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We use historical industrial emissions data to assess the level of abatement and overallocation that took place across European countries during the pilot phase (2005-2007)of the European Union Emission Trading Scheme. Using a dynamic panel data model, we estimate the counterfactual (business-as-usual) emissions scenario for EU member states. Comparing this baseline to allocated and verified emissions, we conclude that both overallocation and abatement occurred, along with under-allocation and emissions inflation. Over the three trading years of the pilot phase we find over-allocation of approximately 376 million EUAs (6%) and total abatement at the member state level of 107 Mt CO2 (1.8%). However, due to over-allocation and possible uncertainty about future allocation methodologies, we calculate that emissions inflation of approximately 119 Mt CO2 (2%) occurred, resulting in emissions over the pilot phase being approximately 12 Mt CO2 (0.2%) higher than they would have been in the absence of the EU ETS.

Integrated assessment models offer a crucial support to decisionmakers in climate policy making. For a full understanding and corroboration of model results, analysts ought to identify the exogenous variables that influence the model results the most (key drivers), appraise the relevance of interactions, and the direction of change associated with the simultaneous variation of uncertain variables. We show that such information can be directly extracted from the data set produced by Monte Carlo simulations. Our discussion is guided by the application to the well‐known DICE model of William Nordhaus. The proposed methodology allows analysts to draw robust insights into the dependence of future atmospheric temperature, global emissions, and carbon costs and taxes on the model's exogenous variables.