Wage differentials between permanent and temporary workers: Firm and occupational segregation

Published as an article in: Moneda y Crédito (2004), 219, pp.: 43-68.

Impacto solvencia II en un seguro de vida

La actividad aseguradora supone la transferencia de riesgos del asegurado al asegurador. El asegurador se compromete al pago de una prestación si el riesgo se realiza. Se produce un cambio en el ciclo productivo. El asegurador vende una cobertura sin conocer el momento y el coste exacto de dicha cobertura. Esta particularidad de la actividad aseguradora explica la necesidad para una entidad aseguradora de ser solvente en cada momento y ante cualquier imprevisto. Por ello, la solvencia de las entidades aseguradoras es un aspecto que se ha ido recogiendo en las distintas normativas que han regulado la actividad aseguradora y al que se ha ido dando cada vez más importancia. Actualmente la legislación vigente en materia de solvencia de las aseguradoras esta regulada por la directiva europea Solvencia I. Esta directiva establece dos conceptos para garantizar la solvencia: las provisiones técnicas y el margen de solvencia. Las provisiones técnicas son las calculadas para garantizar la solvencia estática de la compañía, es decir aquella que hace frente, en un instante temporal determinado, a los compromisos asumidos por la entidad. El margen de solvencia se destina a cubrir la solvencia dinámica, aquella que hace referencia a eventos futuros que puedan afectar la capacidad del asegurador. Sin embargo en una corriente de gestión global del riesgo en la que el sector bancario ya se había adelantado al sector asegurador con la normativa Basilea II, se decidió iniciar un proyecto europeo de reforma de Solvencia I y en noviembre del 2009 se adoptó la directiva 2009/138/CE del parlamento europeo y del consejo, sobre el seguro de vida, el acceso a la actividad de seguro y de reaseguro y su ejercicio mas conocida como Solvencia II. Esta directiva supone un profundo cambio en las reglas actuales de solvencia para las entidades aseguradoras. Este cambio persigue el objetivo de establecer un marco regulador común a nivel europeo que sea más adaptado al perfil de riesgo de cada entidad aseguradora. Esta nueva directiva define dos niveles distintos de capital: el SCR (requerimiento estándar de capital de solvencia) y el MCR (requerimiento mínimo de capital). Para el calculo del SCR se ha establecido que el asegurador tendrá la libertad de elegir entre dos modelos. Un modelo estándar propuesto por la Autoridad Europea de Seguros y Pensiones de Jubilación (EIOPA por sus siglas en inglés), que permitirá un calculo simple, y un modelo interno desarrollado por la propia entidad que deberá ser aprobado por las autoridades competentes. También se contempla la posibilidad de utilizar un modelo mixto que combine ambos, el estándar y el interno. Para el desarrollo del modelo estándar se han realizado una serie de estudios de impacto cuantitativos (QIS). El último estudio (QIS 5) ha sido el que ha planteado de forma más precisa el cálculo del SCR. Plantea unos shocks que se deberán de aplicar al balance de la entidad con el objetivo de estresarlo, y en base a los resultados obtenidos constituir el SCR. El objetivo de este trabajo es realizar una síntesis de las especificaciones técnicas del QIS5 para los seguros de vida y realizar una aplicación práctica para un seguro de vida mixto puro. En la aplicación práctica se determinarán los flujos de caja asociados a este producto para calcular su mejor estimación (Best estimate). Posteriormente se determinará el SCR aplicando los shocks para los riesgos de mortalidad, rescates y gastos. Por último, calcularemos el margen de riesgo asociado al SCR. Terminaremos el presente TFG con unas conclusiones, la bibliografía empleada así como un anexo con las tablas empleadas.

Uptake and factors that influence the use of 'sit less, move more' occupational intervention strategies in Spanish office employees

Background: Little is known about the types of 'sit less, move more' strategies that appeal to office employees, or what factors influence their use. This study assessed the uptake of strategies in Spanish university office employees engaged in an intervention, and those factors that enabled or limited strategy uptake. Methods: The study used a mixed method design. Semi-structured interviews were conducted with academics and administrators (n = 12; 44 +/- 12 mean SD age; 6 women) at three points across the five-month intervention, and data used to identify factors that influenced the uptake of strategies. Employees who finished the intervention then completed a survey rating (n = 88; 42 +/- 8 mean SD age; 51 women) the extent to which strategies were used [never (1) to usually (4)]; additional survey items (generated from interviewee data) rated the impact of factors that enabled or limited strategy uptake [no influence (1) to very strong influence (4)]. Survey score distributions and averages were calculated and findings triangulated with interview data. Results: Relative to baseline, 67% of the sample increased step counts post intervention (n = 59); 60% decreased occupational sitting (n = 53). 'Active work tasks' and 'increases in walking intensity' were the strategies most frequently used by employees (89% and 94% sometimes or usually utilised these strategies); 'walk-talk meetings' and ` lunchtime walking groups' were the least used (80% and 96% hardly ever or never utilised these strategies). 'Sitting time and step count logging' was the most important enabler of behaviour change (mean survey score of 3.1 +/- 0.8); interviewees highlighted the motivational value of being able to view logged data through visual graphics in a dedicated website, and gain feedback on progress against set goals. 'Screen based work' (mean survey score of 3.2 +/- 0.8) was the most significant barrier limiting the uptake of strategies. Inherent time pressures and cultural norms that dictated sedentary work practices limited the adoption of 'walk-talk meetings' and ` lunch time walking groups'. Conclusions: The findings provide practical insights into which strategies and influences practitioners need to target to maximise the impact of 'sit less, move more' occupational intervention strategies.

Spatial-temporal excess mortality patterns of the 1918-1919 influenza pandemic in Spain

Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden. Methods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization. Results: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south-north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918-19, but different factors explained mortality variation in each wave. Conclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.

Predictive score for mortality in patients with COPD exacerbations attending hospital emergency departments

Background: Limited information is available about predictors of short-term outcomes in patients with exacerbation of chronic obstructive pulmonary disease (eCOPD) attending an emergency department (ED). Such information could help stratify these patients and guide medical decision-making. The aim of this study was to develop a clinical prediction rule for short-term mortality during hospital admission or within a week after the index ED visit. Methods: This was a prospective cohort study of patients with eCOPD attending the EDs of 16 participating hospitals. Recruitment started in June 2008 and ended in September 2010. Information on possible predictor variables was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up. Main short-term outcomes were death during hospital admission or within 1 week of discharge to home from the ED, as well as at death within 1 month of the index ED visit. Multivariate logistic regression models were developed in a derivation sample and validated in a validation sample. The score was compared with other published prediction rules for patients with stable COPD. Results: In total, 2,487 patients were included in the study. Predictors of death during hospital admission, or within 1 week of discharge to home from the ED were patient age, baseline dyspnea, previous need for long-term home oxygen therapy or non-invasive mechanical ventilation, altered mental status, and use of inspiratory accessory muscles or paradoxical breathing upon ED arrival (area under the curve (AUC) = 0.85). Addition of arterial blood gas parameters (oxygen and carbon dioxide partial pressures (PO2 and PCO2)) and pH) did not improve the model. The same variables were predictors of death at 1 month (AUC = 0.85). Compared with other commonly used tools for predicting the severity of COPD in stable patients, our rule was significantly better. Conclusions: Five clinical predictors easily available in the ED, and also in the primary care setting, can be used to create a simple and easily obtained score that allows clinicians to stratify patients with eCOPD upon ED arrival and guide the medical decision-making process.

Analysis of multivariate stochastic signals sampled by on-line particle analyzers: Application to the quantitative assessment of occupational exposure to NOAA in multisource industrial scenarios (MSIS)

In multisource industrial scenarios (MSIS) coexist NOAA generating activities with other productive sources of airborne particles, such as parallel processes of manufacturing or electrical and diesel machinery. A distinctive characteristic of MSIS is the spatially complex distribution of aerosol sources, as well as their potential differences in dynamics, due to the feasibility of multi-task configuration at a given time. Thus, the background signal is expected to challenge the aerosol analyzers at a probably wide range of concentrations and size distributions, depending of the multisource configuration at a given time. Monitoring and prediction by using statistical analysis of time series captured by on-line particle analyzers in industrial scenarios, have been proven to be feasible in predicting PNC evolution provided a given quality of net signals (difference between signal at source and background). However the analysis and modelling of non-consistent time series, influenced by low levels of SNR (Signal-Noise Ratio) could build a misleading basis for decision making. In this context, this work explores the use of stochastic models based on ARIMA methodology to monitor and predict exposure values (PNC). The study was carried out in a MSIS where an case study focused on the manufacture of perforated tablets of nano-TiO2 by cold pressing was performed

Occupational exposure to nano-TiO2 in the life cycle steps of new depollutant mortars used in construction

The present work is focused on the measurement of workers exposure to nano-TiO2 in the life cycle steps of depollutant mortars. It has been done in the framework of the SCAFFOLD project, which aims at the management of potential risks arising from the use of manufactured nanomaterials in construction. Main findings can be summarized as follows: (1) The occupational exposure to nano-TiO2 is below 0.3 mg/m(3) for all measured scenarios. The highest concentrations were measured during the cleaning task (in the nano-TiO2 manufacturing process) and during the application (spraying) of depollutant coatings on a wall. (2) It was found a high release of particles above the background in several tasks as expected due to the nature of the activities performed. The maximum concentration was measured during drilling and during adding powder materials (mean total particle concentration up to 5.591E+04 particles/cm(3) and 5.69E+04 particles/cm(3)). However, considering data on total particle concentration released, no striking differences have been observed when tasks have been performed using conventional materials in the sector (control) and when using materials doped with nano-objects.