This cumulative dissertation comprises three independent studies concerning fundamental topics of sustainable agriculture. Chapter 2 draws from the absence of water data, which limits the development of economic models gauging water scarcity impacts. The paper makes a central contribution by developing an in-depth description of national statistics, international and global water databases. Chapter 3 concerns the relationship between deforestation data and widely used institutional indices. The paper offers empirical-based evidence about the relationship between governmental performance, public corruption perception and forest resources. Moreover, computer-intensive data management was employed to convert georeferenced raster data into a format compatible with economic statistical software and enable sample replications of large original data. Chapter 4 investigates the presence of spatial spillovers as providing beneficial opportunities to family farming credit in the Brazilian Amazon. Credit rationing is argued to target wealthier farmers engaged in livestock production while neglecting those producing crops. The paper employs a spatial Durbin error model of credit acquisition for husbandry and agricultural systems in 103 microregions. To enhance the paper’s discussion, 35 semi-structured interviews with key informants were conducted
