Technical Efficiency of Tunisian employment offices Younes BOUJELBENE Wajdi KTHIRI Nejib OUERTENI Research Unit on Economy Application (URECA), Sfax University, Tunisia The 7th International Conference on Data Envelopment Analysis July 10 - July 12, 2009 Fox School of Business Philadelphia, USA

Motivations Objectives of the Research Related literature Methodology Data Results Conclusions Outline The 7th International Conference on Data Envelopment Analysis2

Motivations Increase in unemployment rate Increase in unemployment rate of university graduates Evaluate the efficiency of Active Labor Market policy Evaluate the quality of Tunisian employment offices services Give guideline to policymakers for raising the technical efficiency of employment offices. The 7th International Conference on Data Envelopment Analysis3

Objectives of research Measure technical efficiency of Tunisian employment offices Analyze the evolution of level of technical between January 2006 and October 2008 Compare technical efficiency between employment offices Evaluate the Tunisian experience in employment policy The 7th International Conference on Data Envelopment Analysis4

Related literature the study of Sheldon G. (2003) has presented an approach for analyzing the matching efficiency of PES based on the matching function. This study employs micro cross-sectional data and uses nonparametric frontier estimation techniques (DEA).The methodology is applied to 126 regional placement offices operating in Switzerland in the period 1997– 98. he has shown that the placement offices reached roughly two thirds of their efficiency potential. Up to somewhat less than half of the efficiency loss appears to be due to a failure to exploit increasing returns-to-scale (thick-market externalities) The 7th International Conference on Data Envelopment Analysis5

6 The study of Vassiliev and al., (2006) is evaluating REOs efficiency in Koopman’s sense. Moreover, the study focuses on estimate the relative technical efficiency of REOs in Switzerland between April 1998 and March He found mean inefficiency on the order of 15% of best observed performance, He found that selected socio-economic characteristics of the local labour market explained nearly one third of the variation in REO performance Related literature

Methodology The 7th International Conference on Data Envelopment Analysis7 To estimate the production frontier, several econometric and mathematical programming techniques are available. For instance, we analyze the efficiency of employment offices on the basis of a widely-used, deterministic, non-parametric technique: Data Envelopment Analysis (DEA).

Data (1) 80 employment offices 10 employment offices (BREC ) specialized in graduate of university management 70 employment offices (BEM) specialized in skilled unemployed persons (graduate of university) unskilled unemployed persons The period of analysis is between January 2006 and October 2008: Monsuel data 34 months. 8 The 7th International Conference on Data Envelopment Analysis

Data (2) Variables MeansSt. Dev.MinMax Number of hires Number of unemployed Number of vacancies Number of counsellors Table 1: Inputs and Output of BREC between January 2006 and October 2008 The 7th International Conference on Data Envelopment Analysis9

Data (3) MeansSt. Dev.MinMax Number of hires Stock of unemployment Stock of vacancies Number of counsellors Table 1: Inputs and Output of BEM January 2006 and October 2008 The 7th International Conference on Data Envelopment Analysis10

Results (1) The 7th International Conference on Data Envelopment Analysis (12 month) 2007 (12 month) 2008 (10 month) (34 month) REC REV Scale Table 3: Evolution of the means of technical efficiency of BREC under different assumptions of returns to scale  When the variable returns to scale (REV) are imposed, the means of efficiency score were This implicates that the BREC have to increase into output of about 14.2% while maintaining the same level of inputs.  The score is lesser when we impose constant returns to scale, it is about and the number of efficient BREC is 7.  Under different assumptions we note that the means of efficiency score has increased in 2007 as compared to 2006 and increased in 2008 when compared to 2006.

Results (2) The 7th International Conference on Data Envelopment Analysis (12 month) 2007 (12 month) 2008 (10 month) (34 months) REC REV Scale Table 4: Evolution of the means of technical efficiency of BEM under different assumptions of returns to scale  when the variable returns to the scale imposed, the means of efficiency score is This means that on average the BEM must increase their outputs approximately of 38.9% of course while maintaining the same level of inputs.  As opposed to the variables returns to scale, under the assumption of constant returns to the scale of the means of efficiency score is around

Conclusions The 7th International Conference on Data Envelopment Analysis 13  Active Labour Market Policy are financially costly. Consequently, in Tunisia has so far achieved modest performances when we look to increasing of efficiency score between 2006 and  Among the 80 employment offices over the period of studie, 66 of them exhibit decreasing returns to scale. The others have either constant or increasing returns to scale.  Differences technical inefficiency of BREC and BEM is due to differences in environmental conditions between offices: For example employment opportunities are unequally distributed between regions.  Level of technical of inefficiency of graduate employment offices (BREC) is less than employment offices multiservices (BEM) because measures in Active Labour Market Policy are concentrate in the graduate person.  The ranking of employment offices may be easily interpreted by policymakers and managers of ANETI. Indeed, it provides directive for raising the efficiency of the public employment service.

Thank you for your intention The 7th International Conference on Data Envelopment Analysis14