Although qualified-majority voting is possible, member states in the Council of the European Union (EU) still adopt most policies by consensus. The agent-based model of coalition building in multilateral negotiations presented here addresses this puzzle. The model demonstrates that consensual decisions may emerge as an unintended by-product of government representatives’ desire to form blocking coalitions. A qualitative case study demonstrates the plausibility of the model's assumptions and resulting coalition-building dynamics. Moreover, a quantitative test shows that the model's predictions correspond closely to the observed consensus rates. Finally, computational experiments predict a positive effect of the voting threshold but no effect of increases in membership on winning coalition size, which has important practical implications for institutional design and enlargement policy.
Department of Politics and Public Administration, University of Limerick (email:
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7 Mattila and Lane, ‘Why Unanimity in the Council?’; Hayes-Renshaw et al., ‘When and Why the EU Council of Ministers Votes Explicitly’; Heisenberg, ‘The Institution of “Consensus” in the European Union’; Hagemann and De Clerck-Sachsse, ‘Short Old Rules, New Game’; Mattila, ‘Roll Call Analysis of Voting in the European Union Council of Ministers after the 2004 Enlargement’. Note that, under the qualified majority voting rule, abstentions have the same effect as negative votes.
8 Hayes-Renshaw et al., ‘When and Why the EU Council of Ministers Votes Explicitly’, pp. 180–1
9 The data for the years from 1994 to 2002 are taken from Table 1a of Heisenberg, ‘The Institution of “Consensus” in the European Union: Formal Versus Informal Decision-Making in the Council’, p. 72; the data for the years from 2003 to 2006 are taken from Table 3 of Hagemann and De Clerck-Sachsse, ‘Short Old Rules, New Game’, p. 13. The consensus rates are based on contested votes only (i.e. negative votes or abstentions). Member states also have the opportunity to attach formal statements to the minutes of the meeting in which an act is adopted. Member states who voted in favour of the adoption of the act sometimes use such statements to voice their discontent with aspects of the act. This study is interested in explaining why member states do not outvote each other even though the formal rules allow for the adoption of acts by majority vote. Thus, the appropriate dependent variable is member states’ voting behaviour. Whether or not member states also choose to comment on their voting behaviour through formal statements is not relevant for answering this question.
10 The time-period covered does not include the latest accessions of Romania and Bulgaria in 2007.
11 Tsebelis and Yataganas, ‘Veto Players and Decision-Making in the EU after Nice’; König and Bräuninger, ‘Accession and Reform of the European Union: A Game-Theoretical Analysis of Eastern Enlargement and the Constitutional Reform’; Zimmer et al., ‘The Contested Council’.
12 If anything, the consensus rate increases somewhat over time.
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15 The argument also holds if the Presidency, or any other member state, is considered to be the agenda-setter inside the Council.
16 Mattila and Lane, ‘Why Unanimity in the Council?’, p. 37.
17 Situations in which such Pareto-improving policy changes are possible might be quite common in the EU. For example, Scharpf argues that decision making on product-related regulations exhibits the strategic structure of a coordination game, in which member states agree that a uniform EU standard is preferable to the existing plethora of national standards. Although a distributional conflict about exactly what type of uniform standard to implement still exists, all member states are better off with some uniform standard than none. See Fritz W. Scharpf, ‘Negative and Positive Integration in the Political Economy of European Welfare States’, in Gary Marks, Fritz W. Scharpf, Philippe C. Schmitter and Wolfgang Streeck, eds, Governance in the European Union (London: Sage, 1996), pp. 15–39.
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23 Whether or not logrolling is a competing or complementary explanation depends largely on the negotiation stage at which it is supposed to take place. The computational model developed below is agnostic about the precise mechanisms through which the compromise agreement between blocking coalitions at the final stage of negotiations is reached. Log-rolling across issues within a proposal could surely be one of those mechanisms. Forming blocking coalitions reduces the effective number of actors and policy positions and, therefore, the cognitive demands on negotiators, making successful vote trading more likely. From this point of view, the two explanations potentially complement each other and could be combined in a sequential manner. The conclusion briefly discusses how a competitive empirical test could look if the two theories are considered as alternatives.
24 This informal comparison of different theories cannot replace a more rigorous empirical test. However, the discussion points to potential shortcomings of existing accounts and justifies the consideration of new alternatives.
25 Häge, Frank M., Bureaucrats as Law-Makers: Committee Decision-Making in the EU Council of Ministers (London: Routledge, 2012)
26 Information on member state positions was derived from various internal Council documents. All documents are available from the public register of Council documents (http://www.consilium.europa.eu/showPage.aspx?id=1279&lang=en). Four interviews with Commission, Council, and member state officials in May and June 2007 yielded additional insights into the negotiation process.
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37 In this respect, the approach taken here is in no way different from more classical mathematical modelling, which usually aims to capture some empirical regularity or stylized fact about a political phenomenon. The model is implemented in NetLogo 4.1, see Uri Wilensky, Netlogo, Version 4.1 (Evanston, Ill.: Center for Connected Learning and Computer-Based Modeling, Northwestern University, 1999), available from http://ccl.northwestern.edu/netlogo/. The simplified NetLogo code is provided in the appendix and the entire simulation model is available for download from www.frankhaege.eu.
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47 Computational experiments perform the same theoretical function as comparative statics analysis in mathematical modelling, i.e. the derivation of additional predictions.
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49 Still, it is of course instructive to investigate how sensitive the model predictions are to the inclusion of real-world voting weights and multiple voting thresholds. The online appendix of this paper includes the results of replication analyses based on such models. With the exception of the model specification with Nice treaty rules and twenty-five member states, which results in a predicted consensus rate that is up to 9 per cent higher than the prediction of the base model, the predictions of the modified models generally lie within 6 percentage points of the predictions of the base model, and often considerably closer (see Table A2 in the online appendix). None of the qualitative results of this article is dependent on the exclusion of voting weights from the model.
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51 The online appendix presents replication results of models in which the sequence of moves is ordered according to voting weights and member states with smaller weights move before member states with larger ones. The predicted consensus rates change only marginally from those of the base model (i.e. by no more than three percentage points, see Table A2 in the online appendix).
52 In principle, the formation of a blocking minority could also result in a rejection of the proposal. In reality, Commission proposals are hardly ever rejected in their entirety. Empirical data indicate that 90 to 95 per cent of all proposals are eventually adopted; see König et al., ‘Quantifying European Legislative Research’, p. 563; Häge, ‘The European Union Policy-Making Dataset’, p. 470. Thus, the overwhelming majority of actually observed legislative proposals seem to lead to efficiency-improving negotiation outcomes. A selection effect seems to operate here, in that the Commission refrains from submitting unpopular proposals in anticipation of their rejection by the Council; see König and Junge, ‘Why Don't Veto Players Use Their Power?’ The model could be modified to include at the end of the negotiation process an evaluation of the potential compromise outcome against a reversion point. However, the location of this reversion point could easily be calibrated to make sure that the model output corresponds to a 5–10 per cent rejection rate. While making the model arguably more realistic, such an extension would yield little additional theoretical insight.
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54 Figure 1 presents the same consensus rate data in the form of a time-series. Unfortunately, no voting records are available for the period prior to 1994.
55 The actual percentage voting threshold applied in the Council varied slightly during the observed time period. However, these small changes in the formal voting threshold do not affect the effective voting threshold in terms of the number of member states required to form a winning coalition.
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57 A voting threshold of 100 per cent is not considered in the simulation because the results would be trivial. Under unanimity rule, each individual member state constitutes a blocking minority and therefore does not engage in coalition building. Threshold values between 90 and 100 per cent are also less interesting, as they do not occur in most real-world decision-making systems.
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* Department of Politics and Public Administration, University of Limerick (email: firstname.lastname@example.org). An earlier version of this article was presented at the Fifth Pan-European Conference on EU Politics, Porto, 2010. The author thanks the panel participants and the discussant Madeleine Hosli for useful comments and suggestions. Advice by three anonymous referees of this Journal is also gratefully acknowledged. Supplementary material is available in an online appendix at http://www.journals.cambridge.org/jps, and the NetLogo simulation model is available for download from www.frankhaege.eu.
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