Crescimento econômico no Estado de São Paulo: uma análise espacial

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

O impacto da qualificação da mão-de-obra no desempenho comercial do Brasil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relação entre governança corporativa e gerenciamento de resultados: um estudo em empresas brasileiras listadas na BM&FBOVESPA

The objective of this work was to identify a possible relation between corporate governance, through the structure of the boards of directors and the levels of earnings management of Brazilian public companies. The study is characterized as a descriptive, of a hypothetical-deductive nature, with quantitative approach guided by the estimation model proposed by Kang and Sivaramakrishnan (1995). The sample was comprised by 56 companies, analyzed in the period from 2011 to 2014. The information on the companies were extracted from Economatica databank. For the data analysis, we used multivariate techniques, such as Pearson correlation and panel data in POLS, Fixed Effects and Random Effects approaches. Furthermore, we applied the mean comparison test ANOVA. The results obtained show that, generally, the organizations tend to follow the profile of boards of directors recommended by the codes of corporative governance. However, the characteristics of the composition of the board, regarding its size and the duality of positions that are not yet sufficient to be considered capable of inhibiting the discretionary practice of the studied companies. Relative the control variables, only size and return on equity presented no significant relation with result management. It is important to highlight that literature point many factors that explain the different impacts caused by the formation of the administration board in different regions or countries. Among the factors pointed, we highlight the legal system of the country, the economic and political development, the importance of the capital market, and the level of accounting education.

The impact of climate change on the tourism sector in the Caribbean

The main aim of this study is to estimate the economic impact of climate change on nine countries in the Caribbean basin: Aruba, Barbados, Dominican Republic, Guyana, Jamaica, Montserrat, Netherlands Antilles, Saint Lucia and Trinidad and Tobago. A typical tourism demand function, with tourist arrivals as the dependent variable, is used in the analysis. To establish the baseline, the period under analysis is 1989-2007 and the independent variables are destination country GDP per capita and consumer price index, source country GDP, oil prices to proxy transportation costs between source and destination countries. At this preliminary stage the climate variables are used separately to augment the tourism demand function to establish a relationship, if any, among the variables. Various econometric models (single OLS models for each country, pooled regression, GMM estimation and random effects panel models) were considered in an attempt to find the best way to model the data. The best fit for the data (1989-2007) is the random effects panel data model augmented by both climate variables, i.e. temperature and precipitation. Projections of all variables in the model for the 2008-2100 period were done using forecasting techniques. Projections for the climate variables were undertaken by INSMET. The cost of climate change to the tourism sector was estimated under three scenarios: A2, B2 and BAU (the mid-point of the A2 and B2 scenarios). The estimated costs to tourism for the Caribbean subregion under the three scenarios are all very high and ranges from US$43.9 billion under the B2 scenario to US$46.3 billion under the BAU scenario.

The impact of climate change on the macroeconomy in the Caribbean

In this study, an attempt is made to assess the economic impact of climate change on nine countries in the Caribbean basin: Aruba, Barbados, Dominican Republic, Guyana, Jamaica, Montserrat, Netherlands Antilles, Saint Lucia and Trinidad and Tobago. A methodological approach proposed by Dell et al. (2008) is used in preference to the traditional Integrated Assessment Models. The evolution of climate variables and of the macroeconomy of each of the nine countries over the period 1970 to 2006 is analyzed and preliminary evidence of a relationship between the macroeconomy and climate change is examined. The preliminary investigation uses correlation, Granger causality and simple regression methods. The preliminary evidence suggests that there is some relationship but that the direction of causation between the macroeconomy and the climate variables is indeterminate. The main analysis involves the use of a panel data (random effects) model which fits the historical data (1971-2007) very well. Projections of economic growth from 2008 to 2099 are done on the basis of four climate scenarios: the International Panel on Climate Change A2, B2, a hybrid A2B2 (the mid-point of A2 and B2), and a ‘baseline’ or ‘Business as Usual’ scenario, which assumes that the growth rate in the period 2008-2099 is the same as the average growth rate over the period 1971-2007. The best average growth rate is under the B2 scenario, followed by the hybrid A2B2 and A2 scenarios, in that order. Although negative growth rates eventually dominate, they are largely positive for a long time. The projections all display long-run secular decline in growth rates notwithstanding short-run upward trends, including some very sharp ones, moving eventually from declining positive rates to negative ones. The costs associated with the various scenarios are all quite high, rising to as high as a present value (2007 base year) of US$14 billion in 2099 (constant 1990 prices) for the B2 scenario and US$21 billion for the BAU scenario. These costs were calculated on the basis of very conservative estimates of the cost of environmental degradation. Mitigation and adaptation costs are likely to be quite high though a small fraction of projected total investment costs.

2-D ZO CRS stack by considering an acquisition line with smooth topography

Os dados sísmicos terrestres são afetados pela existência de irregularidades na superfície de medição, e.g. a topografia. Neste sentido, para obter uma imagem sísmica de alta resolução, faz-se necessário corrigir estas irregularidades usando técnicas de processamento sísmico, e.g. correições estáticas residuais e de campo. O método de empilhamento Superfície de Reflexão Comum, CRS ("Common-Reflection-Surface", em inglês) é uma nova técnica de processamento para simular seções sísmicas com afastamento-nulo, ZO ("Zero-Offset", em inglês) a partir de dados sísmicos de cobertura múltipla. Este método baseia-se na aproximação hiperbólica de tempos de trânsito paraxiais de segunda ordem referido ao raio (central) normal. O operador de empilhamento CRS para uma superfície de medição planar depende de três parâmetros, denominados o ângulo de emergência do raio normal, a curvatura da onda Ponto de Incidência Normal, NIP ("Normal Incidence Point", em inglês) e a curvatura da onda Normal, N. Neste artigo o método de empilhamento CRS ZO 2-D é modificado com a finalidade de considerar uma superfície de medição com topografia suave também dependente desses parâmetros. Com este novo formalismo CRS, obtemos uma seção sísmica ZO de alta resolução, sem aplicar as correições estáticas, onde em cada ponto desta seção são estimados os três parâmetros relevantes do processo de empilhamento CRS.

Assessment and comparison of the effects of two techniques on hamstring flexibility

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

AVALIAÇÃO ROBUSTA DA MODELAGEM NEUTROSFÉRICA SOBRE O TERRITÓRIO BRASILEIRO BASEADA EM MODELOS DE PREVISÃO NUMÉRICA DE TEMPO DA AMÉRICA DO SUL

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

PRODUCTIVITY OF CANE SUGAR: LINEAR AND SPATIAL VARIABILITY BETWEEN COMPONENTS AND TECHNOLOGICAL PRODUCTION

Nowadays, the culture of the sugarcane plays an important role regarding the Brazilian reality, especially in the aspect related to the alternative energy sources. In 2009, the municipality of Suzanapolis (SP), in the Brazilian Cerrado, an experiment was conducted with the culture of the sugarcane in a Red eutrophic, with the aim of selecting, using Pearson correlation coefficients, modeling, simple, linear and multiple regressions and spatial correlation, and also the best technological and productive components, to explain the variability of the productivity of the sugarcane. The geostatistical grid was installed in order to collect the data, with 120 sampling points, in an area of 14.53 ha. For the simple linear regressions, the plants population is the component of production that presents the best quadratic correlation with the productivity of the sugarcane, given by: PRO = -0.553**xPOP(2)+16.14*xPOP-15.77. However, for multiple linear regressions, the equation PRO = -21.11+4.92xPOP**+0.76xPUR** is the one that best presents in order to estimate that productivity. Spatially, the best correlation with yield of the sugarcane is also determined by the component of the production population of plants.

Curva de Kuznets ambiental para o Estado de Mato Grosso

Issues concerning deforestation have become a crucial theme in the environmental world debate. In this picture, Mato Grosso State has become an unfavorable example because it represents 36% of the accumulated deforestation in the Brazilian Amazon. In order to investigate the relationship between deforestation and income growth, this paper estimates an Environmental Kuznets Curve (EKC) for 139 cities of Mato Grosso through spatial econometrics. Using data for the year 2006, we estimate an EKC for the deforestation per capita against income per capita and other variables controlling the spatial effects. The preliminary results indicate that an EKC exists in a reversed U shape, i. e., the income growth reduces environmental effects from the maximum point. However, introducing a cubic term for the income, the economic growth would not reveal any relationship with the deforestation in the Mato Grosso State.

Quantitative trait loci with sex-specific effects for internal organs weights and hematocrit value in a broiler-layer cross

Rapid growth in broilers is associated with susceptibility to metabolic disorders such as pulmonary hypertension syndrome (ascites) and sudden death. This study describes a genome search for QTL associated with relative weight of cardio respiratory and metabolically important organs (heart, lungs, liver and gizzard), and hematocrit value in a Brazilian broiler-layer cross. QTL with similar or different effects across sexes were investigated. At 42 days of age after fasted for 6 h, the F2 chickens were weighed and slaughtered. Weights and percentages of the weight relative to BW42 of gizzard, heart, lungs, liver and hematocrit were used in the QTL search. Parental, F1 and F2 individuals were genotyped with 128 genetic markers (127 microsatellites and 1 SNP) covering 22 linkage groups. QTL mapping analyses were carried out using mixed models. A total of 11 genome-wide significant QTL and five suggestive linkages were mapped. Thus, genome-wide significant QTL with similar effects across sexes were mapped to GGA2, 4 and 14 for heart weight, and to GGA2, 8 and 12 for gizzard %. Additionally, five genome-wide significant QTL with different effects across sexes were mapped to GGA 8, 19 and 26 for heart weight; GGA26 for heart % and GGA3 for hematocrit value. Five QTL were detected in chromosomal regions where QTL for similar traits were previously mapped in other F2 chicken populations. Seven novel genome-wide significant QTL are reported here, and 21 positional candidate genes in QTL regions were identified.

GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Space–time zero-inflated count models of Harbor seals

Environmental data are spatial, temporal, and often come with many zeros. In this paper, we included space–time random effects in zero-inflated Poisson (ZIP) and ‘hurdle’ models to investigate haulout patterns of harbor seals on glacial ice. The data consisted of counts, for 18 dates on a lattice grid of samples, of harbor seals hauled out on glacial ice in Disenchantment Bay, near Yakutat, Alaska. A hurdle model is similar to a ZIP model except it does not mix zeros from the binary and count processes. Both models can be used for zero-inflated data, and we compared space–time ZIP and hurdle models in a Bayesian hierarchical model. Space–time ZIP and hurdle models were constructed by using spatial conditional autoregressive (CAR) models and temporal first-order autoregressive (AR(1)) models as random effects in ZIP and hurdle regression models. We created maps of smoothed predictions for harbor seal counts based on ice density, other covariates, and spatio-temporal random effects. For both models predictions around the edges appeared to be positively biased. The linex loss function is an asymmetric loss function that penalizes overprediction more than underprediction, and we used it to correct for prediction bias to get the best map for space–time ZIP and hurdle models.

Probing the properties of Be star discs with spectroastrometry and NLTE radiative transfer modelling: beta CMi

While the presence of discs around classical Be stars is well established, their origin is still uncertain. To understand what processes result in the creation of these discs and how angular momentum is transported within them, their physical properties must be constrained. This requires comparing high spatial and spectral resolution data with detailed radiative transfer modelling. We present a high spectral resolution, R similar to 80 000, sub-milliarcsecond precision, spectroastrometric study of the circumstellar disc around the Be star beta CMi. The data are confronted with 3D, non-local thermodynamic equilibrium radiative transfer calculations to directly constrain the properties of the disc. Furthermore, we compare the data to disc models featuring two velocity laws: Keplerian, the prediction of the viscous disc model, and angular momentum conserving rotation. It is shown that the observations of beta CMi can only be reproduced using Keplerian rotation. The agreement between the model and the observed spectral energy distribution, polarization and spectroastrometric signature of beta CMi confirms that the discs around Be stars are well modelled as viscous decretion discs.