Crossing spatial analyses and livestock economics to understand deforestation processes in the Brazilian Amazon: the case of São Félix do Xingú in South Pará

The Amazon is the largest tropical forest area on Earth, and has been undergoing rapid deforestation for the last four decades. In the Brazilian Amazon, large‐scale pasture for cattle ranching and soybean production are the main land uses, leading to a yearly deforestation rate of 0.5%. These conversions are mostly located in frontier areas distributed along the so‐called “arc of deforestation”. Within this large zone, various land use change processes are interacting through several modes of land valuation and organisation. From several case studies in the State of Pará (Brazil), the current project aims at analysing how landscape dynamics are related to infrastructure development, ecological conditions, zoning policies and to the evolution and the organisation of the production, consumption and marketing chains of livestock products. This paper presents the results for one test site, the region of São Félix do Xingú, South of Pará This region is the focus of land speculation, cattle expansion, and deforestation. Road construction, investments in electrical energy, financial credit for cattle, and the land reform policies have all fuelled this process. All these factors make this region one of the most dynamic agricultural frontiers in the Brazilian Amazon. The main objective of the paper is to improve our understanding of deforestation processes by crossing spatial analyses and 1ivestock economics.studies, and to characterise the role and impact of various natural and anthropic factors in the location and development of the main types of farmers, and their policy implications.     

Dividend Omissions and Intraindustry Information Transfers

We examine potential information transfers from companies that announce dividend omissions to their industry rivals. Specifically, we examine the abnormal stock returns and abnormal earnings forecast revisions of rivals after a company makes a dividend‐omission announcement. Our results show negative and significant abnormal stock returns and negative and significant abnormal forecast revisions for rival companies in response to the announcement, and a significant and positive relation between the two. We conclude that a dividend‐omission announcement transmits unfavorable information across the announcing company's industry that affects cash flow expectations and ultimately stock prices.     

Sanov meets Cramér again

We introduce a new method for proving large-deviation principles (LDPs). This method amounts to "mixing" a collection of LDPs with a sequence of probability measures that obeys itself an LDP. As an illustration, we construct from empirical measures a sequence of capacity-valued maps that can be considered as an indexed collection of LDPs. The index 1 coincides with Sanov's theorem. By taking a Poisson mixture we establish a new connection with Cramér's theorem.