Structural Unemployment in Croatia How Important is the Occupational Mismatch?

1
Structural Unemployment in Croatia How
Important is the Occupational Mismatch?
Iva Tomic 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 (Obadic, 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) 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 Authors calculation based on CES data. Note mm mismatch index. Source Authors calculation based on CES data.
Figure 1. Share of unemployment and vacancies in total unemployment (vacancies) by white- and blue-collar classification 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 Authors calculation based on CES data. 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 Authors 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, ZagrebTrg J.
F. Kennedyja 710000 Zagreb, Croatia Ph
385-1-2362-244Email itomic_at_eizg.hrWeb
http//www.eizg.hr
24th annual EALE Conference, Bonn Germany,
September 20-22, 2012