Developing Analytical Tools to Understand Sustainable Development Goals Synergies and Trade-offs

The Sustainable Development Goals (SDGs) is the current framework for development. It is important to note that the technical synergies and trade-offs between SDGs, as well as how people value trade-offs between goals, will determine the possible and socially desirable level of development. In this thesis, I explore the interactions between SDG 1 [Poverty], SDG 2 [Food Security] and SDG 15 [Land Ecosystems]. Until now, most research on forest poverty dynamics has studied the effect of forest-related policies on monetary poverty, ecosystem services, agricultural productivity and food security. All of these policies affect people's lives and shape forest landscapes. Nevertheless, as far as we know, no study has yet analysed what people's preferences are regarding forest conservation versus poverty alleviation. In chapter 2, I carry out a systematic mapping of the literature to identify research gaps and possible research questions for the project. In chapter 3 and 4, I use secondary data merging spatially referenced household data (Demographic and Health Survey) and high-resolution forest cover/land cover data from Peru. This data is used to construct a quasi-experiment, which combined with covariate balancing generalized propensity score (CBGPS) weights and multiple regression analysis allows the isolation of treatment effects from potentially confounding socioeconomic and biophysical factors. Chapter 3 studies the effect of forest pattern on multidimensional poverty (MPI), finding small but important results. All forest metrics used increase MPI; however when decomposing MPI on its dimensions, some trade-offs appear. Here becomes apparent that forest fragmentation plays a role in poverty alleviation, and that looking into only one poverty dimension or forest metrics will hide the contribution of forest on poverty alleviation. Chapter 4 analyses the effect of Peruvian social programme Juntos (conditional cash transfer) on forest patterns and land-use change, finding that it prevents deforestation and promotes reforestation in 2016, 2020 and 2021. Chapter 5 builds on previous findings to look at how Peruvians value trade-offs between forest conservation, food security and housing quality. The study uses a discrete choice experiment (DCE) to assess the relative preferences over attributes that characterise the outcomes of interest and elicit citizen preferences between them. For this study, a sample of 250 members of the Peruvian public completed an online DCE questionnaire. The data from the DCE is analysed using regression techniques to obtain information on the relative preferences between outcomes. I find that citizens value policies favouring forest conservation over nutrition-related policies, unless they live in an insecure household. Combined, my findings highlight that forest and socio-economic outcomes interact with each other, and the forest-poverty dynamics need to be examined using a multidimensional approach.