1. Structural Unemployment in Croatia How Important is the Occupational Mismatch? Background  In order to completely utilize the stock of human capital in the population it is essential to match individuals’ education- specific skills with the occupational job characteristics (Nordin et al., 2010).  Both the efficiency of the matching process and mismatch may be important determinants of the level of unemployment in the economy (Dur, 1999).  Labour market mismatch (structural imbalance):  inadequate education and training or  insufficient geographical and occupational labour mobility.  In (most) transition countries:  mismatch is the result of significant changes during the 1990ies in the structure of product markets, which have led to changes in the structure of labour demand (Obadić, 2004) ;  low mobility across different occupations, industries and locations (Boeri, 2000) ;  skill shortages as a key impediment to faster labour reallocation and convergence to the EU-15 employment structures (Brixiova et al., 2009). Results Iva Tomić The Institute of Economics, Zagreb & Faculty of Economics, University of Ljubljana Aim  To what extent can the existing level of unemployment (jn Croatia) be attributed to structural (occupational) mismatch or by how much would unemployment fall were structural balance to be achieved? Methodology  Besides the aggregate function, the study estimates the disaggregated matching functions based on the grouping of (similar) occupations;  Matching functions explicitly incorporate mismatch index (based on Dur, 1999) for different submarkets (occupations).  the importance of mismatch on the level of U depends on the distribution of both U and V over submarkets (occupations), but also on the size of the particular submarket. Contact The Institute of Economics, Zagreb Trg J. F. Kennedyja 7 10000 Zagreb, Croatia Ph: +385-1-2362-244 Email: itomic@eizg.hr Web: http://www.eizg.hr Data  Monthly data from CES in the period from January 2004 until December 2011: 1.the number of registered unemployed persons (U), 2.the number of reported vacancies (V), and 3.the number of employed persons from the Service registry (M).  To be able to detect the existence of mismatch in the labour market, all variables are divided according to the 9 broad occupational groups: 1.Legislators, senior officials and managers; 2.Professionals; 3.Technicians and associate professionals; 4.Clerks; 5.Service and shop and market sales workers; 6.Skilled agricultural and fishery workers; 7.Craft and related trades workers; 8.Plant and machine operators and assemblers; 9.Elementary occupations. Summary of the results  the impact of occupational mismatch on the matching process is insignificant on the aggregate level;  however, it affects (negatively) the matching process when labour market is examined through its submarkets;  share of the unemployment benefits users in total unemployment has negative impact on the matching process, while time trend affects it positively;  in most of the cases the hypothesis of CRS cannot be rejected.  the portion of total unemployment that can be attributed to occupational mismatch is estimated to be only up to 6%, which evidently cannot explain high and persistent unemployment in Croatia;  in different submarkets this fraction is even smaller (except for the white-collars).  These 9 occupations are grouped into 2 main categories: 1.white-collar occupations (1-4): a.highly-skilled white-collar occupations (1-2); b.skilled white-collar occupations (3-4); 2.blue-collar occupations (5-9) a.semi-skilled blue-collar occupations (5-7); b.lower-skilled blue-collar occupations (8-9);  Occupational imbalance (mismatch) is measured relative to the existing aggregate levels of unemployment and vacancies in the economy;  occupations represents separate submarkets in the overall labour market. Figure 2. Share of total unemployment attributed to occupational mismatch (left) and unemployment attributed to occupational mismatch as a percentage of the labour force (right) Note: mm – mismatch index. Source: Author’s calculation based on CES data. Figure 1. Share of unemployment and vacancies in total unemployment (vacancies) by white- and blue-collar classification Note: U_wc/U = the share of unemployed in the white-collar segment (submarket) in total unemployment; V_wc/V = proportion of vacancies in white-collar submarket in the total number of vacancies (same applies to blue-collar occupations). Source: Author’s calculation based on CES data. 24th annual EALE Conference, Bonn – Germany, September 20-22, 2012