Bringing EP elections closer to citizens

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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
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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.

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Political offer

• Traditional cleavages ?
• Opaque policy positions ?
• Complex, multidimensional preference mash ?
• Fragmentation ?
• Unholy coalition-building ?
• Unpredictability ?
• -gt DIFFICULTIES FOR LARGE NUMBERS OF VOTERS TO
  IDENTIFY THOSE MOST LIKELY TO REPRESENT THEIR
  INTERESTS - gt DISAFFECTION FROM ELECTORAL POLITICS

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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

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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.)

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Match and mismatch
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kieskompas.nl
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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

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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)

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• 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)

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• 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

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• 3 different types of basic visualisations
  congruence lists, spiders and compasses

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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!).

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Nine categories (policy areas)

• 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

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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

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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)

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3. On Political Behavior

• Pre-profiling and post-profiling questionnaire -gt
  mobilization effect of the Profiler? -gt
  importance of policy preferences vs. party
  identification model? -gt economic voting? -gt
  spatial models? -gt cleavages? etc.

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4. On Campaigning

• Shifts in profile-matching over the campaign -gt
  campaign intensity, matching of campaign
  direction and profile matching
• How parties react/adapt to the tool

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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)

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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

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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

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Thank you for your attention!

• Contact
• Alexander.Trechsel_at_eui.eu
• www.eui.eu
• www.eudo.eu