sector. A comprehensive set of regulations is being developed to govern the licensing provisions,
financial reporting, and performance requirements for commercial banks. Legislation related to
bankruptcy and liquidation, defining the triggers and procedures involved in actions against
insolvent banks, was enacted.
Despite ambitious reforms, challenges remain. Montenegro has a large public sector, including a
significant public sector wage bill (44% of total expenditures), and there is a heavy dependence on
donor assistance and other forms of external finance to cover current consumption levels and
investment. Foreign aid represented almost 12 percent of total revenues. Additional reforms in
state-owned enterprises are still needed. Many socially owned enterprises continue to be
unprofitable, requiring substantial state subsidies to remain in operation. The state-owned power
company continues to effectively subsidize both households and state-owned enterprises, such as
KAP - the Republic’s aluminum producer. Meanwhile, its supply of coal is unstable due to
financial, technical, and organizational problems in the coalmines.
As loss-making public enterprises cease to receive budget subsidies, there are concerns that
unemployment may grow. Unemployment levels are somewhat high compared to other countries in
the region, a problem due to the particulars of the labor market (seasonality and informal sector)
and the mismatch between the education system and job skills demanded in the new economy.
Despite fears of mass-layoffs, in the aggregate, unemployment (defined by ILO standards rather
than the number of registered unemployed) has not been growing steadily in the past years. Yet,
there are some shifts from 2000 and, generally, very large differences in both unemployment rate
and labor force participation rate by gender (see statistics from the Labor Force Survey, 2000, in
Figure 3). These employment indicators fail to reflect the positive gains to GDP in the last two
years. If the growth process does not result in job creation, we may not seem a reduction in
poverty.
What do all of these changes mean for poverty and inequality in Montenegro? The general
perception is that the transition to a market economy has resulted in an increase in poverty and
inequality in Montenegro, although thorough statistics to assess this are not available. Even so, the
on-going transition process, which may include reforms of the pension scheme, potential increases
in unemployment, and on-going efforts to re-target social assistance, could have significant impacts
on the poor. The need to evaluate the magnitude and dimensions of these changes is crucial. These
transitions have different implications for different demographic groups as well as for the different
regions.2
2 Montenegro can be grouped into three regions. The Center region is the most populated and industrialized. The South
is coastal and the most developed region; tourism is the main economic sector. The least developed region is the North,
which is mountainous and less populated. See Annex 1 for a complete list of the municipalities in each region.
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
10
Source: Labor Force Survey, calculations done by Branko Jovanovic (2003)
Recognizing the need for rigorous planning for poverty reduction activities and monitoring, Serbia
and Montenegro completed an Interim Poverty Reduction Strategy Paper (I-PRSP) in July 2002.
The full PRSP is in the drafting process in Montenegro. By analyzing the timely data on poverty
and building on previous analysis, this paper will supply critical information to the PRSP process.
While data constraints have limited the ability to evaluate poverty and living standards in recent
years, new household surveys collected in 2002 allow us to establish a baseline in regards to the
living standards of the Montenegrin population from which changes in the future can be monitored.
Furthermore, with these data on household living standards, analysis can evaluate the role of social
policies in supporting the poor as well as the potential impact of major policy reforms. The
objective of this study is to provide a broad profile of poverty in Montenegro as well as suggest
areas for future analysis.
Figure 3: Labor Force Participation and ILO
Unemployment Rates (1995-2002)
0%
20%
40%
60%
80%
1995 1996 1997 1998 1999 2000 2001 2002
Percent
LFP Men
LFP Women
Unemp Women
Unemp Men
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 11
II. POVERTY IN MONTENEGRO
The Study of Poverty in Montenegro
Poverty is a multidimensional concept encompassing various aspects of well-being. In practice,
there is no one single indicator that captures all the dimensions of poverty. To this end, this
document presents statistics across an array of socio-economic indicators to describe the living
standards of the population. The statistics are drawn mainly from the ISSP Household Survey
(HHS) data collected in July and October of 20023. From these household survey data, we measure
material well-being using total household consumption as our main, but not only, indicator (see
Annex 2). Our consumption indicator is then compared to a poverty threshold which is a minimum
living standard (in Euros) calculated based on the actual consumption patterns and minimum caloric
needs (see Annex 3), applying methodologies based on international best-practices, making the
results internationally comparable.
The ISSP HHS data are not the only source of survey data for poverty analysis. Among the other
sources, there is the Household Consumption Survey (APD) is conducted by Federal Statistical
Office (FSO) of Serbia and Montenegro. This quarterly survey includes 380 households from 12
municipalities in Montenegro, about 11 percent of the total household sample for the Union of
Serbia and Montenegro, all part of the permanent population. A second data source for poverty
measurement is an individual and household survey conducted by the OCHA sub-office in
Podgorica, implemented during the month of June 2000 (OCHA, 2000). The sample size of the
survey was 2,000 permanent resident households, selected randomly and in proportion to the
population density throughout Montenegro’s 21 municipalities. Finally, a third data source are the
four bi-monthly UNDP Household Surveys conducted from September 2000 until March 2001
covering random sample of 2000 households from all Montenegrin municipalities (UNDP, 2001).
While there are many common features of these studies of poverty and this present analysis, the
results using the HHS are not comparable with these previous poverty studies for several reasons.
The sampling frame for the ISSP HHS was based on adult population listing from 2002, while
previous studies drew samples based on the census from 1991. Moreover, the sample size of the
FSO survey (380) will be insufficient for regional statistics and perhaps national statistics also. The
questionnaire of the ISSP HHS includes detailed consumption and expenditure modules as well as a
range of other topics (such as migration information, housing conditions, durable asset ownership,
labor and non-labor income including assistance from social programs and private transfers,
employment characteristics, health care utilization, and subjective assessment of well-being). In
comparison, the APD questionnaire was developed and implemented ten years ago and covers
fewer food items. OCHA Survey had a very limited questionnaire containing a simple basket of
food (15 items) plus personal and household hygiene items, while the UNDP Surveys asked
cumulative questions about households’ expenditures for a one-month recall period. The
differences in the specific list of consumption items as well as the recall period make intra-survey
comparisons difficult.
A third difference in approaches is the poverty indicators used in different studies. These indicators
differ according to the welfare measure (consumption/expenditure or income) and the construction
of the poverty line. Using the ISSP HHS, our welfare measure is consumption/expenditure (see
3 The HHSs have been developed and fielded by the Institute for Strategic Studies and Prognoses (ISSP). This work has
been supported by the European Commission Food Security Programme, USAID Montenegro, and Chesapeake
Associates. In addition, for HHS Rounds 4, 5 & 6, ISSP have received technical assistance and feedback from World
Bank staff. For more information see Annex 1, and ISSP 2002a, 2002b.
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
12
Annex 2). The poverty line in this study identifies the cost of basic needs as the cost of a food
basket to reach a nutrition standard (the food poverty line) and the cost of non-food expenditures of
households whose food consumption is near the food poverty line. The FSO poverty statistics
compare household income (without imputed housing value and with savings) against the official
“minimal food basket”, which is a food poverty line. The OCHA Survey uses both the official FSO
food poverty line and a poverty line based on the “OCHA Podgorica Shopping Basket” constructed
from expenditures for only 15 food items, expenditure on hygiene items, and limited expenditures
for electricity, heating, education, and medicine. The UNDP study uses multiple poverty indicators,
including the ratio of food expenditures, income-to-expenditures ratio, income per capita below 100
DEM4, and household expenditures below 150 DEM. The 100 DEM cutoff was chosen based on
the OCHA report.
The various differences in sample frame, questionnaire design, and poverty indicators bring us to
the conclusion that poverty indicators from this study are incomparable with results from the
previous years. Nevertheless, some comparisons are made where useful, such as comparing budget
shares for different categories of expenditure. However, even these comparisons are made with
caution to the differences in survey design.
Consumption Poverty
Table 3 reports the poverty rates for Montenegro and by region based on the comparison of
consumption with a minimum living standard (poverty line) for the population. The table reveals
that consumption poverty affects a sizeable segment of the population: 9.4 percent of the population
live below the absolute poverty line. This figure may be an underestimate because the sample
misses some of the most vulnerable populations (Roma and IDPs). Poverty is lowest in the Center
and South, and significantly higher among the population in the North, which is least populated, and
least developed. Statistical estimates obtained on the basis of any sample survey have only a certain
degree of precision. In addition to the calculated poverty rate, Table 1 also presents a 95 percent
confidence interval for each point estimate. While the confidence interval for the poverty rate in the
Center and South regions overlap, the confidence interval for the poverty rate in the North, 14.9
percent, is statistically above both Center and South regions. Overall, more than half of the poor
reside in the North (54%). One-third of the poor are in the Center, and the South has the smallest
share of the poor (16%).5
In addition to calculating the poverty rate, we estimate the fraction of the population that is
economically vulnerable and poor by increasing the poverty line by 50 percent. One-third of the
population live below this higher poverty line. Again, the poverty rate in the North, 45 percent, is
significantly higher than in the other regions.
To highlight the complex distributional aspects of poverty, additional measures of the depth
(measured as poverty gap) and the severity of poverty are presented. The poverty depth measures
how badly off the poor are — how far below the poverty line their consumption levels are. The
poverty gap is equal to 1.3 percent, which indicates that if Montenegro could mobilize resources
equivalent to 1.3 percent of the poverty line for every individual (both poor and non-poor) to be
given directly to the poor, all the poor could be lifted out of poverty. This assumes, of course, that
the poor can be perfectly targeted. The total poverty gap is around 1 percent of GDP. A
4 1 EUR=1.95583 DEM
5 In additional to a regional division, the separation of urban and rural areas would also be revealing. While the data
does not explicitly link households to the urban or rural location as defined by the Federal Statistics Office, agricultural
land holdings is one co-variate that is subsequently used in this report and captures some of the urban/rural dimension.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 13
corresponding measure, average shortfall, shows that consumption of the poor falls, on average, 14
percent short of the poverty line.
Poverty severity is a measure closely related to the poverty gap but giving those further away from
the poverty line—the poorest—a higher ‘weight’ in aggregation than those closer to the poverty
line. Its level in Montenegro is 0.3. The North, which is characterized with higher poverty rates,
also has higher poverty depth and severity. In sum, though, these data suggest that the depth and
severity of poverty are not extreme, and are actually small in comparison with other countries
suggesting that social assistance could possibly fill in the gap if targeted well.
Alternative consumption-poverty measures in Table 4 show that four percent of the population live
in households with total expenditure below the value of the minimum food basket, indicating that
there is no measurable extreme poverty.6 However, more than one-thirds of the population is
economically vulnerable, having consumption below 150% of the poverty line.
Table 3: Poverty Rates
Montenegro North Center South
Poverty rate: Head Count 9.4 14.9 6.5 6.8
95% confidence interval [7.5-11.3] [10.9-18.9] [4.1-8.9] [3.3-10.3]
Poverty and Economic Vulnerability: Head
Count
36.4 44.8 33.2 29.8
95% confidence interval [33.5-39.4] [39.6-50.0] [28.8-37.6] [23.8-35.8]
Percent of all poor 100.0 54.0 30.5 15.5
Poverty gap 1.3 2.2 0.9 0.7
95% confidence interval [0.9-1.6] [1.4-2.9] [0.5-1.3] [0.3-1.2]
Severity of Poverty 0.3 0.5 0.2 0.1
95% confidence interval [0.2-0.4] [0.3-0.8] [0.1-0.3] [0.03-0.2]
Average shortfall of the poor as percent of
poverty line
14.0 14.8 14.1 11.2
Source: ISSP Household Survey 5 and 6. Note: Standard errors in parentheses.
About one-fifth of households spend more than 60 percent of their resources on food. These
households are concentrated in the North, where a larger share of total expenditure is for food
more than half on average than the food share among households in the Center or South regions
(see Figure 4).7 The greater allocation of the household budget to food is consistent with the higher
poverty in the North.
6 A strong caveat to this statement is that the sample for Montenegro excludes the Roma population and the population
of IDPs from Kosovo.
7 Likewise, the UNDP study (2001), which reports general expenditure data patterns for 2001, finds that households in
the North had the higher food shares. The food share calculated for Montenegrin households was lower in the study by
OCHA (2000), about 40 percent. The portion of household expenditures on food (about 50% on average) is the same in
Serbia (See Krstic, 2003).
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
14
Table 4: Alternative measures of consumption poverty
% of population
Absolute poverty: Consumption/expenditures below absolute poverty
line (107 Euros per person per month) 9.4
Economically vulnerable and absolute poverty:
Consumption/expenditures below absolute poverty line +50%
(160.5 Euros per person per month) 36.4
Relative poverty: Consumption/expenditures below relative poverty
line (50% of median consumption: 105 Euros per person per month) 9.1
Food poor: Food expenditure < Food poverty line 4.0
Ratio of food expenditures > 0.6 23.5
Household expenditures/average expenditures < 0.5 8.2
Source: ISSP Household Survey 5 and 6.
Source: ISSP Household Survey 5 and 6. Note: See Annex 2 for category definitions
Since poverty is not necessarily very deep (see Table 3), we can expect that small changes in the
poverty line could have a magnified impact on the proportion of the population in poverty. The
effect on the poverty rate from change in the poverty line is presented in Figure 5. This figure
shows that increase of poverty line significantly increases the percentage of poor. Poverty line
increase of 20 percent is associated with an increase in the poverty rate by 100 percent on a national
level. Keeping in mind regional differences, given a poverty line increase of 20 percent, the
poverty rate in the North would in increase by about 90 percent, by almost 130 percent in the
central part, and by almost 70 percent in the south of Montenegro.
Figure 6 reports the cumulative distribution of per capita expenditure by region. Given that the
three curves do not cross, regardless of the choice of the poverty line, the poverty rate in north
Montenegro is always higher than in central and southern part of Republic.
Figure 4: Household Expenditure Patterns
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Montenegro
North
Center
South
Percent
housing
other annual
education
other quarterly
health
clothing
hh items
other monthly
transport
utilities
personal
food
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 15
Figure 5: Poverty Incidence Curve
0
10
20
30
40
50
60
70
80
90
50 75 100 125 150 175 200 225 250 275 300 325 350 375
Poverty line
Poverty rate
Source: ISSP Household Survey 5 and 6.
Figure 6: Cumulative Distribution of Per Capita Expenditure by Region, 2002
Probability <= PCE
Per Capita Monthly expenditure
Nor th Center
South
50 100 200 300 400 500 600 700 800
0
.2
.4
.6
.8
1
Source: ISSP Household Survey 5 and 6.
Other Poverty Indicators
While this paper mostly measures poverty based on household consumption, poverty is a
multidimensional concept encompassing various aspects of well-being. Different aspects of poverty
–consumption and non-consumption – interact and reinforce each other in ways that often
exacerbate the deprivation that poor people face. Poor health outcomes and low educational
achievement not only decrease well-being, but also limit income-earning and consumption
potential. Identifying different dimensions of poverty is important in the context of understanding
p
overt
y
line
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
16
the profile of vulnerable groups. Households that are not income/consumption poor may
nonetheless be poor in other dimensions. Moreover, some households may suffer from multiple
deprivations, thus constituting “the core” of the poor. Table 5 displays several such indicators.
About 5 percent of adults in Montenegro can be considered “education poor”, meaning that they are
not in school and did not attend secondary school. The more relevant challenge in Montenegro in
regards to education is not post-primary enrollment, but, rather, the quality of schooling and the
extent to which skills acquired in the education system match the labor demand in the economy.
The education system was designed to meet the labor demand needs of the pre-transitional period.
In addition to outdated curriculum, the current system suffers from inefficiencies in education
services across locations, such as towns experiencing over-crowding and rural areas being under-
utilized.
Table 5: Multidimensional Poverty Indicators
Indicators % of
population
% of consumption-
poor population
Consumption poverty
absolute poverty
economically vulnerable
9.4
36.4
Education poverty
16-24 years: not in school and did not attend secondary school
4.7
13.5
Health poverty
any illness/injury in last 30 days that precluded usual activities or
disabled
6.4
6.1
Employment poverty
ages 16-65: not working but ready to work if have job opportunity
22.0
40.3
any member age 16-65 not working but ready to work if have job
opportunity
40.2
62.1
Housing poverty
drinking source for dwelling is not piped water (ex: pump well) or
dwelling has no bathroom*
13.1
25.0
Dwelling has less than 10m² per person 8.2 22.7
Lacking consumer assets
No telephone 9.7 14.6
No television 3.7 5.7
No washing machine 7.8 22.7
Source: ISSP Household Survey 5 and 6.
*Housing – Data from ISSP Household Survey 6 only (drinking water not asked in Survey 5).
The measure of health poverty, any illness/injury in last 30 days that precluded usual activities or
disabled, affects 6 percent of the population. Over 22 percent of working-age adults are poor with
respect to employment, defined as not working but ready to work if job opportunity were available.
Lack of employment opportunities remains a challenge for the government. Earlier programs were
aimed at reducing redundant labor through severance and early retirement packages; newer efforts
aim to boost credit to unemployed persons to start a business, while tax on labor for newly created
jobs have been reduce also. In addition to this program, the Employment Office and donors have
organized training programs for unemployed (e.g. preprations for new job, vacation trainings for
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 17
known employer and preparation for labour market8). Nevertheless, nearly one in five prime-age
adults are unable to find work.
Housing conditions for 13 percent of population are below the poverty standard of piped drinking
water or bathroom in dwelling; eight percent of the population live in a dwelling with less than 10
m2 per person. While there is only one household in the sample that had no electricity, about 10
percent of the population live in dwellings with no telephone.
The second column in Table 5 shows the poverty indicator rates for the population of consumption-
poor. It is meant to identify the extent to which this indicator overlaps with non-consumption
poverty measures. While some of these are similar to the poverty rate using consumption, there is
only partial overlap between the consumption-poor and those deprived of the indicators in the table.
Nevertheless, for most indicators, the rate is much higher among the consumption-poor, especially
in housing characteristics and employment.
Box 1: Poverty Where No One Wants to Notice It: “Unofficial” Roma Settlement in Montenegro.
Around ninety persons from twenty Romani families, mostly displaced from Kosovo and currently
settled in the Lovanja settlement, struggle daily just to survive. Lovanja is located in the Tivat Field
(Tivatsko polje), in the territory of Kotor municipality, on the beautiful Montenegrin coast along the
Adriatic Sea. Roma of Lovanja live on the edge of a local garbage dump in substandard housing
conditions in self-made huts. The settlement does not have a supply of potable water or electricity supply,
and is under threat of flooding in heavy rainfall. The closest medical facility in the town of Kotor, around
8 km away from the settlement, and there are no public transport connections. Reportedly, the local
authorities had decided to relocate the settlement to a more humane environment in 1999, but nothing
had happened to date.
Roma in this settlement live in extreme poverty. About one half of the settlement's inhabitants are under
the age of 18, and none of the children attends school. The Lovanja Roma make a living by collecting
scrap materials and occasional manual labor paid by the hour. According to the Secretariat for Displaced
Persons of Montenegro, Lovanja is categorized as an "unofficial centre for displaced persons". Such
unofficial camps vastly outnumber official camps, and provide self-made temporary shelters for a
majority of the estimated 20,000 Roma IDPs from Kosovo in Montenegro.
Source: The European Roma Rights Center (ERRC), citing Tivat-based non-governmental organization
“MARGO” - Association for Help and Support to Marginal Society Groups, see:
http://errc.org/publications/letters/2002/montenegro_jan_10_2002.shtml
8 Source: Employment Fund of The Republic of Montenegro
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
18
III. INEQUALITY
Evaluating inequality is interesting because it can help us understand how the benefits of growth are
distributed over time. Growth that occurs mainly to the top of the income distribution may do little
to improve living standards of the poor, which will be reflected in increases in inequality. The on-
going economic reforms in Montenegro have raised many concerns that inequality would
subsequently increase, especially given the shift from formal to informal employment. While
comparable data for the years prior to 2002 is not available, we can compare consumption
inequality measures in Montenegro with those in neighboring countries.9
There are several ways to display consumption inequality (for more details on those used here, see
Annex 4). Figure 6 shows the Lorenz curve for per capita consumption in Montenegro. This curve
graphs the cumulative frequency of consumption per capita against a uniform distribution (which
represents perfect equality in consumption). This relationship can, in turn, be summarized in the
Gini coefficient.10 A second widely-used inequality measure is the decile ratio (90/10 ratio), which
presents the ratio of the average consumption of the richest 10 percent of the population divided by
the average consumption of the bottom 10 percent. This measure perhaps better captures the
relative position of the poorest in the population, rather than the Gini coefficient, which can be
difficult to interpret with respect to inferences about the poor and poverty. In this sense, the 90/10
ratio may be a more appealing indicator monitoring inequality and progress at poverty alleviation in
Montenegro. These summary statistics are presented in Table 6.
The Gini coefficient in Montenegro is .29, with not statistical difference in this inequality measure
across regions. Montenegro’s inequality is within solidly the range of those of other East European
transition countries. Among the set of neighboring countries, some have lower levels of inequality
(e.g. Albania, Bulgaria, Hungary and Slovenia) while others have higher inequality (Croatia, FYR
Macedonia and Estonia). The Gini coefficient for Montenegro and Serbia are quite close. An
alternative to consumption inequality is income inequality, which is generally higher than
consumption inequality for all countries in the region. Montenegro’s income inequality is in the
upper range in the region (Gini coefficient of .37), whereas Serbia has smaller income inequality
(.33), about average in the region. Given the concern over the ability to measure income well,
considering the large informal sector and seasonal labor earnings, we are cautious in emphasizing
income inequality results.
The 90/10 ratio, however, shows that Montenegro has very high inequality compared to other
countries, second only to the level in Serbia (5.8 and 6.7, respectively). This is closer to the level of
the very unequal economies where this ratio can be as high as 7.
9 While consumption inequality for Montenegro is unavailable prior to 2002, there are data for SAM from the HBS and
Labor Force Survey data on earnings (income inequality). These data sources suggests that, contrary to perceptions in
SAM and experiences in other transition economies, inequality did not change.
10 The Gini is calculated as the area between the curves divided by the area under the line of equality. A larger Gini
indicates greater inequality. If the Gini coefficient is equal to 0 we have perfect equality (represented by diagonal line
in the graph of Lorenz curve).
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 19
Figure 7. Lorenz curve
cumulative proport ion of pce
Lorenz curve
cumulative proportion of sample
_perc _share
0.25 .5 .75 1
0
.25
.5
.75
1
Table 6: Comparison of Consumption Inequality
Country Gini coefficient 90/10 ratio
Bosnia and Herzegovina, 2001 0.26 3.3
Albania, 2002 0.28 3.6
Hungary, 1997 0.28 3.5
Serbia, 2002 0.28 6.7
Slovenia, 1997/1998 0.28 3.7
Montenegro, 2002 0.29 5.8
Bulgaria, 2001 0.30 4.1
Croatia, 1998 0.30 3.9
FYR Macedonia, 2000 0.31 4.3
Estonia, 1998 0.38 5.4
Notes: Statistics for Bosnia from World Bank (2002b); Albania from World Bank (2002a);
Hungary, Slovenia, and Estonia from World Bank (2000); Serbia from Milanovic (2003);
Bulgaria from World Bank (2002c); Croatia from Luttmer (2002); Macedonia from staff
estimates based on HBS data for 2000; Montenegro from ISSP Household Survey 5 and 6.
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
20
IV. POVERTY PROFILE
This section describes the characteristics of the poor and examines the correlates of poverty in
Montenegro. By examining the poverty risk for different groups of the population as well as the
population shares of different groups, we hope to gain insights into how efficient poverty reduction
strategies can be developed.
Table 7 presents the poverty rates for seven different categories of the population. This table
reveals several interesting things. First, there are several groups whose risk of poverty is above the
national average. Second, even if risk is high, it is important to consider the population share of a
group and the contribution of a high-risk group to the total number of poor. Finally, the table
reveals groups that are not among the poor contrary to common belief.
People in large households have a higher poverty risk than those in smaller households. Lack of
education of the household head is associated with higher poverty risk. People in households whose
head has not attended secondary school have poverty rates three times higher than those living in
with household heads having some secondary. However, this first group represents only about 17
percent of the population. Thus, the majority of the poor (65%) live in households whose head has
attended some secondary school.
Employment status is associated with poverty risk. Households headed by those who are non-
working, non-retired have the highest risk of poverty (19%). Having a household head employed is
associated with lower poverty (7%).
Ownership of agricultural land is not associated with increased risk of being poor. While one-third
of households own some agricultural land, it should be noted that only 5 percent of household heads
are engaged in the agricultural sector as their primary activity (including fishing).
Migration is associated with lower poverty risk. Households whose household head was born
outside of Montenegro had lower poverty rates (under 4%) than those whose head was born in
Montenegro (11%), although there are few households in the former category (8% of all
households).
There are several groups that, contrary to common belief, are not more likely to be poor than
average. The first of these conventionally poor groups is the elderly. The elderly are not more
likely to live in poor households (likewise, people in households headed by someone over 50 years
are not more likely to be poor). Another group is children. If we consider the poverty rates by age
groups, we see that children under 16 years have are little bit more likely to be poor in comparisons
to other age groups, but no significantly. Also, there is no significant difference in poverty rates
among individuals in age groups “16-24”, “25-49” and “65+”. In other words, we can say that
poverty is practically equally distributed among the population considering their age. Although less
then 10 percent of households are headed by woman, members of these households are more likely
to be poor.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 21
Table 7: Poverty profile: Poverty Rates by Group
% of
population
% who are
poor
% of the
poor
By household size
1-3 members 24.2 2.2 (0.7) 5.7
4+ members 75.8 11.7 (1.2) 94.3
By age of household head
under 50 years 42.1 8.3 (1.3) 36.9
50-64 years 41.5 9.0 (1.5) 39.6
65+ years 16.4 13.5 (2.9) 23.5
By gender of household head
Male 90.3 9.2 (1.0) 88.3
Female 9.7 11.4 (3.2) 11.7
By education of household head
Primary 16.6 20.6 (3.4) 36.2
Some/completed secondary 83.4 7.2 (0.9) 63.8
By employment status of household head*
Not employed and not retired 9.8 18.6 (4.4) 19.3
Employed 62.4 6.5 (1.0) 43.5
Retired and not employed 27.8 12.1 (2.1) 37.2
By agricultural land holdings of household
No agricultural land 66.3 9.0 (1.1) 64.2
Has agricultural land 33.7 9.9 (1.8) 35.8
By age
under 16 years 17.6 12.4 (1.1) 23.1
16-24 years 19.3 9.2 (0.9) 18.9
25-49 years 35.8 9.7 (0.7) 36.7
50-64 years 18.7 6.6 (0.8) 13.1
65+ years 8.6 9.1 (1.4) 8.3
Place of birth of household head**
Montenegro 91.8 11.0 (1.4) 97.2
Serbia*** 3.5 3.7 (3.6) 1.3
Other 4.7 3.4 (3.3) 1.5
Current location within Montenegro if household
head was born in MN
Same municipality as birth 83.0 11.2 (1.5) 84.6
Moved municipality 17.0 9.2 (3.0) 15.4
Source: ISSP Household Survey 5 and 6. Note: Standard errors in parentheses; 95% confidence interval is
approximately ±2 standard errors.
*Employed is defined as having worked for income in the last week or having a regular job but not worked last
week (vacation, sick, etc..); “retired” are those who are not employed and self-identify and report being retired
as their main activity; “not employed” are all others.
**Migration data is from Survey 6; it was not asked in Survey 5.
*** Kosovo is included in other.
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
22
V. FACTORS INFLUENCING POVERTY IN MONTENEGRO
In this section we investigate factors that influence living standard and poverty by simultaneously
controlling for different characteristics; identification of these factors might be very important for
designing of social policy for poverty reduction. It extends the results in the previous section since
it tries to address the correlations across characteristics. For example, the extent to which the higher
poverty in the north can be “explained” by the characteristics of the household head remains to be
evaluated. This short analysis indicates factors related to poverty but should not be interpreted as
showing causality. Factors that we investigate include: characteristics of the households (age,
education and gender of household head, household size, and demographic composition), economic
activity of adults, agricultural land holdings, and location. These factors are used as explanatory
variables in simple regression model, with per capita expenditures (pce) as the dependent variable.
Table 8 presents estimated coefficients of regressions and the corresponding robust standard errors.
Education is significantly associated with higher pce. Some or completed secondary education of
the household head is associated with almost 10 percent higher pce compared to those in the
reference group which is less then secondary. University education of the household head is
associated with 29 percent higher pce compared to those with basic/no education. We conclude that
households whose heads have higher education are less likely to be poor, although it is also the case
that education is not a guarantee that the household will not be poor. This reflects some of the
challenges facing the education system in Montenegro, including outdated curriculum that can
exacerbate mismatch with labor demand.
While this is true for the overall sample, there are interesting differences across the three main
regions. The positive association of some/completed secondary education is only statistically
significant in the center region. While the coefficient is significant at 10 percent in the South and
larger (13% return), some/completed secondary education of the household head compared to those
in the reference group (less then secondary) is not associated with higher pce for households in the
north. Having in mind regional component, university education of the household head is
associated with statistically higher pce in all regions, but the return is largest in the center region (37
percent compared to 27 percent in the north and south).
Economic activity of adults (which includes formal and informal income generating activities) is
highly associated with higher pce compared to those households with no economically active adults.
Households with at least one adult who is working have pce 17 percent higher than households with
no working adults. Again, we see interesting regional variation: the impact is 13 percent in the
north, 23 percent in the center and highest in the south at 27 percent.
On the other hand, households with at least one non-employed, non-retired adult have 12 percent
lower pce than those with no such adults. In the north, the association is strongest: households
having one or more non-employed, non-retired adult in household have 16 percent lower pce. The
relationship is smallest in the south, where such adults are not statistically associated with lower
pce.
Considering demographic composition of the households, it seems that this factor does not impact
per capita consumption levels significantly. The one only exemption is in south, where households
with an additional child up to six years old have higher pce of almost 50 percent.
Household size impacts the level of consumption significantly. A ten-percent increase in household
size is associated with five percent decrease in pce. The conditional correlation between household
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 23
size and pce is smallest among the households in the north. For these households, the elasticity of
pce to household size is .48, whereas the elasticity is .75 in the south.
Households with access to and agricultural land have significantly larger pce, and this effect is
predominantly in the north and center regions. Households in the north have 17 percent higher pce
if they have any agricultural land holdings; in the center, agricultural land holdings are associated
with 11 percent higher pce. Agricultural land is not associated with higher pce for households in
the south.
By location, controlling for household characteristics, pce among households in the south of
Montenegro and the center are not statistically different. However, with controls for household
characteristics, households located in the north of Montenegro still have 10 percent lower pce
compared to other households. Thus, controlling for this set of household characteristics slightly
reduces the gap between the north and center (which is about 15 percent of the center pce on
average), yet a significant difference in pce between the north and the other regions remains
unexplained by the set of characteristics. Another way to explore the relationship between location
and poverty is to evaluate the difference in poverty rates among the population in the North
compared to other areas, with and without controls for other household characteristics. The
summary of results is given in Figure 8. This figure shows that people living in the North face a
significantly higher observed poverty rate, even after we control for other differences.
Fi
g
ure 8: Povert
y
rate of
p
o
p
ulation in North relative to
p
o
p
ulation in
South and Center: observed and simulated
0
1
2
3
4
5
6
7
8
9
10
No controls Controlling for
Characteristics of
Household head
Controlling for
Characteristics of
Household head and
Household demographics
Controlling for
Characteristics of
Household head,
Household demographics
and Employment
Higher Povetry
(% points)
Source: ISSP Household Survey 5 and 6.
Living Standards and Poverty in Montenegro 2002
The World Bank, Washington DC
24
Table 8: Regression of Log Consumption per capita on Household Characteristics
All North Center South
coefficient robust s.e. coefficient robust s.e. coefficient robust s.e. coefficient robust s.e.
Characteristics of the household head
Age of household head: <50 (reference group)
Age of household head: 50-64 -0.021 (0.035) 0.014 (0.068) -0.063 (0.051) 0.031 (0.076)
Age of household head: 65+ 0.000 (0.051) 0.001 (0.109) -0.061 (0.072) 0.090 (0.105)
Household head is female -0.051 (0.037) -0.095 (0.066) 0.015 (0.057) -0.145 (0.077)
Education of head: <secondary (reference group)
Education of head: some/completed secondary 0.105** (0.033) 0.031 (0.053) 0.171** (0.052) 0.133 (0.070)
Education of head: some/complete post-secondary 0.298** (0.038) 0.265** (0.072) 0.372** (0.059) 0.269** (0.076)
Economic activity of adults
Any working adult 0.165** (0.035) 0.127* (0.054) 0.225** (0.058) 0.268** (0.077)
Any non-working, non-retired adult -0.117** (0.030) -0.161** (0.056) -0.106* (0.047) -0.081 (0.056)
Demographic composition
# of children 0-6/household size -0.191 (0.127) -0.317 (0.213) -0.333 (0.221) 0.494* (0.250)
# of children 7-14/household size -0.130 (0.110) -0.062 (0.199) -0.089 (0.173) -0.053 (0.233)
# of children 15-18/household size -0.006 (0.128) 0.220 (0.268) -0.135 (0.178) 0.129 (0.273)
# of adults 19-25/household size 0.070 (0.083) -0.032 (0.131) 0.134 (0.139) 0.193 (0.214)
# of adults 26-45/household size 0.057 (0.069) 0.088 (0.117) 0.001 (0.106) 0.076 (0.149)
# of adults 46-64/household size (reference group)
# of adults 65+/household size -0.142 (0.089) -0.181 (0.165) -0.106 (0.128) -0.036 (0.177)
ln (household size) -0.537** (0.038) -0.483** (0.063) -0.532** (0.060) -0.745** (0.094)
Household owns agricultural land 0.127** (0.026) 0.173** (0.048) 0.110** (0.037) 0.028 (0.067)
Location
Center (reference group)
North -0.097** (0.028)
South -0.004 (0.030)
constant 5.881** (0.065) 5.796** (0.098) 5.797** (0.101) 5.922** (0.140)
R20.353 0.289 0.376 0.404
Number of observations 1294 427 562 305
Source: ISSP Household Survey 5 and 6. Notes: * indicates significance at 5%; ** at 1%.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
25
VI. SOURCES OF SUPPORT FOR HOUSEHOLDS
Income Sources
Table 9 presents the sources of income for households in Montenegro, breaking down income into 8
categories; the mean amount from each source is presented in Table 10 and the shares are presented
in Figure 8.11
Wage income is the most prevalent source of income for all households, including those above and
below median per capita expenditure. The share of wage income observed here is slightly larger
than the Federal Statistical Office estimates for FRY (FSO, 2000) which estimate a share of about
45 percent. Compared to other transition countries, FRY was below the average for wage share in
household income (see World Bank, 2000), likely to be partly a reflection of the generous pension
plan and private transfers. The UNDP study (2001) reports a larger share of household income
from labor earnings (about 75%), partly due to the exclusion of private transfers as an income
source and perhaps also reflecting a real phenomenon due to subsequent decline in real wages given
price changes.
Non-labor sources of income may be important for supporting living standards. While about 76
percent of all households report some wage earnings, non-labor income sources remain an
important source of support, reflecting the large share of the working-age whom do not have
employment on the one hand, and the generous pension scheme and private transfers on the other
hand. Pensions, unemployment benefits, Family Material Support, Child Allowance, One-off
Support and Other Person Care are social protection programs designed to improve well-being of
the population. Pensions are the second most common income source, received by almost half of
all households. Private transfers (from relatives either in Montenegro, in Serbia or abroad) are
reported by about 20 percent of households.
There are interesting patterns of income sources by expenditure groups. Poorer households are
more likely to have income from a pension program than wealthy households. Social transfers are
more prevalent among the poorest 20 percent of the population. Almost one in ten of the poorest
people reside in households with some social transfer income, compared to 2 percent among the
wealthiest. Wealthy households are two and a half-times more likely to report having some income
from property or other asset holdings than the poorest quintile. Also, they are also three-times more
likely to report self-employment income when compared to the poorest quintile.
Private transfers are received by one out of every five households. The prevalence Wealthy
households are much more likely to be receiving some private transfers. Very few households
received any unemployment benefit income, consistent with other data sources. According to the
data of the Employment Office, only 2.9 percent of registered unemployed, a larger group than
those defined as unemployed by an ILO definition, were receiving unemployment benefits at the
end of 2002.
11 Wages, self-employment earnings, pensions (old-age, disability, family and foreign), scholarships, unemployment
benefits, FMS, Child Allowance, NGO cash and in-kind transfers, and private transfers are reported for the last month.
Income from One-off Momentary Support, Other Person Care and other social programs are reported for the last six
months. Property income is reported for the last 12 months.
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
26
Table 9: Income Sources for Households
(percent of households with any income from source)
Type of income
All
households
Poorest
20-40%
40-60%
60-80%
Richest
Wages income 75.7 71.7 82.7 78.2 74.1 73.0
Self-employment income 6.3 3.3 5.6 4.3 4.9 11.1
Pensions 45.5 47.3 44.4 48.3 49.8 39.4
Scholarships 2.2 1.1 0.5 2.6 2.7 3.2
Unemployment benefits 0.4 1.1 0.0 0.4 0.8 0.0
Social transfers 3.9 9.2 4.6 1.7 3.4 2.2
Private transfers (relatives) 19.3 21.2 14.8 17.5 20.1 21.6
Other income (property &
insurance)
11.2 5.0 12.8 12.0 12.5 12.4
Source: ISSP Household Survey 5 and 6. * The sample excludes 85 households missing information on
wage or self-employment earnings and 22 households who report no income from any source.
Table 10: Composition of Household Income
(mean in Euros)
Type of income
All
households
Poorest
20-40%
40-60%
60-80%
Richest
Wages income 297.3 194.9 279.0 313.9 300.0 354.5
Self-employment income 28.6 8.4 16.0 15.2 15.2 69.2
Pensions 69.1 61.9 63.8 76.3 69.4 71.0
Scholarships 1.0 0.7 0.0 0.9 1.0 1.7
Unemployment benefits 0.4 1.3 0.0 0.2 0.5 0.0
Social transfers 2.4 6.2 2.3 1.2 2.5 1.0
Private transfers (relatives) 58.7 48.3 40.2 35.9 62.0 90.6
Other income (property & insurance) 12.0 4.3 19.0 9.6 10.5 15.4
Total Income 469.5 326.0 420.3 453.4 461.1 603.4
Source: ISSP Household Survey 5 and 6.
Fi
g
ure 9: Composition of Household Income (Share of
total income by expenditure groups)
0%
20%
40%
60%
80%
100%
All households
Poorest
20-40%
40-60%
60-80%
Richest
Percent
Other income
Private transfers
Social transfers
Unemployment benefits
Scholarships
Pensions
Self-employmenti ncome
Wage income
Source: ISSP Household Surve
y
5 and 6.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 27
Pensions
Pensions are the main form of social insurance in Montenegro. Despite being one of the most
generous pension schemes in the region, conventional wisdom in Montenegro is that pensions are
too low to allow for minimum living standards. However, increases in the replacement rates or
benefit levels seem unlikely to be sustainable from a fiscal standpoint. The finances of the social
funds, including pensions, the health fund, and employment fund, reflect an unpredictable and weak
link between their principal sources of funding and the legislated benefits. Accrued social
contributions do not fully cover expenditure commitments. The sustainability of the social
insurance system is further undermined by tax evasion, exemptions from taxes, and unstable
contributions from the Republic Budget. As a consequence, the main insurance funds are either
directly or indirectly dependent on excises, import duties, and foreign grant assistance12.
If the current pension system is not reformed, the gap between contributions and pension
expenditures will balloon from 2.5 percent of GDP to more than 10 percent of GDP. The ratio of
contributors to beneficiaries is currently 1.413. Clearly pension reform is necessary to avoid
disaster. The different reform options, such as increasing contributions, reducing benefits levels,
reducing the rate of pension inflation indexation, and raising the retirement age, have different
implications for both households currently receiving pension and those not receiving this income.
As mentioned above, a large fraction of households receive some pension income, whereas only
about 11 percent of households have only pensions as an income source. The impact of specific
reforms may vary in the short and long-term, and making predictions even for short-run impacts is
complicated. Short-run impacts may have opposite effects for different groups. For example,
reducing replacement rates will reduce benefit levels for those receiving pension income, but also
reduces the pension-financing burden on workers and employers. Pension reform may have
opposite effects in the short-run compared to the long-run, if reform spurs economic growth.
On a population basis, about two fifths of people reside in households with pension income (Table
11). When we breakdown pension income by type, we find that the dominant source of this income
is old-age pension, about one-quarter of people are in households with this income. Disability
income is the second most prevalent source, with 12 percent of the population. Less than five
percent have access to family pension and almost no one receives foreign income.
When we look at expenditures groups, we see that more then 60 percent of the poorest live in
households with pension income: two-fifths of the population are in households with old-age
pension, while more than one-fifth of the poorest are receiving some disability pension.
Despite their name, old-age pensions are not received by all of the elderly: about 35 percent of
people over 65 report no old-age pension income for the household. This coverage rate is low by
European standards. However, the elderly are more likely to report disability income (20 percent of
all elderly compared to about 12 percent for those 25-49 years). Overall, the elderly are most likely
to have some household pension income. Eighty-five percent of people over 65 have some
household pension income, with the dominant source being old-age pensions. If we broaden our
measure to include income from social transfers or pension income, the percent of people over 65
covered does not change. Among the 15 percent of elderly with no pension income, three-quarters
live in households with some wage income; one-third have some property income or private
12 Source: Ministry of Finance
13 Source: Pension Fund
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
28
transfers.
Table 12 compares household pension income and its total expenditures. Only among households
receiving foreign pension does this source cover a large share of monthly expenditures (more then
50%). On average, among households receiving other pension income (old age pension, disability
pension, family pension) the income covers on average 20 percent of monthly expenditures.
We can examine the distributional impact of pensions by evaluating the benefit incidence of this
program (See the section below on Social protection and poverty for more rigorous approach to
assessing the impact of pensions on poverty). This combines information on both the prevalence of
the program for different expenditure groups and the level of benefits received. Figure 10 shows
the concentration curve for pensions. This curve shows the fraction of total pension expenditure
that goes to the population that is ranked by consumption level excluding the pension income
(“counterfactual” consumption). Using this curve we can classify a program’s spending as
progressive or regressive. By comparing the distribution of pensions with the consumption
distribution, we see that expenditure pattern of this program is progressive. Those below the
median (poorer) get a share of benefits that is higher than their share of consumption. More
interesting is the fact that the population at the low end of the distribution get a larger share of
pension expenditure than their population share.
Table 11: Percent of Individuals in Households Receiving Pension Income, by Quintiles (N=4,995)
Any
Pension
Old Age
Pension
Disability
Pension
Foreign
Pension
Family
Pension
All 41.4 25.9 12.3 0.9 4.4
By Quintile*:
poorest 63.4 41.1 23.0 1.1 1.9
20-40% 45.5 27.4 11.7 1.4 6.6
40-60% 39.9 22.2 14.6 0.1 4.4
60-80% 33.0 19.7 7.6 1.2 6.7
richest 25.4 19.0 4.3 0.7 2.5
By age:
<16 years 27.4 16.0 7.2 1.0 4.6
16-24 years 33.1 17.2 11.2 0.3 4.8
25-49 years 36.0 21.8 11.0 0.7 4.2
50-64 years 52.8 34.3 16.3 1.1 3.6
>65 years 86.7 64.6 21.3 2.3 5.6
Source: ISSP Household Survey 5 and 6.
* Consumption quintiles are estimated in the absence of pension income.
Table 12: Household Pension Income as a Percent of Total Expenditures,
conditional on receiving support
Any
Pension
Old Age
Pension
Disability
Pension
Foreign
Pension
Family
Pension
of total household
expenditure
23.8 23.7 19.3 54.0 17.0
number of
households
565 354 163 15 64
Source: ISSP Household Survey 5 and 6.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 29
Social Transfers
Montenegro has instituted sweeping reforms of the social protection system in an effort to improve
targeting and ensure fiscal sustainability of social assistance programs. Currently, the five main
social protection programs are almost 2 percent of GDP (See programs listed in Figure 11). In
addition to holding the total budget constant in nominal terms since 2000, the reforms have included
major shifts in budget allocation across the major social protection programs (Figure 11).
Legislation enacted in 2001 broadened the scope of entitlement for family material support (FMS).
Although not all entitled families received FMS, the increase in the number of eligible families is
mirrored in the increased share of FMS in the total social protection, from 18 to 37 percent of the
total budget. While FMS has expanded, amendments to Child Allowance (CA) regulations made in
2001 restricted the definition of eligibility for CA to include households that already receive FMS, a
new criterion considered to be quite strict. While at the same time, coverage was extended to
households with developmentally disabled children regardless of income.
In comparison, the structure of social assistance in Montenegro is quite different for Serbia, where
social protection programs were 1 percent of GDP in 2002. Specifically, family assistance (MOP)
in Serbia has much smaller coverage while the CA program in Serbia reaches a large share of the
population. Bogicevic14 (2002) estimates that 37% of child population up to 19 years old receive
CA (8.9% of total Serbia population); Tesliuc15 (2003) reports 15% of the total population are in
households receiving CA. CA in Serbia is considered to be quite expensive and the amounts
received seem too small to have a significant impact. In Montenegro, on the other hand, the
program has been sharply re-targeted, but the amounts remain small, as shown below.
14 Bogicevic, Biljana. 2002. “System of Government Support to the Poor in Serbia.”
15 Tesliuc, Cornelia. 2003. “Social Protection and Poverty in Serbia.”
Figure 10: Incidence of Pensions
0%
20%
40%
60%
80%
100%
0 20406080100
Cumulative Share of Population, ranked by Expenditure without Pension (%)
Pensions Exp. without pensions
Source: ISSP Household Survey 5 and 6
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
30
Figure 11: Distribution of Social Protection Budget
0%
20%
40%
60%
80%
100%
2000 2001 2002 2003
Percent
Other person care
Maternity leave
Material support for
veterans
CA
FMS
Source: Ministry of Labor and Social Care.
While labor income and pensions constitute the major income categories for households, social and
private transfers are the third largest income source. In terms of the share of the population that
receives some social assistance income (excluding pension income), one could conclude that the
current structure of public transfers do not play a significant role in terms of households’ welfare in
Montenegro. Only four percent of individuals reside in households receiving some social assistance
(see Table 13).16 Among the population of children 0-16 years, about five percent are in households
receiving some social assistance. In comparison, the Ministry of Labor and Social Welfare reports
that CA was received by seven percent of children in Montenegro in August 2002.
Considering social assistance income (FMS, CA, other social assistance) as a percent of total
household expenditure, this income covers about 15 percent of total household expenditures (Table
14). Table 15 shows some of the reasons for not having applied for FMS given by the population in
the first quintile (half of this population is considered poor, while the other half live just above the
poverty line). Among this group, 10 percent believe that they do not need FMS (and presumably
the other main social assistance program, CA, in case when they have children). It is conceptually
difficult to define these people as excluded since they themselves do not believe that they need
assistance. The lack of information about the existence of FMS is one of the most important
reasons for exclusion: about 30 percent of the population in the poorest quintile reports not being
informed about the existence of FMS. An implication of this finding is that better and more
widespread information may assist in targeting this program appropriately. Some of the other
categories are more difficult to interpret. For example, those who think that applying would
achieve nothing may believe that the amounts are not sufficiently large or that they would not, in
fact, be accepted for receipt. Finally, relatively few households report that the application
procedure is an obstacle towards applying.
Table 16 gives more information about the receipt of income from social program in terms of
number of households receiving social assistance, number of individuals in these households and
the mean amount received.17 The average Euros of FMS and CA (56 and 25, respectively) reported
16 In addition to these types of programs, some type of energy-related social assistance, which exists in Serbia, could
also be considered. The Serbia programs target joint utility bills (district heating, water supply, and garbage removal) as
well as one-time benefits to households with low electricity consumption. As for a targeted program to assist the poor
in heating their dwelling, one tied to electricity consumption as a heating source would not apply to nearly 44 percent of
the population in dwellings that are not heated by electricity but, rather, wood (about almost all of those not heating
with electricity) or coal in a small share of cases.
17 The level of FMS is assigned based on the average wage in Montenegro in the previous month and household size.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 31
are slightly lower, but within range, of the average household amount reported by the Ministry of
Labor and Social Welfare in August 2002 (63 and 31, respectively).
Table 13: Percent of Individuals in Households Receiving Social Assistance,
Unemployment Benefits or Scholarship
Any social assistance
income (CA, FMS,
Other Public
Assistance)
Unemployment
benefits
Scholarship
income
3.8 0.5 2.4
Table 14: Social Transfers (CA, FMS, Other Social Assistance)
as a Percent of Total Expenditures, conditional on receiving
Any social assistance
income
% of total household
expenditure
14.0
number of households 49
Table 16: Why Has Household not applied for Family Material Support
Poorest
20%
20-40%
40-60%
60-80%
Richest
80%
All
Don’t need it 12.0 16.0 23.3 33.5 50.6 27.7
Not informed on
how to be included 29.4
32.8
31.5
29.3 18.5
28.3
It would achieve
nothing 47.1
41.1
36.8
30.0 24.8
35.4
Bad attitude of
social workers 5.2
5.8
3.7
2.5 1.0
3.6
Difficult to get
Documents 2.6
2.3
0.7
1.3 1.1
1.5
Other 3.7 2.1 4.0 3.4 4.1 3.5
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
32
Table 16. Receipt of income from social programs
Number of
households
Number of
individuals
Mean total
amount
(euros)
FMS (last month) 30 130 57.7
CA (last month) 10 54 26.7
One-off momentary support (last 6 months) 8 24 132.5
Other Person Care (last 6 months) 11 29 70.7
Other social programs (last 6 months) 1 1 230
NGO cash (last month) 2 5 100.0
Government in-kind (last month) 5 8 86.8
NGO in-kind (last month) 0 0 -
Social protection and poverty
To what extent do social protection programs result in reductions in poverty? The extent to which
poverty is reduced will depend on both the amount of transfers and the degree to which these
transfers are targeted to the poor. Social projection can include social assistance programs (such as
FMS and CA) and social insurance programs (including pensions and unemployment benefits). The
relationship between poverty and social protection is investigated by evaluating the change in
poverty measures if there were no social protection benefits available assuming a marginal
propensity to consume of 50 percent.
Figure 12 shows the impact of social protection transfers on poverty. The poverty rate would
increase by 34 percent overall if there were no social protection programs. The bulk of this increase
comes from the impact of social insurance programs, for which both coverage and amounts
received are larger than social assistance programs. It is important to look beyond the poverty rate,
given that these programs impact poverty gap and poverty severity, even for the poor who remain
poor with these transfers. Again, we find that social protection has a large impact on depth and
severity of poverty, driven in large part to social insurance transfers. The poverty gap more than
doubles when social insurance is removed. Poverty severity increased by more than 150 percent.
The large changes reflect both the magnitude of social insurance transfers (mainly pensions) as well
as the low level of poverty measures to begin.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 33
Fi
g
ure 12: Chan
g
e in povert
y
without social protection
programs for national population
0%
40%
80%
120%
160%
200%
Poverty Rate Poverty Gap Poverty
Severity
Percent change in poverty measure
Social Assistance
Social Insurance
Social Protection
Source: ISSP Household Survey 5 & 6.
Private Transfers
In last more then ten years, since the dissolution of the Federal Republic of Yugoslavia, there has
been considerable movement of the population, including rural to urban migration within
Montenegro. As well, there has been out-migration of young, well-trained people who leave
Montenegro in search of better education and better-paid jobs abroad. Generally, international
migration is a characteristics coping mechanism for households in the Balkans. Consistent with
this, the data show that private remittances are a significant source of income for Montenegrin
households. As shown in Table 17, about 10 percent of the population are in households receive
private transfers from other households. Private transfers from family abroad are equally frequent.
Since there are few households receiving both sources of income, overall, 20 percent of households
receive some private transfers. When compared with total expenditures, these incomes cover 23
percent for transfers from relatives in Serbia or Montenegro, and twice as much, 48 percent, from
relatives living abroad (see Table 18).
Table 17: Percent of Individuals in Households Receiving Private Transfers,
From any relatives From relatives in
Serbia or
Montenegro
From relatives
living abroad
All 18.0 9.2 10.0
By Quintile*:
poorest 42.8 18.3 28.2
20-40% 13.3 7.2 6.5
40-60% 11.7 6.9 6.1
60-80% 11.7 6.8 5.4
richest 10.5 6.9 3.9
* Consumption quintiles are estimated in the absence of private transfers.
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
34
Table 18: Private Transfers as a Percent of Total Expenditures,
conditional on receiving
From relatives in Serbia
or Montenegro
From relatives living
abroad
% of total household
expenditure
22.9 48.1
number of households 142 118
VII. CONCLUSIONS
The rapid economic transition underway in Montenegro has undoubtedly brought about large
changes in the socioeconomic situation. The dramatic decline in output in the last ten years lead to
the widespread perception that poverty and inequality are high. However, without appropriate data
sources, it is difficult to analyze the true situation. Moreover, as the government continues to
accelerate economic and institutional reforms in an effort to have sustainable fiscal policies and
economic growth, there remains the question of the impact of these changes on poverty and the
poor if appropriate social policies are not also adopted. While the many reforms being undertaken
are critical, the development priorities in Montenegro should not neglect important social policy
issues to ensure that all can benefit from strong economic growth in the future. This includes
evaluation of the existing scheme on social policy programs, careful impact assessment to inform
the design of policy reforms, and assessment of current budget allocations that have implications for
regressive programs, such as allocations to in the education sector across levels.
The goal of this study is to use newly available data to provide a baseline of the level and profile of
living standards in Montenegro. By presenting an array of important results, this document serves
as a platform for important discussions in Montenegro on poverty reduction strategies and efforts to
monitor efforts. The study finds that nearly one in ten Montenegrins are poor, but poverty is not
deep. Although the poverty is low and poverty is shallow, poverty estimates are sensitive to the
poverty threshold. More than one third of the population is classified as economically vulnerable,
living below 150% of the poverty threshold. Raising the poverty line by 20 percent doubles the
poverty rate. Thus, living just above the poverty line, a significant share of the population are
vulnerable in the sense that they are vulnerable to any economy-wide fluctuation, downturn, or
personals income shock. A positive income shock (perhaps those associated with growth and good
policies, for example) would be associated with more-than-proportional declines in poverty;
negative shocks (such as recession) would lead to more-than-proportional increases in poverty.
There is much variation in poverty across different groups in the population. Some of these poverty
is explained by factors such as education in the household and access to land. Employment
opportunities matter. Households with inactive or retire adults are significantly more likely to be
poor, as are those with less education. Still, households in the North remain poorer than their
counterparts in the Center and South, even after controlling for other background characteristics.
This suggests structural differences in the economies across regions, which is also reflected in the
lower impact of education on consumption among households in the north and south regions
relative to the Center.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 35
The analysis also highlights the lack of developed social safety nets. It appears that neither social
welfare programs nor unemployment benefits offer sufficient support to poor households, due to
both coverage and levels of amounts received. On the other hand, the largest social insurance
programs, pensions, strongly protect against poverty. It will therefore be important to evaluate the
impact of alternative pension reforms on the poorest households.
As Montenegro continues to unfold ambitious economic reforms, it will be important to monitor
core indicators. Additional analysis of existing household data can help forecast the potential
impact of proposed reforms on the poor and assess the efficiency of existing programs. Such proper
monitoring and evaluation of living standards will require timely, high-quality, accessible data.
Identifying ways to assess living standards among the main groups not covered by existing data
(Roma, refugees, and IDPs) should be a priority also. Montenegro faces the challenge of
developing a statistical system that can collect, process, analyze, and disseminate information on
living standards of the entire population. A next step in this effort would be to coordinate the
analysis efforts at ISSP with the on-going official household budget surveys at MONSTAT to more
fully develop data systems and analysis for poverty monitoring. Meanwhile, since the regular data
collection is a must, having in mind that Government of Montenegro adopted Law on private sector
participation in public services delivering, it is suggested to continue cooperation with the NGO
sector while capacities of MONSTAT are developed.
Given these considerations, the work to follow from this assessment, therefore, is multifaceted. It
will include, among other activities:
• Collaboration with MONSTAT in the development of staff skills through upcoming
CEED/ISSP surveys
• A special household survey on Roma and IDPs conducted by ISSP with support and
technical advice from the World Bank and United Nations Development Programme,
Liaison Office in Podgorica, Montenegro
• Expanding coverage of the ISSP household survey for analysis of issues related to
environmental analyses18
• Developing the ISSP household survey questionnaire for analysis of the implications of
enterprise restructuring on labor markets and poverty.
18 See World Bank (2003a) for discussion of the need for both data collection and analysis in the area of
environmentally sustainable development in Serbia and Montenegro.
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
36
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Bogicevic, Biljana. 2002. “System of Government Support to the Poor in Serbia.”
Deaton, Angus. 1997. The Analysis of Household Surveys: A Microeconometric Approach to
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Federal Statistical Office. 2002. “Statistical Yearbook.” Belgrade.
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Figini, Paolo. 1998. “Inequality Measures, Equivalence Scales and Adjustment for Household Size
and Composition.” Working Paper No. 185, Maxwell School of Citizenship and Public Affairs,
Syracuse University.
Foster, James., Joel Greer and Eric Thorbecke. 1984. “A Class of Decomposable Poverty
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Institute for Strategic Studies and Prognoses (ISSP). 2002b. “Household Survey Report #6.”
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Institute for Strategic Studies and Prognoses (ISSP). 2002a. “Household Survey Report #5.”
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Institute for Strategic Studies and Prognoses (ISSP). 2003. “Montenegro Economic Trends
(MONET).” Podgorica, Montenegro.
Ivanovic, Petar. 2002. “Pension Reform and Labor Market”
Krstic, Gorana. 2003. “The Poverty Profile in Serbia 2002.”
Luttmer, Erzo. 2002. “Poverty and Inequality in Croatia.”
Milanovic, Branko. 2003. "Inequality and Social Transfers" mimeo. Belgrade, Serbia.
OCHA sub-office in Podgorica and Economics Institute of Belgrade. 2000. “Income and
Expenditures in Montenegro.”
Tesliuc, Cornelia. 2003. “Social Protection and Poverty in Serbia”
UNDP. 2001. “Employment, Labour Market and Standard of Living in Montenegro.”
The World Bank. 2000. Making Transition Work for Everyone: Poverty and Inequality in Europe
and Central Asia. The World Bank, Washington DC.
The World Bank. 2002a. “Albania Poverty Assessment.” The World Bank, Washington DC.
The World Bank. 2002b. “Bosnia and Herzegovina: Poverty Assessment.” The World Bank,
Washington DC.
The World Bank. 2002c. “Bulgaria - Poverty Assessment.” The World Bank, Washington DC.
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Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
37
ANNEX
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
38
ANNEX 1: Overview of Montenegro Household Survey Data
Background of the Project
Spurred by the need to quantify the magnitude of poverty, identify links between well-being and the
labor market, and assess the coverage of social assistance, the Household Survey (HHS) attempts to
provide appropriate data for assessing socio-economic conditions in Montenegro.
The official Household Budget Survey data inherited from the former Yugoslavia in undergoing
reforms in terms of questionnaire, content, sampling and dissemination/availability to analyst and
researchers. To date, however, these reforms have not been realized. Consequently, the lack of
household data makes it difficult to analyze the impact of reforms on the poor and to develop
appropriate programs to improve living standards. Furthermore, with the current effort to develop
the Poverty Reduction Strategy Paper (PRSP), there has been more demand for a solid
understanding of the nature and causes of poverty in order to select and prioritize macroeconomic,
structural, and social policies.
To this end, two research institutions in Montenegro have undertaken several household surveys in
an effort to provide data that is useful for policy makers and analysts in these aforementioned areas.
The HHSs have been developed and fielded by the Institute for Strategic Studies and Prognoses
(ISSP). This work has been supported by the European Commission Food Security Programme
(with significant contribution coming from Mr. Vasilis Panoutsopoulos), USAID Montenegro, and
Chesapeake Associates. In addition, for HHS Rounds 4, 5 & 6, ISSP&CEED have received
technical assistance and feedback from World Bank staff. In an effort to enhance the usefulness of
the HHS to policymakers and researchers studying poverty and living standards in Montenegro,
support from the World Bank for Round 6 was used for two main purposes: expand the sample size,
and undertake collaborative poverty analysis. This support greatly improved the data source in
terms of level of representation and quality, and, therefore, its usefulness as a source for analysis
and fact-based policy-making. The collaboration on analysis should result in a detailed profile of
poverty in Montenegro currently unavailable from any other data source. The sample size of 500
households in Rounds 4 and 5 is just large enough to generate national statistics, but is too small to
generate statistics for regional estimates (North, Center, South) and too small for most subgroups of
particular interest (such as vulnerable populations, including the poor, elderly, children, and
unemployed). Using the existing sampling frame (the listing of individuals from the Mass Voucher
Privatization program, MVP19) the sample has been expanded appropriately, to include a total of
800 households from the MVP listing.
Survey Rounds and Questionnaire Content
To date, six rounds of the ISSP HHS have been completed; Round 6 was fielded in November
2002. The coverage of the questionnaire and sample sizes are described in Table A1.1.
19 The Household Survey Project gratefully acknowledges Mr. Zeljko Brkovic from ZOP (Clearing house) in providing
the MVP and assisting the project in its use.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 39
Table A1.1: ISSP Montenegro Household Survey
Round Date Number of
households
Municipalities Topics Consumption/
Expenditure Module
1 May 2001 2000 12 no
2 July 2001 2000 12 no
3 Sept 2001 2000 12 no
4 April 2002 500 21 expanded yes*
5 Aug 2002 500 21 expanded yes
6 Nov 2002 800 21 expanded yes
* Food consumption was collected for quantity but Euro values need to be imputed using price data from
the Statistics Department.
The emphasis in the first three rounds of the ISSP HHS was the basic demographic characteristics
of the household, individual income earnings, and non-earned sources of income for the household.
In Rounds 1-3, thus, income is the main indicator of well-being. Pursuant to field experiences and
discussions with World Bank staff, representatives from other donors, and government agencies, the
questionnaire has been subsequently revised since Round 3. Rounds 4, 5 and 6 have introduced
detailed consumption and expenditure modules as well as greater range of topics. The main topical
areas of the integrated surveys in Rounds 4, 5, and 6 are:
• Household roster including migration information
• Housing conditions, including information on utilities
• Durable assets owned by the household
• Food consumption values for about 87 food categories (see Annex 3)
• Non-food expenditures
• Receipt of assistance from social programs: pensions (old age and disability),
scholarships for school, unemployment benefits, Family Material Support (FMS),
Child Allowance, one-off support, and other person care
• Other non-labor income sources
• Employment characteristics intended to measure labor force participation in the
formal and informal sector
• Health status
• Subjective well-being (perceived quality of life)
While the questionnaire continued to be revised after Round 4, it should be noted that a critical
change in the questionnaire occurred between Rounds 3 and 4, when the consumption and
expenditure modules were added. The expended set of topics covered in Rounds 4, 5, and 6 are
largely similar with only slight modifications. In order to accommodate the longer questionnaire
starting in Round 4, the sample size was reduced. Subsequent support for the survey has allowed
the sample size to be increased to 800 households in Round 6 (with the support of the World Bank,
as mentioned above).
The questionnaires of Rounds 4, 5 and 6 have the appropriate set of questions for the purposes of
measuring poverty using consumption and expenditures. All rounds collected food consumption for
about 87 food items. However, the data are not comparable in the way in which food consumption
is measured and in the recall period for non-food items. Specifically, in Round 4, households report
only quantities of food consumed across three sources: purchases, self-produced and received as gift
from others. Thus, the value of food consumed must be imputed from reported quantities and the
regional price averages (as collected by the Statistics office).
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
40
The salient features of Rounds 4, 5 and 6 are that a poverty indicator can be developed using
consumption and expenditures, rather than incomes (see Annex 2).
Sample and Data Collection
The data is collected in face-to-face interviewers by a core set of interviewers, about 28, who are in
most cases from the municipality in which they work. The training of interviewers took about 25
hours for each survey round. Given that ISSP retain a large share of interviewers, the majority of
interviewers now have considerable experience in fielding the questionnaire. The field work lasts
about 3 weeks. The data are entered and processed at ISSP offices in Podgorica. The sample sizes
of Rounds 1–6 are summarized in Table A1.2. The samples for Round 5 (500 households) and 6
(800 households) are the basis for the poverty statistics in this assessment.
Data are collected from each of the three main regions of Montenegro, which constitute the north
(mountainous, less populated and least developed), the central region (most populated and
industrialized), and the south (coastal, most developed with tourism as main economic sector).
The last census in Montenegro was done in 1991. A new census was planned for April 2002 but
was postponed and is now planned for November 2003. Given the lack of current Census data for
Montenegro with which to draw a sampling list for the HHS, the ISSP team had to look elsewhere
for household or individual listings. They identified two possible sources for developing the sample
frame. The first is the Voting Registration list. The second source is the Mass Voucher
Privatization (MVP) listing of all people compiled in order to distribute vouchers among the
population of citizens over 18 years in the summer of 2001. Both lists exclude IDPs (which
includes the Roma population in its definition). At the time when sampling was done, the MVP list
was newer than the voting registration list. ISSP concluded that these two lists were fairly
comparable.
The MVP list was used to identify the target sample in each of the 21 municipalities included in
Rounds 4, 5 and 6. The number of households targeted for each municipality was based on the
population share of the municipality in the total population 18 and over. Households were
interviewed based on the sampling list for the municipality, with no clustering design in the sample
within municipality, thereby reducing survey design effects which increase standard errors.
Upon developing the target number of households to be interviewed, interviewers were then
dispersed to their respective municipality to interview households. In Round 6, subsequent to
receiving the actual listing of MVP registrants, within each municipality, a random set of
households was pulled from the listing using a computer program. This random list was then
assigned to interviewers in each municipality.
Dissemination, Feedback and Coordination
For each ISSP HHS, a report on survey results with exhaustive descriptive statistics, was prepared
and widely distributed to the public by researchers at ISSP promptly after the data collection (within
1-2 months).
ISSP has worked closely with World Bank staff to develop the content of the questionnaires
(Rounds 4, 5, and 6) and the sampling frame (in Round 6). In addition, ISSP and World Bank staff
have made considerable efforts to develop design changes in coordination with the government in
Montenegro and donor agencies (such as USAID and UNDP).
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 41
Table A1.2: Samples in ISSP Household Survey Rounds 1-6
Municipality
Rounds 1-3
Households
%
Round 4
Households
%
Round 5 & 6
Households
%
Andrijevica - - 5 1.0
12 0.9
Berane - - 30 6.0
77 5.9
Bijelo Polje - - 43 8.6 90 6.9
Kolasin - - 8 1.6
21 1.6
Mojkovac - - 8 1.6
21 1.6
Mojkovac/Berane 100 5.0
Plav - - 12 2.4
32 2.5
Pljevlja - - 30 6.0
83 6.4
Pluzine - - 4 0.8
10 0.8
Rozaje - - 20 4.0
52 4.0
Savnik/Pluzine 50 2.5
Savnik - - 3 0.6
7 0.5
Zabljak - - 4 0.8
10 0.8
North 250 12.5 169 33.8 432 33.2
Podgorica 800 40.0 128 25.6
335 25.8
Niksic 300 15.0 59 11.8
154 11.8
Cetinje 50 2.5 16 3.2
42 3.2
Danilovgrad - - 12 2.4
32 2.5
Central 1150 57.5 215 43.0 563 43.3
Bar - - 31 6.2
82 6.3
Budva 200 10.0 12 2.4
32 2.5
Herceg Novi 150 7.5 26 5.2 68 5.2
Kotor 150 7.5 19 3.8
49 3.8
Tivat - - 11 2.2
29 2.2
Ulcinj 100 5.0 17 3.4 45 3.5
South 600 30.0 116 23.2 305 23.5
Total 2000 100.0 500 100.0 1300 100.0
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
42
ANNEX 2: Welfare measure: household consumption and expenditures
The welfare measure we want in order to study poverty should identify those without the means to
meet an established minimum living standard. The common practice in the European countries is to
set the poverty line at a fraction of median income. This is the case with most industrialized
countries (except the U.S.): living standards and poverty are assessed with reference to income, not
consumption. However, there are problems in applying this concept to any transition economy, and
Montenegro is not an exception.
Income is considered to be less accurately measured than household expenditures or consumption
for several reasons: (i) in transitional economies people very often do not have regular income,
making it hard to measure at a given point in time; (ii) many of them are engaged in gray economy
and may under-report income, (iii) households very often are engaged in agricultural activities but
do not consider it as an income at all. For these reasons, all of which apply to Montenegro, we
assess a household’s means by its consumption and expenditures rather than income. Thus, our
indicator incorporates the gray economy in our estimation of poverty.
Using the household data to measure income or consumption is not simple at all. The welfare
measure, be it income or consumption, needs to be complete. Omitting any type of income or
consumption will lead to erroneous conclusions. If, for example, the value of home-produced food
were omitted from a consumption aggregate (total consumption measure) then the rural populations
would look much poorer than they actually are. If, a consumption aggregate is constructed using
only cash expenditures, those who receive in-kind benefits from employment might look poorer
than they actually are. This is why the aim to measure imposes many demands on survey data and
requires an expended period of checks and validations.
How a household’s food consumption and non-food expenditure is collected is an important detail.
In ISSP HHS 5 & 6, the most informed respondent (probably a senior female), reported the quantity
and value of food consumed by all household members in the past 7 days. This is reported for 87
food items across three sources of receipt: purchases, self-produced, and received as gift (See
Annex 3 for this list of food items). The food consumption aggregate is based on the sum of the
Euro value of all food consumed in the past 7 days.
For non-food items, the recall period on expenditures vary depending on the frequency with which
purchases for such items are generally made. The specific categories and recall periods are listed in
Table A2.1.
Valuation of Housing
Calculating the value of housing to include in the consumption aggregate is more complicated than
for other consumption items. One consumes housing over a long period of time. Thus, the value of
housing to include in the consumption aggregate must reflect the value one receives during the
month and not the total value of the dwelling. For households that rent housing, it is assumed that
the monthly rental payment captures this housing consumption. However, the vast majority of
households in Montenegro are not renters. These households are not paying any explicit amount for
housing, but clearly their welfare level is improved by having housing. Therefore, we need to
estimate the implicit value of this housing.
The valuation of housing is compiled from three sources. For renters, it is the reported monthly rent
(5.6% of households). For owners, it is the imputed rent self-reported by owners (87.5% of
households). A comparison of the market prices of dwellings based on renters (per square meter in
Euros) with the implicit rent reported by owners found that owners’ assessments were consistent
with market prices (ISSP, 2002a). For renters or owners who do not report either rent type, it is
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 43
imputed based on regressions predicted imputed rent using a set of housing characteristics and
location variables (6.9% of households).
Table A2.1: Non-food expenditure categories, ISSP Household Survey
Non-food
Groupings
Specific categories in survey Recall period
Personal 16 categories including cigarettes*, hygiene
products, newspapers, etc...
reported for the previous month
*reported for last 7 days
Utility 6 categories: non-vehicle fuel and fuel oils,
gas, electricity, water and sewage
maintenance, garbage collection and
telephone
reported for the previous month
Transport 9 categories including gas for vehicles, taxi,
bus, trains, etc...
reported for the previous month
Other monthly 9 categories including video cassettes, CDs,
cleaning products, pet supplies, etc..
reported for the previous month
Household items 10 categories including large furniture,
home repairs. small appliances, linens, etc...
reported for the previous 3 months
Clothing and
footwear
9 categories including: men’s clothing and
footwear, women’s clothing and footwear,
child’s clothing and footwear, etc...
reported for the previous 3 months
Health care 6 categories: dentist, doctor, hospital,
medicines, optical equipment, other
expenditures
reported for the previous 3 months
Other quarterly 14 categories including sports equipment,
toys, sewing equipment, membership fees,
child care, presents, concert tickets, jewelry,
etc...
reported for the previous 3 months
Education 5 categories: enrollment and exam fees,
books and paper supplies, private classes,
tuition and other expenditures
reported for the previous 12 months
Other annual 2 categories: automobile registration and all
types of insurance.
reported for the previous 12 months
Adjusting for Regional Price Differences
In settings with a lot of price variation over time and space, price indices are used to adjust nominal
consumption aggregates in order to account for temporal and spatial price differences. Since the
data used are all reported for the months of July and October, temporal inflation is likely to not be a
concern (although this is not true for non-monthly nonfood items). Spatial price adjustments would
be a concern if there was indication of regional price variation. The official data on prices from the
Statistics department are used to produce one set of price indices that are not broken into regional
(such as north, center and south). Nevertheless, we were able to use the national and regional food
price data available to construct regional price indices based on the food shares in the HHS for July
and October 2002. For non-food, we construct an index from a list of 12 frequently purchased
items and their average regional prices for the two months. Table A2.2 shows these indices. Prices
in the south are highest, followed by the center region. When we deflate nominal consumption and
expenditures using these indices, we find little change in the overall poverty rate.
Table A2.2: Regional prices indices
North South Center Montenegro
Food price index 0.983 1.082 1.022 1.000
Non-food price index 0.997 1.014 1.072 1.000
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
44
Total Household Consumption
The amount of total household consumption and expenditure for food and non-food are reported in
Table A2.3. Official statistics indicate that food expenditures have been taking up a major share of
the household budget throughout the 1990s. According to data of the Republican Statistics Office
(as presented by MONET, ISSP), the share of food related expenditures (including beverages and
tobacco) in total household expenditures exceeded 62 percent in 1999. This is consistent with,
though higher than, the findings in the HHS. About half of total household expenditures where for
food and beverage. The second largest budget item is housing. These statistics can be compared to
slightly lower food shares in total household consumption in Bosnia and Herzegovina (33% in
2001) and Croatia (36% in 1998), whereas housing was a much large share of consumption (36% in
BiH and 32% in Croatia) (World Bank, 2002b and Luttmer, 2002). On the other hand, in Serbia
the food share is comparable (48%) but the housing share was much lower (4.6%) (Krstic, 2003).
The methodology used in Serbia was different to the methodology here and, thus, a direct
comparison is difficult.
Table A2.3: Monthly household consumption and expenditures
(Euros per month)
Mean % of total
Food & beverage consumption 417.8 49.2
Personal items** 64.0 7.5
Utilities 49.3 5.8
Transport 44.2 5.2
Household items 26.1 3.1
Clothing and footwear 46.3 5.5
Health care 7.9 0.9
Education expenditures 9.0 1.1
Other monthly, quarterly and annual expenditures 39.7 4.7
Housing (rent and imputed rent for owners) 145.0 17.1
Average total consumption and expenditure 849.3 100.00
Number of households* 1299
Average consumption expenditures per person 220.6
* The ISSP Household Survey 5 & 6 sample is 1300, but housing expenditure
for 1 household is missing.
** This data does not include consumption on cigarettes since that question was not
included in HHS 5. However, by HHS 6, average household expenditures for cigarettes
amounts to about 27 EUR.
Adult equivalence scales
Poverty studies usually measure living standards by assigning some share of total household
expenditure (or income) to each person in the household. Because needs vary among household
members, and because there are economies of scale in consumption, poverty measures based on per
capita welfare indicators may not be good estimates. An alternative is to base our welfare measure
on expenditure per adult equivalent. If our profile of poverty is not affected by reasonable
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 45
alternative adult equivalence weights that we choose, it is safe to say that those poverty estimates
are not biased because of weighting procedure.
To evaluate an appropriate equivalence scale for households in Montenegro, we start with the
equation:
PAE=(A+αK)θ
where PAE is the per adult equivalent value of household size, A is the number of adults, and K is
the number of children. The parameter α identifies the weight to convert 1 child into an equivalent
adult. Economies of scale are capture with the parameter θ. By comparing the results using a
reasonable range of values for the parameters we test the robustness of the data. Some commonly
used scales do not fall in the category of equivalence scales described by this formula, however.
One scale by OECD, for example, has the following structure:
PAEOECD = 1 + (0.5 * A
dults)
+( 0.3 *
Kids013
)
A number of methods are used to set equivalence scales, but each has drawbacks. As a result, a
wide variety of equivalence scales are used in various countries. The literature suggests that a one-
parameter scale (based on household size) gives fairly similar results to two-parameter equivalence
scales, however. Results based on the OECD scales show similar results to two-parameter
equivalence scales with a value of Ө around 0.5–0.6 (Figini 1998).
There are some ways to try to identify the most appropriate adjustment to make to household size.
One such approach is using Engel’s method. The crucial assumption of the Engel method is that
there is an inverse and monotonic relationship between a household’s well-being and the share of
expenditure spent on food. Hence, this assumption implies that two households are equally well-off
if, and only if, the food share in their expenditure is equal. This assumption is questionable, and
consequently, experts have advised against using this method (for example, see Deaton, 1997). So,
any estimates by this method should not be taken as definitive, but rather as one piece of
information that can aid in the selection of an equivalence scale.
We estimate a semi-log formulation for Engel’s relationship using non-linear least squares:
i
ii
i
iKidsKidsAdults
eExpenditur
FoodShare
ε
αα
ββ
θ
+
++
+= )71806(
ln 21
10 ,
where Foodsharei is the foodshare of household i, Expenditurei its total household consumption
expenditure, Adultsi is the number of adults, Kids06i the number of children 0-6 years, and
Kids718i the number of children 7-18 years. The error term is denoted by
ε
i
while β0, β1, α1, α2 and
θ are parameters to be estimated.
This was the procedure used for the Serbian scale, which they then used for their poverty analysis
(Krstic, 2003):
PAESerbia = 1 + 0.81* (Adults – 1) + 0.24*Kids06 + 0.75*Kids718
For Montenegro, we estimate under this approach using non-linear least squares for the full sample
of households in the HHS. The estimates are shown in Table A3.2.
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
46
The coefficient for young children suggests that young children are more expensive than adults,
whereas the coefficient for children 7-18 years is close to one. While θ is close to one, it is just
below one, suggesting some economies of scale. The standard error of the estimate θ is large
enough that we cannot reject the null hypothesis that θ is equal to one. The food share is
monotonically falling as welfare increases (negative sign on β1). The value of the intercept (close
to one) is also what one would expect since the poorest families will spend a lot of total expenditure
on food. However, the explanatory power of the regression is very weak, indicating significant
“noise” in the data that makes it difficult to calibrate the exact relationship. We conclude that the
estimates suggest using the simplest linear per capita equivalence scale as our preferred estimate.
Table A2.4: Estimates for Equivalence Scale Using Engel’s Method
α1 2.105
(1.010)
α2 1.169
(0.490)
θ 0.936
(0.166)
β0 0.803
(0.052)
β1 -0.058
(0.009)
Adjusted R2 0.044
No. of Observations 1299
Note: Standard errors in parentheses
Sensitivity to Equivalence Scales
The use of different scales to adjust household size is important because it can change the overall
ranking of households. It is therefore important to evaluate the sensitivity of the poverty profile to
different adjustments to household size that seem reasonable to account for economies of scale and
adult equivalence. Setting the fixed poverty rate at 20 percent, Figure 2.1 shows the poverty rate of
different groups when different scales are used. Five scales are used: per capita, economies of scale
of 0.9 (with no adjustment for adult equivalence), the scale developed for the Serbia poverty profile
(with both economies of scale and adult equivalence adjustment, an OECD scale, and finally,
economies of scale of 0.5. Figure 2.2 shows the share of the poorest 20 percent using these
different scales.
The poverty profile is remarkably robust to different scales. In most cases, it is not until the more
extreme scales (OECD or economies of scale of 0.5) are applied that the profile shifts. Children,
large households and households in the North each have elevated poverty risk using the most
reasonable scales. On the other hand, as a share of poor, children and those in large households do
not represent a large portion of the total population of the poorest 20 percent, regardless of the scale
used.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro 47
Figure 2.1: Poverty Rates Using Alternative Scales (fixed poverty at 20%)
0%
5%
10%
15%
20%
25%
30%
per
capita
E O S . 9 Ser bia n OE CD E OS . 5
Percent in lowest Quintile
children 0-15
elderly 65+
0%
5%
10%
15%
20%
25%
30%
per
capita
E O S . 9 Se r bia n O ECD E O S . 5
Percent in lowest Quintile
female head
male head
0%
5%
10%
15%
20%
25%
30%
35%
per
capita
E O S . 9 Se rbi a n O E CD E OS . 5
Percent in lowest Quintile
HH size 1-3
HH size 4+
0%
5%
10%
15%
20%
25%
30%
35%
per
capita
E O S . 9 Ser bia n O E CD EO S . 5
Nort h
Cen t er
So ut h
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
48
Figure 2.2: Share of the Poor Using Alternative Scales (fixed poverty at 20%)
0%
20%
40%
60%
80%
100%
per capita
EOS .9
Serbian
OECD
EOS .5
adults 16-64
elderly 65+
children 0-1 5
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
per capita
EOS .9
Serbian
OECD
EOS .5
male head
female head
0%
20%
40%
60%
80%
100%
per capita
EOS .9
Serbian
OECD
EOS .5
HH size 4+
HH size 1-3
0%
20%
40%
60%
80%
100%
per
capita
E O S . 9 Se rb i a n OE C D E O S . 5
So ut h
Cen t er
Nort h
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
49
ANNEX 3: Poverty Line
In practice, there is typically not one monetary poverty line but many, reflecting the fact that
poverty lines serve two distinct roles. One role is to determine what the minimum level of living is
before a person is no longer deemed to be “poor”. The other role is to make interpersonal
comparisons; poverty lines for families of different sizes and compositions, living in different
places, or for different dates, tell us what expenditures are needed in each set of circumstances to
ensure that the minimum level of living needed to escape poverty is reached.
We are aiming to calculate the absolute and relative poverty lines which allows us to compare living
conditions of one part of population to another one, both within the borders of the same country,
and internationally.
A poverty line is a value of consumption (income) below which one would be considered to be poor
by the society in which one lives. Poverty lines can be set in a variety of manners depending on the
purpose and needs. Here we discuss the difference between absolute and relative poverty lines.
Absolute poverty line: An absolute poverty line, as its name implies, does not measure poverty
relative to others welfare levels but instead attempts to establish the value of consumption that any
person needs, regardless of time and place. The most commonly used absolute poverty line is that
based on food consumption. Nutritionists set minimum food requirements by taking into account
the age, gender and level of effort expended by persons. Using this accepted minimum
requirement, the cost of the absolute food poverty line is set at the value of money required to meet
these minimum norms.
Irrespective of absolute needs, people may consider themselves poor when their living standards are
substantially below those of others in their country. This type of poverty is captured by relative
poverty lines, which define poverty as compared to “typical” national living standard.
However, there is a major disadvantage with relative poverty lines: they are not appropriate to study
changes over time; consequently, relative poverty figures overtime combine and confuse inequality
changes with poverty changes. Further, if the economy has a sizable portion of the population living
below a minimum standard, the relative poverty line will not measure this.
In sum, absolute and relative poverty lines serve very different purposes. To the extent that poverty
is perceived as lack of command over a set of essential commodities, which lack is to be reduced,
and progress has to be monitored over time, then the absolute poverty line needs to be used. This is
clearly the case in Montenegro. However, as Montenegro is aspiring to join the EU, it does make
sense to report relative poverty figures, in addition to absolute ones, to facilitate comparability of
reporting to EU members and candidate countries.
The minimum living standard used to identify the poor is based on the value of a minimum food
basket plus the cost of non-food essentials. The minimum consumption basket of food is based on a
standard of supplying 2,288 calories per person per day. The value of this food basket is then
calculated based on price data. In order to establish a poverty line, we need to define a minimum
basket for non-food items. Unfortunately, for non-food items, we have no notion of a minimum
standard such as calorie intake for foods. There are several methods used to identify a minimum
non-food basket, all of which rely on imputing minimum needs from food and total expenditures in
the survey data. For the minimum standard for non-food spending we used the method of setting an
“upper bound” to non-food expenditures.
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
50
Food poverty line
The minimum living standard in Euros is based on the value of a minimum food basket. This
minimum consumption basket of food is itself based on a standard of supplying 2,28820 calories per
person per day. The value of this food basket is then calculated based on price data. This is the
Food Poverty Line (FPL). The FPL relies on three data sources:
1. data on consumption patterns in order to allocate calories across different food items
based on a chosen reference population
2. data on the caloric content of each food item
3. data on prices in order to establish a monetary cost of the minimum food basket (the
FPL)
We base the minimum food basket on the consumption patterns of the households in the survey data
in the lowest 15%21 of per capita consumption and expenditure. For this population, we compute
one-half the mean intake (quantity, typically in kilograms) of each food item.22 The caloric content
of the 86 food items (excluding the category “other misc foods”) in the survey is based on USDA
(2002). Using these two sets of data, an optimization procedure is applied that establishes the a
minimum quantity for each food item that will reach the standard of 2,288 calories per person per
day and maintain the consumption patterns in the reference population’s food basket. Finally, the
price data from the Statistics department are applied to establish the cost of this basket. This is the
FPL.
Table A3.1 shows the mean quantities in the reference population and the minimum quantities and
Euro values for each of the 86 food items in the food basket.
Table A3.1: Minimum Food Basket
Reference Population Minimum basket
Food item
Mean per capita
quantity
Calorie
content
Price (Average
of July & Oct
2002)
Per capita
quantity Euros
Flour 6.40 3239.5 0.52 4.528 2.35
Corn flour 0.42 3496 0.75 0.294 0.22
Breakfast cereal 0.01 3630 1.33 0.007 0.01
Rice 0.34 3573.9 1.18 0.237 0.28
Pasta 0.57 3420 2.27 0.406 0.92
Bread 6.61 2610 0.68 4.672 3.18
Fresh biscuits, rolls 0.12 3560 0.2 0.088 0.02
Other bakery prod. 0.17 3000 0.83 0.121 0.10
Tomatoes 1.13 180.5 0.59 0.796 0.47
Potatoes 3.47 651 0.37 2.452 0.91
Onions 0.53 312.8 0.82 0.374 0.31
Lettuce 0.06 88.4 0.96 0.043 0.04
Beans 0.48 356.4 2.21 0.338 0.75
Cucumbers 0.66 100.1 0.58 0.466 0.27
Spinach 0.12 187 1.11 0.088 0.10
20 In order to have data and results comparable with the results in the region, for Montenegro we use the same standard
that was used in Serbia.
21 The FPL amounts to about 41 EUR. This is a rough average between the three FPL estimated: 42.26 EUR for
20% reference population, 41.0 for 15%, and 40.15 EUR for 10% reference population.)
22 When the actual amount of intake was taken, the level of consumption was 100% above the minimum for all items
and the optimization procedure does not work.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
51
Reference Population Minimum basket
Food item
Mean per capita
quantity
Calorie
content
Price (Average
of July & Oct
2002)
Per capita
quantity Euros
Cabbage 0.72 136 0.41 0.508 0.21
Peas 0.14 394.8 1.12 0.098 0.11
Pepper 0.85 192.5 0.89 0.599 0.53
Carrots 0.31 34.8 1.03 0.217 0.22
Mushrooms 0.01 24.3 3.25 0.004 0.01
Cauliflower 0.03 97.5 1.25 0.018 0.02
Other fresh veget. 0.08 146.2 0.93 0.058 0.05
Frozen vegetables 0.01 700 1.82 0.005 0.01
Oranges 0.30 338.4 1.36 0.215 0.29
Apples 1.75 542.8 1.02 1.240 1.26
Peach 0.35 374.1 1.08 0.246 0.27
Bananas 0.97 588.8 0.92 0.686 0.63
Nut 0.03 5265 8.06 0.018 0.14
Grape 0.14 388.6 1.99 0.099 0.20
Watermelon 1.55 140.8 0.26 1.096 0.28
Strawberries 0.00 282 1.48 0.000 0.00
Cherries 0.00 450 1.71 0.001 0.00
Lemon 0.24 185.6 1.34 0.171 0.23
Other fresh fruits 0.12 264.6 1.16 0.083 0.10
Frozen fruits 0.00 460 1.6 0.003 0.00
Can vegetables 0.10 840 1.51 0.072 0.11
Can fruit 0.01 423.2 1.75 0.005 0.01
Jams 0.32 2340 2.27 0.223 0.50
Honey 0.11 3040 4.88 0.078 0.38
Other canned veg. 0.00 2641 2.35 0.000 0.00
Veal 0.89 993.6 6.16 0.626 3.86
Pork 0.24 866.4 5.3 0.167 0.89
Lamb 0.18 915 5.59 0.125 0.70
Chicken 0.86 917.4 2.57 0.609 1.56
Sausage 0.10 3133.1 4.95 0.069 0.34
Bacon 0.14 8820 6.32 0.101 0.64
Delicatessen 0.31 3110 5.62 0.216 1.21
Ham 0.05 2250 6.78 0.034 0.23
Canned meats 0.00 5360 5.67 0.000 0.00
Other meats 0.01 1449 4.47 0.009 0.04
Eggs 16.33 758.4 0.12 11.547 1.33
Fresh fish 0.10 356 3.48 0.074 0.26
Frozen fish 0.06 615 5 0.039 0.20
Canned fish 0.01 2380 6.01 0.006 0.04
Fresh milk 8.61 610 0.48 6.091 2.92
Yogurt 1.79 610 0.97 1.265 1.23
Powder milk 0.09 4960 5.24 0.065 0.34
Cheese 1.07 3514.5 3.09 0.754 2.32
Kajmak 0.09 3490 6.24 0.063 0.39
Ice cream 0.03 4170 2 0.019 0.04
Other dairy products 0.00 2118.6 5.64 0.000 0.00
Butter 0.02 7170 4.91 0.016 0.08
Margarine 0.11 7190 1.93 0.079 0.15
Fats 0.13 9000 1.77 0.090 0.16
Olive oil 0.01 8500 4.34 0.007 0.03
Veg. oil 1.13 8840 1.07 0.797 0.85
Other oils 0.01 8840 2.01 0.009 0.02
Salt 0.33 0 0.49 0.235 0.11
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
52
Reference Population Minimum basket
Food item
Mean per capita
quantity
Calorie
content
Price (Average
of July & Oct
2002)
Per capita
quantity Euros
Sugar 0.84 4000 0.66 0.593 0.39
Spices 0.12 2890 3.4 0.084 0.29
Coffee 0.28 20 5.14 0.196 1.01
Tea 0.03 10 0.51 0.020 0.01
Other condiments 0.01 3000 2.24 0.006 0.01
Carbonated drinks 0.76 410 0.82 0.535 0.44
Fruit drinks 0.56 1100 1.59 0.395 0.63
Mineral water 0.71 0 0.43 0.501 0.22
Wine 0.06 1260 2.15 0.041 0.09
Beer 1.07 410 0.74 0.759 0.56
Liquor 0.01 2310 4.72 0.004 0.02
Other drinks 0.08 340 5.08 0.057 0.29
Chocolate 0.09 4000 6.96 0.067 0.46
Candy 0.04 5520 3.55 0.030 0.11
Cakes and cookies 0.16 3210 3.01 0.111 0.33
Other sweets 0.34 4020 2.21 0.240 0.53
Half-prepared food 0.00 3200 3.98 0.000 0.00
Baby food 0.05 780 5.3 0.036 0.19
Total monthly per person:
Food poverty line 2288 41.00
Total annual per person 492.01
Comparing Food Baskets
As noted in Section II of the main text, there are alternative food baskets that have been used to
identify the minimum amount of Euros needed to buy a minimum standard of calories. These
include the FSO food basket and the OCHA food basket. The differences in the food poverty lines
used by different groups will depend on the contents of the food basket (specifically, the
distribution across foods that have different prices per-calorie), the minimum standard the basket
aims to reach (in terms of calories and other nutritional criterion) which impacts the quantity of
each food item in the basket, and the prices used to cost the basket. Taking one of these factors, the
distribution of total basket calories, the FSO basket and the Serbia poverty profile basket can be
compared with the basket used in this study. (Details for the OCHA basket are not available). Note
that this comparison is only a partial evaluation of differences in the food poverty lines, since it
ignores the quantities in the basket (set to reach a calorie standard that varies) and the prices used.
Table A3.2 shows that the FSO basket allocates a higher share of calories in the minimum food
basket to more expensive foods (where “expensive” refers to a per-calorie cost): meat and dairy.
On the other hand, the Serbia food basket used by Krstic (2002) looks similar to the basket we
calculate for Montenegro. This is consistent with the development of the food baskets. Both of the
Montenegro and Serbian baskets in Table A3.2 are determined based on the consumption patterns
of the lower-income population as reflected in the recent household surveys used. The FSO basket,
on the other hand, is not developed from recent food consumption patterns of the population.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
53
Table A3.2: Share of Food Basket Calories by Food Groups
Food group
Montenegro
(ISSP HHS5 & 6)
FSO
Serbia
(Krstic, 2002)
Flour, bread, pasta 44.3 30.2 43.5
Vegetables 3.3 5.6 6.3
Fruit 3.5 4.2 4.0
Meat 4.8 8.5 3.9
Fish 0.1 0.1 0.0
Dairy and eggs 23.7 35.7 16.0
Butter and fats 12.5 8.7 14.4
Beverages 1.5 0.5 5.0
Other (other condiments, spices,
baby food, etc..)
6.4 6.5 7.0
Source: authors’ calculations.
Total Poverty Line
In order to establish a total poverty line, we need to define a minimum basket for non-food items.
Unfortunately, for non-food items, we have no notion of a minimum standard such as calorie intake
for foods. There are several methods used to identify a minimum non-food basket, all of which rely
on imputing minimum needs from food and total expenditures in the survey data. The sum of the
FPL (food minimum basket) and the non-food basket is the overall poverty line.
Based on our FPL of 41 Euros per person per month, a total poverty line (food and non-food) was
estimated by evaluating the median non-food consumption for those whose food consumption lies
within a range of the FPL. In this analysis, we will use the poverty line of 107 Euros per person per
months (41 for food and 66 for non-food goods and services).
ANNEX 4: Poverty and Inequality Measures
Poverty measures
Poverty is multidimensional concept encompassing various aspects of well-being. There is a large
literature on measure of poverty. Three measures in this document are members of a class of
decomposable poverty measures proposed by Foster, Greer and Thorbecke (1984). They are:
(i) the head count ratio, P0, measure the prevalence of poverty
(ii) the poverty gap index, P1, measures the depth of poverty
(iii) the poverty severity index, P2, measures the severity of poverty
All of these measures give no weight to the living standards of households with consumption above
the poverty line.
(i) Head count
The head count ratio, which is the simplest measure, is given by the percentage of people for whom
consumption per capita is less than the poverty line. If q people have consumption per capita below
the poverty line and there are n persons in total, then
P0 = q / n
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
54
Although P0 conveys information on how many people are poor, it does not say how poor they are.
It assigns the same weight to a poor person regardless of the level of consumption being 1 percent
of the poverty line (extremely poor) or 99 percent of the poverty line (close to non-poor status). If
poor people get richer over time but their consumption remains below a stationary poverty line, then
P0 would give the misleading impression of no change in the condition of the poor.
(ii) Poverty depth: poverty gap index
In order to account for the depth of poverty, we use the poverty gap index. It distinguishes among
the poor according to how far below the poverty line their consumption falls. If yi is consumption
(per capita) of the ith poor person and z is the poverty line, then
z
yz
n
Pi
q
i
)(
1
1
1
−
=∑
=
P1 measures the average poverty shortfall in the population (the non-poor have zero shortfall) as a
proportion of the poverty line. Thus it is a measure of the depth of poverty. P1 is sometimes used
to compute the fiscal costs of eliminating poverty, assuming perfectly targeted transfers. The fiscal
cost is calculated as the sum of poverty shortfalls, usually expressed as a percent of GDP. In
practice, there are administrative costs, leakages, and incentive effects would raise the actual fiscal
costs of poverty elimination through transfers.
(iii) Poverty severity gap
The disadvantage of P1 is that it is not sensitive to the distribution of the poor. The P2 measure
gives more weight to individuals who are further away from the poverty line. It is the weighted
sum of the poverty gaps, where the weights are the poverty gaps themselves. It measures the degree
of inequality in distribution below the poverty line, giving greater weight to households at the
bottom of the consumption distribution. It has the disadvantage of being difficult to interpret.
2
2
1
)(1
2z
yz
n
Pi
q
i
−
=∑
=
Inequality measures
Measures of poverty focus on the situation of individuals or households who find themselves at the
bottom of the income distribution; typically this requires information both about the mean level of
income/consumption as well as its distribution at the lower end. Inequality, on the other hand, is a
broader concept in that it is defined over the entire population, and not just for the population below
a specific consumption threshold. Most inequality measures do not depend on the mean of the
distribution, and this property of mean independence is considered to be a desirable property of an
inequality measure.
Sometimes we are more interested in measuring inequality than poverty per se. The simplest way
to begin is by dividing the population into fifths (quintiles) from poorest to richest, and reporting
the levels or proportions of income (or expenditure) that accrue to each level. Commonly used
measures of inequality are:
i.) Gini coefficient of inequality
ii.) decile dispersion ratio
iii.) generalized entropy measures
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
55
iv.) Atkinson's inequality measures
Here we use the first two measures. The most widely used single measure of inequality is the Gini
coefficient. The Gini coefficient is based on the Lorenz curve, a cumulative frequency curve that
compares the distribution of a specific variable (eg. income) with the uniform distribution that
represents equality. To construct the Gini coefficient, graph the cumulative percentage of
households (from poor to rich) on the horizontal axis and the cumulative percentage of expenditure
(or income) on the vertical axis. This gives the Lorenz curve as shown in Figure 4.1. The diagonal
line represents perfect equality. The Gini coefficient is defined as A/(A+B), where A and B are as
shown on the graph. If A=0 the Gini coefficient becomes 0 which means perfect equality, whereas
if B=0 the Gini coefficient becomes 1 which means complete inequality.
Let xi be a point on the X-axis, and yi a point on the Y-axis. Then:
.))((1
1
11
∑
=
−− +−−= N
i
iiii yyxxGini
When there are N equal intervals on the X-axis this simplifies to:
.)(
1
1
1
1
∑
=
−
+−= N
i
ii yy
N
Gini
Lorenz Curve
0
10
20
30
40
50
60
70
80
90
100
0 20406080100
Cumulative % of population
Cumulative % of expenditure
Figure 4.1. Lorenz Curve
The Gini coefficient is not entirely satisfactory. To see this, consider the criteria that make a good
measure of income inequality. Among these criterion that the Gini does satisfy:
• Mean independence. Under this criterion, if all incomes were doubled, the measure would not
change.
• Population size independence. If the population size were to change, the measure of inequality
should not change, ceteris paribus.
• Symmetry. If two individuals swap incomes, there should be no change in the measure of
inequality.
A
B
Living Standards and Poverty in Montenegro 2002
The World Bank,, Washington DC
56
• Pigou-Dalton Transfer sensitivity. Under this criterion, the transfer of income from rich to poor
reduces measured inequality.
• Statistical testability. One should be able to test for the significance of changes in the index
over time. This can be addressed by using bootstrap techniques to generate confidence
intervals.
In addition, it is also desirable to have decomposability, in which case inequality may be broken
down by population groups, by income sources or by other dimensions. The Gini index is not
decomposable or additive across groups. That is, the total Gini of society is not equal to the sum of
the individual Gini coefficients for its subgroups.
A simple and widely-used measure is the decile dispersion ratio, which presents the ratio of the
average consumption of income of the richest 10 percent of the population divided by the average
income of the bottom 10 percent. This ratio can also be calculated for other percentiles (for
instance, dividing the average consumption of the richest 5 percent – the 95th percentile – by that of
the poorest 5 percent – the 5th percentile).
The decile ratio is readily interpretable, by expressing the income of the top 10% (the “rich”) as a
multiple of that of those in the poorest decile (the “poor”). However, it ignores information about
incomes in the middle of the income distribution and the 90/10 ratio does not use information about
the distribution of income within the top and bottom deciles. On the other hand, as a poverty
monitoring tool, in some ways it is more appealing that the Gini coefficient. While the Gini index is
sensitive to changes throughout the distribution, it may be more sensitive to changes in the middle
and may completely overlook changes affecting the poor.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Institut za strate{ke studije i prognoze, Podgorica, Crna Gora
57
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Dragana Radevi}* i Kathleen Beegle**
*Centar za preduzetni{tvo i ekonomski razvoj (CEED), Direktor programa,
Podgorica, Crna Gora
** Development Research Group, World Bank, Washington, DC
Ova studija slu`i kao podr{ka za izradu procjene siroma{tva za Srbiju i Crnu Goru. Autori duguju zahvalnost
doma}instvima u Crnoj Gori koja su u~estvovala u realizaciji istra`ivanja o prihodima i rashodima
doma}instava. Tako|e, zahvaljujemo timu istra`iva~a i analiti~ara Instituta za strate{ke studije i prognoze
koji su radili na projektu Istra`ivanje o prihodima i rashodima doma}instava, na njihovim naporima u
prikupljanju pravovremenih i va`nih podataka. Zahvalnost dugujemo Petru Ivanovi}u i Ruslanu Yemtsovu
za korisne komentare i pru`enu podr{ku. Studija izra`ava nalaze i mi{ljenje autora, a nikako institucija u
kojima oni rade.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
58
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
59
SADR@AJ
Tabele i grafikoni 60
Rezime 61
Ekonomija u tranziciji: reforme i izazovi 61
Koliko je siroma{nih? 61
Ko su siroma{ni? 63
Pogled na budu}nost 64
Budu}i koraci 65
I. Uvod 66
II. Siroma{tvo u Crnoj Gori 68
Prou~avanje siroma{tva u Crnoj Gori 68
Siroma{tvo definisano preko potro{nje doma}instava 70
Ostali indikatori siroma{tva 73
III. Nejednakost 75
IV. Profil siroma{tva 76
V. Faktori koji uti~u na siroma{tvo u crnoj gori 79
VI. Izvori podr{ke doma}instava 82
Izvori prihoda 82
Penzije 84
Socijalni transferi 86
Socijalna za{tita i siroma{tvo 89
Privatni transferi 89
VII. Zaklju~ci 90
LITERATURA 92
ANNEX 1: Pregled istra`ivanja o prihodima i rashodima doma}instava u Crnoj Gori 94
Pozadina projekta 94
Istra`ivanja i sadr`aj upitnika 94
Uzorak i prikupljanje podataka 96
Objavljivanje, povratne informacije i koordinacija 97
ANNEX 2: Mjerenje bogatstva: potro{nja i tro{kovi doma}instava 97
Tro{kovi smje{taja 98
Prilago|avanje razlika u regionalnim cijenama 99
Ukupna potro{nja doma}instva 99
Skale ekvivalentnosti za odrasle 100
Osjetljivosti na skale ekvivalentnosti 102
ANNEX 3: Linija siroma{tva 104
Linija siroma{tva hrane 105
Pore|enje potro{a~kih korpi 107
Ukupna linija siroma{tva 108
ANNEX 4: Siroma{tvo i mjerenje nejednakosti 109
Mjere siroma{tva 109
Mjere nejednakosti 110
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
60
TABELE I GRAFIKONI
Tabela 1 Siroma{tvo u 2002. godini (procenat stanovni{tva) 62
Tabela 2 Siroma{tvo prema zaposlenosti starje{ine doma}instva u 2002 64
Tabela 3 Stope siroma{tva 71
Tabela 4 Alternativne mjere siroma{tva definisanog preko potro{nje doma}instava 72
Tabela 5 Vi{edimenzionalni indikatori siroma{tva 74
Tabela 6 Pore|enje potro{a~ke nejednakosti 76
Tabela 7 Profil siroma{tva: stope siroma{tva po grupama 78
Tabela 8 Regresija logaritma potro{nje po stanovniku po karakteristikama doma}instva 81
Tabela 9 Izvori prihoda za doma}instva 83
Tabela 10 Struktura prihoda doma}instava (prosje~ni iznosi u eurima) 83
Tabela 11 Procenat pojedinaca u doma}instvima koji imaju prihod od penzija 85
Tabela 12 Prihod doma}instava od penzije kao procenat ukupnih tro{kova 85
Tabela 13 Procenat pojedinaca u doma}instvima koja primaju socijalnu pomo},
nadoknade za nezaposlene ili stipendiju
88
Tabela 14 Socijalni transferi (dje~ji dodatak, materijalno obezbje|enje porodice, druga
socijalna pomo}) kao procenat ukupnih tro{kova
88
Tabela 15 Za{to se doma}instvo nije prijavilo za dobijanje MOP-a 88
Tabela 16 Prihodi od socijalnih programa 88
Tabela 17 Procenat pojedinaca u doma}instvima koji primaju privatne transfere 90
Tabela 18 Privatni transferi kao procenat ukupnih izdataka, (uslov na primanje transfera) 90
Tabela A 1.1 ISSP istra`ivanje o prihodima i rashodima doma}instava u Crnoj Gori 95
Tabela A 1.2 Uzorci u ISSP istra`ivanjima o prihodima i rashodima doma}instava 1-6 96
Tabela A 2.1 Kategorije neprehrambenih proizvoda, ISSP Istra`ivanje o prihodima i
rashodima
97
Tabela A 2.2 Regionalni indeksi cijena 99
Tabela A 2.3 Potro{nja i tro{kovi doma}instva (mjese~no, u eurima) 100
Tabela A 2.4 Procjene za skale ekvivalentnosti kori{}enjem Engelovog metoda 101
Tabela A 3.1 Minimalna potro{a~ka korpa 106
Tabela A 3.2 Udio kalorija u prehrambenoj korpi po pojedinim grupama prehrambenih
proizvoda
108
Grafik 1 Siroma{tvo me|u siroma{nima 63
Grafik 2 GDP per capita (US$) 66
Grafik 3 U~e{}e radne snage i ILO stope nezaposlenosti (1995-2002) 68
Grafik 4 Struktura potro{nje doma}instava 71
Grafik 5 Kriva opsega siroma{tva 72
Grafik 6 Kumulativna distribucija per capita tri{kova po regionima, 2002 73
Grafik 7 Lorencova kriva 76
Grafik 8 Stopa siroma{tva na sjeveru u odnosu na stopu siroma{tva na jugu i u
centralnom dijelu: posmatrano i simulirano
80
Grafik 9 Struktura prihoda doma}instava (u~e{}e u ukupnom prihodu po grupama
potro{nje)
83
Grafik 10 Zastupljenost penzija 86
Grafik 11 Distribucija bud`eta socijalne za{tite 87
Grafik 12 Promjena u siroma{tvu bez programa socijalne za{tite 89
Grafik 2.1 Stope siroma{tva uz upotrebu alternativnih skala (siroma{tvo fiksirano na nivou
od 20%)
102
Grafik 2.2 Udio siroma{nih uz upotrebu alternativnih skala (siroma{tvo fiksirano na nivou
od 20%)
103
Grafik 4.1 Lorencova kriva 111
Box 1 Siroma{tvo koje niko ne `eli da ga primjeti: “Nezvani~ni” smje{taj Roma u
Crnoj Gori
75
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
61
REZIME
Ekonomija u tranziciji: reforme i izazovi
U pro{loj deceniji, razvoj crnogorske privrede obilje`ili su unutra{nji i spolja{nji politi~ki i
ekonomski {okovi. Poslednjih godina, Crna Gora je zapo~ela ambiciozan program sveobuhvatnih
ekonomskih reformi u cilju promovisanja ekonomskog rasta i pove}anja `ivotnog standarda. I pored
toga, neophodne su dodatne reforme da bi se, na primjer, izborili sa visokim tro{kovima zarada
javnog sektora, velikom zavisno{}u od pomo}i donatora i neefikasno{}u u dr`avnim preduze}ima.
Neujedna~en napredak u reformama vidljiv je i u makroekonomskoj performansi privrede: iako je
do{lo do blagog oporavka dru{tvenog bruto proizvoda (GDP) u periodu nakon 1999. godine i u
posljednje dvije godine zabilje`en njegov rast od oko 2%, pokazatelji zaposlenosti ne odra`avaju
pozitivne promjene u GDP-u.
Na`alost, mnogo novih politika je realizovano uz malo dostupnih informacija o brojkama i
karakteristikama siroma{nih; tako|e, izostala je procjena uticaja reformi na siroma{ne. Pored toga,
napori za smanjenje siroma{tva i podizanje `ivotnog standarda su dodatno ote`ani velikim
o~ekivanjima stanovni{tva od ekonomskih reformi. Prepoznaju}i potrebu za rigoroznim planiranjem
aktivnosti smanjenja siroma{tva i monitoringa, Srbija i Crna Gora zavr{ile su svoje prelazne
strategije za smanjenje siroma{tva (Interim Poverty Reduction Strategy Paper, I-PRSP) u julu 2002.
godine. Priprema prvog nacrta finalne verzije strategije za smanjenje siroma{tva u Crnoj Gori je u
toku. Analizom odgovaraju}ih podataka o siroma{tvu i nastavkom prethodnih analiza, ovaj
dokument }e zna~ajno doprinijeti procesu izrade startegije za smanjenje siroma{tva.
Ova studija daje prikaz profila siroma{tva i nivoa `ivotnog standarda u Crnoj Gori kori{}enjem
najnovijih i najboljih dostupnih podataka. Rezultati pokazuju da je veoma sumorna percepcija
siroma{tva u Crnoj Gori daleko od realnosti. Sa druge strane, rezultati isti~u va`nost procjene
potencijanog uticaja ekonomskih reformi na najsiroma{nije u Crnoj Gori koji ostaju osjetljivi na
promjene u ekonomskom okru`enju. Prezentuju}i niz zna~ajnih rezultata, ovaj dokument slu`i kao
platforma za va`nu diskusiju u Crnoj Gori na temu izrade strategije za smanjenje siroma{tva i
monitoringa progresa koji se ostvaruje primjenom te strategije.
Koliko je siroma{nih?
Kori{}enjem najnovijih i vjerovatno najboljih raspolo`ivih podataka o `ivotnom standardu u Crnoj
Gori, primjenom preciznih definicija bogatstva doma}instava i uspostavljanjem linije siroma{tva,
ova studija otkriva da broj ljudi koji `ive u apsolutnom siroma{tvu nije velik. Oko 10%
stanovni{tva `ivi u apsolutnom materijalnom siroma{tvu. Siroma{tvo nije duboko; ukupan jaz
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
62
siroma{tva iznosi oko 1% dru{tvenog bruto proizvoda. Ekstremno siroma{tvo ne postoji u
zna~ajnoj mjeri, mada je va`no naglasiti da je ono veoma izra`eno me|u populacijama koje je
te{ko obuhvatiti istra`ivanjem (ovo se naro~ito odnosi na Rome i raseljena lica).
Iako je stopa siroma{tva relativno niska i siroma{tvo nije duboko, procjene broja siroma{nih su
osjetljive na nivo linije siroma{tva. Vi{e od jedne tre}ine stanovni{tva je klasifikovano u grupu
ekonomski ugro`enih, odnosno materijalno nedovoljno obezbije|enih, {to zna~i da `ive ispod
nivoa od 150% definisane linije siroma{tva. Podizanjem linije siroma{tva za 20%, stopa siroma{tva
se udvostru~uje. Tako, `ive}i ta~no iznad linije siroma{tva, zna~ajan dio stanovni{tva je ugro`en u
smislu da su osjetljivi na sve ekonomske fluktuacije, preokrete ili {okove u nivoima li~nih
dohodaka. Pozitivne promjene prihoda (one izazvane npr. rastom ili dobrim razvojnim politikama)
bi rezultirale iznad proporcionalnim smanjenjem siroma{tva; negativne promjene (kao {to je
recesija) dovele bi do iznad proporcionalnog pove}anja siroma{tva.
Tabela 1. Siroma{tvo u 2002. godini (procenat stanovni{tva)
Siroma{tvo
u hrani
Apsolutno
(osnovna
linina)
Ekonomski
ugro`eni ili
siroma{ni
4.0 9.4 36.4
Izvor
: ISSP Istra`ivanja o prihodima i rashodima doma}instava 5 i 6. Siroma{tvo u hrani
definisano je kao situacija u kojoj se poto{nja doma}instva za hranu nalazi na nivou ispod
tro{kova minimalne potro{a~ke korpe (41 euro po osobi na mjese~nom nivou). Apsolutno
siroma{tvo definisano je kao situacija u kojoj je ukupna potro{nja doma}instva na nivou ispod
tro{kova ukupne minimalne korpe, ili linije siroma{tva (107 eura mjese~no); linija koja ozna~ava
ekonomski ugro`ene definisana je na nivou od 50% iznad linije siroma{tva. Pogledati tekst za
vi{e detalja.
Siroma{tvo definisano preko potro{nje doma}instava je samo dio problema. Postoji i siroma{tvo u
drugim dimenzijama, uklju~uju}i siroma{tvo u odnosu na zaposlenost, smje{taj i zdravstveno
stanje. Skoro petina odraslih (20%) ne radi ali su spremni da rade ako bi im se ukazala {ansa za
zaposlenjem; dvije petine svih doma}instava (40%) imaju bar jednog ~lana doma}instva koji je
siroma{an u pogledu zaposlenja (`eli da radi, a nema mogu}nosti da se zaposli). Oko 13%
stanovni{tva `ivi u objektima do kojih se voda ne doprema vodovodnim cijevima ili u objektima
bez kupatila. Oko 6% stanovni{tva je zbog bolesti ili povrede bilo onemogu}eno da obavlja redovne
aktivnosti. U skladu sa ~injenicom da ne postoji izra`eno ekstremno siroma{tvo kada kao indikator
koristimo potro{nju doma}insatva, manji broj osoba pati od vi{e oblika siroma{tva/nedostataka
istovremeno (pogledati grafik 1).
Indikatori nejednakosti se kre}u u intervalu indikatora nejednakosti u ostalim ekonomijama u
regionu, ali nejednakost koja nagla{ava relativnu poziciju siroma{nih u odnosu na bogata
doma}instva (90/10 decil odnos) ukazuje na postojanje visoke nejednakosti.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
63
Grafik 1: Siroma{tvo me|u doma}instvima
1 nedostatak
38%
bez
nedostataka
46%
3-5
nedostataka
3%
2 nedostatka
13%
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6. Napomena:
Vidjeti Tabelu 3 radi potpunih definicija. Siroma{tvo/nedostaci uklju~uju: siroma{tvo
p
o osnovu nivoa
p
otro{n
j
e, siroma{tvo me|u odraslima u doma}instvu u
p
o
g
ledu
zaposlenja, siroma{tvo u pogledu zdravstvenog stanja, nedostatak smje{taja u pogledu
veli~ine mjesta stanovanja i nedostatak telefona.
Ko su siroma{ni?
Prilikom analize profila siroma{nih u Crnoj Gori primjetni su interesantni obrasci. Siroma{ni tro{e
najve}i dio svojih izdataka na hranu. Smje{taj je druga po veli~ini komponenta u tro{kovima.
Vjerovatno}a da }e veliko doma}instvo biti ispod linije siroma{tva je ve}a, mada udio ovih
doma}instava u populaciji siroma{nih nije zna~ajan po{to je prosje~na veli~ina doma}instva mala.
Regionalni aspekt siroma{tva je veoma izra`en; siroma{tvo je najve}e me|u doma}instvima na
sjeveru Crne Gore. Iznena|uju}e je da, u tako kompaktnoj dr`avi kao {to je Crna Gora, postoje 1:2
razlike u stopama siroma{tva izme|u najsiroma{nijeg i najbogatijeg regiona. Dok osnovne
karakteristike, kao {to je nivo obrazovanja, zaposlenost i demografska struktura, obja{njavaju neke
od regionalnih razlika, zna~ajne razlike ostaju i nakon kontrole ovih osnovnih karakteristika i
upotrebe multivarijantne analize. Drugim rije~ima, regionalne razlike ne mogu biti u potpunosti
obja{njene nivoom obrazovanja, statusom zaposlenosti, demografijom i ostalim faktorima
doma}instva koji se razlikuju izme|u regiona. Postoje drugi, generalni faktori koji uti~u na to da
pojedine lokacije budu siroma{ne.
Mogu}nosti za zaposlenje igraju va`nu ulogu; karakteristike statusa zaposlenosti ~lanova
doma}instava, uklju~uju}i njihov humani kapital (ste~eno obrazovanje), su bitne determinante
`ivotnog standarda. Doma}instva sa odraslim osobama koje imaju zaposlenje imaju vi{i nivo
potro{nje; radna neaktivnost i nezaposlenost su u sna`noj vezi sa siroma{tvom. Istovremeno,
siroma{tvo je prisutno u mnogim doma}instvima gdje je starje{ina doma}instva zaposlen; ova
doma}instva ~ine dvije petine siroma{nih doma}instava.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
64
Tabela 2: Siroma{tvo prema zaposlenosti starje{ine doma}instva u 2002
Siroma{ni, %
populacije u grupi
Dio
populacije
Dio medju
siroma{nima
Dubina
siroma{tva
O{trina
siroma{tva
Nezaposleni i nepenzionisani 18.6 9.8 19.3 3.0 0.8
Zaposleni 6.5 62.4 43.5 0.9 0.2
Penzionisani i nezaposleni 12.1 27.8 37.2 1.6 0.3
Ukupno 9.4 100 100 1.3 0.3
Izvor:
ISSP Istra`ivanje o prihodima i rashodima stanovni{tva 5 and 6. Zaposleni su definisani kao oni koji su tokom pro{le nedjelje
(misli se na nedjelju koja prethodni prikupljanju podataka) radili za nov~anu nadoknadu ili imaju redovan posao ali nisu radili pro{le
nedjelje (odmor, bolest, itd..); “penzionisani” su oni koji nisu zaposleni i koji su sami prijavili da im je to glavna aktivnost;
“nezaposleni” su svi ostali.
[tite}i doma}instva od siroma{tva, socijalno osiguranje igra va`nu ulogu u iskorjenjavanju
siroma{tva. Penzije su zna~ajne kao izvor prihoda za siroma{ne sa starosnim i invalidskim
penzijama kao dominantnim kategorijama. Sa druge strane, nadoknadu za nezaposlene, koja je
slede}a bitna kategorija socijalnog osiguranja, prima veoma mali procenat doma}instava. Iako je
vjerovatno}a da siroma{ni primaju socijalnu pomo} ve}a, nivo pomo}i (u~estalost pla}anja i iznos)
je nizak i generalno suvi{e nizak da bi imao zna~ajniji uticaj na `ivotni standard.
Perspektiva za budu}nost
U oblasti monitoringa, neophodno je ustanoviti jasne smjernice za pra}enje siroma{tva u
vremenu na konzistentan i uporediv na~in. Klju~na aktivnost }e zahtijevati izgradnju konsenzusa
povodom zvani~ne linije siroma{tva i metodologije mjerenja siroma{tva. Dalje, definisanje klju~nih
indikatora koji }e se pratiti tokom vremena i `eljenih nivoa ovih indikatora zahtijeva pa`ljivo
razmatranje. U analizi siroma{tva ovaj dokument nagla{ava potrebu za dodatnim analizama,
uklju~uju}i izme|u ostalog: (i) predvi|anje uticaja penzione reforme na siroma{ne, (ii)
procjenjivanje targetiranosti i efikasnosti socijalnih programa, (iii) razumijevanje ograni~enja
ruralnih prihoda, i (iv) simulaciju efekata distribucije planiranog rasta.
Odgovaraju}e pra}enje i ocjena nivoa `ivotnog standarda gra|ana bi trebalo da bude prioritetni
zadatak Vlade. Bez valjanih podataka, politika }e biti pogre{no vo|ena ili ne}e uop{te biti vo|ena.
Studija nagla{ava potrebu za pravovremenim, visoko kvalitetnim, dostupnim podacima za
ostvarivanje ovog zadatka. Implementacija redovnih istra`ivanja o prihodima i rashodima
doma}instava koja obezbje|uje ta~no mjerenje siroma{tva bi stoga bila osnovni dio strategije.
Podaci za analizu siroma{tva u ovoj analizi, kao i u strategiji za smanjenje siroma{tva, u velikoj
mjeri dolaze od spoljno finansiranih istra`ivanja koja je realizovala nevladina organizacija Institut
za strate{ke studije i prognoze i pritom pokazala svoj profesionalizam, ekspertizu i fleksibilnost da
u kratkom vremenskom periodu uvede medjunarodne standarde u sve faze realizacije istra`ivanja.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
65
Crna Gora se jo{ uvijek suo~ava sa izazovom razvoja statisti~kog sistema koji mo`e prikupljati,
obra|ivati, analizirati i ~initi dostupnim informacije o nivou `ivotnog standarda. Slede}i korak u
ovom pravcu bi mogla biti koordinacija napora u prikupljanja podataka u Institutu za strate{ke
studije i prognoze sa teku}im zvani~nim istra`ivanjem bud`eta doma}instava koje sprovodi
Republi~ki zavod za statistiku MONSTAT, kako bi se kompletnije razvio sistem podataka za
pra}enje siroma{tva. U me|uvremenu, po{to je redovno prikupljanje podataka neophodno, a imaju}i
na umu da je Vlada Crne Gore usvojila Zakon o u~e{}u privatnog sektora u pru`anju javnih usluga,
predla`e se nastavak saradnje sa NVO sektorom, sve dok Republi~ki zavod za statistiku ne izgradi
sopstvene kapacitete.
Politi~ka nestabilnost je tako|e va`an faktor koji je uticao na siroma{tvo: posebno kada imamo u
vidu izbjeglice i raseljena lica. Nedostatak informacija u ovoj procjeni o nivou `ivotnog
standarda kod Roma, izbjeglica i raseljenih lica (grupe koje je iz poznatih razloga te{ko uklju~iti
u uzorak istra`ivanja) zahtijevaju pa`nju. Na primjer, veoma je vjerovatno da romska doma}instva
pate od mnogo ekstremnijeg siroma{tva nego {to se to odra`ava u postoje}im uzorcima istra`ivanja
o prihodima i rashodima doma}instava. Istra`ivanje koje slijedi treba da se fokusira na pomenutu
populaciju kako bi postoje}i podaci o siroma{tvu bili komplementirani.
Budu}i koraci
Aktivnosti koje slijede nakon objavljivanja ove procjene siroma{tva su vi{estruke i uklju~uju:
• Saradnju sa Republi~kim Zavodom za statistiku radi obuke zaposlenih kroz u~e{}e u
realizaciji budu}ih istra`ivanja ISSP-a;
• Posebno istra`ivanje o prihodima i rashodima Roma i raseljenih lica koje }e ISSP realizovati
tokom ljeta 2003. godine uz podr{ku i tehni~ku pomo} Svjetske banke i Razvojnog
programa Ujedinjenih nacija, kancelarija u Podgorici
• Pro{irenje obuhvata istra`ivanja ISSP-a radi analize problema koji se odnose na pitanja
za{tite `ivotne sredine;
• Dalji razvoj upitnika koji se koristi za istra`ivanje ISSP-a sa ciljem analize uticaja
restrukturiranja preduze}a na tr`i{te rada i siroma{tvo u Crnoj Gori.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
66
I. UVOD
Tokom poslednjih deset godina, crnogorska privreda pre`ivjela je rapidnu ekonomsku
transformaciju. Od ekonomskog i politi~kog kolapsa Jugoslavije, Republika Crna Gora je pretrpjela
gubitak od 57% ekonomske mo}i koju je imala 1989. godine (vidi grafik 2). GDP se polako
oporavlja od 1999. godine uz rast od oko 2% tokom poslednje dvije godine. Tranzicija je bila
obilje`ena unutra{njim i spolja{njim politi~kim i ekonomskim {okovima koji su doveli do dubokog
i o{trog pada u proizvodnji, do pove}anja inflacije, porasta zvani~ne nezaposlenosti i porasta u~e{}a
neformalnog sektora (“sive” ekonomije). U januaru 2002. godine, Crna Gora je uvela euro kao
zvani~no sredstvo pla}anja. Kao posljedica toga, Crna Gora se suo~ila sa “€ inflacijom”, koja je
karakteristi~na za evropske zemlje koje su usvojile novu valutu.
Grafik 2: GDP per capita (US$)
0.0
300.0
600.0
900.0
1,200.0
1,500.0
1,800.0
2,100.0
2,400.0
2,700.0
3,000.0
3,300.0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Izvor: Institut za strate{ke studije i prognoze (ISSP)
Crna Gora je trenutno dio zajednice Srbija i Crna Gora (SiCG), koja ima zajedni~ki Parlament,
Predsjednika i Savjet ministara. Parlament zajednice bira predsjednika zajednice, koji je odgovoran
za predlaganje Savjeta ministara i kontrolo{e njihov rad. Savjet ministara zajednice ima pet oblasti
djelovanja: spoljni poslovi, odbrana, me|unarodni ekonomski odnosi, unutra{nji ekonomski odnosi
i za{tita ljudskih i manjinskih prava. Ove zajedni~ke funkcije u SiCG }e biti zajedni~ki finansirane,
u mjeri u kojoj Republike doprinose GDP-u. Iako ove dvije Republike imaju neke zajedni~ke
institucije, one ipak vode odvojene ekonomske, fiskalne i monetarne politike.
Ubrzo nakon izbora 1999. godine, Crna Gora je zapo~ela niz ekonomskih reformi, {to zna~i mnogo
prije nego je isti proces zapo~eo u Srbiji.23 Ove po~etne reforme su uklju~ile napore da se stabilizuju
cijene, da se smanji bud`etski deficit i da se elimini{u nepravilnosti u trgovini. Inflacija je pala sa
preko 100% na godi{njem nivou u 1999. godini na 24% u 2001. godini nakon uvo|enja njema~ke
marke kao zvani~nog sredstva pla}anja. Pove}anjem kontrolisanih cijena u energetskom sektoru,
nepravilnosti u cijenama su smanjene dok je istovremeno pobolj{ana finansijska pozicija dr`avnog
preduze}a Elektroprivrede Crne Gore. Stroga ograni~enja uvedena 1999. godine, uklju~uju}i
obavezu od 100% rezervi na depozite preduze}a, pomogli su stabilizaciju bankarskog sektora. U
2000. godini je pojednostavljena struktura sistema carinskih stopa i prosje~na carinska stopa je
smanjena na ispod 3%.
23 Materijal u ovom dijelu dobijen je od Instituta za strate{ke studije i prognoze (2003) i Svjetske banke (2003).
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
67
Proces reformisanja je ubrzan tokom 2001. godine zapo~injanjem va`nih reformi u oblasti
upravljanja javnim finansijama. Na strani bud`etskih prihoda, nedavno usvojeni zakoni bi trebalo
da: pro{ire prihodnu bazu smanjivanjem izbjegavanja pla}anja poreza, pobolj{aju rad poreske
administracije i omogu}e pove}anje naplate poreza. U aprilu 2003. godine, Vlada je dalje pove}ala
nivo prikupljanja indirektnih poreza uvo|enjem poreza na dodatu vrijednost. Tako|e, postoje nove
inicijative za unapre|enje targetiranja socijalne pomo}i i dje~jih dodataka kako bi ovu pomo}
dobijala zaista najsiroma{nija doma}instva. Pitanja nepravilnosti u cijenama su dalje rje{avana;
cijene osnovnih prehrambenih proizvoda su u potpunosti liberalizovane.
U finansijskom sektoru ~ine se napori da se uspostavi zdrav bankarski sistem i da se defini{u
klju~ne funkcije Centralne banke. Uprkos velikom porastu ukupnih depozita koji je nastao nakon
prelaska na euro, visok nivo nepovjerenja gra|ana prema bankarskom sektoru nastavio je da postoji.
Razvijen je obiman set propisa koji treba da reguli{e proces licenciranja, finansijskog izvje{tavanja i
neophodnih zahtjeva za poslovanje komercijalnih banaka. Doneseni su zakoni koji se odnose na
bankrotstvo i likvidaciju, definisanje pokreta~a i procedura koje se odnose na akcije protiv
insolventnih banaka.
Uprkos ambicioznim reformama, izazovi ostaju. Crna Gora ima veliko u~e{}e javnog sektora,
uklju~uju}i zna~ajne tro{kove zarada javnog sektora (44% ukupnih tro{kova), a postoji i jaka
zavisnost od donatorske pomo}i i drugih oblika spoljnog finansiranja u cilju pokrivanja sada{njih
nivoa potro{nje i investicija. Inostrana pomo} predstavlja skoro 12% ukupnih prihoda. Jo{ uvijek su
potrebne dodatne reforme u dr`avnim preduze}ima. Mnoga dr`avna preduze}a nastavljaju da budu
neprofitabilna, zahtijevaju}i zna~ajne dr`avne subvencije radi opstanka. Dr`avno preduze}e
Elektroprivreda Crne Gore, nastavlja da efektivno subvencioni{e i doma}instva i dr`avna
preduze}a, kao {to je Kombinat aluminijuma. U me|uvremenu, ponuda uglja je nestabilna zbog
finansijskih, tehni~kih i organizacionih problema u rudnicima uglja.
Kako javna preduze}a koja posluju sa gubitkom prestaju da primaju bud`etske subvencije, postoji
opasnost da bi nezaposlenost mogla dodatno porasti. Nivo nezaposlenosti je visok u pore|enju sa
drugim zemljama regiona, usljed problema zbog posebnosti tr`i{ta radne snage (sezonski i
neformalni sektor) i nesklada koji postoji izme|u sistema obrazovanja i radnih sposobnosti koje
zahtijeva nova privreda. Uprkos strahovima od masovnog otpu{tanja, agregatno posmatrano,
nezaposlenost (definisana po ILO standardima prije nego po broju registrovanih nezaposlenih) nije
u stalnom porastu tokom poslednjih godina. Postoje promjene u odnosu na 2000. godinu i,
generalno posmatrano, velike razlike i u stopi nezaposlenosti i u polnoj strukturi radne snage
(vidjeti statistiku iz Istra`ivanja radne snage, 2000, grafik 3). Ovi pokazatelji zaposlenosti ne
uspijevaju da odraze napredaku GDP-ju tokom poslednje dvije godine. Ako proces rasta ne rezultira
stvaranjem novih radnih mjesta, nivo siroma{tva se ne}e smanjiti.
[ta sve ove promjene zna~e za nivo siroma{tva i nejednakosti u Crnoj Gori? Op{te shvatanje je da
je tranzicija ka tr`i{noj ekonomiji rezultirala pove}anjem siroma{tva i nejednakosti u Republici,
iako prava statistika za ocjenu ovoga nije dostupna. Ipak, teku}i proces tranzicije, koji mo`e
obuhvatiti reformu penzionog sistema, potencijalne poraste nezaposlenosti i aktivnosti definisanja
novih pravila za dodjeljivanje socijalne pomo}i, mogao bi imati zna~ajne uticaje na siroma{ne.
Potreba za evaluacijom dimenzija ovih promjena je presudna. Ove promjene imaju razli~ite
implikacije na razli~ite demografske grupe kao i na razli~ite regione.24
Prepoznaju}i potrebu za rigoroznim planiranjem aktivnosti smanjenja siroma{tva i monitoringa,
Srbija i Crna Gora zavr{ile su svoje prelazne strategije za smanjenje siroma{tva (Interim Poverty
Reduction Strategy Paper, I-PRSP) u julu 2002. godine. Priprema prvog nacrta finalne verzije
strategije za smanjenje siroma{tva u Crnoj Gori je u toku. Analizom odgovaraju}ih podataka o
24 Crna Gora se mo`e podijeliti u tri regiona. Centralni region ima najvi{e stanovnika i najindustrijalizovaniji je. Jug je
primorski i najrazvijeniji region; turizam je glavni ekonomski sektor. Najmanje razvijen region je sjever Republike, koji
je planinski i manje naseljen. Vidjeti Annex 1 za kompletnu listu op{tina u svakom regionu.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
68
siroma{tvu i nastavkom prethodnih analiza, ovaj dokument }e zna~ajno doprinijeti procesu izrade
startegije za smanjenje siroma{tva.
Izvor: Anketa o radnoj snazi, prora~une je uradio Branko Jovanovi} (2003)
Dok je nedostatak podataka ograni~io mogu}nost procjene siroma{tva i nivoa `ivotnog standarda
poslednjih godina, novo istra`ivanje o prihodima i rashodima doma}instava sprovedeno u 2002.
godini nam omogu}ava da ustanovimo osnovnu liniju u pogledu nivoa `ivotnog standarda
crnogorskog stanovni{tva od koje bi se posmatrale budu}e promjene. Sa ovim podacima o nivou
`ivotnog standarda doma}instava, analiza mo`e ocjenjivati ulogu socijalnih politika u davanju
podr{ke siroma{nih, kao i potencijalan uticaj glavnih politi~kih reformi. Cilj ove studije je da se
prika`e {irok profil siroma{nih u Crnoj Gori kao i da se predlo`e pravci za budu}e analize.
II. SIROMA[TVO U CRNOJ GORI
Prou~avanje siroma{tva u Crnoj Gori
Siroma{tvo je vi{edimenzionalan koncept koji obuhvata razli~ite aspekte blagostanja. U praksi ne
postoji jedan jedinstveni indikator koji obuhvata sve dimenzije siroma{tva. Ovaj dokument daje
statisti~ke podatke kroz brojne socio-ekonomske indikatore i tako opisuje nivo `ivotnog standarda
stanovni{tva. Statisti~ki podaci su uglavnom iz Istra`ivanja o prihodima i rashodima doma}instava
(HHS) koje realizuje Institut za strate{ke studije i prognoze, a koji su prikupljeni tokom jula i
oktobra 2002. godine.25 Na osnovu ovih podataka mjerimo materijalno blagostanje kori{}enjem
ukupne potro{nje doma}instva kao na{eg glavnog, ali ne i jedinog, indikatora (vidjeti Annex 2).
Indikator potro{nje se potom poredi sa linijom siroma{tva koja predstavlja minimalan `ivotni
standard (u eurima), izra~unat na osnovu strukture potro{nje 15% najsiroma{nijih u Crnoj Gori i
minimuma potrebnih kalorija (vidjeti Annex 3). Kori{}enjem podataka iz Istra`ivanja o prihodima i
rashodima doma}instava, u ovoj studiji su primijenjene metodologije mjerenja siroma{tva koje su
zasnovane na najboljim me|unarodnim iskustvima. Time su na{i rezultati me|unarodno uporedivi.
25 HHS je razvijen i realizovan od strane Instituta za strate{ke studije i prognoze (ISSP) iz Podgorice. Istra`ivanje je
podr`ano od strane European Commission Food Security Pogramme, USAID Crna Gora i Chesapeake Associates. Za
istra`ivanja broj 4, 5 & 6, ISSP je dobio tehni~ku pomo} i komentare eksperata Svjetske banke. Za dalje informacije
vidjeti Annex 1 i ISSP 2002a, 2002b.
Grafik 3: U~e{}e radne snage i ILO stope
nezaposlenosti (1995-2002)
0%
20%
40%
60%
80%
1995 1996 1997 1998 1999 2000 2001 2002
Procenat
U~e{}e u radnoj snazi mu{karaca
U~e{}e u radnoj snazi `ena
N
ezaposlenost `ena
N
ezaposlenost mu{karaca
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
69
Podaci Istra`ivanja o prihodima i rashodima doma}instava (HHS) ISSP-a nisu jedini izvor
istra`iva~kih podataka za analizu siroma{tva. Me|u drugim izvorima koji se pominju tu su: Anketa
o potro{nji doma}instava (APD) koju realizuje Savezni zavod za statistiku (SZS) Srbije i Crne
Gore. Ovo kvartalno istra`ivanje obuhvata 380 doma}instava iz 12 op{tina u Crnoj Gori, pri ~emu
na Crnu Goru ide oko 11% ukupnog uzorka doma}instava u zajednici Srbija i Crna Gora. Sva
doma}instva su dio stalnog stanovni{tva. Drugi izvor informacija za mjerenje siroma{tva je
istra`ivanje pojedinaca i doma}instava koje je sprovela OCHA kancelarija u Podgorici, a koje je
implementirano tokom juna 2000. godine (OCHA, 2000). Veli~ina uzorka istra`ivanja je bila 2000
doma}instava stalne populacije, koja su odabrana slu~ajnom metodom i u proporciji koja je u
skladu sa naseljeno{}u u svim crnogorskim op{tinama. Na kraju, tre}i izvor podataka su ~etiri
UNDP istra`ivanja doma}instava koja su realizovana u periodu od septembra 2000. godine do
marta 2001. godine (dakle, svaka dva mjeseca po jedno istra`ivanje) pokrivaju}i slu~ajan uzorak od
2000 doma}instava iz svih crnogorskih oop{tina (UNDP, 2001). Iako postoje mnoge zajedni~ke
karakteristike navedenih studija siroma{tva i ove analize, rezultati dobijeni kori{}enjem ISSP HHS
nisu uporedivi sa prethodnim studijama siroma{tva iz vi{e razloga.
Osnova za odre|ivanje uzorka za ISSP Istra`ivanje o prihodima i rashodima doma}instava je bila
lista punoljetnih stanovnika Crne Gore iz 2002. godine, dok su prethodne studije odre|ivale uzorak
na osnovu popisa stanovni{tva iz 1991. godine. Dalje, veli~ina uzorka SZS istra`ivanja (380) je
nedovoljna za regionalnu statistiku, a vjerovatno i za nacionalnu. Upitnik ISSP Istra`ivanja o
prihodima i rashodima doma}instava obuhvata detaljne sekcije koje se odnose na potro{nju, kao i
niz drugih tema (npr. informacije o migraciji, uslovi stanovanja, vlasni{tvo nad trajnim potro{nim
dobrima, prihodi od rada i koji nisu od rada uklju~uju}i pomo} iz socijalnih programa i privatne
transfere, karakteristike zaposlenosti, kori{}enje zdravstvene za{tite i subjektivne ocjene
blagostanja). U pore|enju sa navedenim, ADP upitnik je kreiran prije deset godina i uklju~uje
manje prehrambenih proizvoda. OCHA Istra`ivanje je imalo veoma ograni~en upitnik koji je
sadr`ao jednostavnu korpu prehrambenih artikala (15 proizvoda) plus sredstva li~ne higijene i
higijene doma}instva, dok je UNDP Istra`ivanje postavljalo pitanja o kumulativnim tro{kovima
doma}instava za prethodnih mjesec dana. Razlike u pojedinim listama proizvoda koji se tro{e, kao i
u periodu na koji se potro{nja odnosi, ~ine veoma te{kim upore|ivanje ovih istra`ivanja.
Tre}a razlika u pristupima su indikatori siroma{tva koji su kori{}eni u razli~itim studijama. Ovi
indikatori se razlikuju u zavisnosti od mjere bogatstva (potro{nja/tro{kovi ili prihod) i konstrukcije
linije siroma{tva. Kori{}enjem ISSP Istra`ivanja o prihodima i rashodima doma}instava, na{a mjera
bogatstva je potro{nja (vidjeti Annex 2). Linija siroma{tva u ovoj studiji odre|ena je kao zbir
tro{kova minimalne potro{a~ke korpe hrane za dostizanje standarda nutricionista (linija siroma{tva
hrane) i drugih izdataka doma}instava ~ija je potro{nja hrane jednaka minimalnoj potro{a~koj korpi.
SZS statistika siroma{tva upore|uje prihod doma}instava (bez vrijednosti rente i sa {tednjom) sa
zvani~nom minimalnom potro{a~kom korpom, koja je linija siroma{tva hrane. OCHA istra`ivanje
koristi zvani~nu SZS liniju siroma{tva hrane i liniju siroma{tva zasnovanu na “OCHA Podgorica
potro{a~koj korpi” koja je izvedena iz tro{kova za samo 15 prehrambenih proizvoda, tro{kova za
higijenske proizvode i ograni~enih tro{kova struje, grijanja, obrazovanja i ljekova. UNDP studija
koristi vi{estruke indikatore siroma{tva, uklju~uju}i u~e{}e tro{kova hrane, odnos prihodi-tro{kovi,
prihod po ~lanu do ispod 100 DEM26, i tro{kovi doma}instva ispod 150 DEM. Granica od 100 DEM
je odabrana na osnovu OCHA izvje{taja.
Brojne razlike u kreiranju uzorka, izgledu upitnika i indikatorima siroma{tva dovode nas do
zaklju~ka da indikatori siroma{tva iz ove studije nisu uporedivi sa rezultatima iz pro{lih godina. U
ovoj studiji, tamo gdje je bilo od koristi, izvr{ena su neka pore|enja; npr. pore|enje djelova bud`eta
koji se odnose na razli~ite kategorije tro{kova. Me|utim, ~ak i ova pore|enja su izvr{ena sa
oprezom zbog razlika u dizajniranju istra`ivanja.
26 1 EUR = 1,95583 DEM.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
70
Siroma{tvo definisano preko potro{nje doma}instava
Tabela 3 prikazuje stope siroma{tva za Crnu Goru i po regionima na osnovu pore|enja potro{nje sa
utvr|enim minimalnim nivoom `ivotnog standardima (linijom siroma{tva). Tabela pokazuje da
siroma{tvo definisano preko potro{nje doma}instava poga|a prili~no velik dio populacije: 9,4%
stanovni{tva `ivi ispod apsolutne linije siroma{tva. Ova brojka je vjerovatno potcijenjena jer uzorak
nije obuhvatio neke od najugro`enijih grupa stanovni{tva (npr. Romi i raseljena lica). Siroma{tvo je
najni`e u centralnom i ju`nom dijelu Republike i znatno vi{e me|u stanovni{tvom sjevernog
regiona koji je manje naseljen i manje razvijen. Statisti~ke procjene dobijene na osnovu bilo kog
istra`ivanja na osnovu uzorka imaju odre|en nivo preciznosti. Pored izra~unate stope siroma{tva,
tabela 3 tako|e sadr`i i interval povjerenja od 95% za svaku procijenjenu veli~inu. Dok se intervali
povjerenja za stopu siroma{tva u centralnom i ju`nom regionu preklapaju, interval povjerenja za
stopu siroma{tva na sjeveru (14,9%) je statisti~ki iznad nivoa registrovanog siroma{tva u
centralnom i ju`nom regionu. Na kraju, vi{e od polovine siroma{nog stanovni{tva `ivi na sjeveru
(54%). Jedna tre}ina siroma{nih `ivi u centralnom dijelu, dok najmanji dio siroma{nih `ivi u
ju`nom regionu (16%).27
Pored ra~unanja stope siroma{tva, procijenili smo i dio populacije za koju se mo`e re}i da je
ekonomski ugro`ena, odnosno da materijalno nije obezbije|ena. Ovo je ura|eno tako {to je linija
siroma{tva pove}ana za 50%. Jedna tre}ina stanovni{tva `ivi ispod ovako definisane “vi{e” linije
siroma{tva. Ponovo, stopa siroma{tva na sjeveru Republike, 45%, je zna~ajno viso~ija nego u
ostalim regionima.
Da bi naglasili kompleksne distributivne aspekte siroma{tva, prikazali smo dodatne mjere dubine
(mjerene kao jaz siroma{tva) i o{trinu siroma{tva. Dubina siroma{tva pokazuje odnos prosje~nih
sredstava doma}instava i linije siroma{tva. Ukoliko ovaj odnos opada, dubina siroma{tva raste. Jaz
siroma{tva iznosi 1,3%, {to zna~i da ako bi Crna Gora mogla da mobili{e resurse u vrijednosti od
1,3% linije siroma{tva za svakog pojedinca (za siroma{ne i nesiroma{ne) koji bi bili direktno dati
siroma{nima, sve siroma{ne osobe bi bile “izbavljene” iz siroma{tva. Naravno, ovo pod
pretpostavkom da siroma{ni mogu biti perfektno ciljani. Ukupan jaz siroma{tva je oko 1% GDP-a.
Prate}i indikator - prosje~ni deficit - pokazuje da je potro{nja siroma{nih, u prosjeku, 14% ispod
linije siroma{tva.
O{trina siroma{tva je mjera koja je u bliskoj vezi sa jazom siroma{tva koja daje onima koji su dalje
od linije siroma{tva – najsiroma{nijima – ve}u “te`inu” u skupu nego onima koji su bli`i liniji
siroma{tva. Njen nivo u Crnoj Gori je 0,3. Sjever, koji karakteri{e visoka stopa siroma{tva, tako|e
ima i ve}u dubinu i o{trinu siroma{tva. Da sumiramo, ovi podaci govore da dubina i o{trina
siroma{tva nisu ekstremne. Naprotiv, u pore|enju sa drugim zemljama ove veli~ine su relativno
male pa prema tome ukazuju da bi adekvatan socijalni program mogao da popuni jaz
ako
bi se
obezbijedila dobra targetiranost.
Alternativne mjere siroma{tva definisanog preko potro{nje doma}instava prikazane u tabeli 4
pokazuju da 4% stanovni{tva `ivi u doma}instvima sa ukupnim tro{kovima ispod vrijednosti
minimalne potro{a~ke korpe hrane, ukazuju}i da ne postoji mjerljivo ekstremno siroma{tvo.28 Ipak,
vi{e od tre}ine stanovni{tva je ekonomski ugro`eno ili materijalno nedovoljno obezbije|eno, sa
potro{njom na nivou ispod 150% linije siroma{tva.
27 Kao dodatak regionalnoj perspektivi, podjela urbano/ruralno zna~ajno bi doprinijela poja{njavanju situacije. Iako
podaci iz istra`ivanja ne povezuju doma}instva eksplicitno sa vrstom lokacije (urbano/ruralno) onako kako je to
definisano u Saveznom zavodu za statistiku, u ovoj studiji, kao jedna od kovarijansi za odra`avanje nekih od
urbano/ruralnih dimenzija kori{}ena je varijabla koja govori o tome da li doma}instvo posjeduje poljoprivredno
zemlji{te.
28 Ovdje treba imati u vidu da uzorak za Crnu Goru nije obuhvatio populaciju Roma i raseljenih lica sa Kosova.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
71
Tabela 3: Stope siroma{tva
Crna Gora Sjever Centar Jug
Stopa siroma{tva: Indeks siroma{tva 9,4 14,9 6,5 6,8
interval povjerenja 95% (7,5-11,3) (10,9-18,9) (4,1-8,9) (3,3-10,3)
Ekonomska i ugro`enost siroma{tvom: Glavni
ra~un 36,4 44,8 33,2 29,8
interval povjerenja 95% (33,5-39,4) (39,6-50,0) (28,8-37,6) (23,8-35,8)
Procenat svih siroma{nih 100,0 54,0 30,5 15,5
Jaz siroma{tva 1,3 2,2 0,9 0,7
interval povjerenja 95% (0,9-1,6) (1,4-2,9) (0,5-1,3) (0,3-1,2)
O{trina siroma{tva 0,3 0,5 0,2 0,1
interval povjerenja 95% (0,2-0,4) (0,3-0,8) (0,1-0,3) (0,03-0,2)
Prosje~an deficit siroma{nih kao procenat linije
siroma{tva 14,0 14,8 14,1 11,2
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6. Napomena: standardne gre{ke procjena su u zagradama.
Oko petine doma}instava tro{i vi{e od 60% svojih resursa na hranu. Ova doma}instva su
koncentrisana na sjeveru, gdje se ve}i dio ukupnih izdataka izdvaja za hranu – vi{e od polovine u
prosjeku – nego {to je udio tro{kova hrane u bud`etu doma}instava u centralnom i ju`nom regionu
(vidjeti grafik 4)29. Ve}a izdvajanja iz mjese~nog bud`eta doma}instva za hranu, u skladu su sa
ve}om stopom siroma{tva u sjevernom regionu Crne Gore.
Grafik 4: Struktura potro{nje doma}instava
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Crna Gora Sjev er Centar Jug
Procent
renta
ost. god. tr.
obrazovanje
ost. kvart. tr.
zdravlje
odje}a
namje{ taj
ost. mjes~ni tr.
transposrt
komunalije
li~na potro{nja
hrana
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6. Napomena: pogledati Annex 2 za
definicije pojedinih kategorija.
29 Tako|e, UNDP studija (2001), koja daje obrazac podataka o potro{nji za 2001. godinu, ukazuje na to da doma}instva
na sjeveru vi{e izdvajaju za hranu. Udio hrane izra~unat za crnogorska doma}instva je bio ni`i u OCHA studiji (2000),
oko 40%. Procenat tro{kova doma}instva koji se odnose na hranu (oko 50% u prosjeku) je isti u Srbiji) vidjeti Krsti},
2003).
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
72
Tabela 4: Alternativne mjere siroma{tva definisanog preko potro{nje doma}instava
% stanovni{tva
Apsolutno siroma{tvo:
Potro{nja/tro{kovi ispod apsolutne linije siroma{tva
(107 eura mjese~no po osobi) 9,4
Ekonomska ugro`enost i apsolutno siroma{tvo:
Potro{nja/tro{kovi ispod
apsolutne linije siroma{tva +50%
(160,5 eura mjese~no po osobi) 36,4
Relativno siroma{tvo:
Potro{nja/tro{kovi ispod relativne linije siroma{tva
(50% srednje potro{nje: 105 eura mjese~no po osobi) 9,1
Ekstremno siroma{ni:
Izdaci za hranu < Linija siroma{tva hrane 4,0
Udio izdataka za hranu > 0,6 23,5
Tro{kovi doma}instva/prosje~ni tro{kovi < 0,5 8,2
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6.
Po{to siroma{tvo nije veoma duboko (vidjeti tabelu 3), mo`emo o~ekivati da bi male promjene u
liniji siroma{tva mogle imati zna~ajan uticaj na dio stanovni{tva koji `ivi ispod definisane linije
siroma{tva. Efekat koji promjena u liniji siroma{tva ima na stopu siroma{tva prikazan je na grafiku
5. Ovaj grafik pokazuje da porast linije siroma{tva zna~ajno pove}ava procenat siroma{nih.
Pove}anje linije siroma{tva za 20% dovodi do porasta stope siroma{tva od 100% na nacionalnom
nivou. Imaju}i u vidu regionalne razlike, rast date linije siroma{tva od 20% rezultira porastom stope
siroma{tva na sjeveru za oko 90%, u centralnom dijelu za skoro 130% i za skoro 70% u ju`nom
dijelu Crne Gore.
Grafik 6 prikazuje kumulativnu distribuciju tro{kova po stanovniku (
per capita
) po regionima.
Imaju}i u vidu, kao {to se na grafiku vidi, da se tri krive ne ukr{taju bez obzira na odabir nivoa
linije siroma{tva, stopa siroma{tva na sjeveru Crne Gore je uvijek ve}a nego u centralnom i ju`nom
dijelu Republike.
Grafik 5: Kriva opsega siroma{tva
0
10
20
30
40
50
60
70
80
90
50 75 100 125 150 175 200 225 250 275 300 325 350 375
Linija siroma{tva
Stopa siroma{tva
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
73
Grafik 6: Kumulativna distribucija
per capita
tri{kova po regionima, 2002
Probabi lity <= PCE
Per Capita Monthly expenditure
Nor th Center
South
50 100 200 300 400 500 600 700 800
0
.2
.4
.6
.8
1
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6.
Ostali indikatori siroma{tva
Dok ovaj izvje{taj uglavnom mjeri siroma{tvo na osnovu potro{nje doma}instava, siroma{tvo je
vi{edimenzionalan koncept koji obuhvata brojne aspekte blagostanja. Razli~iti aspekti siroma{tva –
potro{a~ki i nepotro{a~ki – uti~u i poja~avaju jedni druge na na~in da pogor{avaju probleme sa
kojima se siroma{ni suo~avaju. Ote`an pristup zdravstvenim uslugama i neadekvatnost sistema
obrazovanja ne samo da smanjuju blagostanje, ve} i ograni~avaju zarade od prihoda i potencijal
potro{nje. Identifikovanje razli~itih dimenzija siroma{tva je va`no u kontekstu razumijevanja
profila ugro`enih grupa. Doma}instva koja nisu prihodno/potro{a~ki siroma{na mogu i pored toga
biti siroma{na u drugim dimenzijama. Naime, neka doma}instva mogu patiti od vi{estrukog
siroma{tva i tako ~initi “sr`” siroma{nih. Tabela 5 prikazuje nekoliko takvih indikatora.
Oko 5% odraslih u Crnoj Gori mogu se smatrati siroma{nim u pogledu obrazovanja, {to zna~i da
trenutno ne idu u {kolu i nisu poha|ali srednju {kolu. Kada se radi o obrazovanju, zna~ajniji izazov
u Crnoj Gori nije nastavak {kolovanja nakon zavr{ene osnovne {kole, ve} prije kvalitet {kolstva i
mjera u kojoj vje{tine ste~ene tokom obrazovanja odgovaraju zahtjevima za radnom snagom u
ekonomiji. Sistem obrazovanja je bio kreiran da udovolji potrebe za radnom snagom u
predtranzicionom periodu. Pored zastarjelog nastavnog plana, postoje}i obrazovni sistem u Crnoj
Gori karakteri{e i neefikasnost sistema u zavisnosti od lokacije; na primjer, u gradskim obrazovnim
institucijama imamo problem prevelikog broja u~enika, dok su ruralni regioni nedovoljno
iskori{}eni.
S
j
ever Centar
Ju
g
Per ca
p
ita m
j
ese~ni tro{kovi
V
j
erovatno}a <=PCE
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
74
Tabela 5: Vi{edimenzionalni indikatori siroma{tva
Indikatori %
stanovni{tv
a
% siroma{nog
stanovni{tva
(indikator
potro{nje)
Siroma{tvo definisano na osnovu potro{nje doma}instava
apsolutno siroma{tvo
ekonomski ugro`eni
9,4
36,4
Siroma{tvo u pogledu obrazovanja
16-24 godina: nisu u {koli i nisu poha|ali srednju {kolu
4,7
13,5
Zdravstveno siroma{tvo
bilo koja bolest/povreda u poslednjih 30 dana koja je sprije~ila ili
onemogu}ila uobi~ajenu aktivnost
6,4
6,1
Siroma{tvo u pogledu zaposlenosti
16-65 godina: ne radi, ali je spreman(a) da radi ukoliko se uka`e
prilika za zaposlenje
22,0
40,3
Barem jedan ~lan doma}instva starosti 16-65 godina koji ne radi
ali je spreman/a da radi ukoliko se uka`e prilika za zaposlenje
40,2
62,1
Siroma{tvo u pogledu uslova stanovanja
Izvor pija}e vode u stanu/ku}i nije vodovodna mre`a ili stan/ku}a
nema kupatilo*
13,1
25,0
Manje od 10m² po osobi u stanu/ku}i 8,2 22,7
Nedostatak ku}nih aparata
Bez telefona 9,7 14,6
Bez TV prijemnika 3,7 5,7
Bez ve{ ma{ine 7,8 22,7
Izvor: ISSP Istra`ivanje o prihodimai rashodima doma}instava 5 i 6.
*Smje{taj – samo podaci iz Istra`ivanja #6 (pitanje o vodosnabdijevanju nije bilo obuhva}eno Istra`ivanjem 5)
Pokazatelj siroma{tva kada je u pitanju zdravstveno stanje gra|ana, mjeren bole{}u/povredom u
posljednjih 30 dana koja je sprije~ila ili onemogu}ila uobi~ajenu aktivnost, iznosi 6%. Preko 22%
radno sposobnih odraslih osoba su siroma{ni u pogledu zaposlenja, {to je definisano kao situacija
kada osoba ne radi ali je spremna da radi ukoliko se uka`e prilika za posao. Kreiranje mogu}nosti
za zaposlenje ostaje izazov za Vladu. Raniji programi su ciljali na smanjenje suvi{ne radne snage
kroz otpremnine i rano penzionisanje; noviji napori uklju~uju pove}anje izvora kredita za
nezaposlene za zapo~injanje biznisa, a smanjen je i porez na zarade novozaposlenih. Kao dodatak
ovom programu, Zavod za zapo{ljavanje i me|unarodne organizacije anga`ovani su na kreiranju
obuke za nezaposlene (npr. program pripreme za radno mjesto, obuka za poznatog poslodavca i
priprema za tr`i{te rada30). I pored toga, jedna od pet odraslih osoba u najboljim godinama, nisu u
mogu}nosti da na|u posao.
Uslovi stanovanja za 13% populacije su ispod standarda kada se u obzir uzmu izvor vode i
postojanje kupatila u prostor za stanovanje; 8% stanovni{tva `ivi u stanu/ku}i koje ima manje od
10m2 po osobi. U uzorku imamo i jedno doma}instvo koje nema struju, dok oko 10% populacije
nema telefon.
Druga kolona tabele 5 prikazuje stope indikatora siroma{tva za populaciju koja `ivi ispod linije
siroma{tva definisane na osnovu potro{nje doma}instava. Namjera je da se poka`e do koje mjere se
ovaj indikator poklapa za mjerama nepotro{a~kog siroma{tva. Dok su neki od ovih indikatora sli~ni
30 Izvor: Zavod za zapo{ljavanje Crne Gore
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
75
stopi siroma{tva definisanoj na osnovu potro{nje, postoji samo djelimi~no preklapanje izme|u
siroma{nih po osnovu potro{nje i onih koji su siroma{ni po osnovu drugih kriterijuma nevedenih u
tabeli. Ipak, za ve}inu indikatora stopa je mnogo ve}a me|u siroma{nima u pogledu potro{nje,
pogotovo kada se u obzir uzmu karakteristike smje{taja i zaposlenost.
BOX 1: Siroma{tvo koje niko ne `eli da ga primjeti: “Nezvani~ni” smje{taj Roma u Crnoj Gori.
Oko 90 osoba iz 20 romskih porodica, uglavnom raseljenih sa Kosova i trenutno smje{tenih u
Lovanji, svakog dana se bore da pre`ive. Lovanja se nalazi u Tivatskom polju, na teritoriji op{tine
Kotor, na prelijepoj crnogorskoj obali Jadranskog mora. Romi u Lovanji `ive na ivici lokalne
deponije u “podstandardnim” uslovima stanovanja u samoniklim barakama. Ovo naselje nema teku}u
vodu (vodu sa ~esme), struju i u opasnosti je od poplavljivanja u slu~aju velikih ki{a. Najbli`a
zdravstvena ustanova je u Kotoru, oko 8 km od naselja, i ne postoji veza javnog saobra}aja. Lokalne
vlasti su, navodno, 1999. godine odlu~ile da premjeste naselje u neko humanije okru`enje, ali se do
dana{njeg dana po tom pitanju ni{ta nije dogodilo.
Romi u ovom naselju `ive u ekstremnom siroma{tvu. Oko jedne polovine stanovnika imaju manje od
18 godina, i nijedno dijete ne ide u {kolu. Romi iz Lovanje zaradjuju za `ivot tako {to sakupljaju
otpadni materijal, i povremeno obavljaju neki manuelni posao koji se pla}a po satu rada. Prema
Sekretarijatu za raseljena lica u Crnoj Gori, Lovanja se karakteri{e kao “nezvani~ni centar za
raseljena lica”. Broj ovih nezvani~nih kampova daleko prevazilazi broj zvani~nih, i obezbjedjuje
samonikla privremena skloni{ta za ve}inu od procijenjih 20.000 Roma, raseljenih lica sa Kosova koji
se nalaze u Crnoj Gori.
Izvor: Evropski centar za prava Roma (ERRC), citat iz tivatske NVO “MARGO”- Asocijacija za
pomo} i podr{ku marginalnim dru{tvenim grupama, vidjeti:
http://errc.org/publications/letters/2002/montenegro_jan_10_2002.shtml
III. NEJEDNAKOST
Mjerenje nejednakosti je interesantno jer nam mo`e pomo}i da razumijemo kako se efekti rasta
distribuiraju u vremenu. Rast koji nastaje uglavnom u vrhu distribucije dohotka mo`e malo da u~ini
za unaprije|enje `ivotnog standarda siroma{nih; posljedica ovakve situacije je pove}anje
nejednakosti. Realizacija ekonomskih reformi u Crnoj Gori zabrinjava jer je za o~ekivati da }e do}i
do pove}anja nejednakosti, posebno kada se ima u vidu prelazak sa formalne na neformalnu
zaposlenost. S obzirom da ne postoje raspolo`ivi adekvatni podaci, za period prije 2002. godine,
nejednakost u Crnoj Gori mjerenu na osnovu indikatora potro{nje mo`emo porediti samo sa
nejednako{}u u ostalim zemljema u regionu.31
Postoji nekoliko na~ina za prikazivanje nejednakosti u potro{nji (za vi{e detalja o indikatorima
kori{tenim u ovoj studiji, vidjeti Annex 4). Grafik 7 predstavlja Lorencovu krivu za
per capita
potro{nju u Crnoj Gori. Kriva odslikava kumulativnu frekvenciju
per capita
potro{nje u odnosu na
jednoobraznu distribuciju (koja predstavlja perfektnu jednakost u potro{nji). Ovaj odnos mo`e biti
sumiran Gini koeficijentom.32 Druga {iroko kori{}ena mjera nejednakosti je decil odnos (90/10
koli~nik), koji predstavlja koli~nik prosje~ne potro{nje 10% najbogatijeg stanovni{tva i prosje~ne
potro{nje 10% najsiroma{nijih. Ova mjera vjerovatno bolje odra`ava relativnu poziciju
31 Iako ne postoje podaci o nejednakosti u Crnoj Gori ra~unatoj na osnovu indikatora potro{nje za godine prije 2002.,
postoje podaci za Srbiju i Crnu Goru iz Istra`ivanja o bud`etu doma}instava i Istra`ivanja o tr`i{tu rada (nejednakost u
prihodima). Ovi izvori podataka sugeri{u da se uprkos percepciji problema u Srbiji i Crnoj Gori i iskustvima drugih
ekonomija u tranziciji, nejednakost nije zna~ajno promijenila.
32 Gini koeficijent se ra~una kao povr{ina izme|u krivih podijeljena sa povr{inom ispod linije jednakosti. Ve}i Gini
zna~i ve}u nejednakost. Ako je Gini 0, imamo perfektnu jednakost (koja je predstavljena dijagonalnom linijom na
grafiku Lorencove krive).
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
76
najsiroma{nijih u populaciji nego {to je to slu~aj sa Gini koeficijentom, koji mo`e biti te`ak za
interpretaciju u cilju dono{enja zaklju~ka o siroma{nima i siroma{tvu. U tom smislu, decil odnos
(90/10 koli~nik) mo`e biti bolji indikator za monitoring nejednakosti i smanjenje siroma{tva u
Crnoj Gori. Statisti~ki podaci su prikazani u tabeli 6.
Gini koeficijent u Crnoj Gori iznosi 0,29, bez statisti~ki zna~ajne razlike u ovom indikatoru
nejednakosti me|u regionima. Nejednakost u Crnoj Gori je na nivou nejednakosti u drugim
isto~noevropskim zemljama u tranziciji. Me|u susjednim dr`avama, neke imaju ni`i nivo
nejednakosti (npr. Albanija, Bugarska, Ma|arska i Slovenija) dok druge imaju ve}u nejednakost
(Hrvatska, Makedonija i Estonija). Gini koeficijenti za Crnu Goru i Srbiju su prili~no blizu.
Alternativa nejednakosti ra~unatoj na osnovu potro{nje je nejednakost u prihodu, koja je generalno
posmatrano ve}a od nejednakosti u potro{nji za sve zemlje regiona. Nejednakost u prihodima u
Crnoj Gori je me|u najve}im u regionu (Gini koeficijent iznosi 0,37) dok je u Srbiji nejednakost u
prihodu manja (0,33) i nalazi se negdje oko prosjeka regiona (Milanovi}, 2003). Zbog ograni~enja u
mjerenju prihoda, imaju}i u vidu veli~inu neformalnog sektora i zarada sezonske radne snage,
rezultati mjerenja nejednakosti u prihodima treba da budu interpretirani sa oprezom.
Sa druge strane, koli~nik 90/10 pokazuje da je nivo nejednakosti u Crnoj Gori izuzetno visok u
odnosu na druge dr`ave; jedino je u Srbiji nivo nejednakosti ve}i (5,8 i 6,7 respektivno). Ovo je
bli`e nivou veoma nejednakih ekonomija gdje je koli~nik mo`e iznositi do 7.
Grafik 7: Lorencova kriva
cumulative proportion of pce
Lorenz curve
cumulative proportion of sample
_perc _share
0.25 .5 .75 1
0
.25
.5
.75
1
IV. PROFIL SIROMA[TVA
Ovaj dio studije opisuje karakteristike siroma{nih i ispituje uzajamne veze siroma{tva u Crnoj Gori.
Prou~avanjem rizika siroma{tva za razli~ite grupe stanovni{tva kao i za djelove stanovni{tva koji
pripadaju razli~itim grupama, nadamo se da }emo dobiti uvid u to kako razviti efikasnu strategiju
smanjenja siroma{tva.
Tabela 7 prikazuje stope siroma{tva za sedam razli~itih kategorija stanovni{tva. Ova tabela otkriva
nekoliko interesantnih stvari. Prvo, postoji nekoliko grupa za koje je rizik siroma{tva iznad
nacionalnog prosjeka.
Kumulativno u~e{}e uzorka
Kumulativno u~e{}e
p
ce
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
77
Tabela 6: Pore|enje potro{a~ke nejednakosti
Dr`ava Gini koeficijent 90/10
koli~nik
Bosna i Hercegovina, 2001 0,26 3,3
Albanija, 2002 0,28 3,6
Ma|arska, 1997 0,28 3,5
Srbija, 2002 0,28 6,7
Slovenija, 1997/1998 0,28 3,7
Crna Gora, 2002 0,29 5,8
Bugarska, 2001 0,30 4,1
Hrvatska, 1998 0,30 3,9
Makedonija, 2000 0,31 4,3
Estonija, 1998 0,38 5,4
Napomene: Statisti~ki podaci za Bosnu su iz Svjetske banke (2002b); za Albaniju iz
Svjetske banke (2002a); Ma|arsku, Sloveniju, i Estoniju iz Svjetske banke (2000);
Srbiju od Milanovi}a (2003); za Bugarsku iz Svjetske banke (2002c); za Hrvatsku
od Luttmer (2002); za Makedoniju iz procjena na osnovu HBS podataka za 2000.
god.; za Crnu Goru iz ISSP HHS 5 i 6.
Drugo, iako je rizik visok, va`no je razmotriti dio stanovni{tva koji pripada grupi i udio grupe
visokog rizika u ukupnom broju siroma{nih. Na kraju, tabela otkriva grupe koje uprkos uobi~ajenom
vjerovanju ne spadaju u siroma{ne.
Osobe u velikim doma}instvima imaju vi{i rizik potpadanja u siroma{tvo nego oni koji `ive u
manjim doma}instvima. Nedostatak obrazovanja glave doma}instva je povezan se ve}im rizikom
siroma{tva. Ljudi iz doma}instava ~ije starje{ine nisu poha|ale srednju {kolu imaju rizik potpadanja
ispod linije siroma{tva tri puta ve}i od onih koji `ive u doma}instvu ~ija glava ima neko srednje
obrazovanje. Ipak, prva grupa predstavlja samo 17% populacije. Prema tome, ve}ina siroma{nih
(65%) `ivi u doma}instvima ~ije glave imaju neko srednje obrazovanje.
Status zaposlenosti je povezan sa rizikom siroma{tva. Doma}instva na ~ijem ~elu su oni koji ne rade
i nisu penzionisani imaju najve}i rizik siroma{tva (19%). Zaposlena glava doma}instva po pravilu
zna~i i ni`i rizik potpadanja ispod linije siroma{tva (7%).
Vlasni{tvo nad poljoprivrednom zemljom nije u vezi sa pove}anjem rizika od siroma{tva. Dok jedna
tre}ina doma}instava posjeduje neku poljoprivrednu zemlju, treba primijetiti da je samo 5%
starje{ina doma}instava uklju~eno u obavljanje aktivnosti koju obuhvata poljoprivredni sektor
(uklju~uju}i ribarstvo).
Migracija je u vezi sa ni`im rizikom siroma{tva. Doma}instva ~ije su starje{ine ro|ene van Crne
Gore imaju ni`e stope siroma{tva (ispod 4%) nego ona ~ije su starje{ine ro|ene u Crnoj Gori (11%),
bez obzira {to je u prethodnoj kategoriji samo nekoliko doma}instava (8% od svih doma}instava).
Postoji nekoliko grupa koje, uprkos uobi~ajenom vjerovanju, nisu siroma{nije od prosjeka. Prva od
ovih konvencionalno siroma{nih grupa su starije osobe. Nije vjerovatnije da stariji `ive u
siroma{nim doma}instvima (isto tako, osobe koje `ive u doma}instivma ~ije glave su osobe starije
od 50 godine, nemaju ve}u vjerovatno}u potpadanja ispod linije siroma{tva). Slede}a grupa su
djeca. Ako razmotrimo stope siroma{tva po starosnim grupama, uvi|amo da djeca ispod 16 godina
starosti imaju malo ve}u vjerovatno}u da budu siroma{na u pore|enju sa drugim starosnim grupama,
ali ta razlika je neznatna. Tako|e, nema zna~ajne razlike u stopama siroma{tva me|u pojedincima iz
starosnih grupa “16-24”, “25-49” i “65+”. Drugim rije~ima, mo`emo re}i da je siroma{tvo prakti~no
jednako distribuirano me|u stanovni{tvom posmatraju}i njihovu starost. Iako je u manje od 10%
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
78
slu~ajeva na ~elu doma}instva `ena, ~lanovi tih doma}instava imaju ve}e izglede da budu
siroma{ni.
Tabela 7: Profil siroma{tva: stope siroma{tva po grupama
%
stanovni{tva
% koji su
siroma{ni
% od
siroma{nih
Po veli~ini doma}instva
1-3 ~lana 24,2 2,2 (0,7) 5,7
4+ ~lanova 75,8 11,7 (1,2) 94,3
Po starosti glave doma}instva
manje od 50 godina 42,1 8,3 (1,3) 36,9
50-64 godina 41,5 9,0 (1,5) 39,6
65+ godina 16,4 13,5 (2,9) 23,5
Po polu glave doma}instva
mu{ki 90,3 9,2 (1,0) 88,3
`enski 9,7 11,4 (3,2) 11,7
Po obrazovanju glave doma}instva
osnovno 16,6 20,6 (3,4) 36,2
djelimi~no zavr{ena ili zavr{ena
srednja {kola
83,4 7,2 (0,9)
63,8
Po statusu zaposlenosti glave doma}instva
*
Nezaposlen i nepenzionisan 9,8 18,6 (4,4) 19,3
Zaposlen 62,4 6,5 (1,0) 43,5
Penzionisan i nezaposlen 27,8 12,1 (2,1) 37,2
Po vlasni{tvu doma}instva nad
poljoprivrednom zemljom
Bez poljoprivrednog zemlji{ta 66,3 9,0 (1,1) 64,2
Sa poljoprivrednim zemlji{tem 33,7 9,9 (1,8) 35,8
Po starosti
manje od 16 godina 17,6 12,4 (1,1) 23,1
16-24 godina 19,3 9,2 (0,9) 18,9
25-49 godina 35,8 9,7 (0,7) 36,7
50-64 godina 18,7 6,6 (0,8) 13,1
65+ godina 8,6 9,1 (1,4) 8,3
Mjesto ro|enja glave porodice**
Crna Gora 91,8 11,0 (1,4) 97,2
Srbija*** 3,5 3,7 (3,6) 1,3
Ostalo 4,7 3,4 (3,3) 1,5
Trenutna lokacija u Crnoj Gori ako je glava
doma}instva ro|ena u CG
Ista op{tina kao rodna 83,0 11,2 (1,5) 84,6
Druga op{tina 17,0 9,2 (3,0) 15,4
Izvor: Istra`ivanje o prihodima i rashodima doma}instava 5 i 6. Napomena: Standardne gre{ke su u zagradama; interval
povjerenja od 95% je pribli`no ±2 standardne gre{ke. *Zaposleni se defini{e kao neko ko je radio za prihod protekle
sedmice ili ima regularni posao ali nije radio pro{le sedmice (odmor, bolovanje, itd.); “penzionisani” su oni koji nisu
zaposleni i defini{u sami sebe kao penzionere u okviru primarne aktivnosti; “nezaposleni” su svi ostali. **Podaci o
migraciji su iz istra`ivanja #6; pitanje nije postavljano u istra`ivanju #5. *** Kosovo je obuhva}eno pod “ostalo”.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
79
V. FAKTORI KOJI UTI^U NA SIROMA[TVO U CRNOJ GORI
U ovom dijelu se bavimo faktorima koji uti~u na `ivotni standard i siroma{tvo istovremenim
kontrolisanjem razli~itih karakteristika. Identifikovanje ovih faktora mo`e biti veoma va`no za
kreiranje socijalne politike za smanjenje siroma{tva. To {iri rezultate iz prethodnog dijela jer te`i da
uspostavi i objasni korelaciju me|u karakteristikama. Na primjer, ostaje da se ocijeni u kojoj mjeri
se ve}i nivo siroma{tva na sjeveru mo`e “objasniti” karakteristikama glave doma}instva. Ova
kratka analiza ukazuje na faktore koji su u vezi sa siroma{tvom, me|utim, ona ne govori i o
uzro~nosti. Faktori koje izu~avamo uklju~uju: karakteristike doma}instava (starost, obrazovanje i
pol glave doma}instva, veli~ina doma}instva i demografska kompozicija), ekonomsku aktivnost
odraslih, vlasni{tvo nad poljoprivrednom zemljom i lokaciju. Ovi faktori su kori{}eni kao
obja{njavaju}e varijable u prostom regresionom modelu, sa tro{kovima po stanovniku (pce) kao
zavisnom varijablom. Tabela 8 prikazuje procjenu koeficijenata regresije i odgovaraju}e izra`ene
standardne gre{ke.
Obrazovanje je u direktnoj vezi sa ve}om per capita potro{njom (pce). Djelimi~no zavr{ena ili
zavr{ena srednja {kola glave doma}instva povezana je sa oko 10% vi{om per capita potro{njom u
odnosu na per capita potro{nju ~lanova doma}instava ~iji starje{ina ima zavr{enu samo osnovnu
{kolu. Univerzitetsko obrazovanje glave doma}instva je u vezi sa 29% vi{im pce u pore|enju sa per
capita potro{njom doma}instava ~ije starje{ine nemaju nikakvog ili imaju samo osnovno
obrazovanje. Zaklju~ujemo da doma}instva ~ije starje{ine imaju vi{e obrazovanje imaju manju
vjerovatno}u da budu siroma{na, iako obrazovanje starje{ine doma}instva nije garancija da
doma}instvo ne}e biti siroma{no. Ovo odra`ava neke od izazova sa kojima se susre}e sistem
obrazovanja u Crnoj Gori, uklju~uju}i zastarjeli nastavni plan koji mo`e pogor{ati nesklad sa
zahtjevom za radnom snagom.
Ova konstatacija va`i kada je u pitanju ukupan uzorak, me|utim, postoje interesantne razlike kada
se uporede tri glavna regiona. Pozitivna veza izme|u nivoa per capita potro{nje i djelimi~no
zavr{ene ili zavr{ene srednje {kole je statisti~ki zna~ajna samo u centralnom regionu. Iako je
koeficijent zna~ajan i na nivou od 10%, na jugu i ve}i (13%), obrazovanje starje{ine doma}instva
(djelimi~no zavr{ena ili zavr{ena srednja {kola) kada se uporedi sa referentnom grupom
(doma}instva ~ije su starje{ine zavr{ile samo osnovnu {kolu) nije povezano sa ve}im nivoom per
capita potro{nje na sjeveru. Imaju}i na umu regionalnu komponentu, univerzitetsko obrazovanje
glave doma}instva je povezano sa statisti~ki visokom pre capita potro{njom u svim regionima, ali
je povezanost najve}a u centralnom regionu (37% u pore|enju sa 27% na sjeveru i jugu).
Ekonomska aktivnost odraslih (koja obuhvata formalne i neformalne aktivnosti sticanja prihoda) je
sna`no povezana sa vi{im nivoom per capita potro{nje u pore|enju sa onim doma}instvima koja
nemaju ekonomski aktivne punoljetne osobe. Doma}instva sa najmanje jednom odraslom osobom
koja radi imaju per capita potro{nju 17% ve}u nego {to je ista kod ~lanova doma}instava koja
nemaju punoljetne osobe koje rade. Ponovo uo~avamo interesantne regionalne varijacije: uticaj je
13% na sjeveru, 23% u centralnom dijelu i najve}i je na jugu – 27%.
Na drugoj strani, doma}instva sa najmanje jednom nezaposlenom, nepenzionisanom odraslom
osobom imaju 12% ni`u per capita potro{nju nego ona koja nemaju takvih odraslih. Na sjeveru je
povezanost najsna`nija: doma}instva koja imaju jednu ili vi{e nezaposlenih, nepenzionisanih osoba
imaju 16% ni`i nivo per capita potro{nje. Veza je najmanja na jugu, gdje ovakvi odrasli nisu
statisti~ki povezani sa ni`om per capita potro{njom.
Analiziraju}i demografski sastav doma}instava, ~ini se da ovaj faktor nema zna~ajnog uticaja na
nivo potro{nje po stanovniku. Jedini izuzetak je na jugu gdje doma}instva sa djetetom starim do
{est godina imaju skoro 50% ve}i nivo per capita potro{nje.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
80
Veli~ina doma}instava zna~ajno uti~e na nivo potro{nje. Porast veli~ine doma}instva od 10% je u
vezi sa smanjenjem nivoa per capita potro{nje za 5%. Uslovna korelacija izme|u veli~ine
doma}instva i nivoa per capita potro{nje je najmanja me|u doma}instvima na sjeveru. Za ova
doma}instva, elasti~nost pce u odnosu na veli~inu doma}instva je 0,48, dok je ta elasti~nost na jugu
0,75.
Doma}instva koja posjeduju obradivo zemlji{te imaju znatno ve}i nivo per capita potro{nje; ovaj
efekat je dominantan na sjeveru i u centralnom regionu. Doma}instva na sjeveru koja posjeduju
obradivo zemlji{te imaju 17% ve}i nivo per capita potro{nje; u centralnom regionu vlasni{tvo nad
obradivom zemljom je povezano sa 11% ve}im nivoom per capita potro{nje. Obradivo zemlji{te
nije u vezi sa ve}im nivoom per capita potro{nje kod doma}instava na jugu.
Posmatraju}i karakteristike doma}instava po lokaciji, per capita potro{nja me|u doma}instvima na
jugu Crne Gore i u centralnom dijelu nije statisti~ki zna~ajno razli~ita. Ipak, kontroli{u}i
karakteristike doma}instava, doma}instva sa sjevera Crne Gore imaju 10% ni`i nivo per capita
potro{nje u pore|enju sa ostalim doma}instvima. Prema tome, kontrolisanje ovog skupa
karakteristika doma}instva blago smanjuje jaz izme|u sjevernog i centralnog dijela (koji je oko
15% per capita potro{nje u centralnom dijelu u prosjeku); ipak, zna~ajne razlike u nivou per capita
potro{nje izme|u sjevera i drugih regiona ostaju neobja{njene navedenim setom karakteristika.
Drugi na~in da se objasni veza izme|u lokacije i siroma{tva je da se ocijeni razlika u stopama
siroma{tva me|u stanovni{tvom na sjeveru u pore|enju sa drugim oblastima, sa i bez kontrolisanja
ostalih karakteristika doma}instava. Su{tina rezultata je prikazana na grafiku 8. Ovaj grafik
pokazuje da se ljudi koji `ive na sjeveru suo~avaju sa primjetno ve}im siroma{tvom, ~ak iako
kontroli{emo ostale razlike.
Grafik 8: Stopa siroma{tva na sjeveru u odnosu na stopu siroma{tva na jugu i u centralnom
dijelu: posmatrano i simulirano
0
1
2
3
4
5
6
7
8
9
10
Bez kontrole Kontrola karakteristika
glave doma}instva
Kontrola karakteristika
glave doma}instva i
demografije doma}.
Kontrola karakteristika
glave doma}instva,
demografije doma}. i
zaposlenosti
Vi{e siroma{tvo
(% poeni)
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Institut za strate{ke studije i prognoze, Podgorica, Crna Gora
81
Tabela 8: Regresija logaritma potro{nje po stanovniku po karakteristikama doma}instva
Ukupno Sjever Centralni dio Jug
koeficijent Std. gre{ka. koeficijent t Std. gre{ka. koeficijent Std. gre{ka. koeficijent Std. gre{ka.
Karakteristike glave doma}instva
Starost glave doma}instva: <50 (referentna grupa)
Starost glave doma}instva: 50-64 -0,021 (0,035) 0,014 (0,068) -0,063 (0,051) 0,031 (0,076)
Starost glave doma}instva: 65+ 0,000 (0,051) 0,001 (0,109) -0,061 (0,072) 0,090 (0,105)
Glava doma}instva je `ena -0,051 (0,037) -0,095 (0,066) 0,015 (0,057) -0,145 (0,077)
Obrazovanje glave: <srednje (referentna grupa)
Obrazovanje glave: (ne)zavr{ena srednja {kola 0,105** (0,033) 0,031 (0,053) 0,171** (0,052) 0,133 (0,070)
Obrazovanje glave: zapo~eto/zavr{eno univerzitetsko
obrazovanje 0,298** (0,038) 0,265** (0,072) 0,372** (0,059) 0,269** (0,076)
Ekonomska aktivnost odraslih
Makar jedna zaposlena odrasla osoba 0,165** (0,035) 0,127* (0,054) 0,225** (0,058) 0,268** (0,077)
Makar jedna nezaposlena, nepenzionisana odrasla osoba -0,117** (0,030) -0,161** (0,056) -0,106* (0,047) -0,081 (0,056)
Demografski sastav
# djece 0-6/veli~ina doma}instva -0,191 (0,127) -0,317 (0,213) -0,333 (0,221) 0,494* (0,250)
# djece 7-14/ veli~ina doma}instva -0,130 (0,110) -0,062 (0,199) -0,089 (0,173) -0,053 (0,233)
# djece 15-18/ veli~ina doma}instva -0,006 (0,128) 0,220 (0,268) -0,135 (0,178) 0,129 (0,273)
# odraslih 19-25/ veli~ina doma}instva 0,070 (0,083) -0,032 (0,131) 0,134 (0,139) 0,193 (0,214)
# odraslih 26-45/ veli~ina doma}instva 0,057 (0,069) 0,088 (0,117) 0,001 (0,106) 0,076 (0,149)
# odraslih 46-64/ veli~ina doma}instva (referentna grupa)
# odraslih 65+/ veli~ina doma}instva -0,142 (0,089) -0,181 (0,165) -0,106 (0,128) -0,036 (0,177)
ln (veli~ina doma}instva) -0,537** (0,038) -0,483** (0,063) -0,532** (0,060) -0,745** (0,094)
Doma}instva posjeduju poljoprivredno zemlji{te
0,127** (0,026) 0,173** (0,048) 0,110** (0,037) 0,028 (0,067)
Lokacija
Centar (referentna grupa)
Sjever -0,097** (0,028)
Jug -0,004 (0,030)
konstanta 5,881** (0,065) 5,796** (0,098) 5,797** (0,101) 5,922** (0,140)
R20,353 0,289 0,376 0,404
Broj observacija 1294 427 562 305
Izvor: ISSP Istra`ivanje o prihodimai rashodima doma}instava 5 i 6. Napomene: *ozna~ava zna~aj na 5%, **na 1%.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
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82
VI. IZVORI PODR[KE ZA DOMA]INSTVA
Izvori prihoda
Tabela 9 prikazuje izvore prihoda za doma}instva u Crnoj Gori, prikazuju}i prihod u osam
kategorija; prosje~ni iznosi primanja iz svakog izvora prikazani su u tabeli 10, dok su udjeli
prikazani na grafiku 9.33
Prihod od zarada je naj~e{}i izvor prihoda za sva doma}instva, uklju~uju}i one iznad i one ispod
nivoa prosje~ne per capita potro{nje. U~e{}e prihoda od zarada prema podacima iz ISSP
Istra`ivanja o prihodima i rashodima doma}instava je malo ve}i od procjena Saveznog zavoda za
statistiku (SZS, 2000) koji procjenjuje ovo u~e{}e na oko 45%. U pore|enju sa drugim zemljama u
tranziciji, SRJ je bila ispod prosjeka kada se posmatra u~e{}e zarada u prihodu doma}instva (vidjeti
Svjetska banka, 2000) {to je vjerovatno odraz dare`ljivog plana penzijskog osiguranja i privatnih
transfera. UNDP studija (2001) pokazuje da veliki dio prihoda doma}instva poti~e od zarada
(75%), dijelom zbog isklju~enja privatnih transfera kao izvora prihoda i vjerovatno odra`avaju}i
stvarni fenomen pada realnih zarada nakon promjena cijena.
Izvori prihoda koji ne poti~u od rada mogu biti veoma zna~ajni za odr`avanje odre|enog nivoa
`ivotnog standarda. Dok oko 76% doma}instava prijavljuju neke prihode od zarada, izvori prihoda
koji ne poti~u od rada ostaju va`an izvor podr{ke, pokazuju}i, na jednoj strani, veliko u~e{}e radno
sposobnih koji nemaju zaposlenje, a sa druge strane dare`ljivu penzionu {emu i zna~ajne privatne
transfere. Penzije, naknade za nezaposlene, materijalno obezbje|enje porodice, dje~ji dodatak,
jednokratna pomo} i drugi oblici socijalne pomo}i su programi socijalne politike dizajnirani da
pobolj{aju blagostanje populacije. Penzije su drugi naj~e{}i izvor prihoda koje prima veliki broj
doma}instava, odnosno skoro polovina stanovni{tva. Privatne transfere (od ro|aka iz Crne Gore,
Srbije ili iz inostranstva) je prijavilo oko 20% doma}instava.
Interesantne su {eme izvora prihoda po pojedinim grupama potro{nje. Siroma{nija doma}instva
~e{}e imaju prihode od penzionog programa nego {to je to slu~aj sa bogatijim doma}instvima.
Socijalni transferi su ~e{}i me|u 20% najsiroma{nijeg stanovni{tva. Skoro jedna od deset
najsiroma{nijih osoba (9.2%) `ivi u doma}instvu koje ima prihod od nekog socijalnog transfera, u
pore|enju sa 2% osoba koje `ive u najbogatijim doma}instvima. Bogata doma}instva dva i po puta
~e{}e prijavljuju prihode od imovine ili nekog drugog vlasni{tva, nego {to je to slu~aj sa
najsiroma{nijih 20% stanovnika. Tako|e, oni tri puta ~e{}e prijavljuju prihod od samozaposlenosti
nego najsiroma{niji kvintal34.
Jedno od pet doma}instava prima privatne transfere. Prete`no bogata doma}instva ~e{}e dobijaju
neke privatne transfere. Svega nekoliko doma}instava prijavljuje nadoknadu za nezaposlene, {to je
konzistentno sa drugim izvorima podataka. Prema podacima iz Zavoda za zapo{ljavanje, svega 2,9%
registrovanih nezaposlenih, ve}a grupa nego ona definisana po ILO definiciji, je krajem 2002.
godine primila nadoknade za nezaposlene.
33 Nadnice, zarade od samozaposlenja, penzije (starosne, invalidske, porodi~ne i inostrane), stipendije, nadoknade za
nezaposlene, materijalno obezbje|enje porodice, dje~ji dodatak, nov~ana i robna primanja od nevladinih organizacija i
privatni transferi su prijavljivani za poslednji mjesec. Prihod od jednokratne pomo}i, druge li~ne pomo}i i ostali
socijalni programi su prijavljivani za poslednjih {est mjeseci. Prihod od imovine je prijavljivan za poslednjih 12
mjeseci.
34 Kvintal ozna~ava 20% populacije.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
83
Tabela 9: Izvori prihoda za doma}instva
(procenat doma}instava sa prihodom iz odre|enog izvora)
Vrsta prihoda
Sva
doma}instva
Najsiroma{nij
i
20-
40%
40-
60%
60-
80%
Najbogatiji
Prihod od zarada 75,7 71,7 82,7 78,2 74,1 73,0
Prihod od samozaposlenosti 6,3 3,3 5,6 4,3 4,9 11,1
Penzije 45,5 47,3 44,4 48,3 49,8 39,4
Stipendije 2,2 1,1 0,5 2,6 2,7 3,2
Nadoknade za nezaposlene 0,4 1,1 0,0 0,4 0,8 0,0
Socijalni transferi 3,9 9,2 4,6 1,7 3,4 2,2
Privatni transferi (ro|aci) 19,3 21,2 14,8 17,5 20,1 21,6
Ostali prihodi (imovina &
osiguranje)
11,2 5,0 12,8 12,0 12,5 12,4
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6. *U uzorak nije uklju~eno 85 doma}instava zbog
nedostatka informacija o nadnicama ili zaradama od samozaposlenosti i 22 doma}instva koja nisu prijavila prihod.
Tabela 10: Struktura prihoda doma}instava
(prosje~ni iznosi u eurima)
Vrsta prihoda
Sva
doma}instva
Najsiroma{niji
20-40%
40-60%
60-80%
Najbogatiji
Prihod od zarada 297,3 194,9 279,0 313,9 300,0 354,5
Prihod od samozaposlenosti 28,6 8,4 16,0 15,2 15,2 69,2
Penzije 69,1 61,9 63,8 76,3 69,4 71,0
Stipendije 1,0 0,7 0,0 0,9 1,0 1,7
Nadoknade za nezaposlene 0,4 1,3 0,0 0,2 0,5 0,0
Socijalni transferi 2,4 6,2 2,3 1,2 2,5 1,0
Privatni transferi (ro|aci) 58,7 48,3 40,2 35,9 62,0 90,6
Ostali prihodi (imovina & osiguranje) 12,0 4,3 19,0 9,6 10,5 15,4
Ukupan prihod 469,5 326,0 420,3 453,4 461,1 603,4
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6.
Grafik 9: Struktura prihoda doma}instava
(u~e{}e u ukupnom prihodu po grupama potro{nje)
0%
20%
40%
60%
80%
100%
Sva doma}instva
Najsiroma{niji
20-40%
40-60%
60-80%
Najbogatiji
Procena
t
Os t a li p riho d i
Privatni transferi
Socijalni transferi
Nadonk. za nezaposl.
Stipend ije
Penzije
Zarade od samozaposl.
Zarade
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
84
Penzije
Penzije su glavni oblik socijalnog osiguranja u Crnoj Gori. Uprkos ~injenici {to je penzioni sistem
u Crnoj Gori jedan od najdare`ljivijih u regionu, konvencionalno shvatanje u Crnoj Gori je da su
penzije suvi{e niske da bi obezbijedile egzistencijalni minimum. Ipak, pove}anja u stopama
zamjene ili nivoa benefita izgledaju neodr`iva sa stanovi{ta bud`eta. Finansije socijalnih fondova,
uklju~uju}i penzije, fond zdravstva i fond zaposlenosti, odra`avaju nepredvidljive i slabe veze
izme|u osnovnih izvora finansiranja i zakonskih benefita. Nagomilani socijalni doprinosi ne
pokrivaju u potpunosti obaveze tro{enja. Odr`ivost sistema socijalnog osiguranja je dalje
potkopana utajom poreza i nestabilnim doprinosima iz Republi~kih bud`eta. Kao posljedica, glavni
fondovi osiguranja su direktno ili indirektno zavisni od akciza, uvoznih carina i strane pomo}i kroz
grantove35.
Ako se postoje}i penzioni sistem ne reformi{e, jaz izme|u doprinosa i tro{kova za penzije }e
narasti sa 2,5% GDP-a na preko 10% GDP-a. Odnos onih koji upla}uju u penzioni fond i korisnika
ovih sredstava je trenutno 1,436. Jasno je da je penziona reforma neophodna kako bi se izbjegla
katastrofa. Razli~ite vrste reformi, kao {to su pove}anje doprinosa, smanjenje nivoa benefita,
smanjenje stope indeksacije pove}anja penzija i pove}anje starosne granice za odlazak u penziju
razli~ito uti~u i na doma}instva koja trenutno primaju penzije i na ona doma}instva koji nemaju
ovu vrstu prihoda.
Kao {to je ve} re~eno, veliki dio doma}instava prijavljuje neki oblik prihoda od penzija, dok samo
oko 11% doma}instava ima penzije kao jedini izvor prihoda. Uticaj odre|enih reformi mo`e
varirati u dugom i kratkom roku, komplikuju}i time predvi|anja i u kratkom roku. Kratkoro~ni
uticaji mogu imati suprotne efekte za razli~ite grupe. Na primjer, smanjenje stope zamjene }e
smanjiti nivoe benefita za one koji sada primaju penzije, ali }e tako|e smanjiti optere}enje za
zaposlene i poslodavce koje se odnosi na finansiranje penzija. Ukoliko se penziona reforma
sprovodi sa ciljem podsticanja ekonomskog rasta, efekti preduzetih aktivnosti mogu biti suprotni u
kratkom i u dugom roku.
Posmatrano na nivou ~itave populacije, oko dvije petine ljudi `ivi u doma}instvima koja imaju
prihod od penzija (vidjeti tabelu 11). Kada razvrstamo prihod od penzija po vrsti penzije, vidimo da
starosne penzije predstavljaju dominantan izvor penzionih prihoda: oko 25% ljudi `ivi u
doma}instvu sa prihodom od starosnih penzija. Invalidska penzija je drugi naj~e{}i izvor penzionih
prihoda, i to za doma}instva u kojima `ivi 12% stanovni{tva. Manje od 5% prima porodi~ne penzije
i skoro niko ne prima prihod po osnovu penzija zara|enih u inostranstvu.
Kada pogledamo grupe potro{nje, vidimo da vi{e od 60% najsiroma{nijih `ivi u doma}instvima sa
penzionim prihodom: dvije petine stanovni{tva `ivi u doma}instvima sa starosnom penzijom, dok
vi{e od jedne petine najsiroma{nijih prima invalidsku penziju.
Uprkos svom imenu, starosne penzije ne primaju sve starije osobe: oko 35% osoba starijih od 65
godina nisu prijavile prihod od starosne penzije za svoje doma}instvo. Po evropskim standardima,
ova stopa je niska. Ipak, stariji ~e{}e prijavljuju invalidske penzije (20% starijih u pore|enju sa 12%
onih koji imaju izme|u 25 i 49 godina). Sve u svemu, stariji naj~e{}e imaju neki prihod od penzije
za doma}instvo. ^ak 85% osoba starijih od 65 godina imaju neki prihod od penzija, dok je
dominantan izvor starosna penzija. Ako pro{irimo na{ indikator i uklju~imo prihod od socijalnih
tranfera i penzioni prihod, procenat ljudi starijih od 65 godina koji su uklju~eni se ne mijenja. Me|u
15% starijih osoba koji nemaju prihod od penzija, tri ~etvrtine `ivi u doma}instvima koja imaju neki
prihod od zarada, dok jedna tre}ina ima prihod od svojine ili privatnih transfera.
35 Izvor: Ministarstvo finansija
36 Izvor: Fond za penzijsko invalidsko osiguranje
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
85
Tabela 12 upore|uje penzione prihode doma}instva i ukupne tro{kove. Samo me|u doma}instvima
koja primaju inostrane penzije ovaj izvor pokriva veliki dio mjese~nih tro{kova (vi{e od 50%). U
prosjeku, me|u doma}instvima koja imaju prihod od drugih oblika penzije (starosna, invalidska,
porodi~na penzija) prihod u prosjeku pokriva 20% mjese~nih tro{kova.
Distributivni uticaj penzija mo`emo istra`iti ocjenjivanjem indeksa benefita od ovog programa
(pogledati dio koji slijedi, a koji se odnosi na socijalnu za{titu i siroma{tvo za ozbiljniji pristup
procjeni uticaja penzija na siroma{tvo). U isto vrijeme, ovo kombinuje informacije o zastupljenosti
ovog programa me|u doma}instvima u razli~itim grupama potro{nje i o nivoima primljenih
sredstava. Grafik 9 prikazuje krivu koncentracije za penzije. Ova kriva pokazuje dio ukupnih
tro{kova penzije koji idu na stanovni{tvo koje je rangirano po nivou potro{nje
isklju~uju}i
prihod od
penzija. Upotrebom ove krive mo`emo klasifikovati tro{enja programa kao progresivna ili
degresivna. Pore|enjem distribucije penzija sa distribucijom potro{nje, uvi|amo da je obrazac
tro{kova ovog programa progresivan. Oni ispod medijana (siroma{niji) dobijaju dio benefita koji je
ve}i od njihovog dijela potro{nje. Interesantnija je ~injenica da stanovni{tvo na donjem kraju
distribucije dobija ve}i dio penzionih tro{kova nego {to je njihov udio u populaciji.
Tabela 11: Procenat pojedinaca u doma}instvima koji imaju prihod od penzija,
Po kvintalima (N=4 995)
Bilo koja
penzija
Starosna
penzija
Invalidska
penzija Inostrana
penzija
Porodi~na
penzija
Ukupno 41,4 25,9 12,3 0,9 4,4
Po kvintalima*
najsiroma{niji 63,4 41,1 23,0 1,1 1,9
20-40% 45,5 27,4 11,7 1,4 6,6
40-60% 39,9 22,2 14,6 0,1 4,4
60-80% 33,0 19,7 7,6 1,2 6,7
najbogatiji 25,4 19,0 4,3 0,7 2,5
Po starosti:
<16 godina 27,4 16,0 7,2 1,0 4,6
16-24 godina 33,1 17,2 11,2 0,3 4,8
25-49 godina 36,0 21,8 11,0 0,7 4,2
50-64 godina 52,8 34,3 16,3 1,1 3,6
>65 godina 86,7 64,6 21,3 2,3 5,6
Izvor: ISSP Istra`ivanja o prihodima i rashodima doma}instava 5 i 6.
* Potro{a~ki kvintali su procijenjeni u odsustvu prihoda od penzija.
Tabela 12: Prihod doma}instava od penzije kao procenat ukupnih tro{kova,
(uslov primanja penzije)
Bilo koja
penzija
Starosna
penzija
Invalidska
penzija Inostrana
penzija
Porodi~n
a penzija
od ukupnog tro{ka
doma}instva
23,8 23,7 19,3 54,0 17,0
broj doma}instava 565 354 163 15 64
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
86
Socijalni transferi
Crna Gora je uvela dalekose`ne reforme sistema socijalne za{tite u naporu da pobolj{a targetiranje i
obezbijedi bud`etsku odr`ivost programa socijalne pomo}i. Trenutno, pet glavnih programa
socijalne za{tite iznose skoro 2% GDP-a. Pored odr`avanja ukupnog bud`eta konstantnim u
nominalnim veli~inama od 2000. godine, reforme su obuhvatile i velike zaokrete u bud`etskoj
alokaciji kroz najva`nije programe socijalne za{tite (grafik 10). Zakoni koji su stupili na snagu u
2001. godini pro{irili su obim prava za primaoce materijalnog obezbje|enja porodice. Iako sve
porodice koje imaju pravo na ovu vrstu pomo}i ne primaju materijalno obezbje|enje porodice,
porast broja porodica koje imaju ovo pravo se ogleda u pove}anju udjela materijalnog obezbje|enja
porodice u ukupnoj socijalnoj za{titi, sa 18% na 37% ukupnog bud`eta. Dok je obim izdataka za
materijalno obezbje|enje porodice pove}an, amandmani na propise o dje~jem dodatku koji su
donijeti 2001. godine ograni~ili su definiciju kvalifikovanosti za primanje dje~ijeg dodatka. Prema
novim propisima, dje~ji dodatak mogu da primaju samo ona doma}instva koja ve} primaju
materijalno obezbje|enje porodice i koja imaju djecu. Ovaj kriterijum se defini{e kao prili~no strog.
Istovremeno, obuhvatnost programa je pro{irena i na doma}instva sa djecom sa poreme}ajem u
razvoju, bez obzira na prihod.
Pore|enjem sa Srbijom gdje su socijalni programi za{tite u 2002. godini iznosili 1% GDP-a, vidimo
sa se struktura socijalne pomo}i u Crnoj Gori prili~no razlikuje od one u Srbiji. Konkretno,
materijalno obezbje|enje porodice (MOP) u Srbiji ima mnogo manji obuhvat nego {to je to slu~aj u
Crnoj Gori, dok program dje~jeg dodatka u Srbiji obuhvata veliki dio populacije. Bogi}evi}37
(2002) procjenjuje da 37% dje~je populacije do 19 godina starosti prima dje~ji dodatak (8,9% od
ukupnog broja stanovni{tva Srbije); Tesliuc38 (2003) daje podatak da 15% ukupnog stanovni{tva
Srbije `ivi u doma}instvima koja primaju dje~ji dodatak. Iz ugla bud`etske potro{nje, program
dje~jeg dodatka u Srbiji se smatra prili~no skupim, dok su sume koje se primaju po tom osnovu
suvi{e male da bi imale zna~ajnog uticaja na `ivotni standard. Na drugoj strani, ovaj program je
zna~ajno modifikovan u Crnoj Gori u smislu mogu}nosti za primanje pomo}i, ali sume i dalje
ostaju male, kao {to je prikazano u dijelu koji slijedi.
37 Bogi}evi}, Biljana. 2002. “Sistem vladine podr{ke siroma{nima u Srbiji”
38 Tesliuc, Cornelia. 2003. “Socijalna za{tita i siroma{tvo u Srbiji.”
Grafik 10: Zastu
p
l
j
enost
p
enzi
j
a
0%
20%
40%
60%
80%
100%
0 20 40 60 80 100
Kumulativni udio
p
o
p
ulaci
j
e, ran
g
irane
p
o tro{kovima bez
p
enzi
j
a
(
%
)
Penzi
j
eTro{. bez penzi
ja
Izvor: ISSP Istra`ivan
j
e o
p
rihodima i rashodima doma}instava 5 i 6
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
87
Grafik 11: Distribucija bud`eta socijalne za{tite
0%
20%
40%
60%
80%
100%
2000 2001 2002 2003
Procenat
Ostala li~na njega
Nadoknada za
trudnice
Bora~ka nadoknada
Dje~iji dodatak
MOP
Izvor: Ministarstvo rada i socijalnog staranja
Dok prihodi od rada i penzija ~ine dvije glavne kategorije izvora prihoda za doma}instva, socijalni i
privatni transferi su tre}i po veli~ini izvor prihoda. Govore}i o dijelu stanovni{tva koji prima neki
prihod od socijalne pomo}i (ne uklju~uju}i prihod od penzija), mo`e se zaklju~iti da trenutna
struktura javnih transfera ne igra bitnu ulogu u pogledu blagostanja doma}instava u Crnoj Gori.
Samo 4% osoba `ivi u doma}instvima koja primaju neku socijalnu pomo} (vidjeti tabelu 13)39.
Me|u populacijom djece starosti od 0 do 16 godina, oko 5% `ivi u doma}instvima koja primaju neki
oblik socijalne pomo}i. Pore|enja radi, Ministarstvo rada i socijalnog staranja daje podatak da je u
avgustu 2002. godine u Crnoj Gori dje~ji dodatak primilo 7% djece.
Posmatraju}i prihod od socijalne pomo}i (materijalno obezbje|enje porodice, dje~ji dodatak, drugi
obilici socijalne pomo}i) kao procenat ukupnih tro{kova doma}instva, ovaj izvor prihoda obuhvata
oko 15% ukupnih tro{kova doma}instva (tabela 14). Tabela 15 daje neke od razloga neprijavljivanja
za materijalno obezbje|enje porodice koje je navelo stanovni{tvo iz prvog kvintala (polovina ovog
stanovni{tva se smatra siroma{nim, dok je druga polovina odmah iznad linije siroma{tva). U ovoj
grupi, 10% smatra da im ne treba materijalno obezbje|enje porodice (a vjerovatno ni drugi glavni
program socijalne pomo}i, dje~ji dodatak, u slu~aju da imaju djecu). Te{ko je pojmovno definisati
ove ljude kao “isklju~ene iz programa” jer oni ne vjeruju da im je potrebna pomo}. Nedostatak
informacija o postojanju materijalnog obezbje|enja porodice je jedan od najva`nijih razloga za
isklju~ivanje: oko 30% stanovni{tva iz najsiroma{nijeg kvintala navodi da nije informisano o
postojanju materijalnog obezbje|enja porodice. Implikacija ovog nalaza je da bolje i sveobuhvatnije
informisanje mo`e pomo}i u pravilnom targetiranju ovog programa. Neke od drugih kategorija je
te`e interpretirati. Na primjer, oni koji misle da primjena ne bi ni{ta postigla mogu vjerovati da sume
nisu dovoljno velike ili da oni u stvari ne bi ostvarili pravo. Relativno malo doma}instava ka`e da je
procedura prijavljivanja prepreka primjeni.
Tabela 16 pru`a vi{e informacija o primaocima prihoda iz socijalnog programa u smislu broja
doma}instava koja primaju socijalnu pomo}, broja pojedinaca u ovim doma}instvima i prosje~nom
primljenom sumom.40 Prema istra`ivanju, prosje~ni iznosi (u eurima) koje po osnovu materijalnog
39 Pored ovih vrsta programa, neki oblici socijalne pomo}i povezani sa energetskom situacijom koji postoje u Srbiji, bi
tako|e trebali da budu razmotreni. Programi u Srbiji ciljaju zajedni~ke tro{kove komunalnih usluga (grijanje u oblasti,
vodosnabdijevanje i odvoz sme}a) kao i jednokratne nadoknade doma}instvima koja imaju malu potro{nju elektri~ne
energije. Kako bi ciljani program pomogao siroma{nima u grijanju njihovih mjesta stanovanja, program vezan za
potro{nju elektri~ne energije kao izvora grijanja se ne bi odnosio na 44% stanovni{tva koji za grijanje svojih stambenih
prostora ne koriste elektri~nu energiju, ve} radije drva ili ugalj u malom dijelu slu~ajeva.
40 Nivo MOP-a je orde|en na osnovu prosje~ne zarade u Crnoj Gori za prethodni mjesec i veli~ine doma}instva.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
88
obezbje|enja porodice i dje~ijeg dodatka primaju doma}instva iz uzorka (56 i 25 eura, respektivno)
su ne{to ni`i od prosje~nih iznosa koje su po ovom osnovu primili primili svi korisnici ovih
programa u avgustu 2002. godine (63 i 31 eura, respektivno)41.
Tabela 13: Procenat pojedinaca u doma}instvima koja primaju socijalnu pomo},
nadoknade za nezaposlene ili stipendiju
Prihod od nekog vida socijalne
pomo}i (dje~ji dodatak,
porodi~na pomo}, druga
socijalna pomo})
Nadoknade za nezaposlene Prihod od stipendije
3,8 0,5 2,4
Tabela 14: Socijalni Transferi
(dje~ji dodatak, materijalno obezbje|enje porodice, druga socijalna pomo})
kao procenat ukupnih tro{kova, uslov primanje socijalnih transfera
Bilo koji prihod od socijalne
pomo}i
% ukupnih tro{kova doma}instva 14,0
broj doma}instava 49
Tabela 15: Za{to se doma}instvo nije prijavilo za dobijanje MOP-a
Najsiroma{niji
20%
20-40%
40-60%
60-80%
Najbogatiji
80%
Ukupno
Nije im potrebna 12,0 16,0 23,3 33,5 50,6 27,7
Nisu informisani kako
da se uklju~e 29,4
32,8
31,5
29,3 18,5
28,3
Ne bi ni{ta postigli 47,1 41,1 36,8 30,0 24,8 35,4
Lo{ odnos socijalnih
radnika 5,2
5,8
3,7
2,5 1,0
3,6
Te{ko je dobiti
dokumentaciju 2,6
2,3
0,7
1,3 1,1
1,5
Ostalo 3,7 2,1 4,0 3,4 4,1 3,5
Tabela 16. Prihodi od socijalnih programa
Broj
doma}instav
a
Broj
pojedinaca
Prosje~ni iznos
(euro)
MOP (prethodni mjesec) 30 130 57,7
Dje~ji dodatak (prethodni mjesec) 10 54 26,7
Jednokratna pomo} (poslednjih 6 mjeseci) 8 24 132,5
Druga li~na njega (poslednjih 6 mjeseci) 11 29 70,7
Ostali socijalni programi (poslednjih 6
mjeseci)
1 1 230
NVO – u gotovini (prethodni mjesec) 2 5 100,0
Vlada - u robi (prethodni mjesec) 5 8 86,8
41 Izvor: Ministarstvo rada i socijalnog staranja.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
89
NVO – u robi (prethodni mjesec) 0 0 -
Socijalna za{tita i siroma{tvo
U kojoj mjeri programi socijalne za{tite dovode do smanjenja siroma{tva? U kojoj mjeri }e se
siroma{tvo smanjiti zavisi od iznosa transfera i stepena u kom ovi transferi dolaze do siroma{nih.
Socijalna projekcija mo`e da uklju~i programe socijalne pomo}i (kao {to su materijalno
obezbje|enje porodice i dje~ji dodatak) i programe socijalnog osiguranja (penzije i nadoknade za
nezaposlene). Odnos izme|u siroma{tva i socijalne za{tite se ispituje kroz evaluaciju promjene u
mjerama siroma{tva u situaciji kada nema nadoknada socijalne za{tite, pri ~emu je pretpostavka da
je marginalna sklonost potro{nji 50%42.
Grafik 11 prikazuje uticaj transfera socijalne za{tite na siroma{tvo. Kada ne bi bilo programa
socijalne za{tite, stopa siroma{tva bi porasla za 34%. Najve}i obim ovog porasta poti~e od uticaja
programa socijalnog osiguranja, kod kojih su i obuhva}enost i dobijeni iznos ve}i nego kod
programa socijalne pomo}i. Va`no je problem pratiti {ire, odnosno ne uzimati u obzir samo stopu
siroma{tva, znaju}i da ovi programi uti~u i na jaz i na o{trinu siroma{tva, ~ak i kod siroma{nih koji
i sa ovim transferima ostaju i dalje siroma{ni. Jo{ jednom, uo~avamo da socijalna za{tita ima veliki
uticaj na dubinu i o{trinu siroma{tva, u velikoj mjeri zbog zna~ajnog uticaja transfera socijalnog
osiguranja. Kada bi se uklonilo socijalno osiguranje, jaz siroma{tva bi se vi{e nego udvostru~io.
O{trina siroma{tva bi porasla za vi{e od 150%. Velike promjene odra`avaju i visinu transfera
socijalnog osiguranja (uglavnom penzije) kao i nizak nivo mjera siroma{tva sa kojima se po~inje.
Grafik 12: Promjena u siroma{tvu bez programa socijalne za{tite
0%
40%
80%
120%
160%
200%
Stopa
siroma{tva
Jaz
siroma{tva
O{trina
siroma{tva
Procenat promjene u mjeri siroma{tva
Socijalna pomo}
Socijalno osiguranje
Socijalna za{tita
Izvor: ISSP Istra`ivanje o prihodima i rashodima doma}instava 5 i 6.
Privatni transferi
U poslednjih deset godina i vi{e, od raspada Socijalisti~ke Federativne Republike Jugoslavije, desila
su se zna~ajna pomjeranja stanovni{tva, uklju~uju}i ruralne i urbane migracije stanovni{tva u
okviru Crne Gore. Tako|e su se desila i iseljavanja mladih, dobro obu~enih ljudi koji su napustili
Crnu Goru u potrazi za daljim obrazovanjem i bolje pla}enim poslovima u inostranstvu. Generalno,
me|unarodna migracija je karakteristi~an mehanizam snala`enja doma}instava na Balkanu.
Konzistentno s ovom tvrdnjom, podaci pokazuju da su doznake iz inostranstva zna~ajan izvor
prihoda za crnogorska doma}instva. Kao {to se vidi u tabeli 17, oko 10% stanovni{tva `ivi u
42 Smanjivanje prihoda za 1 euro dove{}e do smanjenja potro{nje za 0,5 eura.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
90
doma}instvima koja primaju privatne transfere od drugih doma}instava. Privatni transferi od
porodica iz inostranstva (doznake) su jednako ~esti. Kako nekoliko doma}instava imaju prihode iz
oba izvora, ukupno, 20% doma}instava prima neki oblik privatnih transfera. U pore|enju sa
ukupnim tro{kovima, transferi od ro|aka iz Srbije ili Crne Gore pokrivaju 23%, a transferi od
ro|aka iz inostranstva duplo vi{e (48%) tro{kova doma}instava (vidjeti Tabelu 18).
Tabela 17: Procenat pojedinaca u doma}instvima koji primaju privatne transfere
Od bilo kojih
ro|aka Od ro|aka iz
Srbije ili Crne
Gore
Od ro|aka koji
`ive u
inostranstvu
Ukupno 18,0 9,2 10,0
Po kvintalima*
:
najsiroma{niji 42,8 18,3 28,2
20-40% 13,3 7,2 6,5
40-60% 11,7 6,9 6,1
60-80% 11,7 6,8 5,4
najbogatiji 10,5 6,9 3,9
* Potro{a~ki kvintali su procijenji u odsustvu privatnih transfera.
Tabela 18: Privatni transferi kao procenat ukupnih izdataka,
(uslov na primanje transfera)
Od ro|aka iz Srbije ili iz
Crne Gore
Od ro|aka koji `ive u
inostranstvu
% ukupnih tro{kova
doma}instva
22,9 48,1
broj doma}instava 142 118
VI. ZAKLJU^CI
Rapidna ekonomska tranzicija koja je u Crnoj Gori u toku, bez sumnje je donijela velike promjene u
socioekonomskoj situaciji u Republici. Dramati~an pad u outputu u poslednjih deset godina doveo
je do ra{irenog shvatanja da su siroma{tvo i nejednakost visoki. Ipak, bez odgovaraju}ih izvora
podataka te{ko je analizirati stvarnu situaciju. Kako Vlada nastavlja da ubrzava ekonomske i
institucionalne reforme u naporu da se dostignu odr`ive fiskalne politike i ekonomski razvoj, ostaje
pitanje uticaja ovih promjena na siroma{tvo i siroma{ne ako se odgovaraju}e socijalne politike ne
usvoje. Dok su mnoge preduzete reforme od izuzetnog zna~aja, razvojni pioriteti Crne Gore ne bi
smjeli zanemariti va`na pitanja socijalne politike koja bi obezbijedila da u budu}nosti svi imaju
koristi od sna`nog ekonomskog rasta. Ovo obuhvata evaluaciju postoje}e {eme socijalnih programa,
pa`ljivu procjenu uticaja radi obezbje|ivanja informacija za dizajniranje reformi i procjenu
trenutnih bud`etskih alokacija koje imaju uticaja na regresivne programe, kao {to su alokacije u
sektor obrazovanja kroz razli~ite nivoe.
Cilj ove studije je da iskoristi nove dostupne podatke kako bi se definisala osnovna linija i profil
`ivotnog standarda u Crnoj Gori. Prezentuju}i niz zna~ajnih rezultata, ovaj dokument slu`i kao
platforma za va`nu diskusiju u Crnoj Gori na temu izrade strategije za smanjenje siroma{tva i
pra}enja efekata realizacije strategije. Studija pokazuje da je skoro 10% stanovnika Crne Gore
siroma{no, ali da siroma{tvo nije duboko. Iako je siroma{tvo nisko (u smislu stope siroma{tva) i
plitko, procjene siroma{tva su osjetljive na liniju siroma{tva. Vi{e od jedne tre}ine stanovni{tva je
klasifikovano kao ekonomski ugro`eno ili materijalno nedovoljno obezbije|eno, jer `ive ispod
nivoa od 150% definisane linije siroma{tva. Podizanje linije siroma{tva za 20% udvostru~uje stopu
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
91
siroma{tva. Prema toma, sa `ivotnim standardom odmah iznad linije siroma{tva, zna~ajan dio
populacije je ugro`en u smislu da su osjetljivi na bilo kakve fluktuacije u ekonomiji, padove ili
iznenadne promjene li~nih prihoda. Pozitivni {okovi u prihodu (oni izazvani npr. rastom ili dobrim
ekonomskim politikama) bi rezultirali vi{e nego proporcionalnim smanjenjem siroma{tva; negativni
{okovi (kao {to je recesija) bi vodili vi{e nego proporcionalnom pove}anju siroma{tva.
Postoji dosta varijacija u siroma{tvu kod razli~itih grupa populacije. Dio ovog siroma{tva se
obja{njava faktorima kao {to su obrazovanje u doma}instvu i pristup zemlji{tu. Mogu}nosti
zapo{ljavanja su bitne. Doma}instva sa neaktivnim ili penzionisanim odraslim osobama imaju
mnogo ve}u vjerovatno}u da budu siroma{na, kao i ona na ~ijem ~elu se nalaze manje obrazovane
starje{ine. Ipak, doma}instva na sjeveru ostaju siroma{nija u odnosu na njima odgovaraju}a
doma}instva u centralnom i ju`nom regionu, ~ak i nakon kontrolisanja ostalih pozadinskih
karakteristika. Ovo ukazuje na strukturalne razlike u ekonomijama kroz regione, {to se tako|e
odra`ava i u manjem uticaju nivoa obrazovanja na potro{nju me|u doma}instvima u sjevernom i
ju`nom dijelu u pore|enju sa centralnim dijelom.
Analiza tako|e nagla{ava nedovoljnu razvijenost mre`e socijalne za{tite. Pokazalo se da, kako
programi socijalnog blagostanja, tako ni nadoknade za nezaposlene ne pru`aju dovoljnu podr{ku
siroma{nim doma}instvima, zbog obuhvatnosti i iznosa koji se prima. Na drugoj strani, najra{ireniji
program socijalnog osiguranja – penzije - jako {tite od siroma{tva. Iz tog razloga }e biti zna~ajno
ocijeniti uticaj alternativnih penzionih reformi na najsiroma{nija doma}instva.
Po{to Crna Gora nastavlja sa ambicioznim ekonomskim reformama, bi}e va`no vr{iti monitoring
klju~nih indikatora. Dodatna analiza postoje}ih podataka o doma}instvima mo`e pomo}i u
predvi|anju potencijalnog uticaja predlo`enih reformi na siroma{ne i procjeni efikasnosti postoje}ih
programa. Odgovaraju}i monitoring i evaluacija `ivotnog standarda }e zahtijevati pravovremene,
visoko kvalitetne i dostupne podatke. Identifikovanje na~ina za procjenu `ivotnog standarda me|u
glavnim grupama koje nisu obuhva}ene postoje}im podacima (Romi, izbjeglice, raseljena lica) bi
tako|e trebalo da bude prioritet. Crna Gora je suo~ena sa izazovom razvoja statisti~kog sistema koji
mo`e prikupiti, procesuirati, analizirati i ra{iriti informacije o `ivotnom standardu cjelokupne
populacije. Slede}i korak u ovom naporu bi bila koordinacija analiti~kih napora Institutta za
strate{ke studije i prognoze sa teku}im zvani~nim istra`ivanjima bud`eta doma}instava koje
sprovodi Republi~ki zavod za statistiku – MONSTAT - kako bi se kompletnije razvio sistem
podataka i analiza za monitoring siroma{tva. U me|uvremenu, po{to je redovno prikupljanje
podataka neophodno, imaju}i na umu da je Vlada Crne Gore usvojila Zakon o u~e{}u privatnog
sektora u pru`anju javnih usluga, predla`e se nastavak saradnje sa NVO sektorom dok Republi~ki
zavod za statistiku ne izgradi kapacitete da preuzme posao.
Imaju}i u vidu sve {to je prethodno navedeno, aktivnosti koje treba da uslijede nakon publikovanja
ove studije su vi{estruke. Izme|u ostalog, potrebno je da se uklju~e slede}e aktivnosti:
• Saradnja sa MONSTAT-om u razvoju vje{tina njihovih zaposlenih kroz naredna istra`ivanja
o prihodima i rashodima doma}instava Instituta za strate{ke studije i prognoze;
• Posebno istra`ivanje o prihodima i rashodima romskih doma}instava, izbjeglica i raseljenih
lica koje }e Institut za strate{ke studije i prognoze realizovatu uz tehni~ku pomo} Svjetske
banke i Programa razvoja Ujedinjenih nacija;
• Pro{irenje obuhvata ISSP istra`ivanja o prihodima i rashodima doma}instava tako {to }e se
uklju~iti pitanja koja se odnose na analizu uticaja na `ivotnu sredinu43;
43 Pogledati World Bank (2003a) za vi{e informacija o potrebama za prikupljanje podataka i analizu u oblasti odr`ivog
razvoja u Srbiji i Crnoj Gori.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
92
• Dalji razvoj upitnika koji ISSP koristi za prikupljanje podataka o prihodima i rashodima
doma}instava kako bi se vr{ila analiza uticaja procesa restrukturiranja preduze}a na tr`i{te
rada i siroma{tvo.
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Deaton, Angus. 1997.
The Analysis of Household Surveys: A Microeconometric Approach to
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Baltimore, MD: Johns Hopkins University Press.
Savezni statisti~ki zavod. 2002. “Statisti~ki godi{njak.” Beograd.
Savezni statisti~ki zavod. 2002. “Potro{a~ka korpa, cijene i prosje~na neto zarada.” Radna verzija,
Sektor za socijalnu statistiku, Metodologija i standardi, Beograd.
Figini, Paolo. 1998. “Inequality Measures, Equivalence Scales and Adjustment for Household Size
and Composition.” Working Paper No. 185, Maxwell School of Citizenship and Public Affairs,
Syracuse University.
Foster, James., Joel Greer and Eric Thorbecke. 1984. “A Class of Decomposable Poverty
Measures.”
Econometrica
, 761-766.
Institut za strate{ke studije i prognoze (ISSP). 2002a. “Household Survey #6.” Podgorica, Crna
Gora.
Institut za strate{ke studije i prognoze (ISSP). 2002b. “Household Survey #5.” Podgorica, Crna
Gora.
Institut za strate{ke studije i prognoze (ISSP). 2003a. “Crnogorski ekonomski trendovi (MONET).”
Podgorica, Crna Gora.
Ivanovic, Petar. 2002. “Penziona reforma i tr`i{te rada”
Krsti}, Gorana. 2003. “Profil siroma{tva u Srbiji 2002.”
Luttmer, Erzo. 2002. “Poverty and Inequality in Croatia.”
Milanovi}, Branko. 2003. "Nejednakost i socijalni transferi" mimeo. Beograd, Srbija.
OCHA kancelarija u Podgorici i Ekonomski institut u Beogradu. 2000. “Prihodi i potro{nja u Crnoj
Gori.”
Tesliuc, Cornelia. 2003. “Social Protection and Poverty in Serbia”
UNDP. 2001. “Employment, Labour Market and Standard of Living in Montenegro.”
The World Bank. 2000. Making Transition Work for Everyone: Poverty and Inequality in Europe
and Central Asia. The World Bank, Washington DC.
The World Bank. 2002a. “Albania Poverty Assessment.” The World Bank, Washington DC.
The World Bank. 2002b. “Bosnia and Herzegovina: Poverty Assessment.” The World Bank,
Washington DC.
The World Bank. 2002c. “Bulgaria - Poverty Assessment.” The World Bank, Washington DC.
The World Bank. 2003a. “Serbia and Montenegro – A Country Environmental Analysis.” The
World Bank, Washington DC
The World Bank. 2003b. “Serbia and Montenegro - Public Expenditure And Institutional Review,
Volume Two.” The World Bank, Washington DC
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
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ANNEX
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
94
ANNEX 1: Pregled podataka iz Istra`ivanja o prihodima i rashodima doma}instava
u Crnoj Gori
Pozadina projekta
Podstaknuto potrebom da se kvantifikuje prisutnost siroma{tva, identifikuje veza izme|u
blagostanja i tr`i{ta rada i ocijeni adekvatnost socijalnih davanja, istra`ivanje o prihodima i
rashodima doma}instava (HHS) koje realizuje Institut za strate{ke studije i prognoze ima za cilj da
obezbijedi podatke neophodne za ocjenu dru{tveno-ekonomskih prilika u Crnoj Gori.
Podaci iz zvani~nog istra`ivanja o bud`etu doma}instva koje je naslije|eno iz biv{e Jugoslavije
trenutno je u procesu reformi u dijelu definisanja sadr`aja upitnika, odre|ivanja uzorka i
{irenja/dostupnosti analiti~arima i istra`iva~ima. Do danas, ove reforme jo{ nisu realizovane. Iz tog
razloga, nedostatak podataka o doma}instvima ote`ava analizu uticaja reformi na siroma{ne kao i
razvoj odgovaraju}ih programa za pobolj{anje `ivotnog standarda. Tako|e, zbog sada{njih napora
koji se ula`u u pripremu Strategije za smanjenje siroma{tva (SSS), pove}ana je tra`nja za dobrim
razumijevanjem prirode i uzroka siroma{tva u cilju odabira i odre|ivanja prioriteta
makroekonomskih, strukturalnih i socijalnih politika.
Gore navedeni razlozi bili su povod da jedna istra`iva~ka institucija u Crnoj Gori sprovede nekoliko
istra`ivanja o prihodima i rashodima doma}instava kako bi obezbijedila podatke koji su korisni
kreatorima ekonomske politike i analiti~arima u pomenutim oblastima.
Istra`ivanje o prihodima i rashodima doma}instava je kreirao, razvio i realizovao Institut za
strate{ke studije i prognoze (ISSP) iz Podgorice, Crna Gora. Ove aktivnosti su podr`ali Program
sigurne hrane Evropske komisije (European Commission Food Security Programme - gdje je
zna~ajan doprinos dao gospodin Vasilis Panoutsopoulos), USAID u Crnoj Gori i Chesapeake
Associates iz Washingtona. Tako|e, za ISSP istra`ivanja broj 4, 5 i 6, Institut za strate{ke studije i
prognoze dobio je tehni~ku pomo} i korisne sugestije od ekonomista Svjetske banke. U cilju
upotrebe ISSP istra`ivanja o prihodima i rashodima doma}instava od strane kreatora ekonomskih
politika i istra`iva~a koji se bave siroma{tvom i `ivotnim standardom u Crnoj Gori, podr{ka
Svjetske banke za istra`ivanje broj 6 je iskori{}ena, prije svega, za: pove}anje veli~ine uzorka i
sprovo|enje zajedni~ke analize i procjene siroma{tva. Ova podr{ka je zna~ajno pobolj{ala izvor
podataka u pogledu reprezentativnosti i kvaliteta, pa samim tim i korisnost ovih podataka kao
izvora za analize i na ~injenicama zasnovanog kreiranja politike. Saradnja na analizi rezultirala je
detaljnim profilisanjem siroma{tva u Crnoj Gori koje je trenutno nedostupno iz bilo kog drugog
izvora podataka. Veli~ina uzorka od 500 doma}instava u ISSP istra`ivanjima 4 i 5 je dovoljna da se
dobiju statisti~ki podaci na nacionalnom nivou, ali je nedovoljna za dobijanje statisti~kih podataka
za regionalne procjene (sjever, centralni dio, jug) kao i za ve}inu grupa od posebnog interesa (kao
{to su ugro`eni djelovi populacije, uklju~uju}i siroma{ne, starije, djecu i nezaposlene).
Kori{}enjem raspolo`ivih izvora podataka (lista za proces masovne vau~erske privatizacije, MVP44)
uzorak je pro{iren tako da uklju~i ukupno 800 doma}instava.
Istra`ivanja i sadr`aj upitnika
Do sada je realizovano ukupno {est istra`ivanja o prihodima i rashodima doma}instava u
organizaciji Instituta za strate{ke studije i prognoze; istra`ivanje broj 6 je sprovedeno u novembru
2002. godine. Opseg upitnika i veli~ina uzorka su opisani u tabeli A1.1.
44 Projektni tim Instituta za strate{ke studije i prognoze zahvaljuje gospodinu @eljku Brkovi}u iz ZOP-a za
obezbije|ivanje lista koje su kori{}ene za proces masovne vau~erske privatizacije.
Living Standards and Poverty in Montenegro 2002
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Tabela A1.1: ISSP istra`ivanje o prihodima i rashodima doma}instava u Crnoj Gori
Broj
istra`ivanja
Datum Broj
doma}instava Op{tine Obuhva}ene
teme
Model
potro{nje/tro{kova
1 Maj, 2001 2000 12 Ne
2 Jul, 2001 2000 12 Ne
3 Septembar, 2001 2000 12 Ne
4 April, 2002 500 21 Pro{ireno Da*
5 Avgust, 2002 500 21 Pro{ireno Da
6 Novembar, 2002 800 21 Pro{ireno Da
* Potro{nja hrane je pra}ena po koli~ini dok su vrijednosti izra`ene u eurima ra~unate na osnovu cijena iz
republi~kog Zavoda za statistiku.
U prva tri istra`ivanja, naglasak je bio na osnovnim demografskim karakteristikama doma}instava,
individualnim prihodima po osnovu zarada i ostalim prihodima doma}instava. U tim istra`ivanjima
dohodak je bio glavni indikator blagostanja. Podu~eni iskustvima sa terena i diskusijama sa
ekonomistima Svjetske banke, predstavnicima ostalih donatorskih organizacija i vladinih agencija,
upitnik je zna~ajno izmijenjen nakon tre}eg istra`ivanja. Istra`ivanja ~etiri, pet i {est su uvela dio
koji se odnosi na detaljne informacije o potro{nji, kao i ve}i obuhvat oblasti. Osnovne oblasti
uklju~ene u istra`ivanja o prihodima i rashodima doma}instava broj 4, 5 i 6 su:
• Struktura doma}instava uklju~uju}i informacije o migraciji
• Imovina doma}instava
• Trajna dobra koja posjeduju doma}instva
• Potro{nja hrane za oko 87 artikala (vidjeti Annex 3)
• Tro{kovi koji se ne odnose na hranu
• Primanja kroz socijalne programe: penzije (starosne i invalidske), stipendije, nadoknade za
nezaposlene, materijalno obezbjedjenje porodice, dje~iji dodaci, jednokratna pomo} i tu|a
njega itd.
• Ostali izvori prihoda koji ne poti~u od rada
• Zaposlenost sa ciljem mjerenja u~e{}a radne snage u formalnom i neformalnom sektoru
• Zdravstveno stanje
• Subjektivno mi{ljenje o blagostanju (zapa`anje o kvalitetu `ivota)
Iako je upitnik mijenjan i nakon istra`ivanja broj 4, treba napomenuti da su se klju~ne promjene
desile izme|u istra`ivanja broj 3 i 4 kada su dodati djelovi u upitniku koji se odnose na potro{nju.
Pro{ireni setovi tema koje su obuhva}ene u istra`ivanjima 4, 5 i 6 su veoma sli~ni, sa vrlo malim
modifikacijama. Kako bi bili u mogu}nosti da se realizuje pro{ireni upitnik, po~ev{i od istra`ivanja
4, veli~ina uzorka je smanjena. Podr{ka Svjetske banke je omogu}ila pove}anje uzorka na 800
doma}instava u istra`ivanju broj 6.
Upitnici za istra`ivanja 4, 5 i 6 sadr`e odgovaraju}i set pitanja sa ciljem mjerenja siroma{tva uz
upotrebu podataka o potro{nji i tro{kovima. Sva istra`ivanja su prikupljala podatke o potro{nji oko
87 razli~itih vrsta prehrambenih proizvoda. Ovi podaci ipak nisu uporedivi s obzirom na na~in na
koji je mjerena potro{nja hrane i period za koji su se prikupljali podaci o izdacima za proizvode koji
nisu hrana. U istra`ivanju broj 4 doma}instva su davala podatke o koli~inama utro{ene hrane u
odnosu na tri izvora: kupljena hrana, hrana proizvedena u doma}instvu i hrana dobijena kao poklon
od drugih doma}instava. Prema tome, vrijednost utro{ene hrane mora biti izvedena iz prijavljenih
koli~ina i regionalnog prosjeka cijena (koje prikuplja Zavod za statistiku).
Najva`nija zapa`anja istra`ivanja 4, 5 i 6 su da se indikatori siroma{tva prije mogu ocijeniti na
osnovu potro{nje i tro{kova, nego na osnovu prihoda (vidjeti Annex 2).
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96
Uzorak i prikupljanje podataka
U okviru istra`ivanja o prihodima i rashodima stanovni{tva, podaci se prikupljaju kroz direktno
intervjuisanje doma}instava. U prosjeku se anga`uje oko 28 ljudi koji uglavnom `ive u op{tinama u
kojima se vr{i prikupljanje podataka. Obuka anketara traje u prosjeku 25 sati prije svakog
istra`ivanja. Anketari koje anga`uje Institut za strate{ke studije i prognoze stekli su zna~ajno
iskustvo u prikupljanju podataka i radu na terenu. Rad na terenu traje oko 3 sedmice. Podaci se
unose i procesuiraju u kancelarijama Instituta, u Podgorici. Veli~ine uzoraka u istra`ivanjima 1-6 su
prikazane u Tabeli A1.2. Uzorci iz Istra`ivanja 5 (500 doma}instava) i 6 (800 doma}instava)
predstavljaju bazu za statistiku siroma{tva u ovom izvje{taju.
Podaci su prikupljeni iz sva tri regiona u Crnoj Gori, sjevernog (planinskog, manje naseljenog i
najmanje razvijenog), centralnog (najnaseljenijeg i industrijalizovanog) i ju`nog (obalskog,
najrazvijenijeg sa turizmom kao glavnim ekonomskim sektorom).
Tabela A 1.2: Uzorci u ISSP istra`ivanjima o prihodima i rashodima doma}instava 1-6
Op{tina
Istra`ivanja
doma}instva 1-
3
%
Istra`ivanje
doma}instva
4
%
Istra`ivanja
doma}instva
5&6
%
Andrijevica - - 5 1,0
12 0,9
Berane - - 30 6,0
77 5,9
Bijelo Polje - - 43 8,6 90 6,9
Kola{in - - 8 1,6
21 1,6
Mojkovac - - 8 1,6
21 1,6
Mojkovac/Berane 100 5,0
Plav - - 12 2,4
32 2,5
Pljevlja - - 30 6,0
83 6,4
Plu`ine - - 4 0,8
10 0,8
Ro`aje - - 20 4,0
52 4,0
[avnik/Plu`ine 50 2,5
[avnik - - 3 0,6
7 0,5
@abljak - - 4 0,8
10 0,8
Sjever 250 12,5 169 33,8 432 33,2
Podgorica 800 40,0 128 25,6
335 25,8
Nik{i} 300 15,0 59 11,8
154 11,8
Cetinje 50 2,5 16 3,2
42 3,2
Danilovgrad - - 12 2,4
32 2,5
Centralni dio 1150 57,5 215 43,0 563 43,3
Bar - - 31 6,2
82 6,3
Budva 200 10,0 12 2,4
32 2,5
Herceg Novi 150 7,5 26 5,2 68 5,2
Kotor 150 7,5 19 3,8
49 3,8
Tivat - - 11 2,2
29 2,2
Ulcinj 100 5,0 17 3,4 45 3,5
Jug 600 30,0 116 23,2 305 23,5
Ukupno 2000 100,0 500 100,0 1300 100,0
Posljednji popis u Crnoj Gori sproveden je 1991. godine. Novi popis je bio planiran za april 2002.
godine, ali je odlo`en i sada se planira za novembar 2003. godine. U nedostatku relevantnih
podataka o doma}instvima iz popisa, ISSP tim je morao da potra`i druge izvore podataka za izbor
doma}instava. Identifikovana su dva mogu}a izvora. Prvi je izvod iz glasa~kog spiska. Drugi izvor
je spisak iz procesa masovne vau~erske privatizacije, odnosno liste koja je sastavljena kako bi se
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
97
ljudima starijim od 18 godina omogu}ilo da preko dobijanja vau~era u~estvuju u procesu masovne
vau~erske privatizacije. Obje liste isklju~uju raseljena lica i izbjeglice. Pore|enje spiskova je
pokazalo da nema zna~ajnijih razlika, medjutim, odlu~eno je da se koristi MVP spisak jer je u
trenutku kreiranja istra`ivanja bio “noviji” i nije bilo dvostrukih unosa.
MVP lista je iskori{}ena da bi se identifikovao ciljni uzorak u svakoj od 21 op{tine u Crnoj Gori
koje su uklju~ene u istra`ivanja 4, 5 i 6. Broj doma}instava obuhva}enih uzorkom iz svake op{tine
je zavisio od procenta u~e{}a populacije starije od 18 godina iz te op{tine u ukupnoj populaciji u
Republici. Doma}instva su intervjuisana na osnovu liste uzorka za op{tinu, bez grupnog
dizajniranja uzorka u okviru op{tine, time umanjuju}i efekte dizajniranja istra`ivanja koje pove}ava
standardne gre{ke.
Nakon odre|ivanja ciljnog broja doma}instava koje treba anketirati, anketari su upu}ivani u
dodijeljene op{tine da intervjui{u doma}instva. U istra`ivanju broj 6, nakon dobijanja MVP liste, u
okviru svake pojedine op{tine, slu~ajan set doma}instava je izvla~en iz liste koriste}i kompjuterski
program. Ova slu~ajna lista je potom dodjeljivana anketarima u svakoj op{tini.
[irenje, povratne informacije i koordinacija
Za svako istra`ivanje o prihodima i rashodima doma}inastava istra`iva~i Instituta za strate{ke
studije i prognoze su odmah nakon prikupljanja podataka (u roku od 1-2 mjeseca) pripremali i
{iroko distribuirali izvje{aj o rezultatima istra`ivanja sa obimnim prikazom i opisom statisti~kih
podataka.
Tim istra`iva~a Instituta za strate{ke studije i prognoze blisko je sara|ivao sa ekonomistima
Svjetske banke na pripremi sadr`aja upitnika (istra`ivanja 4, 5 i 6) i odre|ivanju uzorka
(istra`ivanje 6). Tako|e, tim ISSP-a i ekonomisti Svjetske banke su u~inili zna~ajne napore u cilju
pobolj{anja upitnika u koordinaciji sa predstavnicima Vladinih ministarstava i donatorskim
agencijama (kao {to su USAID i UNDP).
ANNEX 2: Mjere blagostanja: potro{nja i tro{kovi doma}instva
Mjere blagostanja koje su nam neophodne u cilju prou~avanja siroma{tva treba da identifikuju one
koji nemaju sredstava za ostvarivanje uspostavljenih minimuma `ivotnog standarda. Uobi~ajena
praksa u evropskim zemljama je da se linija siroma{tva defini{e kao dio medijane prihoda. Ovo je
slu~aj kod najindustrijalizovanijih zemalja (sa izuzetkom SAD): `ivotni standard i linija siroma{tva
se procjenjuju u odnosu na prihod, a ne u odnosu na potro{nju. Ipak, postoje problemi kod primjene
ovog koncepta u bilo kojoj od tranzicionih ekonomija, a Crna Gora svakako nije izuzetak.
Kada poredimo prihode i tro{kove doma}instava, vidimo da je prihod mnogo te`e mjeriti nego
tro{kove ili potro{nju doma}instva, i to iz vi{e razloga: (i) u ekonomijama u tranziciji ljudi veoma
~esto nemaju redovne prihode {to ote`ava odre|ivanje prihoda u odre|enom vremenskom periodu;
(ii) mnogi su uklju~eni u sivu ekonomiju pa veoma ~esto prijavljuju ni`i iznos prihoda; (iii)
doma}instva se veoma ~esto bave i poljoprivredom, ali to ni u kom slu~aju ne posmatraju kao
prihod. Iz ovih razloga, u slu~aju Crne Gore, procjenjujemo stanje doma}instva na osnovu njegove
potro{nje ili tro{kova, radije nego na osnovu prihoda. Prema tome, na{ indikator uklju~uje sivu
ekonomiju u procjeni siroma{tva.
Kori{}enje podataka o doma}instvima radi mjerenja prihoda ili potro{nje nije ni malo lako. Mjera
blagostanja, bilo da je to prihod ili potro{nja, mora da bude kompletna. Izostavljanje bilo kog oblika
prihoda ili potro{nje vodi}e pogre{nim zaklju~cima. U slu~aju da, na primjer, vrijednost hrane koja
je proizvedena u doma}instvu bude izostavljena iz agregata potro{nje (ukupna mjera potro{nje) tada
bi seosko stanovni{tvo moglo izgledati siroma{nije nego {to stvarno jeste. Sve ovo name}e mnoge
zahtjeve podacima iz istra`ivanja i zahtjeva dug period provjera i potvrda.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
98
Veoma va`an detalj je na~in na koji se prikupljaju podaci o potro{nji hrane u doma}instvu, kao i o
tro{kovima nevezanim za hranu. U istra`ivanjima 5 i 6, najbolje informisani ispitanik (naj~e{}e
starija `enska osoba) je davala podatke o utro{enoj koli~ini i vrijednosti hrane koju su svi ~lanovi
doma}instva tro{ili u toku prethodnih 7 dana. Ovdje je bilo obuhva}eno 87 vrsta prehrambenih
proizvoda koji su svrstani u jedan od tri izvora: kupljena hrana, hrana proizvedena u doma}instvu,
hrana dobijena na poklon od drugih doma}instava (za listu prehrambenih proizvoda vidjeti Annex
3). Agregat potro{nje hrane se zasniva na vrijednosti hrane utro{ene za proteklih 7 dana izra`ene u
eurima.
Za proizvode koji nisu hrana, generalno posmatrano, period na koji se odnose tro{kovi varira u
zavisnosti od u~estalosti vr{enja nabavki tih proizvoda. Pojedine potro{a~ke kategorije i periodi za
koje se prikupljaju podaci su prikazani u Tabeli A 2.1.
Tabela A 2.1: Kategorije neprehrambenih proizvoda, ISSP Istra`ivanje o prihodima i
rashodima
Tro{kovi stanovanja
Ra~unanje tro{kova stanovanja radi uklju~ivanja u agregat potro{nje je komplikovanije nego kod
drugih stavki potro{nje. Osoba “u`iva” prostor u kojem stanuje tokom dugog vremenskog perioda.
Prema tome, vrijednost stanovanja koja se uklju~uje u agregat potro{nje treba da odra`ava
vrijednost koju osoba dobije u toku mjesec dana, a ne ukupnu vrijednost stanovanja. Za
doma}instva koja iznajmljuju prostor u kojem stanuju, pretpostavlja se da mjese~na kirija odra`ava
njihove tro{kove stanovanja. Ipak, velika ve}ina doma}instava u Crnoj Gori ne `ive u iznajmljenim
stambenim prostorima. Ova doma}instva ne pla}aju nikakvu eksplicitnu sumu za stanovanje, ali je
jasno da je nivo njihovog bogatstva pove}an ~injenicom da posjeduju prostor za stanovanje. Shodno
tome, moramo da procjenimo implicitnu vrijednost ovog smje{taja.
Grupe artikala Specifi~ne kategorije u istra`ivanju Period za koji se prikupljaju podaci
Li~ne stvari 16 kategorija uklju~uju}i cigarete*,
higijenske proizvode, novine, itd.
prijavljuje se za prethodni mjesec
*prijavljuje se za prethodnih 7 dana
Komunalne usluge 6 kategorije: razna goriva (bez goriva za
automobile), gas, struja, voda, odvo`enje
sme}a i kanalizacija, i telefon
prijavljuje se za prethodni mjesec
Transport 9 kategorija uklju~uju}i gorivo za vozila,
taxi, autobus, voz, itd… prijavljuje se za prethodni mjesec
Ostali mjese~ni
tro{kovi
9 kategorija uklju~uju}i video kasete, CD,
sredstva za ~i{}enje, tro{kove za ku}ne
ljubimce, itd…
prijavljuje se za prethodni mjesec
Oprema u doma}instvu 10 kategorija uklju~uju}i velike komade
namje{taja, popravke ku}e/stana, male
aparate, posteljinu, itd…
prijavljuje se za prethodna 3 mjeseca
Odje}a i obu}a 9 kategorija uklju~uju}i mu{ku odje}u i
obu}u, `ensku odje}u i obu}u, dje~ju odje}u
i obu}u, itd…
prijavljuje se za prethodna 3 mjeseca
Briga o zdravlju 6 kategorija: zubar, ljekar, bolnica, ljekovi,
opti~ka oprema, ostali tro{kovi
prijavljuje se za prethodna 3 mjeseca
Ostali kvartalni
tro{kovi
14 kategorija uklju~uju}i sportsku opremu,
igra~ke, opremu za {ivenje, ~lanarine, briga
o djeci, pokloni, ulaznice za koncerte, nakit,
itd…
prijavljuje se za prethodna 3 mjeseca
Obrazovanje 5 kategorija: tro{kovi upisa i polaganja
ispita, knjige i papir, privatni ~asovi,
{kolarina i drugi tro{kovi.
prijavljuje se za prethodih 12 mjeseci
Ostali godi{nji tro{kovi 2 kategorije: registrovanje automobila i svi
oblici osiguranja. prijavljuje se za prethodnih 12 mjeseci
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
99
Obra~un tro{kova stanovanja vr{i se na osnovu podataka iz tri izvora. Za ona doma}instva koja `ive
u iznajmljenim stanovima/ku}ama, to je prijavljena mjese~na renta koju pla}aju (5,6%
doma}instava). Za vlasnike, to je pripisana renta koju prijavljuju sami vlasnici (87,5%
doma}instava). Pore|enjem tr`i{nih cijena smje{taja prijavljenih od strane doma}instava koja `ive u
iznajmljenim stanovima/ku}ama (po kvadratnom metru u eurima) sa iznosima rente koje su prijavili
vlasnici, do{li smo do zaklju~ka da su procjene vlasnika konzistentne sa tr`i{nim cijenama (ISSP,
2002). Za doma}instva koja `ive u iznajmljenim stanovima/ku}ama ili za doma}instva vlasnike koji
nisu prijavili vrstu rente, ona je procijenjena na osnovu regresija prognozirane rente kori{}enjem
seta karakteristika smje{taja i varijabli lokacije (6,9% doma}instava).
Prilago|avanje razlikama u regionalnim cijenama
Zbog brojnih varijacija cijena, kori{}eni su indeksi cijena radi prilago|avanja nominalnog agregata
potro{nje. Kako se svi kori{}eni podaci odnose na jul i oktobar 2002. godine, za o~ekivati je da
privremena inflacija ne}e biti zna~ajna (iako ovo ne va`i za proizvode koji nisu hrana i koji se ne
kupuju svakog mjeseca). Prostorna prilago|avanja cijena bi bila od interesa u slu~aju da postoje
nagovje{taji regionalnih varijacija cijena. Za kreiranje seta indeksa cijena kori{}eni su zvani~ni
podaci o cijenama iz Zavoda za statistiku. Bili smo u mogu}nosti da koristimo nacionalne i
regionalne podatke o cijenama prehrambenih proizvoda da bismo stvorili regionalne indekse cijena
koji se zasnivaju na udjelu prehrambenih proizvoda u istra`ivanju o prihodima i rashodima
doma}instava za jul i oktobar 2002. godine. Za proizvode koji nisu hrana formirali smo indeks iz
liste od 12 naj~e{}e kupovanih proizvoda i njihove prosje~ne regionalne cijene za dva mjeseca. Ovi
indeksi su prikazani u tabeli A2.2. Cijene su najvi{e u ju`nom dijelu Republike, a potom u
centralnom regionu. Ako izvr{imo prilago|avanje nominalne potro{nje i tro{kova upotrebom
indeksa, primje}ujemo da su promjene u ukupnoj stopi siroma{tva zanemarive.
Tabela A 2.2: Regionalni indeksi cijena
Sjever Jug Centralni
dio
Crna Gora
Indeks cijena prehrambenih
proizvoda 0,983 1,082 1,022 1,000
Indeks cijena proizvoda koji
nisu hrana
0,997 1,014 1,072 1,000
Ukupna potro{nja doma}instva
Ukupan iznos potro{nje i tro{kova doma}instva za prehrambene i neprehrambene proizvode
prikazan je u tabeli A2.3. Zvani~na statistika pokazuje da su izdaci za hranu ~inili najve}i dio
bud`eta doma}instva tokom ‘90-ih godina. Prema podacima Republi~kog zavoda za statistiku
(prikazanih u MONET-u, ISSP) udio tro{kova vezanih za hranu (uklju~uju}i pi}a i cigarete) u
ukupnim tro{kovima doma}instva prelazi 62% u 1999. godini. Ovaj podatak je, iako ne{to vi{i, u
skladu sa nalazima ISSP istra`ivanja o prihodima i rashodima doma}instava. Oko polovine izdataka
doma}instva izdvaja se za hranu i pi}e. Slede}i najve}i izdatak u bud`etu se odnosi na pla}anje
stanarine. Ovi podaci se mogu uporediti sa ne{to ni`im procentom udjela prehrambenih proizvoda u
potro{nji doma}instva u Bosni i Hercegovini (33% u 2001. godini) i u Hrvatskoj (36% u 1998.) dok
tro{kovi stanovanja predstavljaju mnogo ve}i dio u potro{nji (36% u BiH i 32% u Hrvatskoj)
(Svjetska banka 2002 i Luttmer 2002). Na drugoj strani, udio hrane u Srbiji je pribli`no isti (48%,
ali je udio tro{kova stanovanja znatno ni`i (4,6%) (Krsti}, 2003.). Metodologija za obra~un
tro{kova stanovanja kori{}ena u Srbiji se znatno razlikuje od metodologije koja je ovdje kori{}ena,
pa je samim tim pore|enje ote`ano.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
100
Tabela A2.3: Potro{nja i tro{kovi doma}instva
(mjese~no, u eurima)
Prosjek %
Potro{nja hrane i pi}a 417,8 49,2
Li~na potro{nja** 64,0 7,5
Komunalne usluge 49,3 5,8
Transport 44,2 5,2
Oprema u doma}instvu 26,1 3,1
Odje}a i obu}a 46,3 5,5
Briga o zdravlju 7,9 0,9
Tro{kovi obrazovanja 9,0 1,1
Ostali mjese~ni, kvartalni i godi{nji tro{kovi 39,7 4,7
Smje{taj (renta i procjenjena renta za vlasnike) 145,0 17,1
Prosje~na ukupna potro{nja i tro{kovi 849,3 100,00
Broj doma}instava* 1299
Prosje~ni tro{kovi potro{nje po osobi 220.6
* Uzorak u Istra`ivanjima 5 & 6 je 1300, ali nedostaju tro{kovi smje{taja za jedno doma}instvo.
** Ovi podaci ne uklju~uju potro{nju cigareta jer to pitanje nije bilo uklju~eno u
istra`ivanje 5. Prema podacima iz Istra`ivanja 6, prosje~ni izdaci doma}instva za
cigarete iznose oko 27 eura na mjese~nom nivou.
Ocjene ekvivalentne skale
U studijama o siroma{tvu `ivotni standard se obi~no defini{e tako {to se dodjeljuju odre|eni udjeli
ukupnih tro{kova doma}instva (ili prihoda) svakoj osobi u doma}instvu. Kako potrebe variraju
me|u ~lanovima doma}instva i kako postoji ekonomija obima u potro{nji, mjerenje siroma{tva na
osnovu indikatora per capita blagostanja se mogu pokazati kao lo{e procjene. Alternativa je da na{u
mjeru blagostanja baziramo na jedinicama jadnake potro{nje. Ako na{ profil siroma{tva nije pod
uticajem odgovaraju}ih pondera jednake potro{nje koje izaberemo, mo`e se sa sigurno{}u re}i da su
te procjene siroma{tva korektne i da nisu potcijenjene zbog procedure ponderisanja.
Za evaluaciju odgovaraju}e ekvivalentne skale za doma}instva u Crnoj Gori po~injemo sa
jedna~inom:
PAE=(A+αK)θ
gdje PAE predstavlja ekvivalentnu vrijednost veli~ine doma}instva po odraslom, A je broj odraslih,
dok je K broj djece. Parametar α defini{e ponder kojim se vr{i konverzija jednog djeteta u
ekvivalentnu odraslu osobu. Ekonomija obima je izra`ena parametrom θ. Pore|enjem rezultata tako
{to koristimo racionalan opseg vrijednosti parametara testiramo pouzdanost podataka. Neke ~esto
kori{}ene skale ne spadaju u kategoriju ekvivalentnih skala koje su opisane ovom formulom. OECD
je npr. koristio slede}u skalu ekvivalentnosti:
PAEOECD = 1+ (0,5 *
odrasli)
+( 0,3 *
djeca013
)
Veliki broj metoda se koristi za odre|ivanje skale ekvivalentnosti, ali svaka ima nedostatke. Kao
posljedicu toga, veliki broj razli~itih skala ekvivalentnosti se koristi u razli~itim zemljama.
Literatura ukazuje da skala sa jednim parametrom (bazirana na veli~ini doma}instva) ipak daje
prili~no sli~ne rezultate skalama ekvivalentnosti sa dva parametra. Rezultati zasnovani na OECD
skalama daju sli~ne rezultate u odnosu na one koji se dobijaju upotrebom skala sa dva parametra
gdje je vrijednost θ izme|u 0,5–0,6 (Figini 1998).
Postoje na~ini koji omogu}avaju da se identifikuju najpovoljnija prilago|avanja veli~ne
doma}instva. Jedan od pomenutih na~ina po~iva na upotrebi Engelovog metoda. Osnovna
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
101
pretpostavka Engelovog metoda je da izme|u blagostanja doma}instva i izdataka doma}instva za
hranu postoji inverzan i monoton odnos. Prema tome, ova pretpostavka implicira da su dva
doma}instva u jednako dobrom polo`aju ako i samo ako je udio hrane u njihovim tro{kovima
jednak. Ova pretpostavka je diskutabilna, pa se eksperti uglavnom protive kori{}enju ovog metoda45
(na primjer, pogledati Deaton, 1997). Prema tome, svaka procjena kori{}enjem ovog metoda se ne
smije uzeti kao definitivna, ve} kao dio informacija koji mo`e pomo}i u odabiru skale
ekvivalentnosti.
Kori{}ena je slede}a nelinearna regresija koja je ocijenjena metodom nelinearnih najmanjih
kvadrata:
i
iii
i
iDjecaDjecaOdrasli
Potrosnja
UH
ε
αα
ββ
θ
+
++
+= )71806(
ln
21
10 ,
gde je
UH
i
udio hrane u ukupnoj potro{nji doma}instva
i
,
Potro{nja
i
je ukupna potro{nja
doma}instva
i
,
Odrasli
i
je broj odraslih u doma}instvu,
Djeca06
i
je broj djece od 0-6 godina starosti,
Djeca718i je broj djece od 7-18 godina starosti. Gre{ka ocjene je ozna~ena sa i
ε, a parametri
θααββ ,,,, 2110 ocenjuju se iz navedene regresije.
U Srbiji (Krsti}, 2003) kori{}ena je slede}a jedna~ina:
Srpska skala = (1 + 0.81*(Odrasli-1) + 0.24*Djeca06 + 0.75*Djeca718).
Za Crnu Goru, kori{}en je isti model: kori{}ena je metoda nelinearnih najmanjih kvadrata za
ukupan uzorak doma}instava u istra`ivanju. Procjene su prikazane u Tabeli A3.2.
Koeficijent za malu djecu pokazuje da su ona “skuplja” od odraslih , dok je koeficijent za djecu od
7 do 18 godina starosti blizu 1. Kako je θ blizu 1, odnosno malo ispod 1, to ukazuje na neku
ekonomiju obima. Standardna gre{ka procjene θ je dovoljno velika da ne mo`emo odbaciti nultu
hipotezu da je θ jednako jedinici. Udio hrane opada kako bogatstvo raste (negativan predznak β1).
Vrijednost prekida (blizu jedan) tako|e potvr|uje o~ekivanje da }e najsiroma{nije porodice tro{iti
veliki dio ukupnih tro{kova na hranu. Ipak, obja{njavaju}a mo} regresije je veoma slaba, ukazuju}i
na zna~ajne varijacije u podacima koje ote`avaju odre|ivanje ta~nog odnosa. Zaklju~ujemo da
procjene ukazuju na kori{}enje proste linearne per capita skale ekvivalencije kao na{e
prioritetne
procjene
.
Tabela A2.4: Procjene za skale ekvivalentnosti kori{}enjem Engelovog metoda
α1 2,105
(1,010)
α2 1,169
(0,490)
θ 0,936
(0,166)
β0 0,803
(0,052)
β1 -0,058
(0,009)
Prilago|en R2 0,044
Broj opservacija 1299
Napomena: Standardne gre{ke u zagradama
45 Vidjeti Deaton, Angus, 1997, The Analysis of Househol Surveys: A Macroeconomic Approach to Development and
Policy, Baltimore, MD: Johns Hopkins University Press.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
102
Osjetljivost na skalu ekvivalentnosti
Upotreba razli~itih skala sa ciljem prilago|avanja veli~ine doma}instva je veoma va`na s obzirom
da mo`e uticati na promjenu sveukupnog rangiranja doma}instava. Iz tog razloga, va`no je ocijeniti
osjetljivost profila siroma{tva na razli~ita prilago|avanja veli~ini doma}instva koja, po svemu
sude}i, sa razlogom po~iva na ekonomiji obima i jedinici jednake potro{nje. Definisanjem fiksne
stope siroma{tva na nivo od 20%, grafik 2.1 pokazuje stopu siroma{tva razli~itih grupa kada se
upotrebljavaju razli~ite skale. Kori{}eno je pet skala: per capita, ekonomija obima 0,9 (bez
prilago|avanja za jedinicu ekvivalentne potro{nje), skala koja je kreirana u Srbiji u okviru njihove
procjene siroma{tva (uklju~ni i ekonomija obima i jedinica jednake potro{nje), OECD skala, i na
kraju, ekonomija obima 0,5. Grafik 2.2 pokazuje udio najsiroma{nijih 20% kada se upotrebljavaju
razli~ite skale.
Profil siroma{tva je zna~ajno sna`an za razli~ite skale. U ve}ini slu~ajeva, profil siroma{tva se ne
mijenja dok se ekstremnije skale (OECD ili ekonomija obima od 0,5) ne primijene. Djeca, velika
doma}instva i doma}instva na sjeveru Crne Gore suo~avaju se sa pove}anim rizikom potpadanja
ispod linije siroma{tva kada se koriste najrealnije skale. Sa druge strane, kao dio siroma{nih, djeca i
oni koji `ive u velikim doma}instvima ne predstavljaju veliki dio ukupne populacije 20%
najsiroma{nijih, bez obzira na skalu koja se koristi.
Grafik 2.1: Stope siroma{tva uz upotrebu alternativnih skala
(siroma{tvo fiksirano na nivou od 20%)
0%
5%
10%
15%
20%
25%
30%
per
capita
EO .9 Srbija OECD EO .5
Procenat u najni`em kvintalu
djeca 0-15
stariji 65+
0%
5%
10%
15%
20%
25%
30%
per
capita
EOS .9 Serbian OECD EOS .5
Procenat u najni`em kvintalu
`ena glava
doma}instva
mu{karac glava
doma}instva
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
103
0%
5%
10%
15%
20%
25%
30%
35%
per
capita
E O S . 9 Se r b i a n OE CD E O S . 5
Procenat u najni`em kvintalu
Veli~ina do ma}instva
1-3
Veli~ina do ma}instva
4+
0%
5%
10%
15%
20%
25%
30%
35%
per
capita
EO .9 Srbija OECD EO .5
Procenat u najni`em kvintalu
Sj e v e r
Cen t ar
Jug
Grafik 2.2: Udio siroma{nih uz upotrebu alternativnih skala
(siroma{tvo fiksirano na nivou od 20%)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
per
capita
EO .9 Srbija OECD EO .5
odrasli 16-64
star iji 65+
djeca 0-15
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
per capita
EOS .9
Serbian
OECD
EOS .5
mu{karac glava
doma}instva
`ena glava
doma}instva
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
104
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
per capita
EOS .9
Serbian
OECD
EOS .5
Veli~ina
doma}instva 4+
Veli~ina
doma}instva 1-3
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
per
capita
EO .9 Srbija OECD EO .5
Jug
Cent ar
Sje v e r
ANNEX 3: Linija siroma{tva
U praksi, ne postoji jedinstvena mjera za utvr|ivanje siroma{tva ve} se koristi vi{e razli~itih
indikatora, {to u stvari reflektuje dvije osnovne uloge koje ima linija siroma{tva. Prva uloga linije
siroma{tva je da se utvrdi koji su to `ivotni uslovi koji kada se ostvare ~ine da se osoba vi{e ne
smatra “siroma{nom”. Druga uloga definisane linije siroma{tva je da se omogu}e razli~ita
poredjenja: poredjenja linija siroma{tva porodica razli~itih veli~ina i struktura, porodica koje `ive
na razli~itim mjestima, poredjenja u vremenu koja nam govore koliki su izdaci potrebni u razli~itim
okolnostima da bi se ostvario minimum potreba i izbjeglo siroma{tvo.
Cilj nam je da izra~unamo apsolutnu i relativnu liniju siroma{tva koja nam omogu}ava da
uporedimo uslove `ivota jednog dijela stanovni{tva sa drugim, kako u okviru granica jedne dr`ave
tako i na me|unarodnom planu.
Linija siroma{tva
je vrijednost potro{nje (prihoda) ispod koje bi se osoba smatrala siroma{nom od
strane dru{tva u kom `ivi. Linije siroma{tva se mogu postaviti na razli~ite na~ine u zavisnosti od
svrhe i potreba. Ovdje }emo razmotriti razliku izme|u apsolutnih i relativnih linija siroma{tva.
Apsolutna linija siroma{tva
: Apsolutna linija siroma{tva, kao {to joj i ime govori, ne mjeri
siroma{tvo u odnosu na druge nivoe bogatstva ve} umjesto toga nastoji da defini{e vrijednost
potro{nje koja je potrebna bilo kojoj osobi bez obzira na vrijeme i mjesto. Naj~e{}e kori{}ena
apsolutna linija siroma{tva je ona koja se zasniva na potro{nji hrane. Nutricionisti su postavili
minimum prehrambenih zahtjeva uzimaju}i u obzir godine, pol i nivo napora pojedinca. Koriste}i
ove prihva}ene minimalne zahtjeve, tro{ak apsolutne linije siroma{tva hrane se defini{e kao
nov~ana vrijednost koja je neophodna da se ispune ove minimalne norme.
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
105
Bez obzira na apsolutne potrebe, ljudi mogu sebe smatrati siroma{nim kada im je `ivotni standard
znatno ispod standarda ostalih u njihovoj dr`avi. Ovaj oblik siroma{tva se izra`ava
relativnom
linijom siroma{tva,
koja defini{e siroma{tvo u pore|enju sa ”tipi~nim” nacionalnim standardom
`ivota.
Ipak, relativna linija siroma{tva ima jedan veliki neodstatak: na osnovu nje nije mogu}e pratiti
promjene tokom vremena; relativne ocjene siroma{tva tokom vremena unose zabunu prilikom
ocjene promjena nejednakosti i promjena siroma{tva. Takodje, ukoliko u datoj zemlji postoji
zna~ajan dio populacije koji `ivi ispod linije siroma{tva, relativna linija siroma{tva ovo ne}e
obuhvatiti.
U cjelini gledano, apsolutna i relativna linija siroma{tva slu`e u razli~ite srvhe. U mjeri u kojoj se
siroma{tvo posmatra kao nedostatak osnovnih artikala, ~iji nedostatak treba da bude smanjen i
progres koji se u tome pravi da bude predmet monitoringa tokom vremena, potrebno je koristiti
apsolutnu
liniju siroma{tva. Ovo je zasigurno slu~aj u Crnoj Gori. Ipak, kako Crna Gora ima
namjeru da se priklju~i EU, ima smisla objavljivati
relativne
pokazatelje siroma{tva, kao dodatak
apsolutnim, kako bi se omogu}ila uporedivost sa izvje{tajima EU zemalja i zemalja kandidata.
Minimalni `ivotni standard koji se koristi za identifikovanje siroma{nih se bazira na vrijednosti
minimalne korpe hrane plus tro{kovi proizvoda koji nisu hrana a koji se tako|e smatraju
neophodnim. Minimalna potro{a~ka korpa se zasniva na standardu od 2288 kalorija dnevno po
osobi. Vrijednost ove korpe proizvoda se onda ra~una na osnovu podataka o cijenama.
Linija siroma{tva hrane
Minimum `ivotnog standarda u eurima se bazira na vrijednosti minimalne korpe hrane. Ova
minimalna potro{a~ka korpa se bazira na standardu od unosa 228846 kalorija dnevno po osobi.
Vrijednost ove korpe prehrambenih proizvoda se potom ra~una na osnovu podataka o cijenama.
Ovo je linija siroma{tva hrane. Linija siroma{tva hrane se oslanja na tri izvora podataka:
1. podaci o potro{a~kim obrazcima radi alokacije kalorija u razli~itim prehrambenim
proizvodima koji se zasnivaju na izabranom reprezentativnom dijelu populacije;
2. podaci o broju kalorija koji sadr`i svaki pojedina~ni prehrambeni proizvod;
3. podaci o cijenama kako bi se dobila monetarna cijena potro{a~ke korpe.
Minimalnu potro{a~ku korpu zasnivamo na obrazcima potro{nje doma}instava iz istra`ivanja koja
predstavljaju 15%47 doma}instava sa najni`om potro{njom i tro{kovima per capita. Za ovu
populaciju smo izra~unali polovinu srednjeg unosa (kvantitativno, obi~no u kilogramima) za svaki
prehrambeni proizvod48. Koli~ina kalorija za 86 prehrambenih proizvoda (isklju~uju}i kategoriju
”ostala hrana”) u istra`ivanju se zasniva na USDA (2002). Koriste}i ove dvije grupe podataka,
primijenjena je procedura optimizacije koja uspostavlja minimalnu koli~inu za svaki prehrambeni
proizvod kako bi se dostigao nivo od 2288 kalorija dnevno po osobi i odr`ali potro{a~ki obrasci kod
potro{a~ke korpe odre|ene grupe stanovni{tva. Kona~no, podaci o cijenama iz Zavoda za statistiku
se koriste za dobijanje cijene ove korpe. Ovo je linija siroma{tva hrane.
Tabela A 3.1 pokazuje srednje koli~ine u okviru odgovaraju}e populacije i minimalne koli~ine i
iznose u eurima za svaki od 86 prehrambenih proizvoda u potro{a~koj korpi.
46 U cilju dobijanja podataka i rezultata koji su uporedivi sa rezultatima u regionu, u Crnoj Gori koristimo isti standard
koji je kori{}en u Srbiji.
47 Linija siroma{tva hrane iznosi oko 41 euro. Ovo je grubi prosjek tri procijenjene linije siroma{tva hrane: 42,26 eura
za 20% referentnog stanovni{tva, 41,0 eura za 15% i 40,15 eura za 10% referentne populacije).
48 Kada smo uzimali ta~nu koli~inu unosa, nivo potro{nje je bio 100% iznad minimuma za sve proizvode i procedura
optimizacije nije funkcionisala.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
106
Tabela A3.1: Minimalna potro{a~ka korpa
Odgovaraju}a populacija Minimalna korpa
Proizvod
Prosje~na
koli~ina
(per capita) kalorije
Cijena
(prosjek iz
jula i oktobra,
2002) Per capita
koli~ina Euro
Bra{no 6,40 3239,5 0,52 4,528 2,35
Kukuruzno bra{no 0,42 3496 0,75 0,294 0,22
Pahuljice za doru~ak 0,01 3630 1,33 0,007 0,01
Pirina~ 0,34 3573,9 1,18 0,237 0,28
Tjestenina 0,57 3420 2,27 0,406 0,92
Hljeb 6,61 2610 0,68 4,672 3,18
Kifle 0,12 3560 0,2 0,088 0,02
Ostali pekarskip roizvodi 0,17 3000 0,83 0,121 0,10
Paradajz 1,13 180,5 0,59 0,796 0,47
Krompir 3,47 651 0,37 2,452 0,91
Crni luk 0,53 312,8 0,82 0,374 0,31
Zelena salata 0,06 88,4 0,96 0,043 0,04
Pasulj 0,48 356,4 2,21 0,338 0,75
Krastavac 0,66 100,1 0,58 0,466 0,27
Spana} 0,12 187 1,11 0,088 0,10
Kupus 0,72 136 0,41 0,508 0,21
Gra{ak 0,14 394,8 1,12 0,098 0,11
Paprika 0,85 192,5 0,89 0,599 0,53
[argarepa 0,31 34,8 1,03 0,217 0,22
Pe~urke 0,01 24,3 3,25 0,004 0,01
Karfiol 0,03 97,5 1,25 0,018 0,02
Ostalo svje`e povr}e 0,08 146,2 0,93 0,058 0,05
Smrznuto povr}e 0,01 700 1,82 0,005 0,01
Pomorand`e 0,30 338,4 1,36 0,215 0,29
Jabuke 1,75 542,8 1,02 1,240 1,26
Breskve 0,35 374,1 1,08 0,246 0,27
Banana 0,97 588,8 0,92 0,686 0,63
Orasi/lje{nik 0,03 5265 8,06 0,018 0,14
Gro`|e 0,14 388,6 1,99 0,099 0,20
Lubenica 1,55 140,8 0,26 1,096 0,28
Jagode 0,00 282 1,48 0,000 0,00
Tre{nja/Vi{nja 0,00 450 1,71 0,001 0,00
Limun 0,24 185,6 1,34 0,171 0,23
Ostalo svje`e vo}e 0,12 264,6 1,16 0,083 0,10
Smrznuto vo}e 0,00 460 1,6 0,003 0,00
Konzervirano povr}e 0,10 840 1,51 0,072 0,11
Konzervirano vo}e 0,01 423,2 1,75 0,005 0,01
D`emovi 0,32 2340 2,27 0,223 0,50
Med 0,11 3040 4,88 0,078 0,38
Ostalo konzervirano povr}e 0,00 2641 2,35 0,000 0,00
Teletina 0,89 993,6 6,16 0,626 3,86
Svinjetina 0,24 866,4 5,3 0,167 0,89
Jagnjetina 0,18 915 5,59 0,125 0,70
Piletina 0,86 917,4 2,57 0,609 1,56
Kobasica 0,10 3133,1 4,95 0,069 0,34
Slanina 0,14 8820 6,32 0,101 0,64
Suhomesnati proizvodi 0,31 3110 5,62 0,216 1,21
[unka 0,05 2250 6,78 0,034 0,23
Konzervirano meso 0,00 5360 5,67 0,000 0,00
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
107
Odgovaraju}a populacija Minimalna korpa
Proizvod
Prosje~na
koli~ina
(per capita) kalorije
Cijena
(prosjek iz
jula i oktobra,
2002) Per capita
koli~ina Euro
Ostalo meso 0,01 1449 4,47 0,009 0,04
Jaja 16,33 758,4 0,12 11,547 1,33
Svje`a riba 0,10 356 3,48 0,074 0,26
Smrznuta riba 0,06 615 5 0,039 0,20
Konzervirana riba 0,01 2380 6,01 0,006 0,04
Svje`e mlijeko 8,61 610 0,48 6,091 2,92
Jogurt 1,79 610 0,97 1,265 1,23
Mlijeko u prahu 0,09 4960 5,24 0,065 0,34
Sir 1,07 3514,5 3,09 0,754 2,32
Kajmak 0,09 3490 6,24 0,063 0,39
Sladoled 0,03 4170 2 0,019 0,04
Ostali mlije~ni proizvodi 0,00 2118,6 5,64 0,000 0,00
Puter 0,02 7170 4,91 0,016 0,08
Margarin 0,11 7190 1,93 0,079 0,15
Mast 0,13 9000 1,77 0,090 0,16
Maslinovo ulje 0,01 8500 4,34 0,007 0,03
Biljno ulje 1,13 8840 1,07 0,797 0,85
Ostala ulja 0,01 8840 2,01 0,009 0,02
So 0,33 0 0,49 0,235 0,11
[e}er 0,84 4000 0,66 0,593 0,39
Za~ini 0,12 2890 3,4 0,084 0,29
Kafa 0,28 20 5,14 0,196 1,01
^aj 0,03 10 0,51 0,020 0,01
Ostali za~ini 0,01 3000 2,24 0,006 0,01
Gazirana pi}a 0,76 410 0,82 0,535 0,44
Vo}ni napici 0,56 1100 1,59 0,395 0,63
Mineralna voda 0,71 0 0,43 0,501 0,22
Vino 0,06 1260 2,15 0,041 0,09
Pivo 1,07 410 0,74 0,759 0,56
Liker 0,01 2310 4,72 0,004 0,02
Ostala pi}a 0,08 340 5,08 0,057 0,29
^okolada 0,09 4000 6,96 0,067 0,46
Bombone 0,04 5520 3,55 0,030 0,11
Keks i kola~i}i 0,16 3210 3,01 0,111 0,33
Ostali slatki{i 0,34 4020 2,21 0,240 0,53
Polupripremljena hrana 0,00 3200 3,98 0,000 0,00
Hrana za beeb 0,05 780 5,3 0,036 0,19
Ukupno mjese~no po osobi:
Prehrambena linija
siroma{tva 2288 41,00
Ukupno, godi{nje po osobi 492,01
Pore|enje potro{a~kih korpi
Kao {to je re~eno u poglavlju II glavnog teksta, postoje alternativne potro{a~ke korpe koje su
kori{tene za identifikovanje iznosa novca koji je neophodan za kupovinu minimalnog standarda
kalorija. Ovo obuhvata i potro{a~ku korpu Saveznog zavoda za statistiku, kao i OCHA potro{a~ku
korpu. Razlike u liniji siroma{tva hrane koju koriste razli~ite grupe }e zavisiti od sadr`aja
potro{a~ke korpe (posebno, distribucija me|u prehrambenim proizvodima koji imaju razli~ite cijene
po kaloriji), minimalnih standarda koje korpa treba da zadovolji (u vidu kalorija i drugih
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
108
nutricionisti~kih kriterijuma) {to ima uticaj na koli~inu svakog pojedinog prehrambenog proizvoda
u korpi i na cijene koje se koriste da se procijeni cijena korpe. Uzimaju}i u obzir jedan od ovih
faktora, distribuciju ukupnih kalorija u korpi, korpa Saveznog zavoda za statistiku i korpa kori{tena
u Srbiji se mogu porediti sa korpom koja je kori{tena u ovom istra`ivanju. (Detalji o OCHA korpi
nisu dostupni). Treba napomenuti da je ovo pore|enje samo djelimi~na evaluacija razlika u linijama
siroma{tva hrane, jer ignori{e koli~ine u korpi (postavljena je tako da se dostigne standard u
kalorijama koji varira) i cijene koje su kori{}ene.
Tabela A3.2 pokazuje da korpa Saveznog zavoda za statistiku (SZS) alocira ve}i dio kalorija u
minimalnoj potro{a~koj korpi na skuplju hranu (gdje se ”skupo” odnosi na cijenu po kaloriji): meso
i mlije~ne proizvode). Na drugoj strani, potro{a~ka korpa u Srbiji koju je koristila Krsti} (2002)
izgleda veoma sli~no onoj koju smo mi izra~unali za Crnu Goru. Ovo je konzistentno sa razvojem
potro{a~ke korpe. I crnogorska i srbijanska korpa prikazane u tabeli A3.2 su determinisane na
osnovu obrazaca potro{nje stanovni{tva sa ni`im dohodkom kao {to je to izra`eno i u skoro
kori{tenim istra`ivanjima o prihodima i rashodima doma}instava. Sa druge strane, korpa Saveznog
zavoda za statistiku nije razvijena na osnovu novijih obrzaca potro{nje stanovni{tva.
Tabela A3.2: Udio kalorija u prehrambenoj korpi po pojedinim grupama
prehrambenih proizvoda
Grupa prehrambenih proizvoda
Crna Gora
SZS Srbija
(Krsti}, 2002)
Bra{no, hljeb, tjestenina 44,3 30,2 43,5
Povr}e 3,3 5,6 6,3
Vo}e 3,5 4,2 4,0
Meso 4,8 8,5 3,9
Riba 0,1 0,1 0,0
Mlije~ni proizvodi i jaja 23,7 35,7 16,0
Buter i mast 12,5 8,7 14,4
Pi}a 1,5 0,5 5,0
Ostalo (ostali za~ini, hrana za
bebe, itd.)
6,4 6,5 7,0
Izvor: prora~uni autora
Ukupna linija siroma{tva
U cilju definisanja ukupne linije siroma{tva, moramo definisati minimalnu potro{nju, odnosno
izdatke za proizvode koji nisu hrana. Na`alost, za ove proizvode nemamo pojam minimalnog
standarda kao {to je to unos kalorija za hranu. Postoji nekoliko metoda koje se koriste da se odredi
minimalna korpa neprehrambenih proizvoda, a svaka od njih se oslanja na pripisivanje minimalnih
potreba za hranom i ukupnih izdataka u podacima iz istra`ivanja. Za odre|ivanje minimalnog
standarda za tro{kove koji se izdvajaju za proizvode koji nisu hrana, koristili smo metod
postavljanja ”gornje granice” za neprehrambene izdatke. Zbir iznosa linije siroma{tva hrane i
minimuma neophodnog za obezbje|ivanje proizvoda koji nisu hrana, dobijamo ukupnu liniju
siroma{tva. Na osnovu na{e linije siroma{tva hrane koja iznosi 41 euro po osobi za mjesec dana,
ukupna linija siroma{tva (hrana i ne-hrana) procijenjena je ocjenom medijana neprehrambene
potro{nje onih ~ija je potro{nja za hranu na nivou definisane linije siroma{tva hrane. U ovoj studiji,
koristi}emo liniju siroma{tva na nivou od 107 eura po osobi na mjese~nom nivou (41 euro za hranu
i 66 za proizvode koji nisu hrana i usluge).
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
109
ANNEX 4: Indikatori siroma{tva i nejednakosti
Indikatori siroma{tva
Siroma{tvo je vi{edimenzionalni koncept koji uklju~uje razli~ite aspekte blagostanja. Postoji mnogo
literature koja se bavi mjerenjem siroma{tva. U ovoj studiji, najvi{e su kori{}ena tri indikatora. Ove
mjere su ~lanovi klase razlo`enih mjera siroma{tva koje su predlo`ili Foster, Greer i Thorbecke
(1984)49. To su:
(i) indeks siroma{tva, P0, mjeri prisustvo siroma{tva
(ii) jaz siroma{tva, P1, mjeri dubinu siroma{tva
(iii) o{trina siroma{tva, P2, mjeri o{trinu siroma{tva
(i) Indeks siroma{tva
Indeks siroma{tva, istovremeno i najjednostavnija mjera siroma{tva, predstavlja procenat ljudi ~ija
je potro{nja per capita ni`a od definisane linije siroma{tva. Ako
q
osoba ima potro{nju per capita
ispod linije siroma{tva, a ukupno ima
n
ljudi, tada je
P0 =
q
/
n
Iako P0 daje informaciju o tome koliko je ljudi siroma{no, on ne pokazuje kako su oni siroma{ni.
Jednaka “te`ina” siroma{tva se pripisuje siroma{noj osobi bez obzira da li nivo potro{nje
predstavlja 1% linije siroma{tva (ekstremno siroma{tvo) ili 99% linije siroma{tva (pribli`no
nesiroma{nom statusu). Ukoliko siroma{ne osobe postaju vremenom bogatije, ali njihova potro{nja
i dalje ostaje ispod stalne linije siroma{tva, tada P0 pru`a pogre{an utisak da nije do{lo ni do kakvih
promjena u uslovima `ivota siroma{nih.
(ii) Dubina siroma{tva: indeks jaza siroma{tva
U cilju utvr|ivanja dubine siroma{tva koristimo indeks jaza siroma{tva. Jaz siroma{tva pravi
razliku izme|u ljudi prema tome koliko je njihova potro{nja ispod linije siroma{tva. Ako je
y
potro{nja (per capita)
i-
te siroma{ne osobe, a
z
linija siroma{tva, tada je
z
yz
n
Pi
q
i
)(
1
1
1
−
=∑
=
P1 mjeri prosje~an manjak siroma{tva me|u stanovni{tvom (nesiroma{ni imaju manjak jednak nuli)
kao procenat od linije siroma{tva. Prema tome, on predstavlja mjeru dubine siroma{tva. P1 se
ponekad koristi za ra~unanje finansijskih tro{kova eliminisanja siroma{tva, pod pretpostavkom
perfektno ciljanih transfera. Finansijski tro{ak se ra~una kao suma manjaka siroma{tva, obi~no
izra`enih kao procenat GDP-a. U praksi, propusti i podsticajni efekti }e pove}ati stvarne finansijske
tro{kove eliminisanja siroma{tva kroz transfere.
(iii) O{trina siroma{tva
Nedostatak P1 indeksa je to {to je neosjetljiv na distribuciju siroma{nih. P2 mjera daje vi{e zna~aja
pojedincima koji se nalaze dalje od linije siroma{tva. To je ponderisana suma jazova siroma{tva,
gdje su sami jazovi siroma{tva od zna~aja. Ovaj indikator mjeri stepen nejednakosti u distribuciji
ispod linije siroma{tva, daju}i ve}i zna~aj doma}instvima na dnu distribucije potro{nje.
49 Foster, J., J. Greer and E. Thorbecke (1984) “A Class of Decomposable Poverty Measures,” Econometrica, 761-766.
@ivotni standard i siroma{tvo u Crnoj Gori u 2002. godini
Svjetska banka, Washington DC
110
2
2
1
)(1
2z
yz
n
Pi
q
i
−
=∑
=
Mjere nejednakosti
Mjere siroma{tva se fokusiraju na situaciju pojedinaca ili doma}instava koja se nalaze na dnu
distribucije prihoda; ovo obi~no zahtijeva informacije i o prosje~nom nivou prihoda/potro{nje kao i
o njegovoj distribuciji na donjem kraju. Nejednakost je, sa druge strane, {iri koncept koji je
definisan preko cijele populacije, a ne samo za populaciju ispod odre|ene linije siroma{tva. Ve}ina
indikatora nejednakosti ne zavisi od prosje~ne vrijednosti distribucije, i ova karakteristika
nezavisnosti prosje~ne vrijednosti smatra se po`eljnom karakteristikom indikatora nejednakosti.
Ponekad nas vi{e interesuje da izmjerimo nejednakost nego samo siroma{tvo. Najjednostavniji
na~in da se po~ne je da se stanovni{tvo podijeli na petine (kvintale) od najsiroma{nijih do
najbogatijih, i da se odrede nivoi ili djelovi prihoda (ili tro{kova) koji pripadaju svakom nivou.
Naj~e{}e kori{}ene mjere nejednakosti su:
(i) Gini koeficijent nejednakosti
(ii) Decil odnos disperzije
(iii) Generalizovane mjere entropije
(iv) Atkinsonove mjere nejednakosti
Ovdje koristimo prve dvije mjere. Najvi{e kori{}ena pojedina~na mjera nejednakosti je Gini
koeficijent. Gini koeficijent se zasniva na Lorencovoj krivi, kumulativnoj krivi u~estalosti koja
poredi distribuciju odre|ene varijable (npr. prihoda) sa jedinstvenom distribucijom koja predstavlja
jednakost. Da bi se konstruisao Gini koeficijent, treba nanijeti kumulativne procente doma}instava
(od siroma{nih do bogatih) na horizontalnu osu i kumulativne procente tro{kova (prihoda) na
vertikalnu osu. Ovako dobijamo Lorencovu krivu koja je prikazana na grafiku 5.1. Dijagonalna
linija predstavlja potpunu jednakost. Gini koeficijent se defini{e kao A/(A+B), gdje A i B imaju
vrijednosti koje su prikazane na grafiku. Ako je A=0, Gini koeficijent postaje 0, {to predstavlja
potpunu jednakost. Suprotno, ako je B=0 tada je Gini koeficijent 1, {to predstavlja potpunu
nejednakost.
Lorencova kriva
0
10
20
30
40
50
60
70
80
90
100
0 20406080100
Kumulativan % stanovni{tva
Kumulativan % tro{kova
Grafik 4.1: Lorencova kriva
A
B
Living Standards and Poverty in Montenegro 2002
Institute for Strategic Studies and Prognoses, Podgorica, Montenegro
111
Neka je
x
i
ta~ka na x-osi, i
y
i
ta~ka na y-osi. Tada je:
.))((1
1
11
∑
=
−− +−−= N
i
iiii yyxxGini
Ako postoji N jednakih intervala na x-osi, tada dobijamo prostiji izraz:
.)(
1
1
1
1
∑
=
−
+−= N
i
ii yy
N
Gini
Gini koeficijent nije u potpunosti zadovoljavaju}i. Da bi ovo uvidjeli, moramo imati u vidu
kriterijume koji predstavljaju dobru mjeru nejednakosti prihoda. To su:
•
Nezavisnost prosje~ne vrijednosti
. Ovo zna~i da ako se prihod duplira, mjera se ne}e
promijeniti. Gini zadovoljava ovaj kriterijum.
•
Nezavisnost veli~ine populacije
. Ako bi se populacija promijenila, mjera nejednakosti se ne
bi promijenila, ceteris paribus. Gini zadovoljava i ovaj kriterijum.
•
Simetrija
. Ako vi i ja zamijenimo prihode, ne bi trebalo da do|e ni do kakvih promjena u
mjeri nejednakosti. Gini zadovoljava ovaj kriterijum.
•
Osjetljivost Pigou-Dalton transfera
. Pod ovim kriterijumom, transfer prihoda od bogatih ka
siroma{nima smanjuje mjerenu nejednakost. Gini zadovoljava i ovaj kriterijum.
•
Statisti~ka provjerljivost
. Treba biti u mogu}nosti da se testira zna~aj promjena indeksa u
vremenu. Ovo danas predstavlja manji problem nego nekada zbog intervala povjerenja koji
se mogu dobiti kori{}enjem razli~itih tehnika.
Pored toga, po`eljno je da karakteristika
razlo`ivosti
postoji, {to zna~i da bi u tom slu~aju
nejednakost bez problema mogla da bude dekompozirana prema grupama populacije, izvorima
prihoda i drugim dimenzijama. Gini indeks se ne mo`e razlo`iti ili sabirati kroz razli~ite grupe.
Odnosno, ukupan Gini za dru{tvo kao cjelinu nije jednak zbiru Gini indeksa podgrupa tog dru{tva.
Jednostavna i ~esto kori{}ena mjera je decil odnos disperzije, koji predstavlja koli~nik prosje~no
potro{enog prihoda/potro{nje 10% najbogatijih u populaciji i prosje~nog prihoda/potro{nje 10%
najsiroma{nijih. Ovaj koli~nik se mo`e ra~unati i za druge procente (npr. dijeljenjem prosje~ne
potro{nje 5% najbogatijih – 95. procenat – sa 5% najsiroma{nijih – 5. procenat).
Decil odnos je jednostavan za interpretiranje, tako {to se prihod/potro{nja prvih 10% (“bogati”)
izra`ava kao umno`ak prihoda/potro{nje onih u najsiroma{nijem decilu (“siroma{ni”). Ipak, on
ignori{e informacije o prihodu u sredini distribucije prihoda; tako|e ne koristi ni informacije o
distribuciji prihoda u okviru gornjih i donjih decila. Sa druge strane, kao instrument monitoringa
siroma{tva, na neki na~in je ipak mnogo lak{i za upotrebu i korisniji nego Gini koeficijent. Dok je
Gini indeks osjetljiv na promjene kroz cijelu distribuciju, on mo`e biti i mnogo vi{e osjetljiv na
promjene koje se de{avaju na sredini i mo`e potpuno da previdi promjene koje poga|aju siroma{ne.
