Certificação de qualidade versus qualidade da informação financeira: estudo para empresas portuguesas

O presente estudo tem como objetivo analisar se as empresas que têm implementado um Sistema de Gestão da Qualidade, certificadas segundo a norma da International Organization for Standardization (ISO) 9001, apresentam também uma boa qualidade da informação financeira. Neste sentido, pretende-se testar a expectável relação positiva entre a certificação de qualidade de uma empresa e a qualidade da sua informação financeira. Para isso, identificaram-se as empresas que possuem certificação do Sistema de Gestão de Qualidade, segundo a norma ISO 9001, enquanto a qualidade da informação financeira foi aferida utilizando como proxy os accruals discricionários estimados através do modelo Jones (1991). Utiliza-se um modelo logit para testar a relação pretendida, tendo como variável dependente a variável binária relativa à certificação de qualidade e como principal variável explicativa a qualidade da informação financeira. Com base nos resultados obtidos foi possível verificar a existência de uma relação positiva e estatisticamente significativa entre certificação de qualidade das empresas e a sua qualidade da informação financeira.

Evidence of Discrimination Against Afrocolombians in the Colombian Labor Market in Major Cities in 2007

This paper evaluate the hypothesis that race is a determining factor in access to quality employment in Colombia during 2007 -- Using data from the Large Integrated Household Survey (2007-I), we estimate a generalized ordered logit model -- The results provide evidence that individuals self-identified as Afrocolombian have a higher probability of being in a low quality job than other Colombians -- This probability is higher by 1.9% in Cali, 3.4% in Bogotá, 12.6% in Barranquilla, 1.8% in Cartagena, 1.1% in Medellin and 3.8% overall in these five cities, results that could indicate that there is racial discrimination against Afrocolombians in the Colombian labor market

Resource endowment and opportunity cost effects along the stages of entrepreneurship

In this paper, the start-up process is split conceptually into four stages: considering entrepreneurship, intending to start a new business in the next 3 years, nascent entrepreneurship and owning-managing a newly established business. We investigate the determinants of all of these jointly, using a multinomial logit model; it allows for the effects of resources and capabilities to vary across these stages. We employ the Global Entrepreneurship Monitor database for the years 2006–2009, containing 8269 usable observations from respondents drawn from the Lower Layer Super Output Areas in the East Midlands (UK) so that individual observations are linked to space. Our results show that the role of education, experience, and availability of ‘entrepreneurial capital’ in the local neighbourhood varies along the different stages of the entrepreneurial process. In the early stages, the negative (opportunity cost) effect of resources endowment dominates, yet it tends to reverse in the advanced stages, where the positive effect of resources becomes stronger.

Subfilter-scale Stress Modelling for Large Eddy Simulations

A subfilter-scale (SFS) stress model is developed for large-eddy simulations (LES) and is tested on various benchmark problems in both wall-resolved and wall-modelled LES. The basic ingredients of the proposed model are the model length-scale, and the model parameter. The model length-scale is defined as a fraction of the integral scale of the flow, decoupled from the grid. The portion of the resolved scales (LES resolution) appears as a user-defined model parameter, an advantage that the user decides the LES resolution. The model parameter is determined based on a measure of LES resolution, the SFS activity. The user decides a value for the SFS activity (based on the affordable computational budget and expected accuracy), and the model parameter is calculated dynamically. Depending on how the SFS activity is enforced, two SFS models are proposed. In one approach the user assigns the global (volume averaged) contribution of SFS to the transport (global model), while in the second model (local model), SFS activity is decided locally (locally averaged). The models are tested on isotropic turbulence, channel flow, backward-facing step and separating boundary layer. In wall-resolved LES, both global and local models perform quite accurately. Due to their near-wall behaviour, they result in accurate prediction of the flow on coarse grids. The backward-facing step also highlights the advantage of decoupling the model length-scale from the mesh. Despite the sharply refined grid near the step, the proposed SFS models yield a smooth, while physically consistent filter-width distribution, which minimizes errors when grid discontinuity is present. Finally the model application is extended to wall-modelled LES and is tested on channel flow and separating boundary layer. Given the coarse resolution used in wall-modelled LES, near the wall most of the eddies become SFS and SFS activity is required to be locally increased. The results are in very good agreement with the data for the channel. Errors in the prediction of separation and reattachment are observed in the separated flow, that are somewhat improved with some modifications to the wall-layer model.

“Productivity and Employment in Firm’s Acess to Public Funding to Support Innovation”

Innovation is at the heart of the Europe 2020 Strategy, in order to promote higher levels of employment and productivity. Special attention is given to increasing the effectiveness of innovation policy instruments, mainly as some authors found evidence that productivity could be negatively affected by subsidies. The aim of the study is to assess how the expected impact on firm productivity and employment is taken into account, when firms apply for public funding for innovation. The analysis is based on the case study of the Portuguese Innovation Incentive System in the Alentejo region. In order to understand which factors influence the public decision to financially support private investment, we estimated a logit model based on firms’ and applications’ characteristics, controlling for the macroeconomic environment. The results indicate that government preferences for promoting exports, exploiting firms R&D results and stimulating the level of qualified employment are shown to be more relevant than the impact on firm productivity. Furthermore, the cost to the government of new jobs created, measured at least by exemption of interest and financial charges on the loan, is almost twice as much for non-SMEs as for SMEs.

Determinants of European tourism demand in a demographic ageing society

This study identifies the senior European tourists determinants that explained their decisions to go on holidays. The empirical study was conducted among European tourists by applying a logit model. The model intends to explain the determinants related to the decision to go on holidays since the probability of a senior European tourist taking holidays in a country depends on a mix of motives as previous travel experience and demographic characteristics. Policy and theoretical implications are derived for contributing to the discussion between demographic variables and tourism demand choice patterns.

Determinants of European tourism demand in a demographic ageing society

This study identifies the senior European tourists determinants that explained their decisions to go on holidays. The empirical study was conducted among European tourists by applying a logit model. The model intends to explain the determinants related to the decision to go on holidays since the probability of a senior European tourist taking holidays in a country depends on a mix of motives as previous travel experience and demographic characteristics. Policy and theoretical implications are derived for contributing to the discussion between demographic variables and tourism demand choice patterns.

Development of a numerical platform for the modeling and optimal control of liquid metal flows

The main purpose of this work is to develop a numerical platform for the turbulence modeling and optimal control of liquid metal flows. Thanks to their interesting thermal properties, liquid metals are widely studied as coolants for heat transfer applications in the nuclear context. However, due to their low Prandtl numbers, the standard turbulence models commonly used for coolants as air or water are inadequate. Advanced turbulence models able to capture the anisotropy in the flow and heat transfer are then necessary. In this thesis, a new anisotropic four-parameter turbulence model is presented and validated. The proposed model is based on explicit algebraic models and solves four additional transport equations for dynamical and thermal turbulent variables. For the validation of the model, several flow configurations are considered for different Reynolds and Prandtl numbers, namely fully developed flows in a plane channel and cylindrical pipe, and forced and mixed convection in a backward-facing step geometry. Since buoyancy effects cannot be neglected in liquid metals-cooled fast reactors, the second aim of this work is to provide mathematical and numerical tools for the simulation and optimization of liquid metals in mixed and natural convection. Optimal control problems for turbulent buoyant flows are studied and analyzed with the Lagrange multipliers method. Numerical algorithms for optimal control problems are integrated into the numerical platform and several simulations are performed to show the robustness, consistency, and feasibility of the method.

Spezzare la Doxa? La segregazione di genere nel mercato del lavoro

La segregazione nel mercato del lavoro ha dimostrato di essere un fenomeno molto regolare. Osservando i principali indicatori sintetici, troveremo che circa la metà della forza lavoro femminile dovrebbe cambiare lavoro per potersi distribuire fra le professioni nello stesso modo degli uomini, un dato che negli ultimi decenni non sembra essere cambiato. La ricerca si è concentrata sulla socializzazione e come le strutture influenzano l'agency quando le persone pianificano le loro carriere. Tuttavia, riteniamo sia stato ignorato il ruolo della classe occupazionale d'impiego nel dare forma alla segregazione. Facendo riferimento a Bourdieu, la tesi svolge un'analisi empirica su cinque classi occupazionali: dirigenti, professioni intellettuali, tecnici, colletti blu, e professioni non qualificate e dei servizi, stimando modelli logit per calcolare le probabilità delle donne di accedere alle professioni male-dominated, dove gli uomini sono più dei due terzi della forza lavoro. Di particolare interesse è il ruolo della scelta di perseguire un'istruzione STEM e come il campo di studio moderi la relazione fra genere e probabilità di accedere ad una professione male-dominated. I risultati mostrano differenze rilevanti fra le classi occupazionali, e anche fra diversi tipi di campi di studio STEM, suggerendo che la segregazione sia un fenomeno a geometrie variabili che può essere "spezzata" più facilmente in alcune classi rispetto ad altre.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Model selection for the mixed logit with Bayesian estimation

In this paper, the mixed logit (ML) using Bayesian methods was employed to examine willingness-to-pay (WTP) to consume bread produced with reduced levels of pesticides so as to ameliorate environmental quality, from data generated by a choice experiment. Model comparison used the marginal likelihood, which is preferable for Bayesian model comparison and testing. Models containing constant and random parameters for a number of distributions were considered, along with models in ‘preference space’ and ‘WTP space’ as well as those allowing for misreporting. We found: strong support for the ML estimated in WTP space; little support for fixing the price coefficient a common practice advocated and adopted in the environmental economics literature; and, weak evidence for misreporting.

Bayesian parameter estimation for latent Markov random fields and social networks

Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.

Pseudolikelihood equations for Potts MRF model parameter estimation on higher order neighborhood systems

This letter presents pseudolikelihood equations for the estimation of the Potts Markov random field model parameter on higher order neighborhood systems. The derived equation for second-order systems is a significantly reduced version of a recent result found in the literature (from 67 to 22 terms). Also, with the proposed method, a completely original equation for Potts model parameter estimation in third-order systems was obtained. These equations allow the modeling of less restrictive contextual systems for a large number of applications in a computationally feasible way. Experiments with both simulated and real remote sensing images provided good results.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)