71 Results filtered by...
Filter
Skip to the results
Back
Clear All

View Types > Datasets

Sort

Sort by Alphabetical

Filter

Categories

View Types

Tags

Show All...
View Types > Datasets Clear All

Other: Eurobarometer
Dataset
This report is part of a series of studies that examines Europeans' awareness of and attitudes towards EU Regional Policy.
Respondents were asked about the domains that should be targeted for investment They were asked whether they think each of 11 domains are more or less important for their city or region . All but one of the domains are mentioned among the more important for their city or region by at least a relative majority of respondents.
More than nine in ten respondents (91%) consider education, health or social infrastructures one of the more important domains for investment for their city or region, followed by the environment (90%) and renewable and clean energy (87%). At least eight in ten respondents also mention support for small and medium-sized businesses (81%) and research and innovation (80%) are more important.
Smaller majorities mention the other investment domains. At least three quarters of respondents say investment in vocational training (78%) and transport facilities (75%) are the more important, while over six in ten identify energy networks (63%) and just under six in ten say tourism and culture (57%).
Finally, just over half the respondents say that broadband Internet access (51%) is one of the more important domains for investment for their city or region, while just under half say the same about investment in the reception and integration of migrants and refugees (48%).
Tags eurobarometer, priorities, eu, regional, policy
API Docs
Updated
May 23 2020
Views
93

Other: RCI
Dataset
The Regional Competitiveness Index (RCI) has been measuring the major factors of competitiveness over the past ten years for all the NUTS-2 level regions across the European Union. The Index measures with more than 70 comparable indicators the ability of a region to offer an attractive and sustainable environment for firms and residents to live and work.
Tags 2019 nuts2 nuts-2 regional competitiveness index 2019 index and 2 more
API Docs
Updated
May 23 2020
Views
7,835

Other: RCI
Dataset
The Regional Competitiveness Index (RCI) has been measuring the major factors of competitiveness over the past ten years for all the NUTS-2 level regions across the European Union. The Index measures with more than 70 comparable indicators the ability of a region to offer an attractive and sustainable environment for firms and residents to live and work.
Tags time series regional competitiveness index 2019 index rci european regional competitiveness index and 2 more
API Docs
Updated
May 23 2020
Views
11,733

Other: RCI
Dataset
The Regional Competitiveness Index (RCI) has been measuring the major factors of competitiveness over the past ten years for all the NUTS-2 level regions across the European Union. The Index measures with more than 70 comparable indicators the ability of a region to offer an attractive and sustainable environment for firms and residents to live and work.
Tags european regional competitiveness index time variation
API Docs
Updated
May 23 2020
Views
452

Other
Dataset
This dataset contains the sum of EU annual payments by individual programme / project. The dataset was used as the basis for the regionalisation of historic EU payments presented in this dataset: https://cohesiondata.ec.europa.eu/Other/Historic-EU-payments-regionalised-and-modelled/tc55-7ysv
And described in this datastory:
The dataset was compiled from different sources and carries two important qualifications / shortcomings:
1. The history of ESF payments for 1998-1999 is not complete.
2. The allocation of NUTs codes is not complete and may contains several versions of NUTS codes
Tags historic data historic payments
API Docs
Updated
May 25 2020
Views
231

Other
Dataset
1. PURPOSE: This data set provides, in a single source, regionalised (NUTS-2) annual EU expenditure data (in current prices) for specific EU funds - ERDF, Cohesion Fund, EAFRD/EAGGF and ESF. This data can be used, among other purposes, to facilitate analysis on the effects of the EU funds.
In terms of the regionalisation of EU payments made, this work expands and replaces data sets previous published on the ERDF and Cohesion fund with additional years and additional EU funds.
The following studies on ERDF and Cohesion fund expenditure are to a large extent now superseded:
- "Geography of expenditure" Work Package 13 of the ERDF and CF ex-post evaluation 2007-2013 - http://ec.europa.eu/regional_policy/en/policy/evaluations/ec/2007-2013/#13
- "Final Report - ERDF and CF Regional Expenditure" (2000-2006) - SWECo 2008 - http://ec.europa.eu/regional_policy/sources/docgener/evaluation/pdf/expost2006/expenditure_final.pdf
- "The Territorial Effects of the Structural Funds" (1994-1999) - ESPON 2005, study 2.2.1 - http://www.espon.eu/main/Menu_Projects/Menu_ESPON2006Projects/Menu_PolicyImpactProjects/structuralfundsimpact.html
The dataset does not contain any identification of the thematic nature of the investments made. This is because there was no harmonised system or information available across funds and across programme periods to estimate the thematic composition of the investments. For the ERDF and Cohesion Fund the studies cited above provided some thematic information for specific programme periods.
2. SCOPE
2.1 REGIONALISATION: This dataset provides the most complete historic picture available to date on the annual EU payments made - in EUR in current prices of the year in question (not adjusted or expressed as “in 2015 prices”) - under different shared management funds mapped to or estimated by NUTS-2 regions;
=> presented in the column "EU_payment_annual".
The work undertaken to regionalise the payment data is predominantly based on the NUTS-2013 version as described in the final report of the 2016 WIIW study (link below). In case the EU funded programmes covered more than one NUTS-2 region the regionalisation of the payments was carried out using either (1) regionalised data provided by the managing authorities or (2) the application of certain apportioning rules to the payments in order to estimate the share of the payment by NUTS-2 region.
In regionalising the data, information on the specific national or regional funding programme, which were the source of the payments, was not retained in the processing of the dataset.

2.2 MODELLING OF “REAL” EXPENDITURE: The yearly breakdown of the dataset follows the cycle of the European Commission payments to the Member States and not the date on which real expenditures took place on the ground. This characteristic may negatively affect any subsequent analytic work to carry out policy assessments.
In order to develop a more realistic estimate of the annual profile of real expenditure, the Commission tasked BERGEN to undertake work to develop a modelling of the “real” annual expenditure on the ground, and to test the robustness and sensitivity of assumptions used (see link to final report below).
=> the modelled annual expenditure is presented in the column "Modelled_annual_expenditure" and it represents the mean of 100 000 simulations on the annual EU payments to estimate real expenditure.
=> The column "Standard_Deviation_of modelled_annual_expenditure" provides the standard deviation of the “modelled_annual_expenditure" which is the root mean square of the set of deviations between each estimated annual payment in 100 000 simulations and the mean of the estimations, presented in the column "Modelled_annual_expenditure”.
=> The column "Standard_Error_of_modelled_annual_expenditure" provides the Standard Error of the "Modelled_annual_expenditure", which is a measure of how far this mean is likely to be from its expected value; that is, its scatter in repeated ex
Tags modelling payment timeseries historic payments annual erdf and 15 more
API Docs
Updated
May 29 2020
Views
13,800

Other
Dataset
This is the April 2018 (archived) version of the master "Historic EU payments regionalised and modelled" dataset.
The most recent updated version is found here: https://cohesiondata.ec.europa.eu/EU-Level/Historic-EU-payments-regionalised-and-modelled/tc55-7ysv
Tags esf nuts-2 nuts2 regionalised historic data and 13 more
API Docs
Updated
April 23 2020
Views
9,388

2014 / 2020 Categorisation
Dataset
Tags No tags assigned
API Docs
Updated
May 23 2020
Views
65

Other
Dataset
Tags No tags assigned
API Docs
Updated
August 4 2019
Views
34

Other
Dataset
This lookup table provides lists of the NUTS3 regions that are classed by DG REGIO with specific geographic characteristics as follows:
- Mountain regions: NUTS 3 regions having at least 50% of population and/or at least 50% of area in mountain areas;
- Island regions: NUTS 3 regions entirely composed of islands, or being part of islands;
- Sparsely populated regions: NUTS 3 regions having a population density below 12.5 inhabitants/km²;
- RUPS or Outermost territories - specifically recognised in Article 349 of the Treaty on the Functioning of the European Union.
Tags mountain island sparsely populated rup outermost and 3 more
API Docs
Updated
October 23 2018
Views
274