We assess the macroeconomic impact of the 2014-2020 EU cohesion policy programmes, based on updated data on planned expenditure. We use the spatial dynamic general equilibrium RHOMOLO in order to quantify the direct and indirect effects of the policy in the NUTS 2 regions of the EU. The results...

We employ the spatial dynamic general equilibrium model RHOMOLO to estimate the economic impact of the 2021-2027 Cohesion Policy in Bulgarian NUTS-2 regions and analyse the implications for growth and development in Bulgaria. The main investment areas covered by the policy fall into the...

We assess the macroeconomic impact of the EU cohesion policy investments deployed during the 2014-2020 programming period, employing updated data on planned expenditures, which in most Member States will take place until 2023. We use the spatial dynamic general equilibrium RHOMOLO in order to...

We present an analysis on cohesion policy investments in the regions of Romania using the spatial dynamic general equilibrium model RHOMOLO in order to provide useful insights on the 2021-2027 programmes and their implications for growth and development. The analysis is based on a hypothetical...

We investigate the effects of the 2014-20 European structural funds with a general equilibrium model calibrated on the NUTS 1 regions of the EU. We assume forward-looking agents to account for expectations and long-lasting effects of the policy. The almost €260 billion of investments lead the...

Cohesion policy is the Union's main instrument to promote regional development and reduce disparities among the Union's Member States and regions. It concentrates its support in the fields of R&D, support to SMEs, education, or transport, telecommunication, social and environmental...

The 9th Cohesion Report highlights significant achievements of Cohesion Policy in terms of fostering upwards economic and social convergence in the Union. Challenges remain especially at regional level, and these will be further impacted by structural transformations. Lessons learned from past...