A distribuição de riscos em concessões florestais: uma análise econômico-jurídica dos riscos recorrentes do inventário florestal amostral

A Lei 11.284/2006 é um importante marco legal da atividade de gestão florestal do Brasil. O manejo florestal sustentável de florestas públicas, até então exercido exclusivamente pelo Estado, passou a ser passível de concessão com o advento dessa Lei. A chamada “concessão florestal” se insere, portanto, na nova orientação político-econômica brasileira de “desestatização”, privilegiando o princípio da eficiência. Como resultado, a atividade de exploração sustentável de produtos florestais passa a ser transferida pelo Estado, por intermédio do Serviço Florestal Brasileiro, à iniciativa privada. Para o sucesso de uma concessão florestal, os licitantes interessados precisam de uma estimativa da capacidade produtiva da “Unidade de Manejo Florestal”. O estudo disponibilizado pelo Serviço Florestal Brasileiro para fazer essa estimativa é o inventário florestal que, resumidamente, tem a importante missão de antecipar às características vegetais de área que será objeto da concessão. E os resultados desse estudo são a principal fonte de informação para que o licitante calcule o valor que irá ofertar ao Poder Concedente. Ocorre que, por questões técnico-metodológicas que fogem ao conhecimento jurídico, os estudos de inventário florestal estão sujeitos a erros de grande escala, retratando, de maneira ilusória, a realidade da vegetação que compõe área que será concedida. Isto é um risco intrínseco à atividade de exploração sustentável de produtos florestais. Diante desse contexto, caberia ao Serviço Florestal Brasileiro administrar o risco do inventário florestal da maneira mais eficiente possível. Entretanto, não é isso que vem ocorrendo nos contratos de concessão florestal. Sobre a distribuição de riscos em contratos de concessão, a doutrina especializada no tema oferece critérios que, quando seguidos, possibilitam uma alocação dos riscos peculiares a cada atividade à parte que melhor tem condições de geri-los. Esses critérios aumentam a eficiência da concessão. Contudo, os contratos de concessão florestal até hoje celebrados não vêm considerando esses importantes critérios para uma eficiente distribuição de riscos. Como consequência, o risco do inventário florestal é, igualmente a outros inúmeros riscos, negligenciado por esses contratos, aumentando-se a ineficiência dos contratos de concessão. Diante desse panorama, os licitantes interessados na concessão adotam duas posturas distintas, ambas igualmente rejeitáveis: a postura do Licitante Conservador e a postura do Licitante Irresponsável. Esses perfis de licitantes geram, respectivamente, ineficiência à concessão e, caso o erro do inventário florestal efetivamente ocorra, a possibilidade de inviabilidade da concessão. Como resposta a isso – que é exatamente o “problema” que pretendo resolver –, proponho uma solução para melhor administrar o risco do inventário florestal. Essa solução, inspirada em uma ideia utilizada na minuta do contrato de concessão da Linha 4 do Metrô de São Paulo, e baseando-se nos critérios oferecidos pela doutrina para uma distribuição eficiente dos riscos, propõe algo novo: a fim de tornar a os contratos de concessão florestal mais eficientes, sugere-se que o risco do inventário florestal deve ser alocado na Administração Pública, e, caso o evento indesejável efetivamente ocorra (erro do inventário florestal), deve-se, por meio do reequilíbrio econômico-financeiro do contrato, ajustar o valor a ser pago pelo concessionário ao Poder Concedente. Como consequência dessa previsão contratual, as propostas dos licitantes serão mais eficientes, permitindo-se alcançar o objetivo primordial da Lei 11.284/2006: aumento da eficiência da exploração florestal sustentável e preservação do meio ambiente e dos recursos florestais.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

Evaluación de la distribución de riesgos en los distintos modelos de asociación público-privada para la provisión de infraestructura carretera en México

México es de los pocos países en el mundo que ha realizado dos grandes programas para la construcción de autopistas en colaboración con el sector privado. El primero, fue realizado entre 1989 y 1994, con resultados adversos por el mal diseño del esquema de concesiones; y, el segundo con mejores resultados, en operación desde 2003 mediante nuevos modelos de asociación público-privada (APP). El objetivo de la presente investigación es estudiar los modelos de asociación público-privada empleados en México para la provisión de infraestructura carretera, realizando el análisis y la evaluación de la distribución de riesgos entre el sector público y privado en cada uno de los modelos con el propósito de establecer una propuesta de reasignación de riesgos para disminuir el costo global y la incertidumbre de los proyectos. En la primera parte se describe el estado actual del conocimiento de las asociaciones público-privadas para desarrollar proyectos de infraestructura, incluyendo los antecedentes, la definición y las tipologías de los esquemas APP, así como la práctica internacional de programas como el modelo británico Private Finance Initiative (PFI), resultados de proyectos en la Unión Europea y programas APP en otros países. También, se destaca la participación del sector privado en el financiamiento de la infraestructura del transporte de México en la década de 1990. En los capítulos centrales se aborda el estudio de los modelos APP que se han utilizado en el país en la construcción de la red de carreteras de alta capacidad. Se presentan las características y los resultados del programa de autopistas 1989-94, así como el rescate financiero y las medidas de reestructuración de los proyectos concesionados, aspectos que obligaron a las autoridades mexicanas a cambiar la normatividad para la aprobación de los proyectos según su rentabilidad, modificar la legislación de caminos y diseñar nuevos esquemas de colaboración entre el gobierno y el sector privado. Los nuevos modelos APP vigentes desde 2003 son: nuevo modelo de concesiones para desarrollar autopistas de peaje, modelo de proyectos de prestación de servicios (peaje sombra) para modernizar carreteras existentes y modelo de aprovechamiento de activos para concesionar autopistas de peaje en operación a cambio de un pago. De estos modelos se realizaron estudios de caso en los que se determinan medidas de desempeño operativo (niveles de tráfico, costos y plazos de construcción) y rentabilidad financiera (tasa interna de retorno y valor presente neto). En la última parte se efectúa la identificación, análisis y evaluación de los riesgos que afectaron los costos, el tiempo de ejecución y la rentabilidad de los proyectos de ambos programas. Entre los factores de riesgo analizados se encontró que los más importantes fueron: las condiciones macroeconómicas del país (inflación, producto interno bruto, tipo de cambio y tasa de interés), deficiencias en la planificación de los proyectos (diseño, derecho de vía, tarifas, permisos y estimación del tránsito) y aportaciones públicas en forma de obra. Mexico is one of the few countries in the world that has developed two major programs for highway construction in collaboration with the private sector. The first one was carried out between 1989 and 1994 with adverse outcomes due to the wrong design of concession schemes; and, the second one, in operation since 2003, through new public-private partnership models (PPPs). The objective of this research is to study public-private partnership models used in Mexico for road infrastructure provision, performing the analysis and evaluation of risk’s distribution between the public and the private sector in each model in order to draw up a proposal for risk’s allocation to reduce the total cost and the uncertainty of projects. The first part describes the current state of knowledge in public-private partnership to develop infrastructure projects, including the history, definition and types of PPP models, as well as international practice of programs such as the British Private Finance Initiative (PFI) model, results in the European Union and PPP programs in other countries. Also, it stands out the private sector participation in financing of Mexico’s transport infrastructure in 1990s. The next chapters present the study of public-private partnerships models that have been used in the country in the construction of the high capacity road network. Characteristics and outcomes of the highway program 1989-94 are presented, as well as the financial bailout and restructuring measures of the concession projects, aspects that forced the Mexican authorities to change projects regulations, improve road’s legislation and design new schemes of cooperation between the Government and the private sector. The new PPP models since 2003 are: concession model to develop toll highways, private service contracts model (shadow toll) to modernize existing roads and highway assets model for the concession of toll roads in operation in exchange for a payment. These models were analyzed using case studies in which measures of operational performance (levels of traffic, costs and construction schedules) and financial profitability (internal rate of return and net present value) are determined. In the last part, the analysis and assessment of risks that affect costs, execution time and profitability of the projects are carried out, for both programs. Among the risk factors analyzed, the following ones were found to be the most important: country macroeconomic conditions (inflation, gross domestic product, exchange rate and interest rate), deficiencies in projects planning (design, right of way, tolls, permits and traffic estimation) and public contributions in the form of construction works.

Gender and health inequalities: intersections with other relevant axes of oppression

The risk of disease, disability, and mortality as well as access to health services are unfairly distributed among the population, with certain groups bearing an unequally larger burden of ill health and poorer access to care due to gender, sexual identity/orientation, ethnic background, or class. According to the WHO Commission on Social Determinants of Health (CSDH), these health inequalities emanate from socioeconomic and political factors (governance, cultural values, macroeconomic policies), which generate a set of socioeconomic positions in society according to which populations are stratified based on gender, ethnicity, education, income, or other factors. These societal inequalities influence people’s material and psychosocial circumstances as well as behavioral and biological factors, which in turn impact on health inequalities. Tackling gender, race/ethnic, and socioeconomic inequalities in society is thus recognized as the most powerful action to cope with unequal health risks distribution, and social innovations focusing on these ‘root causes’ are needed in order to prevent and stop endemic social inequalities and social exclusion in health within low-income as well as high-income countries. Increasing existing knowledge and making visible the health status of the most vulnerable and invisible groups are critical in order to contribute to this imperative challenge.

A subsampling approach to estimating the distribution of diversing statistics with application to assessing financial market risks

In this paper we propose a subsampling estimator for the distribution ofstatistics diverging at either known rates when the underlying timeseries in strictly stationary abd strong mixing. Based on our results weprovide a detailed discussion how to estimate extreme order statisticswith dependent data and present two applications to assessing financialmarket risk. Our method performs well in estimating Value at Risk andprovides a superior alternative to Hill's estimator in operationalizingSafety First portofolio selection.

Managing regulatory risks when outsourcing network-related services in the electricity distribution sector

Deregulation of the electricity sector liberated the electricity sale and production for competitive forces while in the network business, electricity transmission and distribution, natural monopoly positions were recognised. Deregulation was accompanied by efficiencyoriented thinking on the whole electricity supply industry. For electricity distribution this meant a transition from a public service towards profit-driven business guided by economic regulation. Regulation is the primary means to enforce societal and other goals in the regulated monopoly sector. The design of economic regulation is concerned with two main attributes; end-customer price and quality of electricity distribution services. Regulation limits the costs of the regulated company but also defines the desired quality of monopoly services. The characteristics of the regulatory framework and the incentives it provides are therefore decisive for the electricity distribution sector. Regulation is not a static factor; changes in the regulatory practices cause discontinuity points, which in turn generate risks. A variety of social and environmental concerns together with technological advancements have emphasised the relevance of quality regulation, which is expected to lead to the large-scale replacement of overhead lines with underground cables. The electricity network construction activity is therefore currently witnessing revolutionary changes in its competitive landscape. In a business characterised by high statutory involvement and a high level of sunk costs, recognising and understanding the regulatory risks becomes a key success factor. As a response, electricity distribution companies have turned into outsourcing to attain efficiency and quality goals. This doctoral thesis addresses the impacts of regulatory risks on electricity network construction, which is a commonly outsourced activity in the electricity distribution network sector. The chosen research approach is characterised as an action analytical research on account of the fact that regulatory risks are greatly dependent on the individual nature of the regulatory regime applied in the electricity distribution sector. The main contribution of this doctoral thesis is to develop a concept for recognising and managing the business risks stemming from economic regulation. The degree of outsourcing in the sector is expected to increase in years to come. The results of the research provide new knowledge to manage the regulatory risks when outsourcing services.

Choosing a random distribution with prescribed risks

We describe several simulation algorithms that yield random probability distributions with given values of risk measures. In case of vanilla risk measures, the algorithms involve combining and transforming random cumulative distribution functions or random Lorenz curves obtained by simulating rather general random probability distributions on the unit interval. A new algorithm based on the simulation of a weighted barycentres array is suggested to generate random probability distributions with a given value of the spectral risk measure.

Distribution of major health risks: findings from the global burden of disease study

Background Most analyses of risks to health focus on the total burden of their aggregate effects. The distribution of risk-factor-attributable disease burden, for example by age or exposure level, can inform the selection and targeting of specific interventions and programs, and increase cost-effectiveness. Methods and Findings For 26 selected risk factors, expert working groups conducted comprehensive reviews of data on risk-factor exposure and hazard for 14 epidemiological subregions of the world, by age and sex. Age-sex-subregion-population attributable fractions were estimated and applied to the mortality and burden of disease estimates from the World Health Organization Global Burden of Disease database. Where possible, exposure levels were assessed as continuous measures, or as multiple categories. The proportion of risk-factor-attributable burden in different population subgroups, defined by age, sex, and exposure level, was estimated. For major cardiovascular risk factors (blood pressure, cholesterol, tobacco use, fruit and vegetable intake, body mass index, and physical inactivity) 43%-61% of attributable disease burden occurred between the ages of 15 and 59 y, and 87% of alcohol-attributable burden occurred in this age group. Most of the disease burden for continuous risks occurred in those with only moderately raised levels, not among those with levels above commonly used cut-points, such as those with hypertension or obesity. Of all disease burden attributable to being underweight during childhood, 55% occurred among children 1-3 standard deviations below the reference population median, and the remainder occurred among severely malnourished children, who were three or more standard deviations below median. Conclusions Many major global risks are widely spread in a population, rather than restricted to a minority. Population-based strategies that seek to shift the whole distribution of risk factors often have the potential to produce substantial reductions in disease burden.

A disztribúció kiszervezéséhez kapcsolódó ellátási és működési kockázatok (Supply and operational risks in the outsourcing of distribution management)

A cikk célja, hogy elemző bemutatását adja az ellátási láncok működéséhez, különösen a disztribúciós tevékenység kiszervezéséhez kapcsolódó működési kockázatoknak. Az írás első része az irodalomkutatás eredményeit feldolgozva az ellátási láncok kockázati kitettségének növekedése mögött rejlő okokat törekszik feltárni, s röviden bemutatja a vállalati kockázatkezelés lehetséges lépéseit e téren. A cikk második gondolati egysége mélyinterjúk segítségével összefoglalja és rendszerezi a disztribúció kiszervezéséhez kapcsolódó kockázatokat, számba veszi a kapcsolódó kockázatkezelési lehetőségeket, s bemutatja a megkérdezett vállalatok által alkalmazott kockázat-megelőzési alternatívákat. ______ The aim of this paper is to introduce operational risks of supply chains, especially risks deriving from the outsourcing of distribution management. Based on literature review the first part of the paper talks about the potential reasons of increasing global supply chain risks, and the general business activities of risk assessment. Analyzing the results of semi-structured qualitative interviews, the second part summarizes the risks belonging to the outsourcing of distribution and introduces the potential risk assessment and avoidance opportunities and alternatives in practice.

Prevalence and social distribution of risk factors for chronic noncommunicable diseases in Brazil

OBJETIVOS: Evaluar los factores de riesgo de enfermedades crónicas no transmisibles (ECNT) e identificar las desigualdades sociales relacionadas con su distribución en la población adulta brasileña.MÉTODOS: Se estudiaron los factores de riesgo de ECNT (entre ellos el consumo de tabaco, el sobrepeso y la obesidad, el bajo consumo de frutas y vegetales [BCFV], la insuficiente actividad física en el tiempo de ocio [IAFTO], el estilo de vida sedentario y el consumo excesivo de alcohol) en una muestra probabilística de 54369 adultos de 26 capitales estatales de Brasil y el Distrito Federal en 2006. Se utilizó el Sistema de Vigilancia de los Factores Protectores y de Riesgo para Enfermedades Crónicas No Transmisibles por Entrevistas Telefónicas (VIGITEL), un sistema de encuestas telefónicas asistido por computadora, y se calcularon las prevalencias ajustadas por la edad para las tendencias en cuanto al nivel educacional mediante la regresión de Poisson con modelos lineales. RESULTADOS: Los hombres informaron mayor consumo de tabaco, sobrepeso, BCFV, estilo de vida sedentario y consumo excesivo de alcohol que las mujeres, pero menos IAFTO. En los hombres, la educación se asoció con un mayor sobrepeso y un estilo de vida sedentario, pero con un menor consumo de tabaco, BCFV e IAFTO. En las mujeres, la educación se asoció con un menor consumo de tabaco, sobrepeso, obesidad, BCFV e IAFTO, pero aumentó el estilo de vida sedentario CONCLUSIONES: En Brasil, la prevalencia de factores de riesgo para ECNT (excepto IAFTO) es mayor en los hombres que en las mujeres. En ambos sexos, el nivel de educación influye en la prevalencia de los factores de riesgo para ECNT

The Poisson-exponential lifetime distribution

In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. (C) 2010 Elsevier B.V. All rights reserved.

On modifications to the long-term survival mixture model in the presence of competing risks

A mixture model for long-term survivors has been adopted in various fields such as biostatistics and criminology where some individuals may never experience the type of failure under study. It is directly applicable in situations where the only information available from follow-up on individuals who will never experience this type of failure is in the form of censored observations. In this paper, we consider a modification to the model so that it still applies in the case where during the follow-up period it becomes known that an individual will never experience failure from the cause of interest. Unless a model allows for this additional information, a consistent survival analysis will not be obtained. A partial maximum likelihood (ML) approach is proposed that preserves the simplicity of the long-term survival mixture model and provides consistent estimators of the quantities of interest. Some simulation experiments are performed to assess the efficiency of the partial ML approach relative to the full ML approach for survival in the presence of competing risks.

Polycyclic aromatic hydrocarbons in gas and particulate phases of indoor environments influenced by tobacco smoke: levels, phase distributions, and health risks

As polycyclic aromatic hydrocarbons (PAHs) have a negative impact on human health due to their mutagenic and/or carcinogenic properties, the objective of this work was to study the influence of tobacco smoke on levels and phase distribution of PAHs and to evaluate the associated health risks. The air samples were collected at two homes; 18 PAHs (the 16 PAHs considered by U.S. EPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) were determined in gas phase and associated with thoracic (PM10) and respirable (PM2.5) particles. At home influenced by tobacco smoke the total concentrations of 18 PAHs in air ranged from 28.3 to 106 ngm 3 (mean of 66.7 25.4 ngm 3),∑PAHs being 95% higher than at the non-smoking one where the values ranged from 17.9 to 62.0 ngm 3 (mean of 34.5 16.5 ngm 3). On average 74% and 78% of ∑PAHs were present in gas phase at the smoking and non-smoking homes, respectively, demonstrating that adequate assessment of PAHs in air requires evaluation of PAHs in both gas and particulate phases. When influenced by tobacco smoke the health risks values were 3.5e3.6 times higher due to the exposure of PM10. The values of lifetime lung cancer risks were 4.1 10 3 and 1.7 10 3 for the smoking and nonsmoking homes, considerably exceeding the health-based guideline level at both homes also due to the contribution of outdoor traffic emissions. The results showed that evaluation of benzo[a]pyrene alone would probably underestimate the carcinogenic potential of the studied PAH mixtures; in total ten carcinogenic PAHs represented 36% and 32% of the gaseous ∑PAHs and in particulate phase they accounted for 75% and 71% of ∑PAHs at the smoking and non-smoking homes, respectively.