Spain Accession to the EMU - A Long and Hilly Road

Europe has been the driving force of economic policy in Spain over the last four decades and the key factor behind the modernisation and globalisation of the Spanish Economy. Being a founding member of the Economic and Monetary Union (EMU) marked the achievement of one of the key goals in the process of European integration. This process was carried out in several stages. First, trade openness, which was bolstered by Spanish accession to the EEC in 1986 and the single market in 1992, and foreign direct investment abroad and portfolio investment, which grew exponentially in the run-up to Euro membership. Second, the process of nominal convergence, which allowed a more stable macroeconomic framework. Lower inflation and fiscal consolidation have resulted in higher sustainable growth. However, the process of real integration could have been even more successful. Spain’s income per capita still lies at 84 per cent of the European average. The slow pace of reform, in particular in the labour market, with high labour costs leading to persistent unemployment, and an inappropriate policy-mix in the late 1980s prevented Spain from reaping the full benefits of integration and of EMU. Achieving real convergence is the key challenge facing the Spanish economy in the future and Europe will remain a focal point in this venture.

Firm heterogeneity and aggregate business services exports : Micro evidence from Belgium, France, Germany and Spain. National Bank of Belgium Working Paper No. 328

This paper uses detailed micro data on service exports at the firm-destination-service level to analyse the role of firm heterogeneity in shaping aggregate service exports in Belgium, France, Germany and Spain from 2003 to 2007. We decompose the level and the growth of aggregate service exports into different trade margins paying special attention to firm heterogeneity within countries. We find that the weak export growth of France is at least partly due to poor performance by small exporters. By contrast, small exporters are the most dynamic contributors to the aggregate exports of Belgium, Germany and Spain. Our results highlight the importance of firm heterogeneity in understanding aggregate export growth

Micro-based evidence of EU competitiveness: The CompNet Database. National Bank of Belgium Working Paper No. 253, March 2014

Drawing from confidential firm-level balance sheets in 11 European countries, the paper presents a novel sectoral database of comparable productivity indicators built by members of the Competitiveness Research Network (CompNet) using a newly developed research infrastructure. Beyond aggregate information available from industry statistics of Eurostat or EU KLEMS, the paper provides information on the distribution of firms across several dimensions related to competitiveness, e.g. productivity and size. The database comprises so far 11 countries, with information for 58 sectors over the period 1995-2011. The paper documents the development of the new research infrastructure, the construction of the database, and shows some preliminary results. Among them, it shows that there is large heterogeneity in terms of firm productivity or size within narrowly defined industries in all countries. Productivity, and above all, size distribution are very skewed across countries, with a thick left-tail of low productive firms. Moreover, firms at both ends of the distribution show very different dynamics in terms of productivity and unit labour costs. Within-sector heterogeneity and productivity dispersion are positively correlated to aggregate productivity given the possibility of reallocating resources from less to more productive firms. To this extent, we show how allocative efficiency varies across countries, and more interestingly, over different periods of time. Finally, we apply the new database to illustrate the importance of productivity dispersion to explain aggregate trade results

Efecto de cambios legislativos en las pensiones de jubilación contributivas. El caso español

..

Firm heterogeneity and aggregate business services exports: micro evidence from Belguim, Germany and Spain

En el presente documento se utilizan microdatos detallados sobre las exportaciones de servicios a nivel de los servicios de destino de las empresas para analizar el papel de la heterogeneidad de las empresas en la configuración de las exportaciones agregadas de servicios en Bélgica, Francia, Alemania y España entre 2003 y 2007. Descomponemos el nivel y el crecimiento de las exportaciones agregadas de servicios en diferentes márgenes comerciales, prestando especial atención a la firme heterogeneidad dentro de los países. Encontramos que el débil crecimiento de las exportaciones de Francia se debe, al menos en parte, a los malos resultados de los pequeños exportadores. Por el contrario, los pequeños exportadores son los que más contribuyen a las exportaciones agregadas de Bélgica, Alemania y España. Nuestros resultados destacan la importancia de la heterogeneidad de las empresas para comprender el crecimiento agregado de las exportacionesThis paper uses detailed micro data on service exports at the firm-destination-service level to analyse the role of firm heterogeneity in shaping aggregate service exports in Belgium, France, Germany and Spain from 2003 to 2007. We decompose the level and the growth of aggregate service exports into different trade margins paying special attention to firm heterogeneity within countries. We find that the weak export growth of France is at least partly due to poor performance by small exporters. By contrast, small exporters are the most dynamic contributors to the aggregate exports of Belgium, Germany and Spain. Our results highlight the importance of firm heterogeneity in understanding aggregate export growt

Firm heterogeneity and aggregate business services exports: Micro evidence from Belgium, France, Germany and Spain

International audienc

Delay from treatment start to full effect of immunotherapies for multiple sclerosis

In multiple sclerosis, treatment start or switch is prompted by evidence of disease activity. Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. In this study we aimed to develop a method that allows identification of the time to manifest fully and clinically the effect of multiple sclerosis treatments ('therapeutic lag') on clinical disease activity represented by relapses and progression-of-disability events. Data from two multiple sclerosis registries, MSBase (multinational) and OFSEP (French), were used. Patients diagnosed with multiple sclerosis, minimum 1-year exposure to treatment, minimum 3-year pretreatment follow-up and yearly review were included in the analysis. For analysis of disability progression, all events in the subsequent 5-year period were included. Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy. Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start; this point represented the point of stabilization of treatment effect, after the maximum treatment effect was observed. The method was developed in a discovery cohort (MSBase), and externally validated in a separate, non-overlapping cohort (OFSEP). A merged MSBase-OFSEP cohort was used for all subsequent analyses. Annualized relapse rates were compared in the time before treatment start and after the stabilization of treatment effect following commencement of each therapy. We identified 11 180 eligible treatment epochs for analysis of relapses and 4088 treatment epochs for disability progression. External validation was performed in four therapies, with no significant difference in the bootstrapped mean differences in therapeutic lag duration between registries. The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12 and 30 weeks. The duration of therapeutic lag for disability progression was calculated for seven therapies and ranged between 30 and 70 weeks. Significant differences in the pre- versus post-treatment annualized relapse rate were present for all therapies apart from intramuscular interferon beta-1a. In conclusion we have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies in patients more than 3 years from multiple sclerosis onset. Objectively defined periods of expected therapeutic lag allows insights into the evaluation of treatment response in randomized clinical trials and may guide clinical decision-making in patients who experience early on-treatment disease activity. This method will subsequently be applied in studies that evaluate the effect of patient and disease characteristics on therapeutic lag

Delay from treatment start to full effect of immunotherapies for multiple sclerosis

International audienceIn multiple sclerosis, treatment start or switch is prompted by evidence of disease activity. Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. In this study we aimed to develop a method that allows identification of the time to manifest fully and clinically the effect of multiple sclerosis treatments (‘therapeutic lag’) on clinical disease activity represented by relapses and progression-of-disability events. Data from two multiple sclerosis registries, MSBase (multinational) and OFSEP (French), were used. Patients diagnosed with multiple sclerosis, minimum 1-year exposure to treatment, minimum 3-year pretreatment follow-up and yearly review were included in the analysis. For analysis of disability progression, all events in the subsequent 5-year period were included. Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy. Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start; this point represented the point of stabilization of treatment effect, after the maximum treatment effect was observed. The method was developed in a discovery cohort (MSBase), and externally validated in a separate, non-overlapping cohort (OFSEP). A merged MSBase-OFSEP cohort was used for all subsequent analyses. Annualized relapse rates were compared in the time before treatment start and after the stabilization of treatment effect following commencement of each therapy. We identified 11 180 eligible treatment epochs for analysis of relapses and 4088 treatment epochs for disability progression. External validation was performed in four therapies, with no significant difference in the bootstrapped mean differences in therapeutic lag duration between registries. The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12 and 30 weeks. The duration of therapeutic lag for disability progression was calculated for seven therapies and ranged between 30 and 70 weeks. Significant differences in the pre- versus post-treatment annualized relapse rate were present for all therapies apart from intramuscular interferon beta-1a. In conclusion we have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies in patients more than 3 years from multiple sclerosis onset. Objectively defined periods of expected therapeutic lag allows insights into the evaluation of treatment response in randomized clinical trials and may guide clinical decision-making in patients who experience early on-treatment disease activity. This method will subsequently be applied in studies that evaluate the effect of patient and disease characteristics on therapeutic lag