The Conditions of Successful Implementation of Cohesion Policy in the New Member States of the EU

The implementation record of Cohesion Policy in the new member states seems to contradict central findings from pre- and post-accession research: Despite low domestic adoption costs in the face of the huge benefits that could arise from EU funding, success in absorption of the funds varies strongly among new member states. While some of them have absorbed already three-quarters of the funds available (Lithuania, Estonia), others are stuck below half (Czech Republic, Bulgaria), or even around a quarter (Romania) close to the end of the current financing period (2007-13). One likely explanation for this variance are different levels of administrative capacity. Still, it is hard to explain why governments would abstain from improving at least capacities for Cohesion Policy, to access millions of funding to boost their countries’ economic situation and pave their ways towards re-election. In line with this reasoning, some authors argue that under certain competitive conditions politicians lack incentives to provide the policies or public goods most or all voters desire. In such a situation voters have problems to access information to evaluate politicians properly, and politicians have problems to make credible promises to voters. While such a perspective has so far been neglected in post-accession studies, it has featured prominently in fields such as research on party politics (Mainwaring/Torcal 2006), post-communist politics (Grzymala-Busse 2006, 2008), or even development economics (Keefer/Khemani 2005). This study aims to integrate these ideas into hitherto existing insights of EU compliance research to account for successful implementation of Cohesion Policy in the new member states of Central and Eastern Europe. Methodologically, I aim to apply a Qualitative Comparative Analysis (QCA) on all 60 centrally-managed Operational Programmes in the new member states. In a second step, process-tracing case studies will help to test the causal mechanisms between the conditions detected and implementation success.