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Matching and Labour Market Efficiency across Space and through EU accession: Evidence from Latvia, Estonia and Slovenia

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  • Jekaterina Dmitrijeva

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    (EPEE, Université d’Evry-Val-d’Essonne)

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    Abstract

    During the transition to market economy and the accession to the EU Central and Eastern Eu- ropean countries have witnessed remarkable changes in the structure and functioning of national economies. The aim of this paper is to analyze the dynamics of aggregate and regional labour markets through the last decade in several new EU member states (Latvia, Estonia and Slovenia). The estimation of aggregate matching functions on monthly panel (1999-2006) data allows per- forming the diagnostics of labour market efficiency in terms of worker-firm matching. We exploit regional and country differences, the dynamics and changes over time (we compare pre to post EU enlargement periods) and measure the importance of spatial spill over effects in matching. The potential misspecification of the matching function is addressed by allowing for stock-flow specification and for spatial interactions between regions in terms of worker and job flows. The results reveal that in transition - EU accession context the hiring process is labour demand driven and displays the existence of stock-flow patterns and spatial spillovers. In Latvia due to job shortage and limited labour demand, hires mainly occur between the stock of unemployed and the inflow of new vacancies, while in Slovenia the inflow of new unemployed also plays an important role in match creation. The aggregate efficiency of the labour market in terms of worker-firm matching increases over time in Latvia and seems to decrease in Estonia and Slovenia. The role of labour demand in creating new hires stands crucial in three countries, but the results also feature the development of a new trend: after the accession to the EU the role of labour demand in the matching process becomes weaker, but the role of labour supply is increasing. The efficiency of matching varies across districts and regions and can partially be explained by the population density in the area or by its geographical location (its proximity to the national borders). Spatial spill over effects in matching are confirmed to be statistically significant: unemployed do not limit their search to the region of residence and search in neighboring areas. The asymmetry of spill over effects is weak in Latvia, while in Slovenia the magnitude of the effects depends on economic context in neighboring regions or also on local population density.

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    File URL: http://epee.univ-evry.fr/RePEc/2008/08-05.pdf
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    Bibliographic Info

    Paper provided by Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne in its series Documents de recherche with number 08-05.

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    Length: 57 pages
    Date of creation: 2008
    Date of revision:
    Handle: RePEc:eve:wpaper:08-05

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    Related research

    Keywords: stock-flow matching; spatially augmented matching function; transition countries; new EU member states;

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    References

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    1. Petrongolo, Barbara & Pissarides, Christopher, 2000. "Looking Into The Black Box: A Survey Of The Matching Function," CEPR Discussion Papers 2409, C.E.P.R. Discussion Papers.
    2. Kamil Galuscak & Daniel Munich, 2005. "Structural and Cyclical Unemployment: What Can We Derive from the Matching Function?," Working Papers 2005/02, Czech National Bank, Research Department.
    3. Hazans, Mihails, 2005. "Unemployment and the earnings structure in Latvia," Policy Research Working Paper Series 3504, The World Bank.
    4. Daniel Munich & Jan Svejnar & Katherine Terrell, 1998. "Worker-Firm Matching and Unemployment in Transition to a Market Economy: (Why) Were the Czechs More Successful than Others?," William Davidson Institute Working Papers Series 107, William Davidson Institute at the University of Michigan.
    5. Coles, Melvyn G & Smith, Eric, 1998. "Marketplaces and Matching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(1), pages 239-54, February.
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    7. Tito Boeri & Katherine Terrell, 2002. "Institutional Determinants of Labor Reallocation in Transition," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 51-76, Winter.
    8. Jekaterina Dmitrijeva & Mihails Hazans, 2007. "A Stock-Flow Matching Approach to Evaluation of Public Training Programme in a High Unemployment Environment," LABOUR, CEIS, vol. 21(3), pages 503-540, 09.
    9. Hughes, Gordon & McCormick, Barry, 1994. "Did Migration in the 1980s Narrow the North-South Divide?," Economica, London School of Economics and Political Science, vol. 61(244), pages 509-27, November.
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    12. Coles, Melvyn G & Smith, Eric, 1996. "Cross-Section Estimation of the Matching Function: Evidence from England and Wales," Economica, London School of Economics and Political Science, vol. 63(252), pages 589-97, November.
    13. Fahr, Rene & Sunde, Uwe, 2006. "Spatial mobility and competition for jobs: Some theory and evidence for Western Germany," Regional Science and Urban Economics, Elsevier, vol. 36(6), pages 803-825, November.
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    15. Melvyn Coles & Barbara Petrongolo, 2003. "A Test Between Unemployment Theories Using Matching Data," CEP Discussion Papers dp0570, Centre for Economic Performance, LSE.
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    Cited by:
    1. Lottmann, Franziska, 2012. "Spatial dependencies in German matching functions," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 27-41.

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