The challenges of the post-industrial development stage of society calls for a shift from rural policy based on the functional-sectoral approach to the integrated policy, which deals with not only agricultural problems, but also with all those relating to the rural territory, specified as the rural region. The previous rural policy measures were oriented mainly to the support of the individual farmer or the settlement. The measures of the new policy paradigm are oriented to the sustainable development of the entire rural region. This implicates the need of regional typologies based on the criteria of the rurality.
Traditionally rural policy decisions are based on the regional typologies where the main criterion is population density and/or number of inhabitants in the settlement. The methodology of the Organization for Economic Cooperation and Development (the OECD) were most often applied for the classification of the regions by rurality for governance purposes. Regions are divided into three groups by this methodology: predominantly urban, intermediate and predominantly rural regions. The main indicator of rurality is the density of the population (OECD, 1994). This methodology in the last decade became the subject of criticism.
In the post-industrial development stage of society mobility became more important feature of the region than density. The growing flows of commodities, services and information as well as the processes of commuting, internal and external migration are changing the concept of the rural region, which is traditionally perceived as a rarely inhabited territory used for agricultural purposes. New rurality concepts focus on the criteria, specifying the opportunities of the residents to be mobile, their traffic flows and mobility speed and take the first place in terms of importance. Mobility is understood in the broad sense, while consisting of residents commuting, changing their place of residence, rates of businesses development, employment and ageing dynamics and other processes (Benaki et al., 2007; Knickel, Renting, 2000; OECD, 2006a).
Firstly analysis of the mobility of rural residents was focused on the commuting that became an important phenomenon. Development of transport systems and road network has formed the habits of living and working in different settlements. However, commuting is not becoming a common practice as there are some regions where cities and the remaining territory exist as separate areas. Inhabitants of cities and countryside contacts only episodically. These cases are more frequent in lower density territories (Baldock et al., 2001). Different commuting development in the regions implies variability of applied rural policy measures.
The newest research studies of rural and urban relationships indicate the growing importance of other reasons to be mobile. Flexible lifestyle is becoming popular when people have several places of residence (Saartenoja et al., 2008), thus the number of urban residents, having a second house in the countryside, is increasing. The residents move from urban agglomerations to live not only in the suburban area, but also to remote small and medium-sized townships (URBED, 2002).
The rapid development of information and communication technologies implicates fundamental changes in the organization of workplaces. Distance working system more often is applied by considerable number of business enterprises and other organizations permitting their employees to work at home or in some other place, convenient for them. It is predicted that a tendency to return a workplace to the employee’s place of residence would become manifest very strongly in the short term. It is possible to expect that the trend of living in a healthy environment will increase the popularity of distance working system and increase a number of people moving from urban to rural areas.
Taking into consideration the above-mentioned factors, the creators of regional typologies state that it was not enough to analyze the role of a city as the coordinating centre. They focused their attention to the formation of networking between smaller settlements. In this case not only monocentric agglomerations, but also polycentric linkages become of importance.
Polycentric conception is recommended as one of the most perspective tool, helping to increase the competitiveness of urban systems (Bailey, Turok, 2001). However the polycentric relationships is practically attempted to be applied only in larger regions connecting several states, or at the EU level. One of the most serious efforts to practically apply the concept of polycentrism in the creation of rural regional typologies may be considered the methodology for regional classification, proposed by Lewis Dijkstra and Hugo Poelman (Dijkstra, Poelman, 2008). The results of their research on regional differences in the EU Member States indicated that four out of five remote rural regions either had a loss of population or grew more slowly than their country’s growth rate. A comparison between regional population trends and national population trends reveals that remote rural regions are far more likely to have suffered a reduction in the share of their country’s population. The same is true for their share of national GDP. Almost three out of four regions saw their GDP shrink or grow more slowly than their country’s rate. This stands in clear contrast to rural regions close to a city which saw better results for these two indicators. The scores obtained by rural areas close to a city were almost identical to the EU-27 average. GDP per head is the lowest in remote rural regions, three index points below rural regions close to a city and substantially lower than in intermediate and urban regions. An analysis of sectoral productivity showed that remote rural regions consistently have the lowest productivity in agriculture, industry and services. Remote rural regions have the highest share of GVA in the agriculture sector, but also the lowest productivity in this sector.
The afore-mentioned trends are relevant to the situation in the regions of Lithuania. In the rural regions classified by remoteness, employment rate is lowest, part of the social allowances is highest. Age dependency ratio and ageing index are highest in the rural regions. Social and economic indicators are higher in semi-rural regions and the best situation is in urban regions.
The typology of Lithuania’s regions specified and evaluated by the remoteness criterion of the region is presented in the article. Classification of the regions was performed by the concept, proposed by Lewis Dijkstra and Hugo Poelman (Dijkstra, Poelman, 2008).
Methodology of remoteness of the regions was corrected taking into account the size of the territory of Lithuania, the number of the population and the road types in the regions. LAU2 regions were used for this analysis. Remoteness was measured by the travelling time from the place of residence to the closest town, using the ViaMichelin GIS system.
A region while grouping Lithuania’s regions according to remoteness was attributed to one of three types:
• rural region, if driving time to the centre of a city takes over 90 minutes for more than 50 per cent of its residents.
• semi-rural region, if driving time to the centre of a city takes from 46 to 75 minutes for more than 50 per cent of its residents
• urban regions, if more than 50 per cent of its residents can drive to the centre of a city within 45 minutes.
Analysis of economic and social indicators of LAU2 regions of Lithuania confirmed that the typology of regions where a region is classified to urban, semi-rural or rural group by remoteness, measured by the driving time from the place of residence to the closest city, is suitable for the classifying of regions for governance purposes. Remote rural regions were clearly faced with a different set of problems than rural regions close to a city. This is clear from social, economic and demographical indicators. The best values of social and economic indicators are in the urban regions, lower in semi-rural regions and the lowest in rural regions.
The proposed new typology of the LAU2 regions in Lithuania will help to review regional and rural policy measures, thus revealing new opportunities for improving the quality of life in the remote regions of Lithuania.
Key words: typology, rural policy, regional policy, remoteness.
Vidickienė, D.; Gedminaitė-Raudonė, Ž. Lietuvos regionų klasifikavimas pagal kaimiškumą remiantis atokumo kriterijumi // Ekonomika ir vadyba: aktualijos ir perspektyvos. ISSN 1648-9098. Nr. 4(24) (2011), p. 51-59 (Index Copernicus).
