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Large scale surveys of rain forest livelihoods open up new possibilities for understanding the role of forest resources in the well-being of forest peoples but often overlook the factors that influence the diverse economic foci of forest-based communities. In this paper we describe the Peruvian Amazon Rural Livelihoods and Poverty (PARLAP) Project which seeks to identify the factors that contribute to rural poverty among indigenous and folk peoples through the first large scale survey conducted in this data poor region. Our paper draws upon a community census undertaken in four major river sub-basins in eastern Peru (n = 919 communities) and asks the question, how do environmental and market factors influence the economic orientation of rain forest communities? Recognizing that standard approaches that explain activity choice by current conditions are problematic because of potential endogeneity, we propose a new analytical framework that examines how historical (initial) conditions determine current conditions and thus current economic activities. Our approach produces a rich array of results that point to the importance of initial environmental endowments and market access of communities in shaping their economic orientation, interacting in different ways depending on the key natural resource upon which they rely. [ABSTRACT FROM AUTHOR]

This paper studies the dynamics of land-use in the Brazilian Amazon using a structural vector autoregressive (SVAR) model. A fixed effect panel data specification is used to control for the heterogeneity in the data. Meanwhile, spatial autocorrelation is also diagnosed by a statistical methodology that allows us to split the model in subsamples (clusters) of more homogenous municipalities. The clustering analysis shows that there are three clusters whose land-use patterns are strongly different in an economical point of view. The first cluster identifies municipalities dedicated to logging, natural resources exploitation and slash-and-burn cultures; the second cluster shows a more diversified agriculture; while the third cluster presents very developed intensive agriculture municipalities. Another contribution of this article relies on the assessment of contemporaneous causal relation among distinct land-uses areas. This new approach allows us to evaluate the dynamics relations arisen from unexpected innovations in the process of soil occupation. The impulse response functions (IRF) and the forecast error variance decompositions (FEVD) generate the following results: (1) in the opposition direction of previous studies, we find that the demand for cropping does not require to clear new areas of forest.; (2) contrary to previous studies we do not find indication that cattle ranching is the primary driver of deforestation; (3) the impact of a shock of pasture land on itself is virtually null at the initial stages, but increases over time, not requiring to clear extra areas of forest land but rather competing with crop land; (4) it seems that if not for all the Amazon Basin, at least in one cluster, cattle ranching and cropping could be competitive activities; and (5) we find out that in the long run pasture innovation is responsible for the major percent of the forecast error concern all land uses. It probably means that the destiny of distinct categories of land, in cluster one, is endogenously determine by activities connected to cattle. [Copyright &y& Elsevier]

Abstract: This paper analyzes the impact of agricultural technical efficiency on the propensity of farmers to convert natural land into agricultural plots, i.e., to deforest, in the Brazilian Legal Amazon (BLA). A two-step econometric approach is adopted. A bootstrapped translog stochastic frontier that is a posteriori checked for functional consistency is used to assess technical efficiency and these estimates are put into a land-use model to assess the impact of productivity on deforestation. Analysis of agricultural census tract data suggests that technical efficiency has a U-shaped effect: both less and more efficient farms use more land for their agricultural activities and so have a positive effect on deforestation. However, the majority of farms in the BLA are on the ascendant slope, so that efficiency implies more deforestation in the BLA. The poor environmental valuation of the Brazilian forest, the uneven land distribution, and the problem of the de facto openly accessed forested and “unproductive” lands in the BLA could explain the U-shaped effect of technical efficiency on the conversion of forested land into agricultural land. [Copyright &y& Elsevier]