Quantitative economic ex-ante assessment of DYNAMIX policy mixes

Citation: Bosello, F., Antosiewicz, M., Bukowski, M., Eboli, F., Gaska, J., Śniegocki, A., Witajewski-Baltvilks, J., Zotti, J. (2016). Report on Economic Quantitative Ex-Ante Assessment of Proposed Policy Mixes in the EU. DYNAMIX project deliverable D6.2. Milano: Fondazione Eni Enrico Mattei.

 

The purpose of deliverable D6.2 is to support with a quantitative economic assessment the evaluation of a set of policies scrutinized within the DYNAMIX project, aiming to promote decoupling of resources use from GDP and material efficiency within the EU.

The analytical tools used for the investigation are three macro-economic models, ICES, MEMO and MEWA, all belonging to the category of Computable General Equilibrium modelling, but with complementary characteristics. They all can assess direct and indirect policy effects on the whole economic system and the full macroeconomic feedbacks, triggered by the policy interventions. However, ICES is better suited to capture intra and extra EU trade effects, while MEWA and MEMO are better equipped to represent technological change, forward looking agents behaviour and have a richer representation of labour supply.

The strongest message from the analysis is that the policy cost, whatever the policy, crucially depends upon (a) the sensitivity of the production system to the dynamic incentive to dematerialize induced by the policy signal, i.e. ultimately upon the reaction of technological progress (b) the use of tax revenues. A responsive technological progress coupled with cuts in distortionary taxes like those on labour can produce more material efficiency and higher GDP. Nonetheless material intensive sectors will be penalized.

Another interesting result is the potential occurring of undesired rebounds effects due to intra and international trade dynamics. This is for instance the case of the pesticide tax that might simply redirect EU pesticide production abroad or of an increased public investment for material efficiency R&D that can trigger a “production scale” larger than the “material use decline” effect. This raises some caveats: all the policies examined should be accompanied by further and more capillary regulation or incentives limiting material use or promoting dematerialized services.