Types of Regional Profiles

Clusterisation according to the Socio-Economic Condition and Development of Districts

Introduction

The aim of clustering the districts is to identify, describe and identify specific groups of districts whose regional profiles are similar.

As described in the methodology, this process is carried out simultaneously for all indicators characterizing the socio-economic situation and the development of districts by using neural networks.

The types of regional profiles identified may be used by different users according to their specific goals and objectives: from analysts to decision-makers who have to make informed management decisions. The key applications of this method can be outlined as:

1. Identifying complex positive or negative phenomena requiring special attention from researchers and policy makers at both local and central levels. It is possible due to the use of multiple indicators simultaneously to identify regional profiles;
2. Identifying and analysing the causes behind these and other types of regional profiles (diagnostic analysis);
3. Identifying and empirically demonstrating new scientific correlations (monographic analysis);
4. Formulating general or sectorial policies for a given type of regional profile identical for all districts within the cluster;
5. Discovering potential "best practices" as well as other potential districts where these could be applied. Because best practices would be most effective if applied to districts with similar characteristics instead of mechanically applying them just anywhere, the clustering of districts with similar regional profiles would considerably help this process;

The types of regional profiles identified as a result of the analysis describe their specific characteristics, with the most important ones appearing in their "titles". The analysis of the dynamics of socio-economic processes covers the period 2008-2010.

Results

As a result of the operation of neural networks, nine types of regional profiles (clusters) were identified. A part of the characteristics of clustered districts is largely similar, that makes them the subject of a detailed description and analysis with a view to their possible use for the above purposes. In other clusters, similarities are not so pronounced. In this sense, they are not "natural" clusters, but they are characterized in the analysis for completeness. 

Very good socio-economic condition: Sofia (capital city)

The district covering the capital city outlines an own cluster and is, quite understandably, ranked in the leading position both for its social and economic indicators. Sofia (capital) only cedes its "primacy" in certain social areas, including healthcare.

Against this background there is the strongly contrasting assessment that Sofia (capital city) is one of two districts with the worst business environment; it is mainly due to the high tax rates. A good example in this regard is the tax rate for the annual retail license tax per 100 square metres of net shopping area, that is the highest in Sofia capital city): BGN 20 in 2012, i.e. two and a half times more than the average rate for the country. This district also receives one of the worst scores awarded by the business community on the level of informal payments given.

The capital city is no exception to the negative trends for the entire country in the demographic and economic spheres; here, however, they are relatively less pronounced than in other areas. Sofia (capital city) reports the highest increase in population density: the rate of increase is twice more intense than that for the country as a whole. Only two other districts (Varna and Burgas) reported an increase for this indicator. Along with the population, an increasing trend is also observed in the number of businesses per 1,000 people. It grew by 1.3% over the past three years, more than twice the average increase for the country.

Strong negative trends yet still reserving a good socio-economic condition: Gabrovo

The Gabrovo district was also placed in a separate cluster. It was caused by certain contrasts which characterize the socio-economic situation and development of the district. The district is among those with the most negative demographic situations in the country. The outlook is rather bleak because negative processes in Gabrovo are persistently deteriorating at one of the fastest rates in the country. A similar picture emerges for education: Gabrovo reports the most negative development of all areas. The number of students in colleges and universities per 1,000 of the population in the district has shrunk by 10.2% within one year, compared to a country-average decrease of 0.1%. In addition, the proportion of the population aged 25-64 with tertiary (higher) education has decreased by 3.6 percentage points, while the nation-wide trend is quite the opposite, having registered an increase of 0.2 percentage points.

The economy of Gabrovo District is also facing newly emerging problems. The district is among the leading economies in the country (immediately after Sofia (capital city) and Varna), but the rate of development in recent years has been the slowest in the country. Unemployment in the district is increasing at a higher rate than the country average, and employment is increasing slower than the national average. In addition, income per household member has decreased by 13.2% within one year. In comparison, the national income for the same period decreased by only 1.2%. Gabrovo District shows a downward trend in the number of businesses per 1,000 people, while the opposite trend is observed for the country as a whole.

Gabrovo District has the most intensively developing infrastructure among all districts, and; this "boom" ranks it second after Sofia (-capital city) in this field. For example the increase in the share of households with Internet access is five times more intense than that for the country. Losses in the transport of water for public water supply and irrigation systems are decreasing 4 times faster for Gabrovo, compared with the overall decrease in the country. 

In contrast to the problems in the socio-economic field, Gabrovo District enjoys the best environmental condition in the country.

Contrasts in the socio-economic development" Stara Zagora, Targovishte

This cluster is characterized by one of the best environments for doing business (Targovishte tops the list in this ranking).

Contrasts in development are characteristic for this cluster. With regard to certain aspects of the socio-economic development, this cluster is among the leaders in the country, while for others it is at the very bottom of the ranking. The cluster contains some of the fastest growing economies (second only to the leaders: Vratsa, Sofia, and Ruse) with declining unemployment in both districts (Stara Zagora and Targovishte). The unemployment rate decreased respectively one and a half and almost nine times faster than the country average. Income per household members for Stara Zagora District increased by 4.7% per year, that is nearly six times faster than the growth for the entire country.

On the other hand, trends in the field of environment are among the worst in the country (Stara Zagora in particular features a very pronounced negative trend). The same applies to the development of the social environment. The two districts in this cluster are among the worst performing in the country.

Infrastructure development is also negative. Household waste collected per person of the serviced population in Stara Zagora has increased while the national trend is in the opposite direction.

As to social environment, the poverty rate increased by about 3.5 percentage points on average in both districts, while this trend remains relatively constant country-wide.

In the field of physical infrastructure, Stara Zagora District has reported an increase in losses during the transport of water for public water supply and irrigation systems by 3.8%, while losses for the country have decreased by 7.3 per cent. The proportion of people aged 16 to 74 years who used the Internet over the preceding year in Targovishte District has decreased while the country as a whole reports a positive trend.

Contrast in the socio-economic situation and development: Vidin, Smolyan

The districts in this cluster are facing demographic issues. The Vidin District is practically in the worst demographic situation in the country. The most revealing indicator is the high negative rate of natural increase that is over three times higher, but with a negative sign, than the country average, and the high age dependency in the district: more than half times higher than that for the country. 

The condition and development of the economy are also negative: Vidin has the worst economy from among all the 28 districts in the country, while Smolyan suffers from some of the most pronounced negative trends in economic development. The decrease in the profitability of sales has the highest rate in Smolyan, (3 times faster than the country average. Vidin has the lowest employment rate: the employment rate of the population aged 15 + in 2010 was 35%, or one-quarter lower than that for the country. The employment rate in Smolyan decreased two and a half times faster than that of the country as a whole.

What distinguishes the districts in this cluster is the dynamic infrastructure development: they are second in the list, immediately after Gabrovo. The same applies to the condition and development of education - this cluster occupies one of the leading positions. Vidin has the fastest growing educational sector in the country, and the quality of education in Smolyan ranks immediately after Sofia (-capital city).

The good performance in education for this cluster is evidenced by the major decrease in the number of school drop-outs. The decrease for the districts of Vidin and Smolyan is 17% and 23%respectively. By comparison, country-average statistics reported no change for this indicator. The proportion of the population aged 25-64 with tertiary education is rapidly increasing in Vidin District. The increase is 14 times faster than that for the country and is higher than that of all other districts. Smolyan District tops the charts in most indicators characterising the condition of education and the educational system. It has the best coverage of the education system: the net enrolment rate of the population for grades 5 to 8 is 5.5 percentage points higher than the country average. Smolyan District also boasts the lowest values of repeaters and school drop-outs as a percentage of all students.

The districts in this cluster are also in leading positions in terms of the current status and trends in healthcare. Patients who sought hospital treatment per 1,000 of the population in Vidin District are 43% less than the country average. In Smolyan District, the population served by an Internal Medicine specialist has decreased by a third, while the country has seen an increase of nearly 5%. The cluster is also characterized by a relatively good social environment.

Poor socio-economic condition and negative trends: Razgrad, Silistra

This cluster contains Razgrad and Silistra. These two districts suffer from the most negative demographic processes in the country. The age dependence rate has increased by 15 and 15.7 percentage points respectively within one year, while country-wide figures show a decrease by 0.2 percentage points. 

The economic situation of these two districts is also among the country's worst: only two other districts reported worse economic development. The educational environment is also in a very poor condition. Razgrad and Silistra have one of the lowest GDP per capita (Silistra District alone reports GDP per capita that is twice lower than the country average). In the districts of Razgrad and Silistra, there are 2 and 3 students per 1,000 of the population, respectively, while for the country they are 37.

Contrasts are also registered in healthcare. The dynamics of development in the healthcare system is one of the most positive in the country, but the current status of healthcare in the districts from this cluster is still poor and it ranks them at the bottom of the scale. 100,000 inhabitants are served by two hospitals for both districts in the cluster; the number is twice as high for the country. 

Promising deveploment trends: Vratsa, Ruse, Sofia

A characteristic feature of this cluster is the fastest economic development compared to all other districts in the country. In practice, the three districts that make up the cluster occupy the top three positions according to the rate of economic development. 

Vratsa reports positive developments in almost all economic indicators, which are particularly intense for the number of enterprises per 1,000 population (ten times faster than that of the country) and investment: expenditure on TFA acquisition registered a growth of 6% against the decrease by one-quarter for the country as a whole.

Of all the districts, Ruse has the fastest decreasing unemployment rate. Sofia District is characterized by a nearly quadruple increase in the profitability of sales against a 13.6 per cent decrease for the country.

The cluster is one of the leaders in education development. Proof in this regard is the 46% growth for the Vratsa District in the number of students in colleges and universities per 1,000 population, contrasting with the overall decrease in the country.

Good socio-economic condition: Blagoevgrad, Burgas, Varna, Plovdiv

The four districts in the cluster enjoy a favourable demographic situation in comparison to other districts in the country. Only Sofia (city) has a relative advantage over them in this respect. In two of the districts in the cluster - Burgas and Blagoevgrad - the general negative demographic trends valid for the whole country are less pronounced. 

The economic situation of the cluster ranks it among the top performing districts. Varna is immediately after Sofia (city). The dynamics of economic development for the cluster, however, is not so pronounced. Only Plovdiv District shows above-average (positive) development, while in the other three districts the trends are negative and lower than those for the country.

In Varna, the number of enterprises per 1,000 population is 37% higher than the country average. In the Plovdiv District, the income per household member has been rapidly increasing: the rate of increase is 6 times higher than that for the country.

The cluster's development in the field of environment is rather negative. Two of the districts (Blagoevgrad and Plovdiv) are at the bottom of the scale. Only Yambol showed an even less favourable development of the environment. In Plovdiv District, the increase of household waste collected per person of the population served is highest: 16%. By comparison, the country average for collected waste has dropped 0.1%.

The development dynamics in the field of healthcare in the cluster is also negative. Plovdiv District occupies the bottommost position in this respect from among all districts in the country, while Burgas is also among the worst developing. The number of patients who sought hospital treatment per 1,000 people in the district of Plovdiv grew the fastest: 8 times (3 times for Burgas) faster than the country average.

Medium socio-economic condition: Dobrich, Kardzali, Kyustendil, Montana, Pleven

The socio-economic condition of districts in this cluster gives them a position that is close to, but still below the country average. 

The cluster is characterized by pronounced negative trends in development of the infrastructure and healthcare. Kyustendil features the most negative assessment of infrastructure development, while Dobrich occupies the bottom position in terms of healthcare development. Kyustendil is the worst performing in terms of water losses within the public water supply and irrigation systems: it reported increased losses by 11.8% versus a decrease of 7.3% for the country.

In Dobrich district, the number of persons served by an Intern is the fastest growing: 5 times higher than the average for the country.

The districts in the cluster are among the best performing in environmental development (Montana, Kardzhali, Kyustendil) and social environment (Kyustendil). The design capacity (average daily volume of water) of existing urban wastewater treatment plants for waste water in Montana District increased by 913 m³/ day / per 10,000 people against an increase of 145 m³/ day / per 10,000 people for the country.

Poor socio-economic condition: Veliko Tarnovo, Lovech, Pazardzik, Pernik, Sliven, Haskovo, Shumen, Yambol

The condition of the infrastructure in all areas of the cluster is poor and below average. It is basically the cluster with least developed infrastructure. Three of the districts occupy the three bottommost positions in this field: Pazardzhik, Yambol, and Sliven. Water losses (million cubic metres per year) within the public water supply and irrigation systems per 10,000 people in Pazardzhik and Yambol districts are nearly four times larger, while for Sliven they are 2 times higher than the country average.

The same applies to the social sphere: all districts within the cluster are characterised by the most deteriorated social environments, and three of them are ranked at the bottom of the list (Yambol, Sliven, and Pernik). The local population of the Pernik District is the most dissatisfied with the quality of life, while the number of those dissatisfied with the performance of the district institutions is the largest in the country - by one-third beyond the national average. Yambol is the district with the highest proportion of the population living in material deprivation. The percentage is 50% higher than that for the country, while for the Sliven District it is higher by one-fifth.

The cluster is characterized by a poor environment for doing business, and the only exception is Yambol District, that ranks second according to this indicator. Part of this cluster, however, is the Pernik District, that has the worst business environment among all districts across the country, followed by Lovech, Haskovo, Veliko Tarnovo, and Shumen. Pernik District also reports the worst rating given to the interaction between businesses and the district/municipal administration: the score provided by surveyed business representatives is one quarter lower than the national average. No more flattering in this respect is the situation in the other districts within the cluster; the level of interaction is rated between 8% and 13% lower than the country average. The rate of property tax in Pernik District is the highest in the country -  26.2 per cent higher than the national average. The situation is similar in Lovech, Haskovo, Veliko Tarnovo, and Shumen.

The condition and trends of economic development, demography and the environment are below the country average. So is the situation in the education sector. Education development, however, is particularly unfavourable. Five of the districts in this cluster are firmly at the bottom of the list from among all 28 Bulgarian districts. Veliko Tarnovo is the district with the most rapidly deteriorating scope of the educational system: it reports a decrease in the net enrolment rate of the population to grades 5 to 8 that is twice worse than the country average. Lovech District experienced a major decline in the number of students at colleges and universities per 1,000 people, that, expressed in percent, is in contrast with the insignificant decrease in the number of students country-wide: within one year, the value of this indicator dropped in the district of Lovech by nearly one-third. The most significant decrease in the number of teachers involved in the primary and secondary education per 1,000 students - in Haskovo District, while Yambol reported the largest drop in scores from the matriculation exam in Bulgarian language and literature.

The dynamics for the natural environment of districts within the cluster is also the most negative for the country. Yambol District is at the very bottom of the ranking, and five other districts in the cluster are also among the worst performing in this area.

Summary

It would be safe to conclude that as a result of clustering using neural networks (Kohonen maps) to identify certain specific types of regional profiles. The most significant profiles are, as follows:

1. The "Very good socio-economic condition" profile, that only includes Sofia (capital city)
2. The "Strong negative trends yet still preserving a good socio-economic condition" profile: Gabrovo District
3. The "Poor socio-economic condition and negative trends" profile: includes the districts of Razgrad and Silistra
4. The "Promising trends & developments" profile, especially in economy and education, specific to the districts of Vratsa, Ruse, and Sofia
5. The "Poor socio-economic condition" profile, describing the districts of Veliko Tarnovo, Lovech, Pazardzhik, Pernik, Sliven, Haskovo, Shumen, and Yambol

Although this analysis only aims to establish the regional profiles without identifying the underlying causes, it is possible to outline some important conclusions:

1. The analysis of the types of regional profiles and in particular their territorial distribution throughout the country shows that generally, they are not territorially clustered, with some exceptions. The districts of Razgrad and Silistra are adjacent and both located in the peripheral areas of Bulgaria. Although not adjacent, the districts of Vidin and Smolyan are both peripheral, too.
2. Proximity to a major centre such as the capital city of Sofia has no immediate positive impact on satellite districts: for instance, the profile of Sofia District shows good development trends while Pernik falls into the profile with poor socio-economic conditions.
3. The range of profiles characterized by poor socio-economic conditions or negative development trends is much wider than the range of good conditions. In practice, no more than three or four districts in Bulgaria can be said to be in relatively good condition with less pronounced negative development trends.

The information and analytical capabilities of the identified types of regional profiles are quite extensive. For example, analysts, and especially policy-makers, would be very interested to find the answer to the question "What are the reasons for the good trends in the districts of Vratsa, Ruse and Sofia?" for making use of them as examples for good practices in other districts, too.

Another object of interest should be the reasons behind the formation of regional profiles in poor condition because taking them out of this condition would require specific policies and measures.

In conclusion, the formation of clusters of regions (e.g. NUTS 3 regions) is a common analytical practice in the EU, that effectively assists the process of making analytically justified, and hence correct and targeted policy decisions. The implementation of such flexible analytical approaches in Bulgaria would provide a good starting point for the formation of regional policies to reduce regional disparities and achieve the economic and social cohesion of regions which are currently widely divergent; moreover, this and other analyses show that there is a persistent trend of a deepening and growing gap between them.

"Reversing" this trend should be among the top priorities of the government.