8 resultados para model risk

em Universidad del Rosario, Colombia


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Introducción: La OMS revela que en 2010 alrededor de 43 millones de niños menores de 5 años presentan sobrepeso. En Colombia según la Encuesta Nacional de Situación Nutricional en Colombia en su versión 2005, mostraba una prevalencia general de sobrepeso de 3.1% niños de 0 a 4 años. Es una condición de salud de origen multifactorial en la que interviene factores genéticos, ambientales, maternos y perinatales. Objetivo: Establecer la asociación de riesgo entre el bajo peso al nacer y el desarrollo de sobrepeso y obesidad en niños de 4 a 5 años. Metodología: Se realizó un estudio observacional descriptivo retrospectivo de corte transversal con los datos nutricionales, maternos y perinatales de la Encuesta Nacional de Demografía en Salud del año 2010 en Colombia. Se analizó la asociación entre la variable independiente bajo peso al nacer con el desenlace sobrepeso y obesidad en menores de 4 a 5 años, usando como medida el IMC según la edad. Se realizaron análisis univariados, bivariados y de regresión logística con un modelo de riesgo según las variables que inciden en el desenlace y la variable independiente. Resultados: La muestra obtenida para el estudio fue de 2166 niños de 4 a 5 años de edad quienes cumplían los criterios de inclusión. La prevalencia de sobrepeso u obesidad en la primera infancia fue de 21.8% (472) y el bajo peso al nacer. Los resultados sugieren la asociación de bajo peso y sobrepeso u obesidad es de ORajustado= 0.560 (0.356 – 0.881). Conclusiones: Los resultados sugieren que existe una asociación como factor protector entre el bajo peso y el sobrepeso u obesidad en la primera infancia. Sin embargo, debido al comportamiento de las variables consideradas en la muestra no hay suficiente información para rechazar completamente la hipótesis nula.

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We design a financial network model that explicitly incorporates linkages across institutions through a direct contagion channel, as well as an indirect common exposure channel. In particular, common exposure is setup so as to link the financial to the real sector. The model is calibrated to balance sheet data on the colombian financial sector. Results indicate that commercial banks are the most systemically important financial institutions in the system. Whereas government owned institutions are the most vulnerable institutions in the system.

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Tanto las industrias legales como ilegales tienen líderez y gerentes. Estas personas al mando deben hacer decisiones estrategicas con el fin de asegurar la rentabilidad de sus negocios. La manera en que ellos toman estas decisiones y las consecuencias de estas mismas son las preguntas que este documento pretende resolver. Haciendo una aplicación general del modelo de Michael Porter, este documento analiza y describe brevemente la configuración de ambos mercados (legal e illegal): es decir las maneras de hacer negocios, las tácticas utilizadas para negociar con los proveedores y compradores, las estrategias para resaltar los beneficios de sus productos frente a los sustitutos, y en general las acciones realizadas para competir, obtener un posicionamiento y porción en el mercado total. El objetivo de este documento no es exaltar las estrategias de los líderes en las industrias ilegales, sino resaltar aquello que los directivos en las industrias legales podrían hacer mejor para mejorar el nombre de los productos colombianos en el exterior.

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Background: Genetic and epigenetic factors interacting with the environment over time are the main causes of complex diseases such as autoimmune diseases (ADs). Among the environmental factors are organic solvents (OSs), which are chemical compounds used routinely in commercial industries. Since controversy exists over whether ADs are caused by OSs, a systematic review and meta-analysis were performed to assess the association between OSs and ADs. Methods and Findings: The systematic search was done in the PubMed, SCOPUS, SciELO and LILACS databases up to February 2012. Any type of study that used accepted classification criteria for ADs and had information about exposure to OSs was selected. Out of a total of 103 articles retrieved, 33 were finally included in the meta-analysis. The final odds ratios (ORs) and 95% confidence intervals (CIs) were obtained by the random effect model. A sensitivity analysis confirmed results were not sensitive to restrictions on the data included. Publication bias was trivial. Exposure to OSs was associated to systemic sclerosis, primary systemic vasculitis and multiple sclerosis individually and also to all the ADs evaluated and taken together as a single trait (OR: 1.54; 95% CI: 1.25-1.92; p-value, 0.001). Conclusion: Exposure to OSs is a risk factor for developing ADs. As a corollary, individuals with non-modifiable risk factors (i.e., familial autoimmunity or carrying genetic factors) should avoid any exposure to OSs in order to avoid increasing their risk of ADs.

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Background: Infection with multiple types of human papillomavirus (HPV) is one of the main risk factors associated with the development of cervical lesions. In this study, cervical samples collected from 1,810 women with diverse sociocultural backgrounds, who attended to their cervical screening program in different geographical regions of Colombia, were examined for the presence of cervical lesions and HPV by Papanicolau testing and DNA PCR detection, respectively. Principal Findings: The negative binomial distribution model used in this study showed differences between the observed and expected values within some risk factor categories analyzed. Particularly in the case of single infection and coinfection with more than 4 HPV types, observed frequencies were smaller than expected, while the number of women infected with 2 to 4 viral types were higher than expected. Data analysis according to a negative binomial regression showed an increase in the risk of acquiring more HPV types in women who were of indigenous ethnicity (+37.8%), while this risk decreased in women who had given birth more than 4 times (-31.1%), or were of mestizo (-24.6%) or black (-40.9%) ethnicity. Conclusions: According to a theoretical probability distribution, the observed number of women having either a single infection or more than 4 viral types was smaller than expected, while for those infected with 2-4 HPV types it was larger than expected. Taking into account that this study showed a higher HPV coinfection rate in the indigenous ethnicity, the role of underlying factors should be assessed in detail in future studies.

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In this chapter, an asymmetric DSGE model is built in order to account for asymmetries in business cycles. One of the most important contributions of this work is the construction of a general utility function which nests loss aversion, risk aversion and habits formation by means of a smooth transition function. The main idea behind this asymmetric utility function is that under recession the agents over-smooth consumption and leisure choices in order to prevent a huge deviation of them from the reference level of the utility; while under boom, the agents simply smooth consumption and leisure, but trying to be as far as possible from the reference level of utility. The simulations of this model by means of Perturbations Method show that it is possible to reproduce asymmetrical business cycles where recession (on shock) are stronger than booms and booms are more long-lasting than recession. One additional and unexpected result is a downward stickiness displayed by real wages. As a consequence of this, there is a more persistent fall in employment in recession than in boom. Thus, the model reproduces not only asymmetrical business cycles but also real stickiness and hysteresis.

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Asset correlations are of critical importance in quantifying portfolio credit risk and economic capitalin financial institutions. Estimation of asset correlation with rating transition data has focusedon the point estimation of the correlation without giving any consideration to the uncertaintyaround these point estimates. In this article we use Bayesian methods to estimate a dynamicfactor model for default risk using rating data (McNeil et al., 2005; McNeil and Wendin, 2007).Bayesian methods allow us to formally incorporate human judgement in the estimation of assetcorrelation, through the prior distribution and fully characterize a confidence set for the correlations.Results indicate: i) a two factor model rather than the one factor model, as proposed bythe Basel II framework, better represents the historical default data. ii) importance of unobservedfactors in this type of models is reinforced and point out that the levels of the implied asset correlationscritically depend on the latent state variable used to capture the dynamics of default,as well as other assumptions on the statistical model. iii) the posterior distributions of the assetcorrelations show that the Basel recommended bounds, for this parameter, undermine the levelof systemic risk.

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Attitudes toward risk influence the decision to diversify among uncertain options. Yet, because in most situations the options are ambiguous, attitudes toward ambiguity may also play an important role. I conduct a laboratory experiment to investigate the effect of ambiguity on the decision to diversify. I find that diversification is more prevalent and more persistent under ambiguity than under risk. Moreover, excess diversification under ambiguity is driven by participants who stick with a status quo gamble when diversification among gambles is not feasible. This behavioral pattern cannot be accommodated by major theories of choice under ambiguity.