Economic Causes of Deforestation in the Brazilian Amazon: An Empirical Analysis of the 2000s

Transcription

1 Economic Causes of Deforestation in the Brazilian Amazon: An Empirical Analysis of the 2000s Jorge Hargrave, IPEA Krisztina Kis-Katos, University of Freiburg Latin America Modeling Project Belo Horizonte, January 2012

2 AGENDA Motivation and stylized facts Hypothesis, data and methods Results 1

3 THE DEFORESTATION ARCH CONCENTRATES ALL: CATTLE RANCHING, SOYBEAN PLANTATIONS, BETTER INFRA-STRUCTURE AND DEFORESTATION The states of PA, MT and RO concentrate: 82% of deforestation ( ) 74 % of cattle herd 68% of soybean 47% of area 49 % of people Best production climate, best roads and smaller distance to markets Source: MT RO PA x Amazon.xls 2

4 THE TYPICAL DEFORESTATION CYCLE CONSISTS OF SEVERAL STEPS 3

5 CATTLE HERD DENSITY HAS INCREASED MAILY IN THE DEFORESTATION ARCH FROM 1990 TO 2006 Source: Barreto 2009

6 DEFORESTATION IN THE BRAZILIAN AMAZON IN THE 2000s REMAINED AT HIGH LEVELS DESPITE THE DECREASE IN GOVERNMENT DEVELOPMENT POLICIES FOR THE REGION Average yearly deflorestation Thousand Km 2 19,4 15,9 There should be endogenous drivers linked to the development process Média Média Source: INPE, Fearnside (2005) 5

7 THERE ARE LARGE FLUCTUATIONS OF DEFORESTATION RATES THAT LITERATURE HAS NOT EXPLAINED Average yearly deforestation Thousand Km 2 27,4 25,2 21,4 18,2 18,2 18,8 14,1 11, ~2,5x Possible causes: Commodity prices Environmental policy Credit Conservation units Rain / El Nino Other??? Source: INPE 6

8 PRICES OF MEAT, SOYBEANS AND DEFORESTATION HAVE FLUCTUATED VERY CLOSELY Deforestation, soy and meat prices ( ) R$ (2007) for soybean, IGP meat for meat Km2 (thousands) Soya bean price Meat price (lagged) Deforestation Source: Adated from Barreto et al. (2008)

9 POLICY INFLUENCE? PPCDAm

10 AGENDA Motivation and stylized facts Hypothesis, data and methods Results 9

11 OBJECTIVE Understand the determinants / correlates of deforestation rates fluctuations between 2002 and 2009 Using variables that are decision parameters of agents

12 MAIN HIPOTHESIS Rational Hipothesis 1: Higher prices of soybean and meat increase deforestation It increases agricultural profitability, representing an incentive to clear Hipothesis 2: More subsidized credit make more deforestation possible It allows farmers to invest in clearing the area for pastures and soybean plantations Hipothesis 3: Presence of protected areas decrease deforestation It represents a barrier to deforestation Hipothesis 4: Government environmental police became more effective in recent years It increases the risk of clearing, decreasing the expected agricultural profitability 11

13 DATA AND MODELING STRATEGY Municipality data (457 municipalities), OLS panel data with first differences Differences in time within municipalities Controls for constant non-observables (e.g. economic structure) Exclude areas with <10% of forest Control for spatial autocorrelation Possible problems: endogeneity, spatial, nonobservables (GMM solves partialy) 12

14 ESTIMATED EQUATION lndit = X itβ + λst + εit. lndit = lndit lndit-1: yearly growth rate of deforestation / municipality (aug-jul) Elements of X it : beef price soybean price (regional) ln protected areas ln real rural credit / area ln real environmental fines / deforest. ln settlement area / area Rainfall (proxy) λst : yearly time trends state-year fixed effects

15 AGENDA Motivation and stylized facts Hypothesis, data and methods Results 14

16 FACTORS INFLUENCING DEFORESTATION Higher soy prices Higher meat prices paid at farmgate Larger credit availability Larger risk perception (higher fining density) More areas under protection More settlement areas

17 BASELINE RESULTS Dependent: ln Deforestation (1) (2) (3) (4) OLS OLS OLS OLS Soy price ** ** * * Meat price ** * ln Fines intensity ** ** ** ** ln Protected areas ln Indigenous areas ln Settlement areas ** High rainfall ** ** ** ** Deforestation rates (neighb.) lnfines intensity (neighb.) ** ** Year fixed effects No Yes No No State-year fixed effects No No Yes Yes No. observations (municip.) 3199 (457) 3199 (457) 3199 (457) 3199 (457) R-squared Robust -Robust -Disappears with state-year FE -Robust, negative -Robust, positive - Spillover effects Note: OLS in first difference form. Robust standard errors, clustered at municipality level, are reported in parentheses.,*,** denote significance at 10%, 5%, and 1% level.

18 IMPLICATIONS FOR POLICY MAKING New policies should focus on changing economic incentives in favor of sustainable land uses Commodity prices should be taken seriously for new policies, policy evaluation and deforestation forecasts Fines are effective Credit granting rules should be revised (were only partially) Extensions: Spatial econometrics Refine temporal analysis with field research to understand decision process Focus on specific aspects with RDD? Integrate in with IAMs 17

19 THANKS! QUESTIONS? Commets of further questions: 18