Global efforts to reduce tropical deforestation rely heavily on the establishment of protected areas. Measuring the effectiveness of these areas is difficult because the amount of deforestation that would have occurred in the absence of legal protection cannot be directly observed. Conventional methods of evaluating the effectiveness of protected areas can be biased because protection is not randomly assigned and because protection can induce deforesta- tion spillovers (displacement) to neighboring forests. We demon- strate that estimates of effectiveness can be substantially im- proved by controlling for biases along dimensions that are observable, measuring spatial spillovers, and testing the sensitivity of estimates to potential hidden biases. We apply matching meth- ods to evaluate the impact on deforestation of Costa Rica’s re- nowned protected-area system between 1960 and 1997. We find that protection reduced deforestation: approximately 10% of the protected forests would have been deforested had they not been protected. Conventional approaches to evaluating conservation impact, which fail to control for observable covariates correlated with both protection and deforestation, substantially overesti- mate avoided deforestation (by over 65%, based on our estimates). We also find that deforestation spillovers from protected to un- protected forests are negligible. Our conclusions are robust to potential hidden bias, as well as to changes in modeling assump- tions. Our results show that, with appropriate empirical methods, conservation scientists and policy makers can better understand the relationships between human and natural systems and can use this to guide their attempts to protect critical ecosystem services.
avoided deforestation conservation policy empirical evaluation spatial spillovers
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