Abstract
Scholars, policy-makers and advocates have, in the last decade, recommended greater involvement by non-governmental organizations (NGOs) in community forest management in developing countries. Behind these recommendations lies a notion that NGOs are a sound complement to formal governments and that NGOs can improve communities’ abilities to manage their own forests. There is limited empirical work, however, testing how NGO activity affects local forest governance and deforestation. This paper reports the results of quantitative statistical tests on the effects of local NGO importance—as measured by local forest users’ reports of NGO importance—on deforestation in a sample of 200 rural Bolivian communities. In addition, it examines the effect of NGO importance on community forestry institutions—specifically, the presence of institutions for rule-making, forest monitoring, sanctioning, and enforcement of rules. Contrary to earlier research, these results suggest that NGOs have no discernible effect on community forestry institutions, though other external actors—most notably, municipal governments—seem to have a positive effect. The paper also reports a negative correlation of NGO importance on deforestation. Although these quantitative results are in part supported by qualitative field observations in selected Bolivian communities, care is needed in drawing generalized causal inferences from this evidence.
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Notes
‘NGO importance’ is measured as local residents’ assessments of the importance of NGOs in local forestry management. ‘Community Forestry Institutions’ include institutions for rule-setting, monitoring and sanctioning. These variables are described in greater detail in ‘Descriptions of Variables for Analysis,’ below.
The natural logarithm of the raw value was used to transform raw area (in ha) to a normal distribution. The same transformation was used with community population.
None of these municipalities experienced forest cover growth rates of more than 1% per year. This model was further tested with several other appropriate count data estimation techniques, all of which generated similar results.
These are three different measures of the error of the statistical model, used for generalized linear models to diagnose the influence of outlier observations.
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Acknowledgments
Financial support from the National Science Foundation (Grants HSD-0527138; SEB-0648447) is gratefully acknowledged. We would like to thank Steve Harrison for useful suggestions on an earlier version of the text.
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Wright, G., Andersson, K. Non-Governmental Organizations, Rural Communities and Forests: A Comparative Analysis of Community-NGO Interactions. Small-scale Forestry 12, 33–50 (2013). https://doi.org/10.1007/s11842-012-9206-2
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DOI: https://doi.org/10.1007/s11842-012-9206-2