The 2014–2020 European Regional Development Fund Indicators: The Incomplete Evolution

Nigohosyan, Daniel; Vutsova, Albena

doi:10.1007/s11205-017-1610-8

Cited by 11 publications

(12 citation statements)

References 8 publications

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“…The selection of data for regional classification is non-trivial because chosen variables define and describe studied regions (Fiaschetti et al, 2021) and a framework we use to assess regional performance is a crucial factor in designing and evaluating regional policy (Greco et al, 2018). Variables used in the analyses of socio-economic development represent diverse concepts and the final set depends also on the availability of statistical data (Nigohosyan and Vutsova, 2018). As it was pointed out before Polish communes are classified as urban (U), urban-rural (UR) and rural (R).…”

Section: Data and Resultsmentioning

confidence: 99%

Typology and Development of Local Administrative Units: Spatial Discriminant Analysis

Batóg¹,

Batóg²

2021

ERSJ

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Purpose:The aim is the evaluation of the consistency of typology of local administrative units (LAU) with their level of socio-economic development. The authors identified also the impact of the incorporation of spatial relations on the stability of such consistency. Design/Methodology/Approach: The spatial linear discriminant analysis with various weights matrices has been applied. Introducing the spatial relationship between observations in different locations to the classical classification method allows to identify non-measurable spatial factors differentiating different locations as well as the directions of their development. Findings:The results confirmed a high discrepancy between the administrative type and the level of development of Polish communes in 2006-2018. The higher compliance of official typology of examined units with their actual level of development was found when spatial relations were incorporated. The obtained results indicated the marginalisation of mediumsized cities, and underdevelopment of urban-rural communes. The following predictors, new dwellings, employment rate, population density, and registered entities, had the highest power of discrimination in the classification process. Practical Implications: Proposed models could have the practical application for determining the actual type of local administrative unit and designing regional policy. Especially in the case when some intervention is needed in the area of financial external support. Such policy may reduce disparities between the levels of development of the various regions, especially addressing the problems of less developed areas. Originality/Value: This research presents a concept of spatial linear discriminant analysis with a spatial component of regional structure integrated in form of spatial weights matrices. The proposed method was applied to identify the meaning of neighbouring regions characteristics in classification of territorial units, as well as to indicate the group of Polish voivodeships characterized by a high and low degree of correspondence between the actual and expected type of the territorial unit.

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Section: Data and Resultsmentioning

confidence: 99%

Typology and Development of Local Administrative Units: Spatial Discriminant Analysis

Batóg¹,

Batóg²

2021

ERSJ

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“…The need for further improvement of monitoring systems for regional strategies and regional programs for the use of EU funds is confirmed by studies concerning EU's financial perspectives 2004-2006 and 2007-2013, by Dvorak [54] and Kupiec, who stated that "most studies were of limited value as they concentrated on the implementation process, not on the effects and justification of intervention" [55]. Similar problems are faced by other EU countries in terms of EU structural funds [56].…”

Section: Discussionmentioning

confidence: 96%

Taxonomic Assessment of Transition to the Green Economy in Polish Regions

Godlewska

Sidorczuk-Pietraszko

2019

Sustainability

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In this paper, an aggregate indicator of a regional green economy (Regional Green Economy Index—RGEI) was proposed and applied to assess the level of green economy in Polish regions and its changes in the period 2004–2016. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method was applied, which is one of the multi-criteria decision making methods (MCDM), widely used to assess the spatial diversity of socio-economic phenomena. Common reference values (ideal and anti-ideal solution) were used for variables for the entire study period. It allowed not only for creating a ranking of regions, but to assess progress towards the green economy as well. It was found that all regions of Poland made progress in this respect. Most importantly, the regions ranked the worst before Poland’s accession to the European Union, made substantial progress. It was stated as well that none among the studied regions had high values of all variables included in the aggregate index. The maximum value of the RGEI index was about 0.5, while the index range is [0,1]. Additionally, an important finding was the fact that the weights of all diagnostic variables obtained using information entropy method were about equal, which confirms the approach of researchers and institutions who do not use weighting in aggregate indicators for well-being or sustainable development—which means implicitly using equal weights.

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“…Moreover, the assessment of funded programs is still a largely discussed topic. In this regard, the EC identified two main assessment problems with the system of indicators (Nigohosyan & Vutsova, 2018): difficulties in establishing the cause-andeffect relationships between actions, results, and impacts, due to the influence of external factors; and difficulties in measuring the impacts, because they are usually the cumulative effect of many actions, affect diverse populations, and it takes time for them to show their actual effects. For the 2014-2020 period the EC tried to overcome these difficulties in the ERDF context by discarding the concept of impact indicators and introducing a new intervention logic.…”

Section: Introductionmentioning

confidence: 99%

“…For the 2014-2020 period the EC tried to overcome these difficulties in the ERDF context by discarding the concept of impact indicators and introducing a new intervention logic. Nevertheless, Nigohosyan & Vutsova (2018) claimed that despite the changes, some of the identified problems with the indicators were not solved. Besides, these authors suggested that ongoing evaluations should include activity's in-depth analysis of the relevance of the selected output indicators.…”

Section: Introductionmentioning

confidence: 99%

EU Operational Programmes Reporting: From Basics to Practices

Amaro

Henriques

Viseu

2022

Springer Proceedings in Political Science and International Relations

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We examine the main existing challenges that currently arise in the assessment of European Union (EU) funds devoted to three thematic objectives (TOs): Research and Innovation (R&I); Low-carbon economy (LCE); and Information and Communication Technologies (ICT). In this regard, a literature review on the European Regional Development Fund (ERDF) initiatives is performed, with a special focus on the Portuguese (PT) case, also addressing their assessment and reporting practices. Data systematization is coupled with the European Commission (EC)’s main guidelines and with the guidance recommendations brought by Management authorities (MA) for the 2014–2020 period. A bibliometric analysis is conducted to further understand the current research interest in the evaluation of EU funds, and the type of assessment methods and reporting practices employed. Most of the approaches rely on cost–benefit analysis and place less attention on data availability, variable selection, and monitoring/assessment options. The selection and application of the framework indicators, either related to their financial execution or achievement, are assumed as critical factors concerning the monitoring, reporting, and assessment processes. Our findings emphasize the need for harmonization and simplification of the reporting techniques, also highlighting the sparse data availability and some reporting conflicts.

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The 2014–2020 European Regional Development Fund Indicators: The Incomplete Evolution

Cited by 11 publications

References 8 publications

Typology and Development of Local Administrative Units: Spatial Discriminant Analysis

Typology and Development of Local Administrative Units: Spatial Discriminant Analysis

Taxonomic Assessment of Transition to the Green Economy in Polish Regions

EU Operational Programmes Reporting: From Basics to Practices

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