A number of countries offer domestic consumers the option of buying their electricity supply through a 'green tariff', whereby the supplier typically guarantees that all or part of the supply has been generated using renewable energy sources. Various studies have sought to identify variables describing and/or predicting why domestic consumers choose to purchase a green tariff. This study builds on previous work by reviewing the UK market in particular. Using data from the Understanding Society Survey (USS), a number of variables were tested for their predictive power. This included variables identified as statistically significant within other studies, and variables that -to the authors' knowledge -have not been tested through other work. Results find that individuals in the highest income quartile, those with higher qualifications, those supporting the Green political party, those exhibiting strong environmental behaviour and those households not in receipt of winter fuel payments were all more likely to have purchased green tariffs. Significant to a lesser degree were strong environmental attitudes and those households with some form of renewable energy technology installed. JEL Codes: Q4, Q5, H4, L94

Evaluability assessments (EAs) have differing definitions, focus on various aspects of evaluation, and have been implemented inconsistently in the last several decades. Climate change adaptation (CCA) programming presents particular challenges for evaluation given shifting baselines, variable time horizons, adaptation as a moving target, and uncertainty inherent to climate change and its extreme and varied effects. The Adaptation Fund Technical Evaluation Reference Group (AF-TERG) developed a framework to assess the extent to which the Fund’s portfolio of projects has in place structures, processes, and resources capable of supporting credible and useful monitoring, evaluation, and learning (MEL). The framework was applied on the entire project portfolio to determine the level of evaluability and make recommendations for improvement. This chapter explores the assessment’s findings on designing programs and projects to help minimize the essential challenges in the field. It discusses how the process of EA can help identify opportunities for strengthening both evaluability and a project’s MEL more broadly. A key conclusion was that the strength and quality of a project’s overall approach to MEL is a major determinant of a project’s evaluability. Although the framework was used retroactively, EAs could also be used prospectively as quality assurance tools at the pre-implementation stage.