Browsing by Author "Herrera, Diego"

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    Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation.
    (PLoS One, 2015) Sills, Erin O; Herrera, Diego; Kirkpatrick, A Justin; Brandão, Amintas; Dickson, Rebecca; Hall, Simon; Pattanayak, Subhrendu; Shoch, David; Vedoveto, Mariana; Young, Luisa; Pfaff, Alexander
    Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts' selection of best case comparisons. The synthetic control method (SCM) offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal "blacklist" that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual) scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012). This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and permutations on policies that are implemented in just a few locations.
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    Protected Areas' Impacts on Brazilian Amazon Deforestation: Examining Conservation-Development Interactions to Inform Planning.
    (PLoS One, 2015) Pfaff, Alexander; Robalino, Juan; Herrera, Diego; Sandoval, Catalina
    Protected areas are the leading forest conservation policy for species and ecoservices goals and they may feature in climate policy if countries with tropical forest rely on familiar tools. For Brazil's Legal Amazon, we estimate the average impact of protection upon deforestation and show how protected areas' forest impacts vary significantly with development pressure. We use matching, i.e., comparisons that are apples-to-apples in observed land characteristics, to address the fact that protected areas (PAs) tend to be located on lands facing less pressure. Correcting for that location bias lowers our estimates of PAs' forest impacts by roughly half. Further, it reveals significant variation in PA impacts along development-related dimensions: for example, the PAs that are closer to roads and the PAs closer to cities have higher impact. Planners have multiple conservation and development goals, and are constrained by cost, yet still conservation planning should reflect what our results imply about future impacts of PAs.