Attila Kovács PhD candidate Corvinus University of Budapest Political networks in the European...

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Attila Kovács PhD candidate Corvinus University of Budapest Political networks in the European Parliament Network analysis of the 2013 CAP reform ‚MAKE’ Conference 12 May 2015

Transcript of Attila Kovács PhD candidate Corvinus University of Budapest Political networks in the European...

Page 1: Attila Kovács PhD candidate Corvinus University of Budapest Political networks in the European Parliament Network analysis of the 2013 CAP reform ‚MAKE’

Attila Kovács

PhD candidate

Corvinus University of Budapest

Political networks in the European Parliament

Network analysis of the 2013 CAP reform

‚MAKE’ Conference12 May 2015

Page 2: Attila Kovács PhD candidate Corvinus University of Budapest Political networks in the European Parliament Network analysis of the 2013 CAP reform ‚MAKE’

- Political coalitions of decision-making in the European Parliament:- Network of Member States;

- Network of EP Groups;

- To highlight the non-visible relations between MEPs in the CAP legislation;

- To observe the internal evolution of networks at each stages of the legislative process.

Motivation and objectives

Page 3: Attila Kovács PhD candidate Corvinus University of Budapest Political networks in the European Parliament Network analysis of the 2013 CAP reform ‚MAKE’

- Organic farming (Moschitz and Stolze, 2009) – EU-15 MSs tie with each other more frequently;

- Agricultural policy network of the 1992 MacSharry reform (Daugbjerg, 1999) – the structure of policy networks influence policy outcomes;

- Social network analysis in the European Parliament- EP Intergroups (Patz, 2011)- EP Committees (Patz, 2012)

Previous research and literature

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Amendments tabled to four legislative proposals:- Direct Payments

- European Agricultural Fund for Rural Development

- Single Common Market Organisation

- Horizontal Regulation

Dataset

Total amendments Amendments tabled jointlyTotal 6.749 3.093COMAGRI adopted 875 396EP Plenary adopted 829 371Final Regulation 514 225

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Social Network Analysis- Edges: links that connect pairs of nodes;- Nodes: individual actors within the network (EP Groups,

Member States);- Degree of a node: the sum of edges for a node;- Path length: the distances between pairs of nodes in the

network;- Density of the graph: ratio of the number of lines present to

the maximum possible.

Methodology

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Overview on the networks – EP Groups

Nodes EdgesAverage Degree

Average Weighted Degree

Graph Density

Average path length

Total 8 13 3,25 271,5 0,46 1,64COMAGRI 8 10 2,5 19 0,36 1,93Plenary 7 9 2,57 20,57 0,43 1,76Final 7 9 2,57 16,86 0,43 1,76

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Overview on the networks – Member States

Nodes EdgesAverage Degree

Average Weighted Degree

Graph Density

Average path length

Total 26 73 4,42 351,77 0,18 1,94COMAGRI 20 72 3,6 62 0,19 2,19Plenary 20 70 3,5 57,65 0,18 2,22Final 20 39 3,9 29,4 0,21 2,11

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The network of EP Groups 1.

Total number of amendments COMAGRI adopted amendments

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The network of EP Groups 2.Plenary adopted amendments Amendments in the Final Regulations

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The network of Member States – total number of amendments

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The network of Member States – COMAGRI adopted amendments

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The network of Member States – amendments adopted by EP plenary

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The network of Member States – amendments in the final regulations

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- Degree and Weighted Degree decreases at later stages of decision-making;

- Graph density is higher in the network of EP Groups;

- Average path length is higher in the network of Member States;

- COMAGRI changes the networks the most;

- The network of EP Groups is unchanged between EP Plenary and Final Regulation (unlike the network of Member States);

- The link between Germany and Austria is the strongest in the network of Member States;

- The links in the EPP-EFD-S&D triangle are the strongest in the network of EP Groups.

Preliminary conclusions

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[email protected]

Thank you for your attention!