What Drives Deforestation in the Brazilian Amazon?

Joint Program Report
What Drives Deforestation in the Brazilian Amazon?
Pfaff, A. (1996)
Joint Program Report Series, 46 pages

Report 16 [Download]

Abstract/Summary:

This paper analyzes the determinants of deforestation in the Brazilian Amazon. From a model of optimal land use, it derives and then estimates a deforestation equation on country-level data for the period 1978 to 1988. The data include a deforestation measure from satellite images, which is a great advance in that it allows improved within-country analysis. Evidence exists that: increased road density in a country leads to more deforestation in that country and in neighboring countries; government-subsidized development projects increase deforestation; greater distance from markets south of the Amazon leads to less deforestation; and better soil quality leads to more deforestation. The results for government provision of credit are mixed across specifications. The population density, although the primary explanatory variable in most previous empirical work, does not have a significant effect when all the variables motivated within the model are included. However, a quadratic specification yields a more robust population result: the first few people entering an empty country have significantly more impact than the same number of people added to a densely populated country. This result suggests the importance of the spatial distribution of population.

Citation:

Pfaff, A. (1996): What Drives Deforestation in the Brazilian Amazon?. Joint Program Report Series Report 16, 46 pages (http://globalchange.mit.edu/publication/14739)
  • Joint Program Report
What Drives Deforestation in the Brazilian Amazon?

Pfaff, A.

Report 

16
46 pages
1996

Abstract/Summary: 

This paper analyzes the determinants of deforestation in the Brazilian Amazon. From a model of optimal land use, it derives and then estimates a deforestation equation on country-level data for the period 1978 to 1988. The data include a deforestation measure from satellite images, which is a great advance in that it allows improved within-country analysis. Evidence exists that: increased road density in a country leads to more deforestation in that country and in neighboring countries; government-subsidized development projects increase deforestation; greater distance from markets south of the Amazon leads to less deforestation; and better soil quality leads to more deforestation. The results for government provision of credit are mixed across specifications. The population density, although the primary explanatory variable in most previous empirical work, does not have a significant effect when all the variables motivated within the model are included. However, a quadratic specification yields a more robust population result: the first few people entering an empty country have significantly more impact than the same number of people added to a densely populated country. This result suggests the importance of the spatial distribution of population.