Corporate scandals and global indexes: examining the roles of corruption, development, press freedom, sustainability, and democracy

This study explores the relationship between corporate scandals and a set of global indices to understand whether governance institutions and structures, levels of economic, social, and democratic development, and freedom of the press influence the number of scandals. The study uses the Human Development Index, Corruption Perceptions Index, Sustainable Development Goals Index, World Press Freedom Index, and Democracy. The research question is whether the more corrupt, underdeveloped, and anti-democratic a country is, the greater the number of corporate scandals. The study uses descriptive statistics between 1989 and 2015 to analyze the relationship between these factors. Surprisingly, the results show that more developed countries had more reported scandals on average. The study highlights the need for governments, corporations, and civil society to work together to prevent and address corporate scandals and promote sustainable development, democratic governance, and human rights.publishe

Particle Learning and Smoothing

Particle learning (PL) provides state filtering, sequential parameter learning and smoothing in a general class of state space models. Our approach extends existing particle methods by incorporating the estimation of static parameters via a fully-adapted filter that utilizes conditional sufficient statistics for parameters and/or states as particles. State smoothing in the presence of parameter uncertainty is also solved as a by-product of PL. In a number of examples, we show that PL outperforms existing particle filtering alternatives and proves to be a competitor to MCMC.Comment: Published in at http://dx.doi.org/10.1214/10-STS325 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Particle Learning for General Mixtures

This paper develops particle learning (PL) methods for the estimation of general mixture models. The approach is distinguished from alternative particle filtering methods in two major ways. First, each iteration begins by resampling particles according to posterior predictive probability, leading to a more efficient set for propagation. Second, each particle tracks only the "essential state vector" thus leading to reduced dimensional inference. In addition, we describe how the approach will apply to more general mixture models of current interest in the literature; it is hoped that this will inspire a greater number of researchers to adopt sequential Monte Carlo methods for fitting their sophisticated mixture based models. Finally, we show that PL leads to straight forward tools for marginal likelihood calculation and posterior cluster allocation.Business Administratio

Influence of arterial mechanical properties on carotid blood flow: comparison of CFD and FSI studies

Carotid artery blood flow is studied to compare models with rigid and elastic walls. Considering a patient-specific geometry and transient boundary conditions. In the case of rigid walls, only the fluid (blood) behavior is considered, in a typical Computational Fluid Dynamics study. With the elastic walls, the reciprocal influence of both fluid and solid (blood and artery) are taken into account, constituting a Fluid-Structure Interaction study. Further more, the study of the influence of mechanical properties of the artery, which become stiffer with the progression of atherosclerosis, on blood flow is also presented, an innovative approach relative to the work done in this field. Results show that the carotid sinus is the preferential zone to develop atherosclerosis, given its low values of Time-Averaged Wall Shear Stress. Additionally, it is fundamental to consider the arterial wall as elastic bodies, given that the rigid model overestimates the flow velocity and Wall Shear Stress. On the different mechanical properties of the vessel, its influence is minimal in the Time-Averaged Wall Shear Stress profiles. However, given the results of the displacement and velocity profiles, their inclusion in blood flow simulations in stenosed arteries should be considered.This work was supported by FEDER funds through the COMPETE program with the reference project PTDC/SEM-TEC/3827/2014. Additionally, this work is supported by FCT with the reference projects UID/EEA/04436/2019, UID/CEC/00319/2019 and UID/EMS/04077/2019

Using MACBETH with the choquet integral fundamentals to model interdependencies between elementary concerns in the context of risk management

Effective risk management typically requires the evaluation of multiple consequences of different sources of risk, and multicriteria value models have been used for that purpose. The value of mitigating a risk impact is often considered by risk managers as dependent on the levels of other impacts, therefore there is a need for procedures to identify and model these interactions within a value measurement framework. The Choquet Integral (CI) has been used for this purpose, and several studies in the performance measurement literature have combined the 2-additive CI operator with the MACBETH approach to model interdependencies in real contexts. In this paper, we propose an alternative procedure to model interdependencies and determine the CI parameters from one single MACBETH global matrix. The procedure is illustrated with the construction of a descriptor of impacts to evaluate the risk impacts at ALSTOM Power. The paper further explains the questioning protocol to apply the proposed procedure, as well as how decision-makers can interpret the CI parameters

Site-condition map for Portugal based on Vs30 values and evaluation of the applicability of Vs30 proxies

Maps providing information on site conditions are essential tools to accurately represent the spatial distribution of ground motions, both in seismic hazard maps and in instrumental intensity maps (ShakeMaps). Project SCENE, funded by the Portuguese Foundation for Science and Technology, aims at characterizing the site conditions for Portugal and to outline a first-order site effects map to be used in seismic hazard assessment at a national level. In the context of project SCENE we developed a database of available shear-wave velocity profiles to- gether with surface-geology data and geotechnical data. Currently the database includes around 60 profiles dispersed in a variety of lithological and geological units. The vast majority of data consist of seismic refraction sections that were acquired both within the scope of ongoing research projects SCENE and NEFITAG, and previously performed CAPSA and ERSTA campaigns. Few sites analyzed with multichannel analysis of surface waves by Lopes et al. (2005) were also included. The Vs30 values calculated from the profiles range from 100 m/s to1000 m/s, but the higher values are poorly represented. We performed a careful evaluation of the geological conditions at database sites, using the smallest scale available maps (usually 1:50000), and grouped it into six generalized geological units. The variability of the distribution of Vs30 values varies significantly with the generalized geological unit. Holocene deposits and Pliocene units display the lowest variance. On the other hand the Pleistocene and Miocene units, which are characterized in Portugal by a large lithological variety, display a large dispersion. Geological outcrop studies and the analysis of geotechnical data in close association the seismic refraction data acquisition are currently under way to better understand this velocity-lithology relation. The use of proxies based either on exogenous geological-geographical defined units (Wills et al., 2006) or topographic slope shows relatively unbiased residual distributions of the logarithm of Vs30. Although the variance is large for both methods the geological/geographical-defined units method shows a better performance with respect to the topographic slope method. Lemoine et al. (2012) evaluated the applicability of the topographic slope method for stable and active re- gions of Europe using the Vs30 dataset compiled in the context of project SHARE. The variability of the entire residuals distribution is larger for the Portuguese dataset than for the European dataset, suggesting that the European database is far from being representative of the near-surface conditions in Europe

Simulation-based sequential analysis of markov switching stochastic volatility models

Abstract We propose a simulation-based algorithm for inference in stochastic volatility models with possible regime switching in which the regime state is governed by a first-order Markov process. Using auxiliary particle filters we developed a strategy to sequentially learn about states and parameters of the model. The methodology is tested against a synthetic time series and validated with a real financial time series: the IBOVESPA stock index (São Paulo Stock Exchange)