Este capitulo es parte de un libro del proyecto Específico “Procesos socio-técnicos de innovación en los territorios” del Instituto Nacional de Tecnología Agropecuaria (INTA) de Argentina.
The efforts to adapt to climate change in developing countries are in their infancy, and hopefully CSA will be a major contributor to these efforts. But CSA itself is evolving, and there is a growing need to refine and adapt it to the changing realities. This section of the book focus on the implications of the empirical findings for devising effective strategies and policies to support resilience and the implications for agriculture and climate change policy at national, regional and international levels.
In this chapter, it is applied the CGPE model to analyzing the performance of policy processes with respect to the production of efficient policy choices. Within the CGPE approach participation of stakeholder organizations is modeled in two ways. First, as classical lobbying influence and second as informational influence within a model of political belief formation.
This chapter proposes a network-based framework to analyze and evaluate participatory and evidence-based policy processes. Four network based performance indicators are derived by incorporating a network model of political belief formation into a political bargaining model of the Baron–Grossmann–Helpman type. The application of our approach to the CAADP reform in Malawi delivers the following results: (i) beyond incentive problems, i.e.
The chapter presents a research for development program’s shift from a Logframe Approach to an outcome and results-based management oriented Monitoring, Evaluation and Learning (MEL) system. The CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) is designing an impact pathway-based MEL system that combines classic indicators of process in research with innovative indicators of change. The chapter presents the approach to theory of change, impact pathways and results-based management monitoring, evaluation and learning system