Benchmarking Regions: Estimating the Counterfactual Distribution of Labor Market Outcomes

Bernd Fitzenberger and Marina Furdas ()
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Marina Furdas: Humboldt University Berlin

No 6465, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: This paper develops and implements a new benchmarking approach for labor market regions. Based on panel data for regions, we use nonparametric matching techniques to account for observed labor market characteristics and for spatial proximity. As the benchmark, we estimate the counterfactual distribution of labor market outcomes for a region based on outcomes of similar regions. This allows to measure both the rank (relative performance) and the absolute performance based on the actual outcome for a region. Our outcome variable of interest is the hiring rate among the unemployed. We implement different similarity measures to account for differences in labor market conditions and spatial proximity, and we choose the tuning parameters in our matching approach based on a cross-validation procedure. The results show that both observed labor market characteristics and spatial proximity are important features to successfully match regions. Specifically, the modified Zhao (2004) distance measure and geographic distance in logs work best in our applications. Our estimated performance measures remain quite stable over time.

Keywords: matching function; regional employment offices; performance measurement; nonparametric matching; conditional quantile positions (search for similar items in EconPapers)
JEL-codes: C14 J68 R50 (search for similar items in EconPapers)
Pages: 56 pages
Date: 2012-04
New Economics Papers: this item is included in nep-eff, nep-lab, nep-ltv and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: Benchmarking regions: Estimating the counterfactual distribution of labor market outcomes (2012)
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