1 / 27

IVA TOMIĆ The Institute of Economics, Zagreb

The efficiency of the matching process: Exploring the impact of regional employment offices in Croatia. IVA TOMIĆ The Institute of Economics, Zagreb. Outline. Objective Background Croatian Employment Service Data Empirical strategy Estimation results Conclusions. Objective.

gusty
Download Presentation

IVA TOMIĆ The Institute of Economics, Zagreb

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 18th Dubrovnik Economic Conference - Young Economist's Seminar The efficiency of the matching process:Exploring the impact of regional employment offices in Croatia IVA TOMIĆ The Institute of Economics, Zagreb

  2. Outline • Objective • Background • CroatianEmployment Service • Data • Empirical strategy • Estimationresults • Conclusions 18th Dubrovnik Economic Conference - Young Economist's Seminar

  3. Objective • the main objectiveof the paperis to investigate the role played by (local) employment offices inthematchingprocessbetween vacancies and unemployment in Croatia while controlling for different regional characteristics of the labour markets; • the aimof the paperis to estimate and explain the efficiency changes that may have taken place both over time and across regionstaking into account the impact of regional employment offices on the matching efficiency. 18th Dubrovnik Economic Conference - Young Economist's Seminar

  4. Background • Ferraginaand Pastore (2006) explain how the differences in (un)employment between regions in transition countries persistedover time for three main reasons: • restructuring is not yet finished; • foreign capital concentrated in successful regions for many years; • various forms of labour supply rigidity impeded the full process of adjustment. • The existing literature (Botrić, 2004 & 2007; Obadić, 2006; Puljiz and Maleković, 2007) indicatestheexistence regional labour market disparities in Croatia as well. 18th Dubrovnik Economic Conference - Young Economist's Seminar

  5. Background 18th Dubrovnik Economic Conference - Young Economist's Seminar

  6. Background • FahrandSunde (2002): reasons for high and persistent unemployment may lie on the: • supply side • inadequateincentives for unemployed to search for a job actively and inefficient labour market in terms of matching unemployed job-seekers and vacant jobs; • demand side • insufficient demand for labour. • A traditional rationale for labour market institutions has been to facilitate the matching process in the labour market (Calmfors, 1994; Tyrowicz and Jeruzalski, 2009). • Kuddo (2009) explains how in addition to (inadequate) funding, public policies to combat unemployment largely depend on the capacity of relevant institutions. 18th Dubrovnik Economic Conference - Young Economist's Seminar

  7. Background • Hagen (2003) andDmitrijeva and Hazans (2007) argue that raising the efficiency of matching process is usually regarded as the main aim of ALMPsand can be reached by: • adjusting human capital of job seekers to the requirements of the labour market (important in transition economies) and • by increasing search intensity (capacity) of the participants. • Same ALMP measures canhave different impact in different regions (AltavillaandCaroleo, 2009; DestefanisandFonseca, 2007; Hujer et al., 2002). • Budget constraints are limiting the prospects of implementing active labour market measures with real impact which, together with enormous staff caseload, limits the scope of ALMP measures (Kuddo, 2009). 18th Dubrovnik Economic Conference - Young Economist's Seminar

  8. CroatianEmploymentService • The Croatian Employment Service (CES) is defined as a public institution aimed at resolving employment and unemployment related issues in their broadest sense. Its priority functions are: • job mediation; • vocational guidance; • provision of financial support to unemployed persons; • training for employment; and • employment preparation. • CES operates on two main levels: • Central Office - responsible for the design and implementation of national employment policy & • Regional Offices (22) - perform professional and work activities from the CES priority functions, as well as provide support for them via monitoring and analysing of (un)employment trends in their counties. 18th Dubrovnik Economic Conference - Young Economist's Seminar

  9. CroatianEmploymentService • The effectiveness of employment offices varies by regions: • vacancy penetration ratio approximates the capacity of regional employment office to collect information on job vacancies: • it determines the effectiveness of job intermediation services provided by employment offices; • unemployment/vacancies ratio has important policy implications too: • besidesindicating that the problem probably lies in the demand deficiency, it also negatively affects the effectiveness of employment services, such as job search assistance and job brokerage; • the returns to job matching services are sharply diminishing when the unemployment/vacancies ratio goes up (as in the time of the crisis). • Regionalallocation of ALMP funds is largely historically determined (by the offices’ absorption capacity) and changes little in response to the changing local labour market conditions. 18th Dubrovnik Economic Conference - Young Economist's Seminar

  10. CroatianEmploymentService 18th Dubrovnik Economic Conference - Young Economist's Seminar

  11. Data • Regionaldata on a monthly basis within the NUTS3 (county) level obtained from the Croatian Employment Service over a period 2000-2011; • insteadof using county-level data, for the purpose of exploring the role of regionalemployment offices, CES regional office–level data are used. • Main variables used in the analysis are: • number of registered unemployed personse.o.m.(U), • number of reported vacanciesd.m. (V), • number of newly registered unemployedd.m.(U_new); and • number of employed persons from the Service registryd.m.(M). e.o.m. – end of the month; d.m. – during the month 18th Dubrovnik Economic Conference - Young Economist's Seminar

  12. Data U – primary axis; U_new and V – secondary axis. 18th Dubrovnik Economic Conference - Young Economist's Seminar

  13. Empirical strategy • Two main techniques for evaluating matching efficiency: • stochastic frontier estimation & • panel data regressions. • The use of stochastic frontier approach allows a more detailed analysis of the determinants of regional matching efficiencies while fixed effect model implies an unrealistic time-invariance assumption of the matching efficiency and it is difficult to test for the potential influence of explanatory variables on matching inefficiencies. • Thus, in order to explore the efficiency on a regional level, stochastic frontier approachis used (Ibourk et al.,2004;Fahr and Sunde, 2002 & 2006;Destefanis and Fonseca, 2007; Jeruzalsky and Tyrowicz, 2009), as well as its modified version – basic-form first-difference panel stochastic frontier model (WangandHo, 2010). 18th Dubrovnik Economic Conference - Young Economist's Seminar

  14. Empirical strategy whereξit is the level of efficiency for region i at time t; and it must be in the interval (0; 1]. If ξit<1, the ‘regionalemployment office’ is not making the most of the inputs U and V given the ‘technology’ of the matching function . whereuit=-ln(ξit).υitrepresents the idiosyncratic error (υit~N(0,συ2)). 18th Dubrovnik Economic Conference - Young Economist's Seminar

  15. Empirical strategy uit is usuallyassumed to havehas half standard normal distribution or to bea function of region-specific variables and time and it is independently distributed as truncation of normal distribution with constant variance, but with means which are a linear function of observable variables, i.e.: whereωitis defined by the non-negative truncation of the normal distribution with zero mean and variance σω2, such that the point of truncation is –zitδ. Consequently,uit is a non-negative truncation of the normal distribution with N~(zitδ, σu2). uitcanvaryover time: where Ti is the last period in the ith panel, η is an unknown (decay) parameter to be estimated, and the ui’s are assumed to be iid non-negative truncations of the normal distribution with mean μ and variance σu2. 18th Dubrovnik Economic Conference - Young Economist's Seminar

  16. Empirical strategy Total variance of the process of matching which is not explained by the exogenous shocksis denoted asσs2 (σs2= συ2 + σu2), and the share of this total variance accounted for by the variance of the inefficiency effect is γ(γ=σu2 /σs2 ), where γ actually measures the importance of inefficiency for the given model specification. The technical efficiency of the matching process is based on its conditional expectation, given the model assumptions: 18th Dubrovnik Economic Conference - Young Economist's Seminar

  17. Empirical strategy In order to introduce policy relevant variables into the model, the homogeneity of unemployed is relaxed by varying individual search intensities: where small letters indicate log of the variables andδj=β2cj; cjrepresents deviations from average search intensity, so that negative values are characteristic for less than average search effort. The assumption is that heterogeneity effects that affect search intensity have direct impact on the matching efficiency, i.e. that they are included in termzit in the following equation: 18th Dubrovnik Economic Conference - Young Economist's Seminar

  18. Empirical strategy Munich and Svejnar (2009) argue that the explanatory variables in the matching function (U and V) are predetermined by previous matching processes through the flow identities. In order to obtain consistent estimates they suggest that one needs to apply first difference approach to estimation of the matching function. However, Jeruzalski and Tyrowicz (2009) argue that this approach does not allow to capture the relation between local conditions and the matching performance which is the main aim of this research. Possible solution is presented in Wang and Ho (2010)wherethey remove the fixed individual effects prior to the estimation by simple (first-difference) transformations, taking into an account both time-varying inefficiency and time-invariant individual effects. In order to compute technical efficiency index the conditional expectation estimator is used, i.e. conditional expectation of uit on the vector of differenced εit (εit =υ it -u it): 18th Dubrovnik Economic Conference - Young Economist's Seminar

  19. Estimationresults 18th Dubrovnik Economic Conference - Young Economist's Seminar

  20. Estimationresults 18th Dubrovnik Economic Conference - Young Economist's Seminar

  21. Estimationresults Mean technical efficiency across regional offices 18th Dubrovnik Economic Conference - Young Economist's Seminar

  22. Estimationresults Mean technical efficiency overyears 18th Dubrovnik Economic Conference - Young Economist's Seminar

  23. Estimationresults 18th Dubrovnik Economic Conference - Young Economist's Seminar

  24. Estimationresults 18th Dubrovnik Economic Conference - Young Economist's Seminar

  25. Estimationresults 18th Dubrovnik Economic Conference - Young Economist's Seminar

  26. Conclusions • large regional differences in both employment and unemployment levels among Croatian regions (counties); • main results point to larger weight of job seekers in the matching process in comparison to posted vacancies; • the efficiency of the matching process is risingover time with significant regional variations; • even though most of the used ‘labour market structure’ variables as well as ‘policy’ variables proved to be significant, none of the estimated coefficients is large enough to explain regional variation in matching efficiency; • it seems that demand fluctuations remain as the main determinant of matching (in)efficiency in Croatia; • preliminary results from the basic-form first-difference transformation model show that there are no significant differences in estimated technical efficiency coefficients in comparison to the original panel stochastic frontier model. 18th Dubrovnik Economic Conference - Young Economist's Seminar

  27. Thankyou for yourattention! Iva Tomić itomic@eizg.hr 18th Dubrovnik Economic Conference - Young Economist's Seminar

More Related