Entrepreneurship status

Number of active enterprises per 10,000 persons is an important indicator of business economy and business demography, so do indicators of birth rate of enterprises and three year survival rate of enterprises. Distribution characteristics of these measures by groups of IP delineations and other EU regional typologies, unfortunately cannot cover all European countries, since the dataset used only includes a narrow selection of countries with data available: Austria, Bulgaria, Czech Republic, Denmark, Spain, France, Croatia, Hungary, Italy, Lithuania, Portugal, Romania and Slovakia.

Business demography provides information for numbers, births, and survival rates of enterprises, as well as indirect information on related employment²³. The largest number of active enterprises is registered in urban regions as well as in IP 3 (SGI access) regions, but it also reaches a considerable level in the group of IP 1 (regional centres), IP 2 (interstitial), intermediate regions, mountainous areas and islands too (the average is above 600 per 10,000 people).

Regarding unstandardized data, there are no significant differences between the four groups of inner peripheral areas identified by ESPON PROFECY project (Figure 3.12). Nevertheless, the position of IP 3 regions seems to be better than others based on its standardized data as percentages of national averages (see descriptive statistics) (Table 3.11). For example, among IP 1 regions the largest number of active enterprises is detected in Slovakia, Czech Republic, France, Italy, while among IP 2, IP 3 and IP 4 (depleting) regions, areas from Southern European are overrepresented regarding these characteristics (e.g. Italy, Portugal, Spain).

Figure 3.12: Number of active enterprises per 10000 persons in Europe by IP delineations and EU regional typologies, 2013

A – unstandardized

B – standardized as percentages of national averages

These findings are in accordance the results of analyses by Eurostat (based on data from 2014): the largest active enterprise population is registered in Italy (3.9 million), followed by France (3.4 million) and Spain (2.9 million). The services sector was dominant in every country, as measured by the highest proportion of active enterprises in 2014²³.

Table 3.11: Descriptive statistics related to data on active enterprises A – unstandardized

Mean Median Max. Min. Relative range

(max-min)/mean Std.

Deviation No. of enterprises per 10,000

persons

B – standardized as percentages of national averages Mean

The smallest number of active enterprises from regions defined as inner peripheries is detected especially in post-socialist countries (e.g. in Bulgaria, Romania, Croatia), but there are some disadvantaged regions from this aspect in France both in IP 2, IP 3 and IP 4

groups. In comparison of groups of inner peripheries with high travel time to regional centres and economic potential interstitial areas, similarities are emphasized, but some data from descriptive statistics show a little bit more unfavourable position of IP 2 regions compared to IP 1 regions according to their lower level of mean, median and maximum values. Positions of the group of IP 4 regions seems to be more similar to the group of IP 2 regions, while in general, the best positions regarding density of enterprises usually belongs to the group of IP 3 regions. According to unstandardized data, among the examined regions the group of IP 3 regions has the second best position – after Urban regions – based on average level of number of active enterprises per 10000 persons. This fact is also actual according to standardized data as percentages of national averages. Thus, the group of IP 3 regions has only higher arithmetic mean than national average.

The comparison of regions identified as inner peripheries with other typologies might outline more advantages of inner peripheries. From this aspect, rural or lagging areas among the examined groups of European NUTS 3 regions have the most handicaps due to the examined indicator. Thus, those regions which are defined as Lagging (<EUNAT75%) regions due their low economic performance compared to both the EU average and national average levels, have the lowest level of mean and maximum value among the examined groups of regions processed into this analysis.

In summary, number of active enterprises can confirm the relatively better position of regions defined as inner peripheries in ESPON PROFECY project. In other words, inner peripheral status does not go together with the lack of active enterprises. It is also current for accessibility-based inner peripheries (IP 3). Namely, worse accessibility does not go together with lack of active enterprises.

Birth rate of enterprises

The birth of new enterprises is often seen as one of the key determinants of job creation and economic growth. Enterprise births are thought to increase the competitiveness of a region's enterprise population, by obliging them to become more efficient in view of newly emerging competition. As such, they stimulate innovation and facilitate the adoption of new technologies, while helping to increase overall productivity within an economy²³.

In general, if increasing the possibilities of becoming disadvantaged regions – and other areas belonging to the groups of inner peripheral, rural or lagging regions – the birth rate is also increasing. For example, groups of IP regions have quite good position across the examined typologies of regions regarding their number of active enterprises, but due to the

Figure 3.13: Birth rate of enterprises (compared to the number of active enterprises) in Europe by IP delineations and EU regional typologies, 2013

A – unstandardized

B – standardized as percentages of national averages

Moderate differentiation can be detected among IP regions identified by the project with the result of relative better position of IP 2 regions (interstitial) due to its mean and median, or higher maximum and minimum values (Figure 3.13). The mean of birth rate of enterprises in inner peripheries varies between 8.1% and 10.4%. According to standardized data as percentages of national averages, the arithmetic mean of birth rate of enterprises regarding inner peripheries are generally lower than national averages, and varies between 88.9% and 96.5% (Table 3.12). This gap is smallest for IP 4 regions, while the largest for IP 3 regions. It seems inner peripheries create more compact group in comparison to unstandardized data rather than standardized data. Many outliers belong to IP 1 and IP 2 regions based on standardized data, while these outliers do not appear by standardized data.

Similarities between IP delineations and other groups of NUTS 3 regions are coming from the maximum values of birth rate: approximately, one third rate of active enterprises is newly born in all groups (except for islands), while the level of minimum values is around 4.5–6.0%.

Generally, the mean level of birth rate varies between 8.0% and 12.9% with the highest rate in Lagging (<OnlyEU75%) regions and the lowest rate in islands. There is an interesting fact:

Island regions are in the worst position according to unstandardized data, but the birth rate of enterprises (compared to the number of active enterprises) is higher in islands than their national averages.

In the comparison of inner peripheral regions with lagging regions we can conclude that besides strong similarities between these two groups, lagging regions have a little bit more advantaged position compared to inner peripheries. Considering geographical patterns of birth rate of enterprises in inner peripheral regions, several assumptions can be highlighted.

On the one hand, many of regions defined as inner peripheries are located in Romania or in Portugal with the maximum values of birth rate, on the other hand, the lowest level based on minimum values is detected in inner peripheries mainly from Italy or Spain.

In summary, the most important highlight is that the more advantages of IPs based on number of active enterprises might be lost due to birth rate of enterprises. It is current especially for IP 3 regions which have the best position among IPs based on number of active enterprises while this is eliminated due to birth rate of enterprises.

Table 3.12: Descriptive statistics related to birth rate of enterprises

B – standardized as percentages of national averages Mean

Contrary to the more static indicators of business demographics, the focus in examination of three year survival rate of enterprises is to present information about the life cycle of newly born enterprises and the ability to survive up to three years after their creation.

All examined groups appear as very compact according to standardized data as percentages of national averages (Figure 3.14). On the other hand, some differences can be experienced among them according to unstandardized data, but these differences are not so much significant or very considerable.

Figure 3.14: Three year survival rate of enterprises (born in t-3) in Europe by IP delineations and EU regional typologies, 2013

A – unstandardized

B – standardized as percentages of national averages

Considering both unstandardized and standardized data as percentages of national averages, we can see relatively good positions in all examined groups of identified inner peripheries in comparison with other types of territories in Europe. Firstly, all groups of IP regions are above their national level regarding the measure of survival rate of enterprises, which implies more advantaged position within their countries. Only average level of IP 4, Urban, Island, Lagging (OnlyNAT75%) regions are below of their national average, but the level of backwardness in this sense is quite low (they all reach 98–99% compared to national averages). Secondly, there are no significant differences among NUTS 3 regions, since their mean level based on unstandardized data changes between 50.3% and 58.7%.

Minimum level varies between 32.5% and 47.4%: it means at least one third of enterprises exist three years after their birth date. South European regions are overrepresented among regions with lower levels, but some regions from East Central European, post-socialist countries are also can be found among them.

Among the groups of inner peripheries IP 3 regions appear again with their better average position based on unstandardized data. But this advantage is not so much significant compared to other IPs. Anyway, the group of IP 3 regions seems the most compact among IPs, because it has not got any outliers. Inner peripheries might be more compact due to the standardized data as percentages of national averages. Only IP 4 regions are slightly lagging behind other IP regions.

The highest average level of three year survival rates is recorded for the group of mountainous, IP 4 (depleting) and Lagging (<OnlyNAT75%) regions (as average both above 58%) (Table 3.13). Urban regions are not represented among European regions with the most advantaged positions. The lowest average level of this business demography indicator is reported in the group of Lagging (<OnlyEU75%) regions. A paradox situation is coming from that one of the maximum values can be detected in this group. The highest maximum values can be experienced in the group of Intermediate, Rural, Lagging (<OnlyEU75% and

<EUNAT75%) regions (more than 80%). In other words, enterprises have higher survival rates in these regions. For example, many of them are from Latvia.

Slight differences can be found between inner peripheries and lagging regions with relatively better position of IP regions. Probably, similarities could also be seen between the groups of depleting inner peripheries (IP 4) and Lagging (<EUNAT75%) regions according to the presented descriptive statistics.

Comparing enterprise survival rate to birth rate of enterprises and the number of active enterprises, it can be seen that the most disadvantaged regions are Lagging (<EUNAT75%

and <OnlyNAT75%) regions in this respect. In these groups of NUTS 3 regions, the number of active enterprises is relatively low, and despite of the highest level of birth rate, enterprises are unviable. It results that the half of newly born enterprises is not existing three years later in those lagging regions where the development level measured as GDP per capita is lower than 75% compared both to EU average and national levels.

Table 3.13: Descriptive statistics related to survival rate of enterprises

B – standardized as percentages of national averages Mean

In summary, regarding comparisons based on examined indicators of business demography from the point of view of inner peripheries, it is worth mentioning moderately advantaged position of them among other groups of European regions and emphasizing differences

market conditions. The potential contribution that enterprise creation can make to employment is also one of the most important aspects drawing the attention of policy makers to the subject of enterprise demography. In this context, enterprise creation can be seen as an indicator of competitiveness, as a factor of economic growth and as a vital means of creating jobs²³.

3.3.5 Status in density of SGI