Greenhouse gas emissions from alternative futures of deforestation and agricultural management in the southern Amazon

The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006-2050) impacts on carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO(2)-equivalents (CO(2)-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO(2)-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.

Financial distress, financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.

Sampled Control for Mean-Variance Hedging in a Jump Diffusion Financial Market

In this technical note we consider the mean-variance hedging problem of a jump diffusion continuous state space financial model with the re-balancing strategies for the hedging portfolio taken at discrete times, a situation that more closely reflects real market conditions. A direct expression based on some change of measures, not depending on any recursions, is derived for the optimal hedging strategy as well as for the ""fair hedging price"" considering any given payoff. For the case of a European call option these expressions can be evaluated in a closed form.

Is the Australian wool futures market efficient as a predictor of spot prices?

Giles and Goss (1980) have suggested that, if a futures market provides a forward pricing function, then it is an efficient market. In this article a simple test for whether the Australian Wool Futures market is efficient is proposed. The test is based on applying cointegration techniques to test the Law of One Price over a three, six, nine, and twelve month spread of futures prices. We found that the futures market is efficient for up to a six-month spread, but no further into the future. Because futures market prices can be used to predict spot prices up to six months in advance, woolgrowers can use the futures price to assess when they market their clip, but not for longer-term production planning decisions. (C) 1999 John Wiley & Sons, Inc.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

The Controllership Relevance or Risk Management in non-Financial Companies: a study of risk managers` and controllers` perceptions

The purpose of this study is to analyze the Controllership relevance as support risk management in non-financial companies. Risk management is a widely discussed and disseminated subject amongst financial institutions. It is obvious that economic uncertainties and, consequently, prevention and. control must also exist in non-financial companies. To enable managers to take safe-decisions, it is essential for them to be able to count on instrumental support that provides timely and adequate information, to ensure lower levels of mistakes and risk exposure. However, discussion concerning risk management in non-financial companies is still in its early stages in Brazil. Considering this gap, this study aims at assessing how Controllership has been acting in? companies under the insight of risk and how it can contribute to risk management in non-financial companies. To achieve the proposed goal, a field research was. carried-out with non-financial companies that are located in the city Sao Paulo and listed in the Sao Paulo Stock Exchange (Bovespa). The research was carried out using questionnaires, which were sent do Risk Officers and Controllers of those companies with the purpose of evaluating their perception on the subject. The results,of the research allow us to conclude that Controllership offers support to risk management, through information that contributes to the mitigation of the risks in non-financial companies.

Diagnosis of Organizational Soft Problems in a Peruvian Financial Institution by Systemic Thinking

Managing financial institutions in an underdeveloped economic context has become a real challenge nowadays. In order to reach the organization`s planned goals, they have to deal with structural, behavioral and informational problems. From the systemic point of view, this situation gets even worse when the company does not present organizational boundaries and a cohesive identification for their stakeholders. Thus, European countries have some special financial lines in order to help the development of micro credit in Latin communities in an attempt to help the local economy. However, institutions like Caixa dos Andes in Peru present management problems when dealing with this complexity. Based on this, how can the systemic eye help in the diagnosis of soft problems of a Peruvian financial company? This study aims to diagnose soft problems of a Peruvian financial company based on soft variables like identity, communication and autonomy and also intends to identify possible ways to redesign its basic framework. The (VSM--Viable System Model) method from Beer (1967), applied in this diagnostic study, was used in a practical way as a management tool for organizations` analysis and planning. By describing the VSM`s five systems, the creation of a systemic vision or a total vision is possible, showing the organization`s complexity from the inside. Some company`s soft problems like double control, inefficient use of physical and human resources, low information flows, slowness, etc. The VSM presented an organizational diagnosis indicating effective solutions that do integrate its five systems.