Cosponsorship in the European Parliament Via Social Networks

Term Paper (Advanced seminar) 2019 12 Pages

Politics - Methods, Research


Table of Contents

1. Cosponsorship in the European Parliament

2. Determinants of Cosponsorship

3. A Network of Amendments

4. Only Limited Evidence

5. References

1. Cosponsorship in the European Parliament

A large part of the work of representatives in legislative bodies consists of crafting bills and amendments to them. Often, representatives cooperate in this task. There are many reasons for this: Getting more support from colleagues or acceptance from constituents (Gross, 2008), the sharing of workload (Puccio, Pajala, Piilo, & Tumminello, 2016) or to signal policy positions (Fowler, 2006a, 2006b; Rocca & Sanchez, 2007). Tam Cho and Fowler (2010) even found that the interconnectedness of representatives can influence the productivity of their institution, leading to influential bills. Fowler (2006a, 2006b) used cosponsorship to determine connectedness or social distance in order to explain roll call votes while controlling for ideology and party. Cosponsorship has been found to have position taking and policy significance (Rocca & Sanchez, 2007). But research about these effects is largely focused on the US with its presidential two-party system. The European Parliament (EP) plays an increasingly important role not only for research but also in the polity of the European Union (EU). As a body consisting of publicly elected representatives from national parties organizing in political rather than in national groups, it constitutes a peculiar case to study. With the elections for the 9th EP just around the corner, in this paper I examine what determines cosponsorship in the EP. In order to answer this question, I briefly discuss the relevant literature and theoretical considerations before I present my hypothesis. Then I first present the results of a social network analysis of members of the European Parliament (MEPs), specifically members of the Legal Affairs Committee (JURI) based on amendment cosponsorship. To conclude, I discuss those findings and express thoughts about future improvements of the dataset.

2. Determinants of Cosponsorship

As the EP is embedded in a relatively unique polity, there is not an abundance of cases to compare. Therefore, there is not much literature addressing the question directly. Most work done about the underlying mechanisms is about bill cosponsorship, and in the US American context (e.g.(BRATTON & ROUSE, 2011; Clark & Caro, 2013; Fowler, 2006a, 2006b; Gross, 2008; Rocca & Sanchez, 2007; Tam Cho & Fowler, 2010). Common findings in social network analysis of bill cosponsorship support arguments about homophily, i.e. similar/same partisanship, ideology, region etc. are positively associated with sponsoring bills together (BRATTON & ROUSE, 2011; Clark & Caro, 2013; Fowler, 2006a, 2006b; Gross, 2008, 2008; Puccio et al., 2016; Rocca & Sanchez, 2007; Tam Cho & Fowler, 2010). For example Clark and Caro (2013) find that partisanship and ideology cosponsorship networks. Most frequent is empirical support for social identity theory, i.e. the hypothesis that members of a minority like ethnic minorities or female legislators cosponsor (Bratton & Rouse, 2011). But there are not only microlevel factors at play. Governments and opposition have shown to build different networks for cosponsorship (Puccio et al., 2016). Fowler (2006b) shows that not only individual level factors but also institutional arrangements can shape networks of legislators. The EP certainly provides different incentives for its members than the US Congress and European multiparty systems are hard to compare to the ethnically divided two-party US environment. The EP with its supranational political groups of national parties is a really special case. So, I doubt that one can rely on the mainly US based or even national empirical evidence but has to examine the EP itself.

In the social networks of MEPs, there could be many factors cosponsorship, some which may be absent elsewhere studied so far: national interests, political groups of the EP, the GALTAN or the common left/right dimension, the economic and social left/right dimension, North-South cleavage, net donor and net receiver country representatives etc. Given the limited data employed here, I theorize that arguments of homophily and social identity theory are also valid for the EP, i.e. that EPP and S&D will sponsor together. Also, I think that those MEPs are more interconnected/independent.

Given the strong support for social identity theory in the literature, I expect members of minorities to cosponsor (Bratton & Rouse, 2011). In the context of the EP, this could be ‘opposition’ members, MEPs from small members states that do not have many seats in the EP, women, or MEPs from the 2004 accessed member states. The Social Identity model predicts members of the majority to not cosponsor the proposals of minority group members (Bratton & Rouse, 2011). This hypothesis is further based on evidence that for example women cosponsor ‘women’s issues’ (Clark & Caro, 2013) or ethnic minorities bills about equal opportunities (Fowler, 2006a). Therefore, I expect members of the Group of the Progressive Alliance of Socialists and Democrats in the European Parliament (S&D) as well as members of the Group of the European People’s Party (EPP) to be more central in cosponsorship networks.

3. A Network of Amendments

As cosponsoring is a social act based on and building social networks among legislators (Tam Cho & Fowler, 2010), I apply social network analysis to examine the question at hand. The sample consists of 839 amendments of JURI members from a time frame between July 2017 and January 2019. I hand-coded an edgelist with weights of the members of JURI indicating the number of amendments they sponsored together. The network includes the JURI members who sponsored one or several amendments in the sampled cases. This reduced the sample size from the 72 members of JURI to 48 and defined the network boundary. Sometimes the name of a cosponsor in the amendment did not appear in the EP’s list of the JURI members. I tried different methods to alleviate that, e.g. change the time frame of the sample, but I could not find out why or how that happened. Maybe they were MEPS from outside of the committee, but single MEPs cosponsoring JURI amendments was no theoretical strong argument for me to expand the population from the members of JURI to all 751 MEPs. It would have created so many isolates in such a large network that it would have been difficult to distinguish the isolated JURI members. I only selected proposals where at least one amendment was cosponsored. This, the rather small sample size and the time frame may have biased the sample. The initial idea was to automatically scrape the information from ParlTrack, but neither this nor collecting the same information from ParlTrack per hand worked as I would have needed to visit every MEPs profile (which takes a considerable amount of time to load on ParlTrack) and search for JURI amendments before I could code them. Sampling the whole EP per hand was not an option because of its size.

In the current network, a tie exists between two MEPs if they sponsored at least one amendment together. The weight of a tie represents the number of amendments two MEPs sponsored together. Out of that I combined the edgelist with metadata on the MEPs such as the name, the political group in the EP, the function in the JURI and the nationality. The node attribute EP political group encompasses ideology and partisanship but also strategic considerations. It also shows if an MEP is from one of the ‘Grand’ EP political groups S&D or EPP (Kreppel & Hix, 2003).

The MEPs with the highest degree centrality are Sergio Gaetano Cofferati, Virginie Rozière and Tiemo Wölken with eleven ties respectively. They are all members of the S&D which supports my hypothesis. The MEPs with the highest eigenvector centrality are Virginie Rozière (0.992), Evelyn Regner (0.968), Tiemo Wölken (0.998) and Jytte Guteland (1). Evelyn Regner and Jytte Guteland are also S&D members and have high degree centrality. This is especially striking as there is not one MEP in the network effectively connecting different parts of the network but most seems to happen around a few MEPs. From a theoretical point of view, it would have been interesting to examine closeness centrality, but it is hard to interpret for graphs with so many isolates (Prell, 2012).

As one can see in the graph, there are four cliques in the network (Prell, 2012). In order to examine if there is a meaningful clique relevant to the question, I created a second version of the graph only including ties of those MEPs who sponsored at least 42 amendments together, which is the rounded average tie weight (Prell, 2012). It seems like there is a clique involving Virginie Rozière, Sergio Gaetano Cofferati, Evelyn Regner, Evelyne Gebhardt, Mady Delvaux, Tiemo Wölken, Jytte Guteland, Sylvia-Yvonne Kaufmann and Enrico Gasbarra, who are all S&D members.

I also compared the transitivity of the two networks, the idea that friends of my friends are also my friends, small world etc. (Tam Cho & Fowler, 2010). The average path length of the basic network is rounded 1.923 compared to 1.071 in the reduced one. The clustering coefficient is rounded 0.725 compared to 0.91. The density is 0.062 compared to 0.035 for the new network. This supports the impression that most of the cosponsoring activity in the sampled amendments of JURI takes place among the mentioned clique members even if other committee members may sponsor high numbers of amendments.



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University of Mannheim
Social Network Analysis Netzwerkanalyse Soziale Netzwerke Co-Autorschaft Legislative Cosponsorship European Parliament EU EU Parliament EP Network SNA Methods Sozialwissenschaftliche Methoden




Title: Cosponsorship in the European Parliament Via Social Networks