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Evaluating the long‐term impacts of promoting “green” agriculture in the Amazon
Author(s) -
Sills Erin O.,
CavigliaHarris Jill L.
Publication year - 2015
Publication title -
agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.29
H-Index - 82
eISSN - 1574-0862
pISSN - 0169-5150
DOI - 10.1111/agec.12200
Subject(s) - amazon rainforest , agriculture , frontier , georeference , deforestation (computer science) , business , ecosystem services , land use , matching (statistics) , natural resource economics , agricultural economics , geography , environmental planning , agroforestry , environmental resource management , ecosystem , economics , environmental science , ecology , computer science , statistics , mathematics , archaeology , physical geography , biology , programming language
Frontier development in the Brazilian Amazon has created vast areas of largely deforested landscapes. Conservation efforts in these post‐frontier zones seek to protect the remaining forest fragments and promote sustainable agricultural practices that absorb labor, meet market demand, and generate ecosystem services. Assessments of these efforts often find that rates of sustained uptake are disappointingly low and that impacts are difficult to discern, but this could be due to the short‐time frames of both the efforts themselves and their evaluation. We investigate the impacts of participation in an internationally sponsored farmer association that for 15 years promoted sustainable agricultural practices in the heavily deforested state of Rondônia, Brazil. Using data from a georeferenced four‐period panel survey of farmers in combination with remote sensing data on land use spanning the life of the association, we apply matching methods to estimate the impacts of participation. We find that membership resulted in more diversified production systems, including more land allocated to agroforestry. Members also deforested less of their farms, but this difference is not statistically significant after we control for selection bias in membership.