The world's forests provide valuable contributions to people but continue to be threatened by agricultural expansion and other land uses. Counterfactual-based methods are increasingly used to evaluate forest conservation initiatives. This review synthesizes recent studies quantifying the impacts of such policies and programs. Extending past reviews focused on instrument choice, design, and implementation, our theory of change explicitly acknowledges context. Screening over 60,000 abstracts yielded 136 comparable normalized effect sizes (Cohen's d). Comparing across instrument categories, evaluation methods, and contexts suggests not only a lack of “silver bullets” in the conservation toolbox, but that effectiveness is also low on average. Yet context is critical. Many interventions in our sample were implemented in “bullet-proof” contexts of low pressure on natural resources. This greatly limits their potential impacts and suggests the need to invest further not only in understanding but also in better aligning conservation with local and global development goals. Expected final online publication date for the Annual Review of Resource Economics, Volume 12 is October 5, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Reduced emissions from deforestation and forest degradation (REDD+) promise to deliver performance-based, cost-effective climate change mitigation. 15 years after REDD+’s conception, we analyse the rigorous counterfactual-based ev-idence for environmental and welfare effects from national and subnational initiatives, along a REDD+ Theory of Change. Using machine-learning tools for literature review, we compare 32 quantitative studies including 26 primary forest-related and 12 socioeconomic effect sizes. Average environmental impacts were positively significant yet moderately sized, comparable to impacts from other conservation tools, and mostly impermanent over time. Socioeconomic impacts were welfare-neutral to slightly positive, especially at outcome stage (e.g. rising incomes). Moderator analysis shows that REDD+ environmental additionality was likely restricted by project proponents’ ‘high-and-far’ spatial targeting of low-threat areas (adverse selection bias). Disappointingly scarce funding flows from carbon markets and ill-enforced condi-tionality probably also limited impacts. Hence, important policy and implementation lessons emerge for boosting effec-tiveness in the current global transition towards larger-scale, jurisdictional REDD+ action.

Despite a wealth of case‐specific insights from agricultural adoption studies, we lack systematic evidence on which technology characteristics matter for adoption across different innovation contexts. We synthesise the results of 304 quantitative farm‐level adoption studies for a wide range of agricultural innovations across more than 60 countries using multi‐level meta regression. Our results show that land, capital and knowhow are generally more important when an innovation uses the respective factor intensively, but this effect is reduced in contexts where the factor is abundant. Our findings have implications for the design of rural development and agricultural extension programmes. Both should consider the interplay of geographic context and innovation characteristics to develop more effective sustainable intensification strategies.

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