Monitoring and Evaluation for Adaptation: Lessons from Development Co-operation Agencies

In the context of scaled up funding for climate change adaptation, it is more important than ever to ensure the effectiveness, equity and efficiency of adaptation interventions. Robust monitoring and evaluation (M&E) is an essential part of this, both to ensure that the prospective benefits of i...

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Detalles Bibliográficos
Autor principal: Lamhauge, Nicolina (-)
Otros Autores: Lanzi, Elisa, Agrawala, Shardul
Formato: Capítulo de libro electrónico
Idioma:Inglés
Publicado: Paris : OECD Publishing 2012.
Colección:OECD Environment Working Papers, no.38.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009706306106719
Descripción
Sumario:In the context of scaled up funding for climate change adaptation, it is more important than ever to ensure the effectiveness, equity and efficiency of adaptation interventions. Robust monitoring and evaluation (M&E) is an essential part of this, both to ensure that the prospective benefits of interventions are being realised and to help improve the design of future interventions. This paper is the first empirical assessment of M&E frameworks used by development co-operation agencies for projects and programmes with adaptation-specific or adaptation-related components. It has analysed 106 project documents across six bilateral development agencies. Based on this, it identifies the characteristics of M&E for adaptation and shares lessons learned on the choice and use of indicators for adaptation. This analysis has found that Result Based Management, the Logical Framework Approach and the accompanying logframe are the most common M&E approaches used for adaptation. In applying these approaches, the long-term perspective of most adaptation initiatives means that it is particularly important to clearly differentiate between outcomes, outputs and activities. In addition, M&E frameworks for adaptation should combine qualitative, quantitative and binary indicators. The baselines for these indicators should include the effects of future climate change, particularly for projects with long-term implications, such as investments in infrastructure. Significant challenges remain in relation to dealing with shifting baselines, attribution and time lags between interventions and outcomes.
Descripción Física:1 online resource (49 p. )