Presentation is loading. Please wait.

Presentation is loading. Please wait.

24th annual EALE Conference, Bonn – Germany, September 20-22, 2012

Similar presentations


Presentation on theme: "24th annual EALE Conference, Bonn – Germany, September 20-22, 2012"— Presentation transcript:

1 24th annual EALE Conference, Bonn – Germany, September 20-22, 2012
Structural Unemployment in Croatia How Important is the Occupational Mismatch? Iva Tomić The Institute of Economics, Zagreb & Faculty of Economics, University of Ljubljana 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). These 9 occupations are grouped into 2 main categories: white-collar occupations (1-4): highly-skilled white-collar occupations (1-2); skilled white-collar occupations (3-4); blue-collar occupations (5-9) semi-skilled blue-collar occupations (5-7); 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. 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. 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? 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). Data Monthly data from CES in the period from January 2004 until December 2011: the number of registered unemployed persons (U), the number of reported vacancies (V), and 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: Legislators, senior officials and managers; Professionals; Technicians and associate professionals; Clerks; Service and shop and market sales workers; Skilled agricultural and fishery workers; Craft and related trades workers; Plant and machine operators and assemblers; Elementary occupations. Results Contact The Institute of Economics, Zagreb Trg J. F. Kennedyja Zagreb, Croatia Ph: Web: 24th annual EALE Conference, Bonn – Germany, September 20-22, 2012


Download ppt "24th annual EALE Conference, Bonn – Germany, September 20-22, 2012"

Similar presentations


Ads by Google