What drives deforestation in the Brazilian Amazon? : Evidence from satellite and socioeconomic data.
Abstract in HTML and technical report in HTML and PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).
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Language: | eng |
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MIT Joint Program on the Science and Policy of Global Change
2003
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Online Access: | http://mit.edu/globalchange/www/abstracts.html#a16 http://hdl.handle.net/1721.1/3633 |
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author2 | Pfaff, Alexander Strickland Putalik. |
author_facet | Pfaff, Alexander Strickland Putalik. |
collection | MIT |
description | Abstract in HTML and technical report in HTML and PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/). |
first_indexed | 2024-09-23T13:37:42Z |
id | mit-1721.1/3633 |
institution | Massachusetts Institute of Technology |
language | eng |
last_indexed | 2024-09-23T13:37:42Z |
publishDate | 2003 |
publisher | MIT Joint Program on the Science and Policy of Global Change |
record_format | dspace |
spelling | mit-1721.1/36332019-04-12T08:10:05Z What drives deforestation in the Brazilian Amazon? : Evidence from satellite and socioeconomic data. Pfaff, Alexander Strickland Putalik. QC981.8.C5 M58 no.16 Abstract in HTML and technical report in HTML and PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/). Includes bibliographical references. 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. 2003-10-24T14:57:43Z 2003-10-24T14:57:43Z 1996-12 no. 16 http://mit.edu/globalchange/www/abstracts.html#a16 http://hdl.handle.net/1721.1/3633 eng Report no. 16 33, [13] p. 361137 bytes application/pdf application/pdf MIT Joint Program on the Science and Policy of Global Change |
spellingShingle | QC981.8.C5 M58 no.16 What drives deforestation in the Brazilian Amazon? : Evidence from satellite and socioeconomic data. |
title | What drives deforestation in the Brazilian Amazon? : Evidence from satellite and socioeconomic data. |
title_full | What drives deforestation in the Brazilian Amazon? : Evidence from satellite and socioeconomic data. |
title_fullStr | What drives deforestation in the Brazilian Amazon? : Evidence from satellite and socioeconomic data. |
title_full_unstemmed | What drives deforestation in the Brazilian Amazon? : Evidence from satellite and socioeconomic data. |
title_short | What drives deforestation in the Brazilian Amazon? : Evidence from satellite and socioeconomic data. |
title_sort | what drives deforestation in the brazilian amazon evidence from satellite and socioeconomic data |
topic | QC981.8.C5 M58 no.16 |
url | http://mit.edu/globalchange/www/abstracts.html#a16 http://hdl.handle.net/1721.1/3633 |