Author: Vassilen Iotzov

As part of its transnational outreach efforts, ESPON has been working with the Austrian Institute for Regional Studies, ÖIR, on assessing counterfactual methods for their applicability to Interreg. The results have been published in a transnational brief for Interreg programming authorities, outlining popular causal inference methods typically applied to policy impact assessments. The paper offers conclusions about their applicability to Interreg, taking into account basic statistical assumptions.

Such conclusions are not only relevant for designing the performance framework. Interreg programmes are often designed to support projects that internalise area-specific negative externalities occurring across jurisdictions. In such cases, eligible applicants (e.g. local administrations) are selected because of negative externality, leading to the problem of reversed causality, i.e. the locality causing the treatment. Counterfactual comparisons would then always tend to be downwardly biased. Is this a bad thing? Not necessarily: it may be more difficult to statistically infer improvements as a result of the treatment (i.e. the Interreg intervention), but this does not mean that the treatment has not been beneficial.