Frequently asked questions

How were the different indicators in each of the categories weighed?

All indicators in each category are considered of equal importance and are hence assigned equal weights. For example, all six indicators, used in the “Demography” category (rate of natural increase, net migration, dependency ratio 65+/0-14, dependency ratio 65+/15-64, population density, urban population) carry an equal 1/6^th weight in this category. 

What are the resulting clusters of regions?

The obtained clusters are specific groups of regions with similar regional profiles. The clustering process is conducted simultaneously for all categories of indicators, describing the socio-economic state and development of the regions, using neural networks. 

What can the resulting clusters be used for?

The identified types of regional profiles can be used by different parties according to the specifics of their work – ranging from analysts to government officials, who are expected to take informed decisions. The main uses of the method can be defined as follows:

1. Identification of complex positive or negative phenomena, requiring special attention from explorers and politicians on local or central level. This is possible due to the simultaneous use of many indicators in the making of the regional profiles.
2. Detection and analysis of the reasons that led to the formation of different types of regional profiles (diagnostic analysis).
3. Empirical definition and proof of new scientific laws and patterns (nomographic analysis)
4. Formulating global and sectorial policies for certain types of regional profiles, identical for all the regions within a certain cluster.
5. Identification of existent good practices as well as potential focus regions, where those practices can be transferred. And, since good practices will be best applied to regions with similar characteristics rather than just applying them everywhere, defining such clusters of regions with similar regional profiles can substantially simplify this process.

What are the general conclusions of the study?

Some of the general conclusions of the study are as follows:

1. Until 2008, all districts demonstrated growth, but the rich ones developed faster than the poor ones; i.e. the gap between them increased and a group of regions that developed much faster than the others emerged;
2. The gap has increased in the period of economic boom as well as in the period of crisis;
3. The number of districts with poor socioeconomic profiles or showing negative trends is much bigger than the number of those with good socioeconomic profiles and positive trends;
4. Demographic developments have an extremely strong – and usually negative – impact on the economic development of the regions;
5. The high sense of security and the good quality of the environment increase personal satisfaction with life, while work conditions, income levels and the quality of infrastructure bring dissatisfaction;
6. In spite of rather prolonged negative developments in the poorest regions, the majority of the population in them features rather low mobility;
7. Proximity to Sofia (the capital) doesn’t have a singular effect on all the neighboring regions and does not automatically bring any advantage;
8. The central government still plays a major role in local policies; this can be attributed to the unwillingness to delegate more powers to the local authorities;
9. Even though local policies are restricted by law, they can have a paramount impact on the living conditions and business environment on regional level;
10. Data is extremely scarce on a regional level, and sometimes its quality is questionable, which casts doubt on the ability of the government (both central and local) to take informed decisions.

Who financed the study?

The study came into being with the financial support of the “America for Bulgaria” foundation.

What is the source of information on the different indicators used in the study?

Information on the different indicators, used in the study was gathered in a few different ways:

• downloading free, public data from official sources – the National Statistical Institute (NSI), municipality webpages, the National Center for Health Information and Analyses.
• buying data from the NSI when such data is not available free-of-charge.
• sending requests for access to public inflation to all 264 municipalities in the country, the National Health Insurance Fund, the National Revenue Agency, The Ministry of Education, Youth and Sport.
• conducting two public opinion surveys among citizens and representatives of local businesses in all 28 districts.

Can I see the statistical data used in the study?

The raw statistical information used in the study can be found and downloaded in xlsx format here.