Adaptive efficiency in coffee clusters: Resilience through agglomeration, global value chains, social networks, and institutions

Abstract

This dissertation builds and tests a model of economic and environmental resilience in developing country agricultural clusters. Borrowing from economic geography, institutional economics, global change, and environmental management theories, I seek to explain resilience through adaptive efficiency. The dissertation examines adaptive efficiency and its impact on resilience in the specific context of coffee production in Costa Rica and Mexico. Local coffee economies (sub-clusters) are adaptively efficient within Global Value Chains (GVCs) when they can capitalize on spatial agglomeration economies, and are organized around institutional structures and organizations that promote strong and open networks. This adaptive efficiency model is measured and tested using a mixed-methods approach that incorporates statistical models, social network analysis (SNA), and comparative case studies to assess the model’s efficacy in predicting coffee cluster resilience. From the standpoint of a coffee cluster, resilience is the capacity to withstand market-based and environmental shocks, and upgrade over time to remain competitive in the Global Value Chain and in terms of environmental practices. Coffee cluster resilience is measured through changes in local coffee land use patterns and production volumes, as well as qualitative data, focused on product and production upgrading, governance reorientation, and support for farmers. In terms of planning and development practice, this research will help to build methods that allow policy makers to promote more effective institutions and develop policies at the cluster level with greater knowledge of the factors leading to resilient local industries.