Towards a set of Composite Indicators on Flexicurity: a Comprehensive Approach

The European Commission¿s Lisbon Agenda aims to enhance both flexibility and security in the labour markets in order to reconcile competitiveness and sustainable economic growth with more and better jobs and greater social cohesion (COM(2007)359). The pursuit of a balance between flexibility and security addresses simultaneously -the flexibility of labour markets, work organization and labour relations, and -security, including employment and social security for weaker groups in and out of the labour market. This is the concept of flexicurity whereby flexibilisation of employment and labour markets is advocated to support productivity, competitiveness and growth, while security is advocated from a social policy perspective emphasising the importance of preserving social cohesion within society (Wilthagen, 1998). The approach of flexicurity implies that the policies for more and better jobs are developed in coordination with social partners from both sides, i.e. employees and employers, through public or private partnership and are aimed to ensure security to workers in and out of the labour market reducing risks of social exclusion (Wilthagen and Tros, 2004). Moreover, flexicurity also concerns progress of workers into better jobs, development of talent and support of transitions during life course, e.g. from school to work, from job to job, between unemployment and employment and from work to retirement. Therefore, security implies equipping people with the skills that enable them to progress in their working lives, and helping them find a new job rapidly when unemployed. It is also about adequate unemployment benefits to facilitate transitions towards new jobs. Finally, it encompasses training opportunities for all workers, especially weaker groups such as the low skilled and older workers. This paper has been developed in this framework and presents the findings of a research project carried out by the Joint Research Centre- (Unit G09-Econometrics and Applied Statistics) and DG Employment (Unit D1 ¿ Employment Analysis) of the European Commission . The project aimed to develop statistical tools to measure flexicurity achievements of EU Member States through a set of four composite indicators corresponding to the four dimensions of flexicurity identified by the Commission (COM(2007)359) ¿Lifelong Learning (LLL), ¿Active Labour Market Policies (ALMP), ¿Modern Social Security Systems (MSS) and ¿Flexible and Reliable Contractual Arrangements (FCA). This project represents a significant step forward with respect to previous analyses of flexicurity, in many respects: Comprehensiveness, Soundness and transparency of statistical methodology used, Solid theoretical framework on flexicurity, Policy relevance: possibility to replicate the exercise for policy monitoring, Robustness of results is extensively assessedJRC.DG.G.9-Econometrics and applied statistic

Towards a set of composite indicators on Flexicurity: the Indicator on Flexible and Reliable Contractual Arrangement

As a fourth and last step in the process of construction of a set of composite indicators on flexicurity within a joint DG EMPL-JRC project, this paper presents a composite indicator on Flexible and Reliable Contractual Arrangements (FCA), i.e. one of the four dimensions of flexicurity identified by the Commission (see COM(2007) 359). The indicator is based on 19 basic indicators and three sub-dimensions, i.e. i) Regulations on dismissals and use of flexible contractual forms - external flexibility; ii) Flexibility of working time - internal flexibility; iii) Flexibility of work organisation to help combine work and family responsibilities ¿ work-life balance combination flexibility. The indicator covers a four years period (2005 to 2008). The large set of indicators included, going well beyond the strictness of employment protection legislation whereby labour market flexibility is often measured, makes this exercise broader and more comprehensive than any previous attempt to characterise the flexibility dimension within a holistic attempt to measure flexicurity. All indicators used are based on institutional EU-level data sources. Results point to considerable heterogeneity in FCA across the EU, although Member States are not always grouped across well defined geographical clusters often mentioned in relevant literature (e.g. Southern, Anglo-Saxon etc.). The indicator's country ranking is quite stable over time, in particular in the years 2006-2008, while significant differences can be observed between 2005, on the one hand, and 2006-2008, on the other hand. Uncertainty and sensitivity analyses have been performed in order to test the robustness of the Composite Indicator. Those were based on 12000 different simulated scenarios, generated by considering different options with respect to standardization methods, weighting scheme, aggregation rules and the inclusion/exclusion of basic indicators. Results show that the composite indicator's scores and rankings are overall robust, albeit with some variability mainly due to imputation of missing data and low correlation among basic indicators. On average, ranking variability is higher than in the Life Long Learning and Modern Social Security composite indicators, but lower than in the Active Labour Market Policies one, reflecting the varying presence of missing data.JRC.DG.G.9-Econometrics and applied statistic

Towards a set of composite indicators on Flexicurity: the Indicator on Modern Social Security Systems

As a third step in the process of construction of a set of composite indicators on flexicurity within a joint DG EMPL-JRC project, this paper presents an attempt to calculate a Composite Indicator on Modern Social Security System, which is one of the main four dimensions of flexicurity according to relevant Commission policy documents (see COM(2007) 359). The dimension of Modern Social Security System is captured through three different indicators: 4. the main indicator, which is based on 20 basic indicators and covers the three year period from 2005 to 2007, 5. a first additional indicator, based on 17 basic indicators and covering only 2004, 6. a second additional indicator built on 24 basic indicators and covering only 2007. All indicators used are based on three different sources. Results point to a heterogeneous Europe, with an overall good performance of Continental countries, and less favourable scores for Mediterranean and Eastern Member States. The indicator's country ranking is quite stable over the period considered with a few changes from one year to another. Uncertainty and sensitivity analyses have been performed in order to test the robustness of the Composite Indicator. Those were based on 29400 different simulated scenarios for the main indicator, 25200 different scenarios for the 2004 indicator and 35000 simulated scenarios for the 2007 indicator, generated by considering different options with respect to standardization methods, weighting scheme, aggregation rules and the inclusion/exclusion of basic indicators. Results show that the composite indicator's scores and rankings are overall robust over the period, although some variability is present in each year. This is mainly due to the imputation of missing data. On average, countries record a higher ranking variability with respect to the Life Long Learning Composite indicator, but a lower one compared to the index on Active Labour Market Policies. This is due to the varying presence of missing data. However, the MSS index is quite robust compared to similar indicators developed in the literature.JRC.G.9-Econometrics and applied statistic

Beta-Blocker Use in Older Hospitalized Patients Affected by Heart Failure and Chronic Obstructive Pulmonary Disease: An Italian Survey From the REPOSI Register

Beta (β)-blockers (BB) are useful in reducing morbidity and mortality in patients with heart failure (HF) and concomitant chronic obstructive pulmonary disease (COPD). Nevertheless, the use of BBs could induce bronchoconstriction due to β2-blockade. For this reason, both the ESC and GOLD guidelines strongly suggest the use of selective β1-BB in patients with HF and COPD. However, low adherence to guidelines was observed in multiple clinical settings. The aim of the study was to investigate the BBs use in older patients affected by HF and COPD, recorded in the REPOSI register. Of 942 patients affected by HF, 47.1% were treated with BBs. The use of BBs was significantly lower in patients with HF and COPD than in patients affected by HF alone, both at admission and at discharge (admission, 36.9% vs. 51.3%; discharge, 38.0% vs. 51.7%). In addition, no further BB users were found at discharge. The probability to being treated with a BB was significantly lower in patients with HF also affected by COPD (adj. OR, 95% CI: 0.50, 0.37-0.67), while the diagnosis of COPD was not associated with the choice of selective β1-BB (adj. OR, 95% CI: 1.33, 0.76-2.34). Despite clear recommendations by clinical guidelines, a significant underuse of BBs was also observed after hospital discharge. In COPD affected patients, physicians unreasonably reject BBs use, rather than choosing a β1-BB. The expected improvement of the BB prescriptions after hospitalization was not observed. A multidisciplinary approach among hospital physicians, general practitioners, and pharmacologists should be carried out for better drug management and adherence to guideline recommendations

Proposal of a New Parameter for Evaluating Muscle Mass in Footballers through Bioimpedance Analysis

The evaluation of muscle mass in athletes correlates with sports performance directly. Bioimpedance vector analysis is a growing method of assessing body composition in athletes because it is independent of predictive formulas containing variables such as body weight, ethnicity, age, and sex. The study aims to propose a new parameter (Levi’s Muscle Index, LMI) that evaluates muscle mass through raw bioelectrical data. A total of 664 male footballers underwent bioimpedance assessment during the regular season. LMI was correlated with body cell mass (BCM) and phase angle (PA) to establish efficacy. The footballers were 24.5 ± 5.8 years old, 180.7 ± 5.9 cm tall and weighed 76.3 ± 7.1 kg. The relationships were: LMI-BMI: r = 0.908, r2 = 0.824, p < 0.001; LMI-PA: r = 0.704, r2 = 0.495, p = 0.009 and PA-BCM: r = 0.491, r2 = 0.241, p < 0.001. The results obtained confirm that LMI could be considered a new parameter that provides reliable information to evaluate the muscle mass of athletes. Furthermore, the higher LMI-BCM relationship than PA-BCM demonstrates specificity for muscle mass evaluation in athletes regardless of body weight, ethnicity, age, and sex