The Geographical Distribution Of Unemployment At Localities Desegregation Level.Case Study For South Muntenia Region - Romania

The fifth Cohesion Report highlighted the strategic perspective of the new cohesion policy, expressed by the „added territorial cohesion to the twin goals of economic and social cohesion”. The expected contribution of the cohesion policy is strongly linked to overcoming the crisis, reducing disparities and reaching the ambitious objectives of Europe 2020 Strategy. Unemployment represents the reverse of the medal, a concept and a measure at the intersection of many dimensions, complex and with a large spectrum of interpretations. The spatial dimension of the unemployment was relatively recently addressed by new regional theories, which focused on its: geographical/spatial concentration [Alonso-Villar O. and Del R o C (2008)], agglomeration, returns and spatial unemployment disparities [Suedekum J. (2004)] with aspects of dynamic [Martin R. (1997)], persistence, factors, regional policy rethinking [Chisholm M. (1976)], convergence/divergence of regional disparities [Marshall (1920), Krugman (1991) and Krugman/Venables (1995)), etc]. Overman and Puga (2002) bring empirical evidences regarding the spatial effects of „Unemployment clusters across European regions and countries”. Following Niebuhr idea, by measuring the spatial autocorrelation, „regions marked by high unemployment as well as areas characterised by low unemployment tend to cluster in space” (Niebuhr, 2005). Therefore, we analysed the case of intra-regional unemployment disparities at the region level (NUTS2 level - for the case of South Muntenia Region), by using the finest possible disaggregated level for data - the localities. The interest to measure the intraregional unemployment clusters is based on (Goschin, Roman, Ileanu, 2008) the characteristic of the current state and dynamics of regional disparities in Romania descried as “low amplitude of both inter-regional and intra-regional disparities”, with the distinction that, “intra-regional disparities are much higher than the inter-regional disparities.” Next to agglomeration and persistence of unemployment in some specific areas, the crisis period and its persistence during the period 2009-2010, emphasized the European tendency of increasing „regional disparities” . In order to better respond to the crisis` pressure, Romania, started in 2010 a massive process of budgetary sector restructuring, folowed by important exits from employment to unemployment. The significant number of persons without a job suddenly increased the pressure over the labour market insitutions and diminished the dynamics of the labour market (induced by the limited occupational mobility) acting as a shock (intense and/or long time pressure probability) and being very difficult to be compensated in time by policies. The variables are built with one set of reference data and one set of working data, all for the characteristics: age between 18-62 years (total, feminin and masculin (calculated). The reference data was provided by The National Institute of Statistics (INS) demographic data, respectively the stable population registered at the level of a locality, considered to be constant during the analysed period. The working data was obtained from ANOFM/AJOFM (National Employment Agency) and covers 567 localities out of the total number of 2121 localities from South Muntenia Region, including the number of registered unemployed people under the administrative definiton (unemployed people with indemnisation and without indemnisation), for the characteristic total, female and male (calculated). The secondary working data set is represented by the share of unemployed people as a proxy for the unemployment rate. Using administrative data implies both disadvantages and advantages. Some limits of this method induced by the indicators source are: reduced comparability, national unemployment definition, the statistical quality of data, the interval 18-62 years represents the functional age for entrance and exist in and out of the labour market in Romania. We consider very important to emphasis the advantages of this approach, especially in the context of the cohesion policy future development. Thus, the advantages refer to: data is public, covers the finest regional level (localities, over LAU /2, 3174), is available with the best frequency among the labour market indicators - monthly frequency, are the main indicators used in the labour protection policy implementation, etc. Another very important advantage is the perspective of using the flux data (entrance and exits in unemployment at the localities level) next to the stock data we used in our model. We used the Anselin method, 2005 / Varga, 2009 , to analyze the Local Spatial Autocorrelations characteristics, to identify the clusters HH, LL with different significance level, for the unemployment and the share of unemployment in the stable population for the mentioned characteristics (total, feminine, masculine, age 18-62 years, at locality level), for December 2009 compared to March 2010, at locality level using Arc GIS 9.3. (Arc GIS Catalog and Arc MAP). Spatial econometrics through the GeoDa software was applied under the hypothesis that localities represent the centres of the Thiessen polygons, using rook contiguity weight file. Results are presented through maps and tables indicated the localities situated in the HH and LL clusters.