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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]