Causal Forces of Deforestation in the Brazilian Amazon: Does Size Matter? Diana Weinhold London School of Economics Eustaquio Reis Institute for Applied Economic Research (Ipea) Danilo Igliori University of Cambridge III LBA Scientific Conference Brasilia, July 2004

Policy Problem Maintenance of biologically diverse ecosystems Land requirements and the opportunity costs of non-conversion  critical trade-off for developing countries

Motivation The economic literature on land use in developing countries has traditionally focused on efficiency and equity issues. Farm size is at central stage to discuss variation in the economic performance, and political and social issues in rural areas. Causes of deforestation have growing in interest recently in the land use literature. With few exceptions (Fearnside 1993, Walker et al 2000) the relationship between farm size and deforestation has not been properly addressed.

Objective In this paper we attempt to empirically investigate the existence of the relationship between farm size and deforestation. We use some traditional and some more recent econometric results for model evaluation in panel data and a comprehensive data set on land use in the Brazilian Amazon. We study the question of whether the size composition of agricultural establishments in the Amazon region plays a role in determining the rate of deforestation.

Data The data used is part of a database (Desmat) managed by IPEA/DIMAC (The Directorate of Macroeconomic Studies of the Institute of Applied Economic Research, Brazil). This is a data panel for all the municipalities of Brazilian Legal Amazon (AML) including thousands of variables on major economic, demographic and geo-ecological aspects. Desmat includes spatially detailed geo-ecological information available in GIS and socio-economic sources, in particular Demographic and Economic Census data observed in 5-year periods from 1970 to 2000.

Explaining Levels Is the size composition of establishments correlated with the level of land clearing? Dependent Variable: Log of Cleared Land, 1995 Size composition: shares of private land within different size classes (7 classes, from tiny - 100,000 ha)

Explaining Levels Control variables Property rights: shares of private land within different ownership status (owners, sharecroppers, renters, squatters) Area: municipality and establishments Other: state dummies, distance to state and federal capitals,percentage of good soil, km of navigable river, and natural vegetation variables. Omitted categories: Large establishment share (>1000 and <5000), and Owner-titled land share

Dependent Variable: Log of Cleared Land, 1995

Explaining Levels Results In levels it is the small and tiny establishments and squatters that are clearing the most as a proportion of their land.

Explaining Changes Is the change of composition of establishments size correlated with changes in the extent of land clearing? We then model the change in cleared land from 1985 to 1995 and condition on levels in Dependent Variable = Growth of cleared land, Control variables for changes: total private land, shares of estab sizes and ownership. other control variables and omitted variables as in the analysis for levels

Dependent Variable = Growth of cleared land,

Explaining Changes Results This more or less confirms the first result, Caution: there is evidence that the reason squatters are associated with more clearing has to do with the fact that they operate on very small scales.

Causality The model for changes has the additional benefit that, controlling for the initial levels of the variables, many of the hidden omitted-variable problems so common in levels will be eliminated from the analysis. This does not mean that omitted variable problems have been eliminated entirely, however, for again, a correlation in changes could be due to other, unmeasured and/or omitted variables.

Causality 2 we adopt some recent econometric techniques for panel model evaluation to test for a type of Granger-causality. Essentially we shall test whether knowledge about the size composition of establishments will help us predict, out-of-sample, the future rate of deforestation (and vice versa). We use panel model evaluation techniques suggested by Granger, C.W. and L. Huang (1997). Evaluation of Panel-data models: Some Suggestions from Time-series, unpublished manuscript, UC San Diego.

Causality 3 Applications for the Amazon Andersen, L., C. Granger, E. Reis, D. Weinhold, and S. Wunder (2003). The Dynamics of Deforestation and Economic Growth in the Brazilian Amazon, Cambridge University Press: Cambridge. Weinhold and Reis (2003). Land Use and Transportation Costs in the Brazilian Amazon, Working paper, AAE, UW-Madison.

Causality 4 In our first evaluation attempts we find no evidence of causality. This suggests that the correlations found are just that and we should be careful before making policy decisions with the hope of altering the rate of land clearing.

Conclusions Our cross-section modelling using regression analysis for levels and changes in cleared area suggests correlation between size and deforestation. Tiny establishments apparently clear more land proportionally. These results don’t pass a more rigorous causality test. We should be cautious and extra attention should be paid to trying to figure out the underlying causal mechanisms between establishment size and deforestation. There is large scope for further research on the matter.