2007-2013 Cohesion Categorisation Raw Data (from Closure Reports) by European Structural and Investment Funds (ESI Funds) | Politics and Governance

About this Dataset

2007-2013 Cohesion Categorisation Raw Data (from Closure Reports)

This dataset provides the raw cumulative categorisation data on the projects selected for support as reported in ERDF/CF/ESF programme final implementation reports (FIR) as presented in the closure documentation. The dataset is the best approximation of thematic content of what was financed during 2007-2013.

Each row presents a volume of EU support allocated to selected projects along with a combination of categorisation dimension codes. The Categorisation information system 2007-2013 was composed of 5 dimension providing information on:

Priority themes (activities supported)
Form of Finance
Territorial context
Location (NUTS codes)
Economic Dimension

This raw data is of interest because it allows cross analysis of the different dimensions to answer questions such as:

Which industries were supported under enterprise support measures? - (Comparing Priority themes vs Economic dimension)
What sectors benefited from support to research activities
What form of finance was used to deliver support to energy efficiency measures? - (comparing form of finance vs Priority theme)

More background information on the categorisation system 2007-2013 is available here: http://ec.europa.eu/regional_policy/en/policy/evaluations/data-for-research/

A version of this data as at the end of 2014 was previously published here: https://cohesiondata.ec.europa.eu/2007-2013/2007-2013-ERDF-CF-Categorisation-Projectselection-/b5xq-38ds

The planned categorisation amounts under certain dimension were also published in dataset for end-2008 and end-2015 : https://cohesiondata.ec.europa.eu/2007-2013/SF-2007-2013-Categorisation-Planned-2008-and-2015/x2d8-jjj2
Publisher name: DG Regional Policy
Last updated: 2025-06-26T16:56:21Z

Tables

Table 1

@esifunds.qt3c_wiyg_1.table_1

49.89 KB
1000 rows
18 columns


CREATE TABLE table_1 (
  "ms" VARCHAR,
  "ms_name" VARCHAR,
  "dg" BIGINT,
  "cci" VARCHAR,
  "title" VARCHAR,
  "year" BIGINT,
  "priority_cd" BIGINT,
  "priority_description_short" VARCHAR,
  "priority_description_long" VARCHAR,
  "territory_cd" BIGINT,
  "territory" VARCHAR,
  "finance_cd" BIGINT,
  "finance" VARCHAR,
  "location_cd" VARCHAR,
  "location" VARCHAR,
  "economic_cd" BIGINT,
  "economic" VARCHAR,
  "ar_com_amnt_eur_mil" DOUBLE
);