Российская академия наук институт международных экономических и политических исследований модели системной трансформации и социальная цена реформ (опыт России, СНГ и стран цве)
| Вид материала | Документы |
Содержание7. The MONEE project MONEE Topics and variables Coverage by Country in TransMONEE Database 2003 |
- Российская академия наук институт международных экономических и политических исследований, 2692.27kb.
- Российская академия наук институт международных экономических и политических исследований, 2837.49kb.
- Российская академия наук институт международных экономических и политических исследований, 3986.17kb.
- Российская Академия Наук институт международных экономических и политических исследований, 2718.17kb.
- Терроризм как угроза в системе международной безопасности: особенности современного, 101.81kb.
- Иммиграция населения как фактор экономического развития ( на примере развитых стран), 595.95kb.
- В. И. Вернадский российская академия естественных наук, 56.62kb.
- Программа спецкурса " опыт российских реформ в зеркале общественного мнения" для студентов, 212.59kb.
- Данной статьи хроника рыночной реформы в одном богатом постколхозе Юга России, анализ, 247.25kb.
- Российская академия наук санкт-петербургский научный центр ран институт лингвистических, 13.04kb.
The most noteworthy feature of Table 4 is that, consistently, the countries of Central and South-Eastern Europe are ranked higher on the HDI than their per capita GDP rankings, a difference of 3 places in the case of Slovenia, and a full 15 places in the case of Macedonia. This can be traced to the positive human development legacy of socialism or communism in terms of higher levels of education and health care than GDP would predict.
UNDP uses two Human Poverty Indices. HPI-1 is calculated on the basis of five measures: life expectancy; access to improved water sources; adult literacy; under 5’s weight; and poverty (based on less than $1, less than $2 per day and national lines). HPI-2 is based on life expectancy, adult functional literacy, long-term unemployment rate, and income poverty (less than 50% of median income; less than $11 a day; less than $4 a day). The countries of SEE are, however, included neither in HPI-1 nor in what would seem to be the more appropriate HPI-2, largely because of lack of data. HPI-2, whilst combining absolute and relative income poverty measures, comes closest to some of the EU Laeken indicators.
The HDI appears to have a high level of validity and objectivity and allows for systematic long-term comparisons between countries and over time. It remains less well suited to transition countries and, in particular, the failure to utilise any HPI measure for the countries of SEE is a major problem. There is, also, little public awareness of the HDI nor does it link with policy processes.
7. The MONEE project
UNICEF established the Innocenti Research Centre (IRC), formerly known as the International Child Development Centre (ICDC), in 1988. It focuses on research, monitoring and policy analysis to promote the effective implementation of the CRC in developing and industrialised countries. The MONEE (Monitoring in CEE, the CIS and the Baltics) project initiated in 1992 is the most extensive and most influential source of comparative data. They offer an analysis of the situation of children, women, and the population as a whole, in the post-socialist countries of Central, Eastern and South-Eastern Europe and the former Soviet Union, gradually including more countries until, in 1998, all 27 countries were included.
From 1993 onwards annual Regional Monitoring Reports, now renamed Social Monitors, have been published, combining comparative data and incisive analysis of the social and economic impacts of transition, with each report highlighting a particular theme. The earlier reports, in particular, chronicled a serious mortality and health crisis facing many of the countries of the region, and warned of a societal crisis of “unexpected proportions, unknown implications, and uncertain solutions.” Later reports emphasised the divergence in welfare between the countries of Central and Eastern Europe and the Baltic States, on the one hand, and the CIS and Central Asian FSU Republics, on the other hand. Throughout, the project utilised theoretical insights to seek to explore and explain causalities and to suggest alternative policy options28, with specific issues explored in greater depth in Innocenti Occasional Papers, now re-named Working Papers.
The MONEE project utilises secondary data collected by respondents within the central National Statistical Office of each country. The large amount of data collected, some of it otherwise unused, is then filtered by Innocenti researchers to maximise its analytical value and statistical credibility. Importantly, a more extensive data set than that produced in the statistical annexes is made publicly available in a user-friendly format in the annual TransMONEE database29.
The list of topics and number of variables within each, in the 2003 Social Monitor and TransMONEE database, is shown in table 5. The TransMONEE database is not quite as extensive as it appears, since the same data sometimes appears twice, once as a crude number, and once as a rate (per 100,000 children for example).
Table 5
MONEE Topics and variables
Topic | Social monitor | TransMONEE |
| 1. Population | 7 variables | 16 variables |
| 2. Natality | 10 variables | 22 variables |
| 3. Child and Maternal Mortality | 9 variables | 23 variables |
| 4. Life Expectancy and Adult Mortality | 10 variables | 15 variables |
| 5. Family Formation | 6 variables | 10 variables |
| 6. Health | 10 variables | 19 variables |
| 7. Education | 6 variables | 8 variables |
| 8. Child Protection | 6 variables | 8 variables |
| 9. Crime Indicators | 4 variables | 9 variables |
| 10. Economic Indicators | 11 variables | 15 variables |
Whilst all of the countries in this case study are covered by the TransMONEE database, the extent of coverage varies, as shown in Table 6. In addition, there appears to be no data for Kosovo inputted into the database.
Table 6
Coverage by Country in TransMONEE Database 2003
| Country | No. of indicators for 2001 | % of total |
| Bulgaria | 138 | 95.17% |
| Romania | 138 | 95.17% |
| Hungary | 136 | 93.79% |
| Macedonia | 135 | 93.10% |
| Croatia | 128 | 88.28% |
| Slovenia | 111 | 76.55% |
| Serbia & Montenegro | 105 | 72.41% |
| Albania | 96 | 66.20% |
| Bosnia-Herzegovina | 74 | 51.03% |
The MONEE project has been the most consistent study of well being particularly related to children, of the transition countries. It has provided important tools for researchers and has filled something of a gap between indicators focused on the richest countries, and those focused on the poorest. The recently released Social Monitor 2004 has a particular focus on child poverty and finds that, for nine countries for which data are available, some 14 million out of 44 million children are in poverty according to national poverty lines. Unfortunately, only one SEE country, Albania, where 32.8% of children are in poverty, is included in this list30.
Crucially, not unlike the HDI, the MONEE project has no explicitly link with policy developments and rarely allows for comparisons with either the more developed world or the underdeveloped world. Reliance on national statistical offices appears to result in some discrepancies and, indeed, much retrospective changing of data. Nevertheless, the database as a whole probably captures most of the important aggregate social trends in the post communist countries of Central and Eastern Europe. Crucially, it also includes indicators, which are not addressed in the EU Laeken indicators. However they are of immense relevance in the countries of SEE, including those relating to child protection (rates of children in care, including in residential care; rates of children adopted, nationally and internationally; and juvenile crime and sentencing rates).