Bringing EP elections closer to citizens

1. Bringing EP elections closer to citizens Prof. Dr. Alexander H. Trechsel European University Institute Florence Council of Europe Forum for the Future of Democracy Workshop track no. 5 „e-democracy from the grassroots“ Madrid, Spain 15-17 October 2008

2. Democracy in Europe • Long list of challenges to democracy in Europe (Schmitter and Trechsel 2004, Kriesi 2007 etc.) • In particular: traditional mechanisms of representation break down • trust ▼ • electoral turnout ▼ • party identification ▼ • party cohesion ▼ • party government ▼ • guardian institutions ▲ • etc.

3. Political offer: • Traditional cleavages ▼ • Opaque policy positions ▲ • Complex, multidimensional preference mash ▲ • Fragmentation ▲ • Unholy coalition-building ▲ • Unpredictability ▲ -> DIFFICULTIES FOR LARGE NUMBERS OF VOTERS TO IDENTIFY THOSE MOST LIKELY TO REPRESENT THEIR INTERESTS - > DISAFFECTION FROM ELECTORAL POLITICS

4. The irony • Voters get lost, but their political curiosity does not • Thanks to ICTs: opportunity for the social sciences and the interested public to learn more about: • parties • candidates • public opinion • political behavior • campaign dynamics

5. The tool: e-Profiling • Started in the Netherlands in the mid.90s (Stemwijzer) • Since: spread to Switzerland, Bulgaria, Finland, Germany, Lithuania and many other places… • Millions of users everywhere (1 million in CH, 1.7 million in NL, 5 million in D, etc.)

11. Match and mismatch

12. kieskompas.nl

14. Impact of smartvote in Switzerland (trial questionnaires on the cantonal level): • 67.2%: „the smartvote result was important for my decision“ • 74.1%: „smartvote has influenced my decision“ • 33.4%: voted for „unusual“ candidates

15. Additional features of smartvote • Initial questionnaire (basic socio-demographic data, initial vote intentions, traditional voting behavior etc.) • Smartvote profiling • Final questionnaire (socio-demographic data, change from initial vote intentions etc.) • Sampling according to known socio-demographic distribution and matching with profiles • Cost: very low (both candidates and voters provide the information for free)

16. Target: EP elections in June 2009 • Consortium consisting of the European University Institute, Florence (lead), kieskompas.nl and smartvote.ch (technological development) • Very close coordination and collaboration with the European Election Study (EES)

17. In every Member State (and possibly more!) • Large group of PhD researchers (about 75) from all EU27 countries build up country teams for the coding of the parties’ stances • So far totally independent financing

18. 3 different types of basic visualisations : congruence lists, spiders and compasses

19. The logic behind the conceptualisation • Every visualisation is based on the answers voters/coders give to statements • Every statement can be answered with „completely disagree“, „somehow disagree“, „neutral„“,somehow agree“ or „completely agree“ • Every statement will need to be weighted by the user with a center-category as default • We formulate 28 statements, unevenly distributed across nine categories (policy areas) • We leave it up to country teams to formulate a maximum number of country-specific questions (if relevant!).

20. 1. Welfare, family and health 2. Migration and immigration 3. Society, religion and culture 4. Finances and taxes 5. Economy and work 6. Environment, transport and energy 7. Law and order 8. Foreign policy 9. European integration Nine categories (policy areas)

21. What will we be able to learn from the EU Profiler?1. On political parties • intra-party cohesion (Luxembourg) • spatial distribution of parties - inter-party (EU-wide) congruence - EU vs. national level politics

22. 2. On Public Opinion • Mapping of detailed policy preferences within countries and across the EU27 • Mapping of saliency of policy preferences of citizens within countries and across the EU27 • Mapping of elite/citizen congruence (issue multidimensionality, European vs. national level issue salience etc.) • Mapping of citizen/citizen congruence! (“Your European Alter Ego” – post-EU-Profiler)

23. 3. On Political Behavior • Pre-profiling and post-profiling questionnaire -> mobilization effect of the Profiler? -> importance of policy preferences vs. party identification model? -> economic voting? -> spatial models? -> cleavages? etc.

24. 4. On Campaigning • Shifts in profile-matching over the campaign -> campaign intensity, matching of campaign direction and profile matching • How parties react/adapt to the tool

25. 5. On Methodology • Experimental and novel data gathering on public and elite opinion, matching techniques, econometric models, online tools etc. • Pre-vote online survey vs. post-electoral CATI survey (profiling vs. EES)

26. 6. On other actors • Idea: have civil society organisations, national and EU elites and media exponents fill out the same questionnaire • Match policy preference across actors

27. Past and next steps • Decision taken to launch the project in the spring of 2008 • Financial support from the Robert Schuman Centre for Advanced Studies at the European University Institute and from the NCCR research program at the University of Zurich • Joint press conference was held in May 2008 in Brussels • Currently: conceptualisation of the tool • Next: finalising demo version, marketing among potential media partners

28. Thank you for your attention! Contact: Alexander.Trechsel@eui.eu www.eui.eu www.eudo.eu