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Purpose – The purpose of the paper is to evaluate the effect of mobbing in workers' health. Design/methodology/approach – Using a dataset of Spanish workers from the VI Spanish Survey on Working Conditions, the authors identify mobbed and not mobbed workers and use two different health indicators: the worker's perception that work affects health, and the presence of bad health symptoms. The authors analyze the incidence of both indicators in mobbed and not mobbed workers then estimate an econometric model to explain the probability of suffering bad health in terms of mobbing and a set of job and workers' characteristics. The authors deal with the potential endogeneity of mobbing. Findings – It is found that, regardless of the health indicator used, the probability of suffering bad health is significantly higher among mobbed workers than among those not being mobbed. Moreover, when the health indicator is based on the worker's perception, not taking into account the endogeneity of mobbing leads to underestimation of its effect on health. Practical implications – The results can be of interest for workers, firms and policy makers in charge of designing policies related to working conditions. Given the well-known link between worker's health and productivity, the paper's results can have implications from the economic point of view. Originality/value – To the authors' knowledge, this paper is the first attempt to empirically analyze the relationship between mobbing and health at Spanish workplaces. [ABSTRACT FROM AUTHOR]

This paper analyses how outliers affect the identification of conditional heteroscedasticity and the estimation of generalized autoregressive conditionally heteroscedastic (GARCH) models. First, we derive the asymptotic biases of the sample autocorrelations of squared observations generated by stationary processes and show that the properties of some conditional homoscedasticity tests can be distorted. Second, we obtain the asymptotic and finite sample biases of the ordinary least squares (OLS) estimator of ARCH( p) models. The finite sample results are extended to generalized least squares (GLS), maximum likelihood (ML) and quasi-maximum likelihood (QML) estimators of ARCH( p) and GARCH(1,1) models. Finally, we show that the estimated asymptotic standard deviations are biased estimates of the sample standard deviations. [ABSTRACT FROM AUTHOR]

This article studies the relationship between the prices of fuel and EU Allowances (EUA) for carbon emissions during Phase 3 of the European Union Emissions Trading System. We find that the forward prices of EUA, coal, gas and Brent oil are jointly determined in equilibrium. The existence of such a long-run relationship entails a permanent-transitory decomposition for the series of EUA and fuel prices that reveals the short- and long-term causal influence of the EUA market in shaping the joint dynamics of fuel prices. This result complements the literature that suggests that EUA prices are driven by the dynamics of fuel prices. Interestingly, we do not find an equilibrium relationship in the spot market. EUA and fuel spot prices are driven by independent unit root processes. The differences between spot and forward markets are attributed to the tradability of forward prices that are used for speculation and hedging in financial markets. In contrast, spot prices are mainly driven by supply and demand in energy markets. [ABSTRACT FROM AUTHOR]

Novel periodic extensions of dynamic long-memory regression models with autoregressive conditional heteroscedastic errors are considered for the analysis of daily electricity spot prices. The parameters of the model with mean and variance specifications are estimated simultaneously by the method of approximate maximum likelihood. The methods are implemented for time series of 1,200-4,400 daily price observations in tour European power markets. Apart from persistence, heteroscedasticity, and extreme observations in prices, a novel empirical finding is the importance of day-of-the-week periodicity in the autocovariance function of electricity spot prices. In particular, the very persistent daily log prices from the Nord Pool power exchange of Norway are effectively modeled by our framework, which is also extended with explanatory variables to capture supply-and-demand effects. The daily log prices of the other three electricity markets--EEX in Germany, Powernext in France, and APX in The Netherlands are less persistent, but periodicity is also highly significant. The dynamic behavior differs from market to market and depends primarily on the method of power generation: hydro power, power generated from fossil fuels, or nuclear power. The article improves on existing models in capturing the memory characteristics, which are important in derivative pricing and real option analysis. [ABSTRACT FROM AUTHOR]

This study investigated the use of a rapid bacterial toxicity test for detecting disinfectant residues released by disinfected materials. The test substances included an environmental disinfectant used in hospitals in high-risk areas, such as critical care units or emergency services, and three disinfectants used on clinical devices when a high level of disinfection is required. The test materials were polyurethane, polypropylene, glass, latex and cotton from different instruments and utensils used in hospitals. Of the four test disinfectants,o-phthalaldehyde (OPA) and 2-bromo-2-nitro-1,3-propanediol (BNP) showed the greatest inhibitory activity (as much as 300-fold greater than hydrogen peroxide in the case of OPA) according to the toxicity text. However, with the exception of hydrogen peroxide on latex, it was the most porous test materials, namely latex and cotton, that accumulated the least residue. BNP was the disinfectant that left the least residue on the five test materials, while the greatest residual concentration was left by hydrogen peroxide on latex (as much as 5 µg/cm2). The biotest used in this study permitted the detection of disinfectant residues released by different types of previously disinfected clinical materials, and can be adapted to simulate elution conditions similar to those existing in routine hospital practice. [ABSTRACT FROM AUTHOR]

The definition of limits of any geographic unit, based in the physiography of the landscape, is useful at the moment of developing environmental management politics and guidelines. Several authors have divided the Argentine Republic into regions according to the characteristics of native vegetation. The resulting units are known as phytogeographic provinces. The Monte Phytogeography Province is one of the largest ecoregions of the country and is defined as a unit where the environmental aspects are complex and difficult to categorize. In the present paper, a review of the limits of this phytogeographic province is made, according to bibliographic records of different authors. Survey trips were made and the collected data was georeferenced. A geographic information system was created with geodata and through records analysis, field work and adopting several criteria for its evaluation; the adjusted limits for the ecoregion were adjusted. A new map of the Monte Phytogeography Province is proposed for its use as input in the application of politics in the territory. [ABSTRACT FROM AUTHOR]

The objectives of the present study were to investigate whether interferon alpha (IFN) maintenance could prolong response duration and survival in patients with multiple myeloma (MM) in objective response and to analyze the characteristics of relapse and subsequent survival. From January 1991 to November 1994, 92 patients from the Spanish Cooperative Group PETHEMA with MM in objective response after 12 courses of VCMP/VBAP chemotherapy were randomized to receive IFN maintenance vs no treatment until relapse. Prognostic factors at diagnosis were similar in both groups. IFN was administered at a starting dose of 3 mU/m2 three times per week. The IFN toxicity was moderate with granulocytopenia and fatigue being the most common adverse effects. Median duration of response from randomization until relapse was 13 months in the IFN group vs 7.7 months in the no treatment arm (P = 0.042). Median survival from randomization was 38.8 months for patients given IFN vs 32.7 months for those allocated to the no treatment arm (P = 0.12). Features at relapse were similar in patients who received IFN maintenance and in those assigned to no treatment. Finally, survival from relapse was identical in both groups. In summary, our results show a significant prolongation of response in patients maintained with IFN with no significant influence on survival. In addition, in our series features at relapse and subsequent outcome were similar in both groups. [ABSTRACT FROM AUTHOR]