Expansion of global demand for soy products and biofuel poses threats to food security and the environment. One environmental impact that has raised serious concerns is loss of Amazonian forest through indirect land use change (ILUC), whereby mechanized agriculture encroaches on existing pastures, displacing them to the frontier. This phenomenon has been hypothesized by many researchers and projected on the basis of simulation for the Amazonian forests of Brazil. It has not yet been measured statistically, owing to conceptual difficulties in linking distal land cover drivers to the point of impact. The present article overcomes this impasse with a spatial regression model capable of linking the expansion of mechanized agriculture in settled agricultural areas to pasture conversions on distant, forest frontiers. In an application for a recent period (2003)(2004)(2005)(2006)(2007)(2008), the model demonstrates that ILUC is significant and of considerable magnitude. Specifically, a 10% reduction of soy in old pasture areas would have decreased deforestation by as much as 40% in heavily forested counties of the Brazilian Amazon. Evidently, the voluntary moratorium on primary forest conversions by Brazilian soy farmers has failed to stop the deforestation effects of expanding soy production. Thus, environmental policy in Brazil must pay attention to ILUC, which can complicate efforts to achieve its REDD targets.

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Understanding the impact of road investments on deforestation is part of a complete evaluation of the expansion of infrastructure for development. We find evidence of spatial spillovers from roads in the Brazilian Amazon: deforestation "rises" in the census tracts that lack roads but are in the same county as and within 100 km of a tract with a new paved or unpaved road. At greater distances from the new roads the evidence is mixed, including negative coefficients of inconsistent significance between 100 and 300 km, and if anything, higher neighbor deforestation at distances over 300 km. Copyright Blackwell Publishing, Inc. 2007

This article addresses deforestation processes in the Amazon basin, using regression analysis to assess the impact of household structure and economic circumstances on land use decisions made by colonist farmers in the forest frontiers of Brazil. Unlike many previous regression-based studies, the methodology implemented analyzes behavior at the level of the individual property, using both survey data and information derived from the classification of remotely sensed imagery. The regressions correct for endogenous relationships between key variables and spatial autocorrelation, as necessary. Variables used in the analysis are specified, in part, by a theoretical development integrating the Chayanovian concept of the peasant household with spatial considerations stemming from von Thünen. Results from the empirical model indicate that demographic characteristics of households, as well as market factors, affect deforestation in the Amazon basin associated with colonists. Therefore, statistical results from studies that do not include household-scale information may be subject to error. From a policy perspective, the results suggest that environmental policies in the Amazon based on market incentives to small farmers may not be as effective as hoped, given the importance of household factors in catalyzing the demand for land. The article concludes by noting that household decisions regarding land use and deforestation are not independent of broader social circumstances, and that a full understanding of Amazonian deforestation will require insight into why poor families find it necessary to settle the frontier in the first place.

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