†
∗
Earlier versions of this paper has been presented in seminars at the University of Manchester, University of Oslo and University of Uppsala, as well as at the 3 rd
Pan-European
Conference on EU politics in Istanbul 20 th
-23 rd
September 2006. I would like to thank the participants, in particular Giacomo Benedetto, Fang-Yi Chiou, Fabio Franchino, Sara Hagewould also like to thank the Scientific Computing Group, USIT at the University of Oslo, in particular Jon Kristian Nilsen and Simen Gaure, for computational assistance.
†
Post-doctoral research fellow, Department of Political Science, University of Oslo. P.O.
Box 1097, Blindern 0317 Oslo E-mail: bjorn.hoyland@stv.uio.no
1

Abstract
The legislative powers of the European Parliament (EP) vary considerably across procedures. Resolutions adopted by the EP have no direct policy implications. The position of the EP matters in the codecision procedure. Existing research has been criticized for pooling across procedures. This paper compares voting behaviour in in these two procedures.
The Bayesian approach allows for joint estimation of legislators ideal point and proposal parameters, as well as associated uncertainty. The results complement existing research as it finds that the left-right pattern dominates voting behaviour in both procedures.
However, the size of the uncertainty around the point estimates cautions against subsequent use of these to distinguish between individual legislators.
2

Legislative bodies perform two essential functions in democratic societies.
They legislate and provide the electorate with competing elites to choose between in elections
1
. The voting behaviour of the legislators contains elements of both functions. In order to legislate, a legislator needs to form a coalition of a sufficient size. The size will depend on the majority requirement in the chamber and the role of other veto-players in the political system
2
. These considerations are not relevant if the purpose of the voting behaviour is posturing. Posturing highlights differences between elites. The prevalence of either of these two logics vary as a function of the power of the legislature. Differences exist both across and within individual legislatures. The variance within is a legislature is function of procedure.
The power of the European Parliament varies considerably across procedures
3
.
Resolutions are without any direct policy implications. They may however be on issues of considerable interest among the European publics, e.g. the legitimacy of the war in Iraq. EP amendments in the codecision procedure may have substantive implications for both business and consumers in the European Union.
In the 2 nd reading of the codecision procedure, MEPs vote on amendments to the Common Position (CP) of the Council of Ministers (CoM). The CP will be adopted as EU law unless an absolute majority of Members of the European
Parliament (MEPs) vote to amend. This can be considered a super-majority requirement as there are always some MEPs not present at each vote 4 . The amendments adopted by the EP as this stage may, in full or modified form, have direct impact on EU public policy.
The paper compares voting behaviour under these two procedures. Previous research, reviewed in the next section, has found that the there is a stable leftright pattern in roll-call votes in the European Parliament 5 . These findings have been criticized for generalizing from roll-call votes to the whole population of votes and for pooling voting decisions across procedures. The second section discusses the statistical estimation of the spatial model of politics and
3

presents the data. Existing studies rely on the Nominate for estimating the ideal point of Members of Parliament (MEPs) in the policy space 6 . The technique has been criticized for introducing a false sense of precision by not reporting any uncertainty around the point estimates of individual members 7 . There are two alternative strategies for obtaining uncertainty estimates, bootstrapping 8 and Markov Chain Monte Carlo (MCMC) simulation
9
. This paper adopts the latter approach. The results are reported in the third section. The findings complement existing research as it finds the left-right pattern dominates voting behaviour on both codecision amendments and resolutions. The uncertainty around the point estimates should caution researchers against the use of ideal points estimated from roll call votes to distinguish between representatives from within the same party-group. While the pattern of requesting roll-call votes differ across party groups, there is not clear whether there is a relationship between the location of the roll call vote and the party requesting it.
The European Parliament is the only directly elected body in the European
Union. The power of the institution has increased substantively through a process of repeated treaty negotiations 10 11 . A common justification for increasing the powers of the EP is to reduce the democratic deficit of the EU 12 . This view is contested
13 14 15
. Nevertheless, a clear understanding of how MEPs vote will help us to assess the effects of increasing the power of the institution. Studies of roll call votes have found that the transnational party groups are able to command cohesion levels comparable to parties in many national parliaments 16 17 . A study of all roll call votes taken between the beginning of the first directly elected parliament in 1979 and the end of the fifth parliament in 2004 found growing level of party group cohesion. Ideological diversity does not depress party group cohesion, but national fragmentation does 18 . Surveys of MEPs political preferences find overlaps between representatives in different
4

party groups. This pattern is not replicated in their revealed voting behaviour, as measured by Nominate scores 19 . One of the key questions in the literature is to what extent the transnational party group or the national party guides the behavior of MEPs. MEPs defection from the national party group can be explained in terms of divergent national party preferences 20 . National party leaderships pay most attention to MEPs behaviour when in government
21
.
Nominate scores show that politics in the European Parliament is predominantly one-dimensional. A second dimension may also be present. As Nominate is an explorative, rather than a confirmative technique, the interpretation of the dimensionality is post-hoc. This is either conducted through visual investigation of the spatial maps, or by using the nominate scores as dependent variables in subsequent regression analysis. The main dimension can be explained by the ideological location of the national party on the left-right dimension. A lot of the variation on the second dimension can also be explained in terms of left-right politics. Pro-anti integration and government-opposition dynamics may explain where MEPs are located on this dimension 22 .
The existing research has been criticized for pooling voting decisions across procedures. Hix, Noury and Roland 23 use all roll call votes taken during the period under investigation. These votes are not randomly sampled from a large population of votes. It is hence necessary to employ the concept of apparent populations in order for standard notion of repeated sampling to hold. An apparent population is the particular realization of a series of random events that could in principle have been different. It is one realization of the state of the world drawn from a population of possible realizations
24
. The second problem associated with the use of roll-call votes in the EP is that they are only taken on a subset of all votes 25 . Both the decision to call a vote on an issue, as well as the decision to ask for the individual voting decisions to be recorded is a result of decisions taken by involved actors 26 . These decisions are unlikely to be random. To the extent that requesting a roll call vote influence how MEPs
5

vote, the results from the study of these votes will not be generalizable to all voting decisions in the European Parliament. The population of roll call votes is not a representative sample of all voting decisions in the European Parliament
27
.
Behavior in roll-call votes may differ from behaviour in non-recorded votes.
Carubba and his coauthors
28 question the reliability of traditional studies of roll call voting in legislatures where the majority of votes are not by roll-call.
Their study of the first year of the 1999-2004 European Parliament reveals that roll call votes were neither called on a random sample of votes, nor requested proportionally be the different party groups. A large majority of the roll call votes was taken on resolutions. These votes do not have any direct impact on
EU public policy. Roll call votes on codecision and assent legislation were in the minority. MEPs who voted against their own party group on codecision legislation were more likely to be absent on resolution votes, thereby inflating the party cohesion scores. The strategic use of roll call votes may bias the results of traditional roll-call votes both in terms of cohesion scores and in terms of the main policy dimensions.
One of the key concerns of Carubba and his co-authors
29 is that votes on resolutions dominate the population of roll-call votes. The findings from the analysis of the aggregated voting data may not provide an accurate description of the cohesion of the party groups in the votes that influence EU public policy. This concern is addressed by comparing the roll-call votes from 2 nd reading codecision amendments with roll-call votes on non-binding resolutions. Dimensionality and the pattern of requesting votes to be recoded are compared across the two types of votes.
A second concern is that roll call votes are called for strategic reasons 30 . Several different strategic considerations for asking for a roll-call vote has been mentioned in the literature. It has been argued that the smaller party groups ask for roll-call votes to expose the grand-coalition of PES and EPP. Similarly, both
6

of the two largest party groups may ask for a roll-call vote to ensure that the grand-coalition hold in order to meet the absolute majority requirement in the codecision procedure. Party group also may ask for roll-call votes to ensure that their members vote the ”right” way against the other party groups, both on ”political” codecision amendments and on resolutions.
Finally, if it is the case that the voting behaviour of MEPs in the 2 nd reading of the codecision procedure is guided by the logic of policy making while voting behaviour on non-binding resolutions is guided by the desire to make a public stand, we would expect the estimated position to differ if a party group include national parties with heterogeneous national party preferences but with a pay off from being able to agree on a collective position on votes with policy consequences.
The spatial model of politics arranges both actors and policies geometrically in a low-dimensional Euclidian space. Actors are represented as ideal point. An actor receives the highest possible utility if a policy is located at her ideal point.
She loses utility as the policy moves away from her ideal point. Conversely, she gains utility if a policy is moved towards her ideal point 31 . Direct maximum likelihood estimation of this theory is considered infeasible, even with the computational power of modern desktop computers. The computational difficulties are due to the combination of a high number of parameters and the scarcity of the information available in the roll-call votes
32
. The solution within the standard statistical tradition has been marginal maximum likelihood 33 . As the estimates of bill parameters are conditional on the value of the legislator parameters and visa versa, marginal maximum likelihood does not offer joint estimates of legislator and bill parameters nor any estimates of the uncertainty associated with these estimates. It is nevertheless possible to use bootstrapping to obtain standard errors of the ideal points of legislators 34 .
7

The Bayesian approach the analysis of roll-call votes is taken from Clinton,
Jackman and Rivers
35
. The approach is implemented in the pscl package in
R 36 . The description of the model follows their paper 37 . The data has n legislators. They vote on m proposals. On each vote j=1,...,m , legislator i=1,...,n choose between a ”Yea” position ζ j and a ”Nay” position ψ j located in the policy-space,
R d where d is the number of dimensions. Then, y ij
= 1 if legislator i votes Yea on roll call j and y ij
= 0 if he votes Nay. The model assumes quadratic utility functions. The ideal point of legislator i is x i
∈
R
, while η ij and
υ ij are stochastic elements whose distribution is jointly normal. The variance of the stochastic elements is ( η ij
− υ ij
) = σ 2 j
. The Euclidian norm is k · k . Utility maximising implies that legislator i votes ”Yea” on vote j if U i
( ζ j
)= k x i
ζ j k 2
+ η ij
> U i
( ψ j
)= k x i
ψ j k 2
+ υ ij and ”Nay” otherwise. Clinton, Jackman and Rivers 38 show that the model can be understood as a hierarchical probit model, P( y ij
= 1) = Φ( β
0 j x i
α j
), where β j
=
2( ζ j
− ψ j
σ j
) and α j
=
( ζ
0 j
ζ j
− ψ
0 j
ψ j
σ j
)
. Φ( · ) is the standard normal function.
β j the midpoint between the ”Yea” and ”Nay” position on proposal j .
x i is the legislator’s ideal point. The direction of α j indicates the location of the status quo relative to the proposal. If α j is positive, the new proposal is located higher on the dimension than the status quo. If α j is negative, the new proposal is located lower on the dimension than the status quo. In a one dimensional model where the underlying dimension is left-right, a negative intercept implies that the proposal shift the policy to the left. A positive intercept implies a shift to the right.
Figure 1 here
The logic of the model is illustrated for
R
1 in figure 1. Legislators l , c and r have ideal-points, x l
, x c and x r
, respectively. They consider how to vote on proposal f, g and h. The location of proposals f, g and h relative to the current policy, is β f
, β g and β h
. We see that β f is very close to the ideal point of legislator c . She is nearly indifferent between the status quo and the proposal.
8

Legislator r vote against legislator l on this proposal. Proposal β g pits legislator r against l and c . All legislator vote the same way on proposal β h
. As it stand the model is only identified up to scale. To fully identify the model it is necessary to specify the direction of the scale and the metric 39 . This can be done by constraining the location of one more legislator or proposal than there are dimensions, or by normalising the distribution to have a mean of zero and a standard deviation of one and fixing the directionality of the policy space 40 .
The European Parliament had 628 Members during most of the 1999-2004 Parliament
41
. Some members served for parts of the period. These were replaced by other members. The model is identified by constraining Monica Ridruejo, from the Spanish Popular Party to have a positive ideal point and Erik Meijer from the Dutch Socialist party to have a negative ideal point. The model is normalized to have zero mean and standard deviation of one. This setup is used to estimate the one-dimensional version of the model for both the codecision amendments and the resolution votes. All 2 nd reading codecision amendments and resolutions decided by roll-call votes during the 1999-2004 European Parliament were collected from the Hix, Noury and Roland 42 data-set. The codecision votes were cross-checked against data from the Council of Ministers and the official minutes to ensure that only 2 nd reading amendments were included. All except 6 unanimous votes were included in the analysis.
Not all MEPs serve the full term. There are also some MEPs who only infrequently participate in the plenary sessions during their time of service. The position of an MEP who vote infrequently is associated with large uncertainty.
In order not to waste computational time on MEPs whose position will be poorly estimated anyway, participation is capped at 50. MEPs who participated in fewer than 50 votes are excluded from the analysis. This excluded 40 out of the 696 MEPs who served in the EP at some point between the first roll call vote on a 2 nd reading codecision amendments, taken on 16 th November
1999 and the last such vote on 21 st April 2004. A total of 380 amendment votes
9

and 656 MEPs are hence included in the analysis. The same set of selection criteria is applied for the resolutions. 18 of the 696 MEPs participated in fewer than 50 roll call votes on resolutions. They were dropped from the analysis.
18 unanimous votes were discarded. This resulted in 2371 resolutions and 678
MEPs.
The pattern of roll-call requests by policy-area for both codecision amendments and resolutions is given in table 1. Policy areas with fewer than 10 requested roll-call votes were grouped as others. There may be some ambiguity related to the classification of policy-areas, as reflected in the large number in the ”Other” category. This is particular the case for resolutions, as these have not necessarily been prepared in any committee before reaching the floor. Nevertheless, it is clear that environment is the most frequent policy area for roll call votes.
Almost one-third of all requests for roll call votes on codecision amendments are on environmental legislation. There are a lot of resolutions by roll call on institutional aspects. The other main areas are Economics, Market and, perhaps surprisingly, Science. This is partly due to the controversy over EU funding to research on human stem cells in the EU research framework.
Table 1 here
Clinton, Jackman and Rivers 43 find that the computation time is increasing in nmT, where n is the number of legislators, m is the number of votes and T is the number of MCMC iterations. Although they argue that very long runs are normally not necessary, they nevertheless advise long runs to ensure that the
MCMC algorithm has converged. Elsewhere, Jackman
44 reports results from
1.5 million iterations. Due to the high number of legislators and votes in the
European Parliament, it is extremely time-consuming to estimate the model on on a standard desktop computer. To facilitate the estimation, we modified the ideal function in the pscl library 45 in R 46 such that it could be estimated on a cluster of 32 computers simultaneously. The MCMC chain runs for 1 million
10

iterations. The result of every subsequent 3150 iteration is recorded. The iteration histories suggest that the model converges before 200,000 iterations in the case of most parameters. The first 400,000 iterations were discarded in order to ensure that the results are nor driven by starting values. This means that there are 98 samples from the posterior distribution.
This section presents the results. The first subsection analyzes voting behaviour on 2 nd reading codecision amendments. The second subsection looks at voting behaviour on resolutions. The third subsection investigates to what extent the location of the proposals party-groups request roll calls on differ across these two procedures.
Figure 2 presents the results from the one-dimensional model of the codecision analysis. The key features are that it is possible to distinguish between
MEPs from different party groups, but not between different national delegations within the party-groups. It is not possible to distinguish between MEPs from V/ALE 47 and GUE/NGL 48 , nor between ELDR 49 , UEN 50 , EDD 51 and
TDI
52 within the framework of the one-dimensional model. These groups are nevertheless clearly distinguishable from the EPP 53 and the PES 54 . The model estimates the position of MEPs towards either of the endpoints of the dimension with large uncertainty.
Figure 2 here
The one dimensional model correctly predicts 87 percent of all individual voting decisions on codecision amendments. 84 percent of the proposals discriminate between MEPs along the first dimension. The one dimensional model correctly
11

predicts less than 70 percent the voting behaviour of MEPs from EDD, TDI and
UEN. This may suggest that there is a second dimension present in the data.
Table 2 gives a breakdown of how the votes in the different policy-areas feed into the first policy-dimension. The majority of the roll call votes in all policy-areas distinguish between the MEPs on the first dimension. The policy-area that distinguishes least well is Science. Only 15 out of the 24 roll calls on codecision amendments in this policy area separates the MEPs on the first dimension. The other policy-areas with less than 80% of the votes separating on the first dimension are Transport and Employment.
Table 2 here
Close votes that do not distinguish between the MEPs on the primary dimension can be identified. Close votes are defined as those with a spilt of less than 250 and participation above 400. This is a slight departure from Jackman
55
, who defines close as those with less than a 40-60 percent split. What should constitute a close vote is perhaps open to some debate. The approach taken here might run the risk classifying too many votes as close. Nevertheless, closer votes are easily identified amongst the selected candidate votes. The only risk associated with a broad definition, is an increase in candidate votes and a chance of fitting a two dimensional model to a data-set that is best captured by a one-dimensional.
These issues will be addressed when comparing the fit of the models. A vote is classified as not being able to distinguish on the first dimension if the 95 percent credibility interval of the bill discriminating parameter overlaps zero.
According to these criteria, 5 codecision amendments qualify as close. Four of these votes took place 15 May 2002. It was on a report drafted by Caudron
(PES, FR). The roll call votes were all demanded by EDD, EPP, UEN and
V/ALE. They are the only 4 rcvs jointly demanded by these four party groups.
The policy-area was Science. The legislation was the EU research framework.
12

All four amendments failed. It is hence not possible to obtain the full text of the amendments voted on. The debate in the plenary the day before the vote and the adopted text indicate that the key issue of conflict was funding of research on human stem sells. Representatives from all of the party groups that requested the roll calls made strong statements. The debate made frequent references to ethical questions. The minority wanted to limit funding to this type of research. This was defended with reference to ethical convictions in the cases of Ribeiro e Castro (UEN, PT), Fiori (EPP, IT) and Raschhofer (Non-attached,
DE). Pietrasanta (V/ALE, FR) and Ahern (V/ALE, IR) defended their opposition to the compromise text by emphasized the need to protect the environment.
The majority, represented by speakers like Plooij-van Gorsel (ELDR, NL), Mc-
Nally (PSE, UK), Dell’Alba (non-attached, FR), Purvis (EPP), Linkohr (PSE,
DE), Zrihen (PSE, FR) and Matikainen-Kallstrom (EPP, FI) argued that scientists in the EU would lose out in the global competition for scientific talent if this type of research was not funded by the EU and that many of the biggest environmental and health problems may be solved through research into human stem-sells. They also emphasized the need to stay competitive. Almost all
MEPs vote the same way in all of the votes.
The dimension that reveals itself on these votes may be classified as a traditionalistmodernist dimension. Those at the upper end of the scale believe in progress through science while those at the lower end do not. These compromise amendments are location at the upper half of this dimension. The first 2 votes have an almost identical split (147 and 148 yea vs 359 and 348 nay). The main spokesperson on the winning side, Plooij-van Gorsel, a Dutch liberal representing the ELDR, is used as a positive prior on the second dimension. As her estimated ideal point on the 1 st dimension does not overlap zero, it is unproblematic to give her a prior of zero on the first dimension. Raschhofer, non-attached from the Austrian Freedom party is used as the negative constraint on the second dimension. The 95 percent credibility interval of her estimated ideal point in the one-dimensional model also overlaps zero. She could not approve of EU
13

funding for research on embryos, which, she pointed out, was illegal in many of the EU member states.
This information is used to identify the directionality of the second dimension.
Plooij-van Gorsel is assigned a positive prior on the second dimension, while
Raschhofer is assigned a negative prior. The most extreme at either end of the spectrum in the one-dimensional model are used as constraints on the first dimension. The left constraint is Erik Meijer from the Dutch socialist party.
Monica Riduejo from the Spanish Party Populaire is the right constraint. The one-dimensional model explains more than 90 percent of the voting behaviour of these two members. The two-dimensional model is estimated with these priors. The Gibb-sampler runs for 1 milion iterations. To ensure that the two dimensions were orthogonal, the iterations were subjected to a series of linear transformations, where the most extreme legislators in both directions on the first dimension (Lucio Manisco from the Italian Communist Party and Giles
Chichester from the British Conservative Party) and the positive extreme on the second dimension (Gary Titley from the British Labour party) were constrained 56 .
The two-dimensional model correctly predicts 89.4 percent of all individual voting decisions. This is 2.4 percent more than the one-dimensional model. The main difference between the one- and two-dimensional models is the latter’s ability to distinguish between the centrist part-groups, as shown in figure 3.
The ELDR is located higher on the second dimension than the other centrist party groups like UEN, EDD and TDI. The two main parties in the UK are clearly distinguishable from the rest of their party groups. British Labour are located much higher on the second dimension than the rest of the PES, but at a similar location on the first dimension. In fact, most of the variation on the second dimension is between MEPs from the PES. The British Conservatives are located further to the right than the rest of the EPP, but at a similar position on the second dimension. The positions of the party-groups are more
14

easily distinguishable from each other on the first dimension than on the second.
Table 3 here
Figure 3 here
Only 8 of the 380 votes (2.1 percent) fail to load into one of the two dimensions.
In only one of the votes did the losing minority exceed 50. 81percent of the votes separates MEPs on the 1 st dimension. 17 percent of the votes separate uniquely on the first dimension. 12 percent of the votes separate uniquely on the
2 nd dimension. While the estimation of a second dimension marginally improve the ability of the model to predict individual voting behaviour. It increased the capability of the model to identify how the votes separated the MEPs from 84 percent to 97.9 percent.
It hence make sense to fit a second dimension if the interest is in explaining coalitions-formation the different votes, but not necessarily if the sole purpose is to estimate the ideal points of the MEPs under this procedure. There is no easily identifiable secondary policy-dimension in the roll-call votes on 2 nd reading codecision amendments, although science and market related aspects seem to distinguish better along the second than the first dimension. A one-dimensional policy-space suffice to explain roll-call voting behavior at this stage in the codecision procedure, but not the coalition-space as there are a lot of votes that separates on both dimensional. These votes distinguish between PES, ELDR and EPP on one side and the smaller party groups on the other. Only 14 of the 50 votes that separate only on the second dimension fail to meet the absolute majority requirement. This suggests that it is the desire amongst the three main party-groups to influence EU public policy policy by compromising on the left-right dimension. The cutting-planes in figure 4 suggest that these votes may divide the PES. The majority of the party-group join the ELDR and the EPP, while the minority team up with the V/ALE and GUE/NGL
15

on the left and UEN, EDD and TDI. The British Labour is the most likely delegation from the PES to break ranks with the rest of the party group to form an alliance with the ELDR and EPP. As this is a procedural requirement, specific to this reading of the codecision procedure, a different pattern should emerge when roll-calls on resolution votes are being analysed in the next section.
Figure 4 here
Table 7 here
Table 7 compares the correctly predicted proportion of individual voting decisions by party group means. The biggest increase in correctly predicted votes from fitting a second dimension is for MEPs from the smaller party groups like the UEN and the EDD, whose mean increase in corrected predicted votes are
7 precent and 9 percent, respectively. The increase is substantively smaller for the other party groups.
Table 5 here
Figure 5 presents the estimates from the one-dimensional model of MEPs ideal points on the resolution votes. There are considerable overlaps in the confidence intervals of most members from the PES, ELDR and EPP. Most of the members from GUE/NGL and V/ALE are distinguishable from MEPs from PES. Some of the members of the EPP are clearly distinguishable from all the other legislators. Closer inspection reveals that most of the MEPs located at the extreme upper end of the scale are British conservatives. The model is able to correctly predict 88.5 percent of all individual voting decisions. 80 percent of all proposals are able to discriminate between the MEPs in the one-dimensional setting.
16

The one-dimensional model of the resolutions votes predicts more of the voting decisions of MEPs from the main party groups correct than the one-dimensional model of the codecision amendments. The reverse is the case for MEPs from the smaller party groups.
Figure 5 here
Table 6 show to what extent the different policy-areas distinguish between MEPs on the first dimension. Roll calls on Institutional Aspects, Enlargement, Economics, Defence and Development have a substantive proportion of roll-call votes failing to distinguish on the left-right dimension. The debates surrounding these policy-areas are related to the institutional infrastructure of Europe.
The issues ranged from how the the guiding principles of the European economic system, via EU’s defence capabilities independently from NATO, to the tradeoff between further integration and enlargement. It is straightforward to identify two camps in these debates. One camp could be labelled internationalists, favouring free trade, a large Union and a close relationship with the US and the rest of NATO. The other camp favours an integrated and regulated European economy with a clear leadership and the military capabilities to mirror its economic power. If this represents the second dimension, the first camp should be located at the lower end of the second dimension, the second camp is located at the upper end.
Table 6 here
A similar approach to the one used to identify the second dimension on codecision amendments is adopted in order to fit a 2-dimensional model to the resolution votes. Using the same criteria, 30 votes qualify as close. 9 of these votes were related to institutional aspects.
Three of these close votes were on a resolution on the Barcelona European Council at the beginning of the
Spanish Presidency of the first half of 2002. As a part of the Lisbon strategy,
17

the summit meeting had called for EU tax coordination at EU level, as well as a general reduction of the cost of employing people. During the debate in the plenary session, Thursday 28 February 2002, Fatuzzo, a Christian Democrat representing the pensioners party in Italy supported the initiative, while Bushill-
Matthews from the British Conservatives was against the initiative. The report the initiative while Andersson from the Swedish Labour Party supported it.
dimension. Fatuzzo is assigned a positive prior on the second dimension. These members’ relative positions on the first dimension were used to identical the direction of first dimension. The model was then re-estimated, letting the Gibb sampler run for 1 million iterations. The iterations are then subjected to a series of linear transformations to ensure that the dimensions are orthogonal
57
. The constraints are identical to those used in the two-dimensional codecision model.
Table 7 here
Table 7 compares the fit of the one and two-dimensional models. The twodimensional model correctly predicts 91.7 percent of all individual voting decisions. This represent a 3.1 percent increase in the total proportion of correctly predicted individual voting decisions. The improvement in fit is substantive for the smaller party groups. The most striking is EDD. The mean percentage of correctly predicted voting decisions increases from 52.11 percent to 73.88 percent for its members. There is also a substantive increase in the percentage of correctly predicted votes for MEPs from GUE/NGL and TDI.
Table 8 here
Table 8 shows how the resolutions load into the different dimensions. 80 percent of the votes separate MEPs along the first dimension, but only 8 percent of the votes are 1 st dimension only. 18 percent of the votes are pure 2 nd dimension.
18

Only 8 percent are pure 1 st dimension votes. It is noteworthy that the proportion of pure 2 nd dimension votes is higher than pure 1 st dimension votes on resolutions. The opposite is the case for codecision amendments. Only 46 votes, less than 2 percent of the total fail to distinguish between the MEPs on at least one of the 2 dimensions. None of these votes had a losing minority of more than
55 MEPs.
Figure 6 presents the two-dimensional plot of the resolution votes. MEPs located towards the bottom of the plot belong to the independent and Euro-sceptic
EDD. MEPs from the leftwing GUE/NGL are considerable less integrationist than the green party group V/ALE. A less integrationist subgroup can be identified amongst the members of the EPP. This subgroup consists almost exclusively of MEPs from the British Conservative Party. Of the centrally located party groups, the liberal ELDR is clearly the most integrationist. The majority of
MEPs from the PES and EPP share the same preferences for a stronger, integrated Europe. As these observations are in line with the established consensus in the field regarding preferences over European integration, it does not seem unreasonable to argue that the second dimension on resolution votes can be characterized as pro-anti integration. Table 9 show the mean location of the party groups and the associated 95 percent credibility interval. There is no overlap between the position of the EPP and ELDR on the first dimension, but their positions overlaps considerably on the second dimension. ELDR, UEN,TDI and
EDD are not distinguishable on the first dimension, but EDLR is different from the other centrally located party groups on the second dimension. The PES overlaps somewhat with the TDI and EDD on the first dimension, and the EPP on the second dimension. The left-wing parties, GUE/NGL and V/ALE are not distinguishable from each other on any of the dimensions.
Figure 6 here
Table 9 here
19

MEPs individual voting decisions are only recorded if a party group leader or
32 individual MEPs request it 58 . There may be strategic reasons for requesting a roll call on a vote
59
. The decision to request a roll call may be motivated by a desire to change the voting behaviour of MEPs of backbenchers in the same party group, or to pressure backbenchers in other party groups to defect 60 . Frequent use of roll call votes may be a policy goal in itself for parties wishing to increase the transparency of EU decision-making. It may also simply be a devise to check who are present in the chamber. We would expect differences in the location of the cut-point between those supporting and those opposing a proposal if the first reason for requesting roll-call votes is the dominating logic.
If the latter types of logics are motivating requestors of roll call votes, there may not be systematic differences in the location of the cut-points. The Bayesian approach allows us to investigate the characteristics and location of individual cut-points. The β j parameter indicates the location cut-point on vote j and the sign of the α j parameter indicates the direction of the proposal relative to the status quo.
Table 10 here
Table 10 shows the number of requests for roll-call votes tabled by the different party groups. V/ALE single-handedly requested 125 of the 380 roll call votes on
2 nd reading codecision amendments. This amounts to one-third of the roll call votes. V/ALE was only the 4 th largest party group with 45 MEPs. It requested twice as many rcvs on 2 nd reading codecision amendments as the EPP. The number of roll call requests is hence clearly not guided by the number of MEPs in the party group. While the V/ALE consisted of 48 MEPs, the EPP had 233.
PES, the second biggest party-group with 180 MEPs, requested about half as
20

many roll calls as the EPP. 35 requests is of similar magnitude to the EDD, which only consists of 16 MEPs. ELDR and GUE/NGL are of a similar size as the V/ALE but these parties requested less than one-fifth as many roll-calls as
V/ALE. The pattern of roll-call requests on resolutions is quite similar to the request pattern on codecision amendments, although the British conservatives are clearly more actively requesting roll calls on resolutions than on codecision amendments. It is clearly not the case that the number of roll-call requests is a function of number of MEPs. In order to evaluate to what extent the results are biased due to the uneven request pattern the relationship between the party group requesting a roll-call and the location of the cut-point of the proposal is presented in figure 7 and 8. The figures present the location of the cut-points in the one-dimensional space by party group requesting the roll call. Only proposals that were able to distinguish between MEPs on the first dimension is included. Joint requests are excluded.
Figure 7 here
Most of V/ALE’s requests are on codecision amendments would, if adopted, move the policy towards the left. The location of the cut-points on the roll call votes requested by the V/ALE on codecision amendments overlaps substantively with the cut-points of the requests made by the party-groups at the opposite ends of the scale, the EPP and the PES. There is some evidence to suggest that the EPP and PES requests roll-calls on differently located cut-points. This is supported by the fact that most of the proposals requested by the EPP had a positive α parameter while the majority of the requests made by the PES had a negative α parameter. Hence the EPP requested roll-calls on proposals that divided the left and were designed to move the policy towards their preferred position. The PES requested roll-calls on proposals that divided the left and moved the policy towards their preferred location. This may be interpreted as evidence to suggest that these two parties use roll-call requests on codecision amendments to check that their coalition partners keep their part of the bargain.
21

Figure 8 here
The mean location of the cut-point on roll call requests made by the V/ALE on resolutions were to the left of all party-groups except the GUE/NGL, as illustrated in figures 8. While the mean location of the cut-point requested by the different party groups followed the left-right pattern, there were substantive overlaps between requests made by all party groups. The directionality of the proposals is more mixed for all party groups. This may be because the policy consequences of ending up on the losing side are relatively minor, allowing the party-groups to use roll-call votes to distinguish themselves from the other party groups, as well as distinguishing subgroups within their own party group from the rest. There is not enough evidence to suggest that the request pattern by the V/ALE is so different from the request pattern of other party groups that the fact that they requested a lot more roll call votes than the other party groups substantively influences the results.
The analysis of roll-call voting in the European Parliament has substantively enhanced our understanding of politics in the European Parliament. Critics of this body of research have argued that roll-call votes are not a random selection of all votes. Most of the roll-call votes do not have any policy implications as they are held on resolutions. The pattern that holds in the aggregate might not hold for roll call votes taken when the voting decisions of the MEPs have policy consequences. Furthermore, the pattern of requesting a roll-call vote is not random. The analysis of roll-call votes as a random sample of all votes may not be appropriate. Standard statistical techniques assume that data is a random sample of the population. When all roll-call votes are used in the analysis and roll-calls have been shown not to be representative of all votes, standard understanding of statistical inference breaks down 61 . Rather than invoking the
22

apparent population justification, this paper took a Bayesian approach to analyzing voting behaviour. While more computational intensive than the marginal maximum likelihood algorithms of the Nominate-family
62
, the advantage is that both location and the uncertainty surrounding those estimates are simultaneously estimated.
The results show that MEPs location on the main policy dimension does not vary from votes with potential policy-implications to votes without such implications. The main dimension ordering MEPs is the standard left-right dimension.
Location on this dimension explains well over 80 percent of both individual voting decisions and the discriminating ability of the proposals. This is completely in line with the existing results based on votes pooled across all procedures and estimated using Nominate
63
. However, the large uncertainty around the point estimates cautions against relying on these as proxies for individual preferences.
They could perhaps better be interpreted as revealed coalition-patterns. A more advisable route would be to use survey-data
64
. It is however clear that there is more variance on the second dimension on resolutions than on codecision amendments. It is debatable to what extent it is necessary to fit a second dimension in order to explain individual voting behaviour on second reading codecision amendments. As the predictive power of the model increases substantively in the case of the smaller party groups on resolutions, it may be argued that the additional complexity is justified. The British Conservatives defect from the rest of their party group on votes that do not feed directly into EU public policy. This suggests that they signal their difference from the rest of the EPP when it is cheap to do so, and unite with their party group when it matter for
EU public policy. This interpretation would also explain why the British Conservatives are more frequently requesting roll-call votes on resolutions than on codecision amendments. This is supported by the evidence that EPP displays a different pattern of roll call request on resolutions than on codecision amendments. They demand more often roll call votes on left-leaning resolutions than on left-leaning codecision amendments. Requests for roll calls on resolutions are
23

for the purpose of posture. A request for a roll call on codecision amendments is a commitment device.
This paper has shown that the pattern of voting behavior in roll call votes do display some procedural effects. However, the key finding from the recent literature on roll-call voting in the EP, the dominance of normal left-right politics holds within different procedures, regardless of the difference in the policyimplications of MEPs voting decisions.
Future research would benefit from estimating party
65
, agenda
66 and dynamic
67 effects on MEPs voting behaviour.
Another possible avenue is to systematically investigate the interaction between decision-making in the Council of Ministers and the European Parliament.
24

1
Joseph Schumpeter, Capitalism, Socialism and Democracy (London: Allen and Unwin, 1942).
2 George Tsebelis, Veto Players: How Political Institutions Work (Princeton:
Princeton University Press, 2002).
3 Simon Hix, The Political System of the European Union , 2nd edition (Basingstoke: Palgrave MacMillan, 2005), series The European Union Series, Chapter 3 offers an overview.
4 Robert E Goodin and Christian List, “Special Majorities Rationalized,”
British Journal of Political Science (forthcoming).
5
Simon Hix, Abdul Noury and Gerard Roland, “Dimensions of Politics in the European Parliament,” American Journal of Political Science 50/2 (2006).
6 Keith T Poole, Spatial Models of Parliamentary Voting (Cambridge University Press, 2005).
7 Simon Jackman, “Estimation and Inference via Bayesian Simulation: An
Introduction to Markov Chain Monte Carlo,” American Journal of Political
Science 44/2 (2000).
8
Jeffery B. Lewis and Keith Poole, “Measuing Bias and Uncertainty in Ideal
Point Estimates via the Parametric Bootstrap,” Political Analysis 12 (2004).
9 Simon Jackman, “Multidimensional Analysis of Roll Call Data via Bayesian
Simulation: Identification, Estimation, Inference and Model Checking,” Political Analysis 9/3 (2001).
10 Simon Hix, “Constitutional Agenda-Setting Through Discretion in Rule
Interpretation: Why the European Parliament Won at Amsterdam,” British
Journal of Political Science 32/2 (2002).
11
Andrew Moravcsik and Kalypso Nicolaidis, “Explaining the Treaty of Amsterdam: Interests, Influence, Institutions,” Journal of Common Market Studies
37/1 (1999).
12 Juliet Lodge, “The European Parliament and the Authority - Democracy
Crises,” The Annals of American Academy of Political and Social Science 531
(1994).
13 Andreas Follesdal and Simon Hix, “Why There is a Democratic Deficit in the EU: A Response to Majone and Moravcsik,” Journal of Common Market
Studies 44/3 (2006).
14
Giandomenico Majone, “The Credibility Crisis of Community Regulation,”
Journal of Common Market Studies 38/2, June (2000).
15
Andrew Moravcsik, “In Defence of the ”Democratic Deficit”: Reassessing
25

the Legitimacy of the European Union,” Journal of Common Market Studies
40/4 (2002).
16 Fulvio Attina, “The Voting Behaviour of the European Parliament Members and the Problem of Europarties,” European Journal of Political Research 18/2
(1990).
17
Abdul G. Noury, “Ideology, Nationality, and Euro-Parliamentarians,” European Union Politics 3/1 (2002).
18 Simon Hix, Abdul Noury and Gerard Roland, Democracy in the European
Parliament (Cambridge University Press, 2007).
19 Simon Hix, “Parliamentary Behavior with Two Principals: Preferences,
Parties, and Voting in the European Parliament,” American Journal of Political Science 46/3 (2002).
20
Thorsten Faas, “To defect or not to defect? National, institutional and party group pressures on MEPs and their consequences for party group cohesion in the European Parliament,” European Journal of Political Research 42 (2003).
21 Tapio Raunio, “Losing Independence or Finally Gaining Recognition? Contact between MEPs and National Parties,” Party Politics 6/2 (2000).
22 Hix, Noury and Roland, Democracy in the European Parliament .
23 Hix, Noury and Roland, Democracy in the European Parliament .
24
Bruce Western and Simon Jackman, “Bayesian Inference for Comparative
Research,” American Political Science Review 88/2 (1994).
25
Simon Hug, Selection Effects in Roll Call Votes, 2006.
26 Amie Kreppel, “Moving Beyond Procedure: An Empirical Analysis of European Parliament Legislative Influence,” Comparative Political Studies 35/7
(2002).
27 Clifford J. Carrubba et al., “Off the Record: Unrecorded Legislative Votes,
Selection Bias and Roll-Call Analysis,” British Journal of Political Science
36/11 (2006).
28
Carrubba et al., op. cit.
29 Carrubba et al., op. cit.
30 Carrubba et al., op. cit.
31 Melvin J. Hinich and Michael C. Munger, Analytical Politics (Cambridge:
Cambridge University Press, 1997).
32 Jackman, Multidimensional Analysis of Roll Call Data via Bayesian Simulation .
33
Poole, op. cit.
26

34 Lewis and Poole, op. cit.
35 Joshua Clinton, Simon Jackman and Doug Rivers, “The Statistical Analysis of Roll Call Votes,” American Political Science Review 98 (2004).
36
Simon Jackman, pscl: classes and methods for R developed in the Political
Science Computational Laboratory, Stanford University, 2006.
37
Clinton, Jackman and Rivers, op. cit.
, p. 456.
38 Clinton, Jackman and Rivers, op. cit.
39 Douglas Rivers, Identification of Multidimensional Spatial Voting Models,
2003.
40 Joseph Bafumi et al., “Practical Issues in Implementating and Understanding Bayesian Ideal Point Estimation,” Political Analysis 13/1 (2005).
41
The number of MEPs was extended to 732 1 st analysed is this paper took place in April 2004.
May 2004. The final vote
42 Simon Hix, Abdul Noury and Gerard Roland, “Power to the Parties: Cohesion and Competition in the European Parliament, 1979-2001,” British Journal of Political Science 35/2 (2005).
43 Clinton, Jackman and Rivers, op. cit.
, p. 369.
44
Jackman, Multidimensional Analysis of Roll Call Data via Bayesian Simulation .
45
Jackman, pscl .
46 www.r-project.org
47 Group of the Greens / European Free Alliance.
48 Confederal Group of the European United Left / Nordic green Left.
49
European Liberal, Democratic and Reformist Group.
50
Group of Europe of Nations.
51 Europe of Democracies and Diversities.
52 The non-attached members.
53 Group of European People’s Party (Christian Democrats) and European
Democrats.
54
Group of the Party of European Socialists.
55 Jackman, Multidimensional Analysis of Roll Call Data via Bayesian Simulation .
56 Rivers, op. cit.
27

57 Rivers, op. cit.
58 Some procedures requires the use of roll-call votes
59 Richard Corbett, Francis Jacobs and Michael Shackleton, The European
Parliament , 4th edition (London: John Harper, 2000).
60
Amie Kreppel and Simon Hix, “From Grand Coalition to Left-Right Confrontation: Explaining the Shifting Structure of Party Competition in the European Parliament,” Comparative Political Studies 36/1/2 (2003).
61 Western and Jackman, op. cit.
62 Poole, op. cit.
63 Hix, Noury and Roland, Democracy in the European Parliament .
64
Hix, Parliamentary Behavior with Two Principals .
65 Fang-Yi Chiou, Jointly Estimating Party Effects and Ideologies, 2005.
66 Joshua D. Clinton and Meirowitz, “Integrating Voting Thoery and Roll Call
Analysis: A Framework,” Political Analysis 11/4 (2003).
67 Andrew D. Martin and Kevin M. Quinn, “Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999,”
Political Analysis 10/1 (2002).
28

l
1−dimensional Item−Response Model c
ββ
(f)
ββ
(g) r
ββ
(h)
Figure 1: The figure shows the relationship between x l,c,r point of votes β f,g,h
.
and the indifference
29

Policy
Agriculture
Asylum
Communication
Competition
Culture
Defense
Development
Economics
Employment
Enlargement
Environment
External/Trade
Fisheries
Foreign
Home
Industry
Institutional
Justice
Legal
Market
Other
Regional
Science
Trade
Transport
Total
Codecision Resolution
30
14
3
26
15
113
9
39
25
69
24
13
54
14
53
501
19
30
40
30
51
333
43
28
197
18
11
339
42
70
67
192
93
96
21
3
26
380 2371
Table 1: The table compares the number of roll call votes requested across the procedure by policy area.
30

31

Agriculture
Communication
Economics
Employment
Environment
Institutional
Market
Other
Science
Transport
Total
Dimension 1 Not dimension 1 Proportion
101
33
21
68
15
9
25
12
23
11
318
5
2
3
4
12
6
4
13
9
4
62 .837
.833
.857
.885
.733
.894
.846
.840
.839
.625
.692
Table 2: The table shows a breakdown of to what extent the different policyareas load into the 1st dimension.
32

1 st
2 nd dimension dimension 95% CI does not overlap 0 95% CI overlaps 0 Total
95% CI does not overlap 0
95% CI overlaps 0
Total
261
47
308
64
8
72
325
55
380
Table 3: The table offers a breakdown of to what extent the different votes distinguish between MEPs along the different dimensions.
33

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UEN − Right−Nationalist
V/ALE − Green
GUE/NGL −Left
ELDR − Liberal
EDD − Eurosceptic
PES − Social−Democratic
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Figure 3: The figure shows the mean location of MEPs in the 2 dimensional space.
34

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Figure 4: The lines show how the proposals separates the MEPs.
35

R
1
R
2
EDD EPP UEN V/ALE GUE/NGL ELDR TDI PES Total
62.71
90.90
67.18
86.18
70.05
92.16
76.57
89.79
90.95
91.96
79.98
81.01
67.02
71.76
89.72
92.42
Table 4: The table compares correctly predicted voting decisions by party group means.
86.97
89.44
36

Dimensions 1 st 2 nd
EPP
Mean 2 .
5% 97 .
5% Mean 2 .
5% 97 .
5%
1.21
0.67
2.02
0.56
− 0.01
0.97
ELDR 0.21
0.07
UEN
TDI
0.13
0.00
−
0.03
0.33
EDD − 0.23
− 0.67
0.39
0.22
0.48
−
0.36
0.01
0.01
−
−
0.25
0.12
0.25
0.42
0.10
0.29
0.03
− 0.15
− 0.34
− 0.03
PES − 0.27
− 0.63
− 0.01
GUE/NGL − 0.89
− 1.05
− 0.69
V/ALE − 0.93
− 1.07
− 0.72
1.12
0.01
0.23
−
0.52
0.21
0.01
1.62
0.24
0.36
Table 5: Party group location on codecision amendments.
37

38

Agriculture
Asylum
Competition
Culture
Defense
Development
Economics
Employment
Enlargement
Environment
External/Trade
Fisheries
Foreign
Home
Industry
Institutional
Justice
Legal
Market
Other
Regional
Science
Trade
Transport
Total
Dimension 1 Not dimension 1 Proportion
8
47
416
17
26
34
25
271
34
17
163
18
8
267
51
48
47
145
79
34
78
19
22
29
1903 468 .803
88
2
6
6
4
6
5
72
3
0
3
62
9
11
34
22
20
47
14
17
18
2
4
13
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.887
.825
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.833
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.607
.827
1.
.727
.788
.944
.813
.905
.846
.690
.686
.701
.755
.849
.667
Table 6: The table shows to what extent proposals in the different policy-areas loads into the first dimension.
39

R
1
R
2
EDD EPP UEN V/ALE GUE/NGL ELDR TDI PES Total
52.11
94.33
67.66
87.73
73.84
95.63
73.24
91.18
79.70
88.88
81.55
82.66
60.60
73.22
92.84
95.07
88.53
91.74
Table 7: Correctly predicted voting decisions by party group means.
40

1 st
2 nd dimension dimension 95% CI does not overlap 0 95% CI overlaps 0 Total
95% CI does not overlap 0
95% CI overlaps 0
Total
1587
432
2019
306
46
352
1893
478
2371
Table 8: The table shows to what extent proposals load into the two dimensions.
41

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V/ALE − Green
GUE/NGL −Left
ELDR − Liberal
EDD − Eurosceptic
PES − Social−Democratic
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Figure 6: The figure shows the mean location of MEPs in the 2 dimensional space.
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42

Dimensions 1 st 2 nd
EPP
Mean 2 .
5% 97 .
5% Mean 2 .
5% 97 .
5%
1.21
0.67
2.02
0.56
− 0.01
0.97
ELDR 0.21
0.07
UEN
TDI
0.13
0.00
−
0.03
0.33
EDD − 0.23
− 0.67
0.39
0.22
0.48
−
0.36
0.01
0.01
−
−
0.25
0.12
0.25
0.42
0.10
0.29
0.03
− 0.15
− 0.34
− 0.03
PES − 0.27
− 0.63
− 0.01
GUE/NGL − 0.89
− 1.05
− 0.69
V/ALE − 0.93
− 1.07
− 0.72
1.12
0.01
0.23
−
0.52
0.21
0.01
1.62
0.24
0.36
Table 9: The table shows the mean location of the party groups in the 2 dimensional space.
43

44

EPP
ELDR
GUE
V/ALE
EDD
PES
−2 0
Location of cutpoints
2
Figure 7: Location of proposals cut-points on codecision amendments.
4
45

GUE
V/ALE
EDD
PES
ELDR
EPP
−4 −3 −2 −1 0
Location of cutpoints
1
Figure 8: Location of proposals cut-points on resolutions.
2
46