The study underlines the importance of the economic evaluation of environmental and climate policies in the process of developing the policies themselves. This ensures that the costs of a policy are reasonable, ensuring that the public and decision makers are more likely to accept it.

The research suggests carrying out economic evaluations both before (ex ante evaluations) and after the implementation of a policy (ex post evaluations), to obtain more effective policies and interventions based on concrete data. Ex post evaluations can help improve the accuracy and reliability of ex ante evaluations, as they will be based on real-world data and experiences rather than assumptions and projections. While ex ante evaluations can inform the design and implementation of a policy and its evaluation principles, to improve its effectiveness and efficiency once implemented.

Linking the two types of assessments can be difficult due to a number of factors. One of these is for example the strong likelihood that policy making differs between the two types of evaluation, due to policy changes that occur during implementation. As a result, the two assessments may be based on different data sources and scales of analysis which are difficult to compare.

The report therefore provides a first attempt to outline multiple areas for improvement regarding the economic evaluation process, such as connecting experts and practitioners ex-ante and ex-post, promoting open access to data and improving the understanding of complex ex-ante models.

Download Excel repository

Download D1.1 report

The study provides an analysis of economic evaluation methods used in climate and biodiversity policies, aiming to extract the best practices that can be useful in the PATTERN project case studies. It consists of four sections: the first provides an overview of the main approaches related to the analysis proposed in the case studies; the second examines various applied case studies to extract common best practices; the third focuses on the proposed methods for evaluation, such as carbon handprint, Q-method, or life cycle impact assessment; the fourth illustrates the main challenges and needs identified in the analysis. Some of the identified good practices include: (i) a clear definition of the scope of the analysis; (ii) the use of appropriate discount rates; (iii) the use of reliable data and the assessment of all relevant tangible and intangible costs and benefits; (iv) sensitivity analysis to understand how key assumptions change or how variables can influence results; (v) consultation with relevant professionals to ensure that the analysis reflects their concerns and interests.

Overall, the best practice for using economic evaluation methods is to use a combination of approaches and carefully consider the context and specific objectives of the project or policy.

Download D1.2