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The Complexity of Turnout: An Agent-Based Simulation of Turnout Cascades

The Complexity of Turnout: An Agent-Based Simulation of Turnout Cascades. Ed Fieldhouse, Institute for Social Change, University of Manchester Laurence Lessard-Phillips, Institute for Social Change, University of Manchester

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The Complexity of Turnout: An Agent-Based Simulation of Turnout Cascades

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  1. The Complexity of Turnout: An Agent-Based Simulation of Turnout Cascades Ed Fieldhouse, Institute for Social Change, University of Manchester Laurence Lessard-Phillips, Institute for Social Change, University of Manchester Bruce Edmonds, Centre for Policy Modelling, Manchester Metropolitan University

  2. Introduction • Election campaigns matters • Persuading people to change their minds/vote • Mobilisation efforts (GOTV, etc) have an impact • Turnout cascades • Dimensions of turnout cascades • Spatial contagion (social influence) • Temporal spill over (habit) 11/09/2013 - The complexity of turnout

  3. Introduction • Turnout literature can be divided into two (broad) groups: • Sociological models: • Political attachments assumed to be shaped by voters’ social and psychological characteristics, social group belonging, and social context in which individuals grow up, live and work • Instrumental/choice-based models • Focus on cost/benefit analysis of voting and its expected utility (focussing on party preference) • Various definitions of rationality, taking group benefits and expressive benefits into account, and importance of satisfaction 11/09/2013 - The complexity of turnout

  4. Introduction • Also cross-cutting body of evidence looking at individual and group dynamics in voting, often overlooked in models based on observational data: • Role of habit and inertia (Plutzer, 2002; Fowler, 2006) • Importance of interpersonal influence (Huckfeldt, 1986; Huckfeldt and Sprague, 1995) • Correspondence within families/households (Cutts and Fieldhouse, 2009) 11/09/2013 - The complexity of turnout

  5. Aim of paper • Explore interaction of the social, rational, and dynamic processes, using a method that allows us to capture complex dynamic behavioural processes: agent-based simulations • Adopting descriptively complex modelling approach • Focus on short- and long-term influences of party and interpersonal mobilisation processes • Effect of different degrees of party mobilisation in various types of campaigns • Second order effect of GOTV efforts • Explore channels through which voting cascades operate 11/09/2013 - The complexity of turnout

  6. Modelling turnout • (Most) Previous analyses based on observational data and ‘top-down’ statistical methods • Yet, situation more complex • Overlaps and interactions • Agent-based models allow for the complexity, non-linearity, path dependence and self-organisation that arises out of studying human systems • With regard to our research, agent-based models will allow us to extrapolate the effects mobilisation in a complex model that incorporates other elements of voting behaviour 11/09/2013 - The complexity of turnout

  7. The voter model • Holistic model incorporating aspects relevant to the evolution of a hypothetical electorate • System representing a constituency/single candidate election in an imaginary location of approximately 1,000 inhabitants nested in households • Agents’ characteristics are initiated from existing data (BHPS) • Simultaneously occurring processes 11/09/2013 - The complexity of turnout

  8. Overview of processes 11/09/2013 - The complexity of turnout

  9. 11/09/2013 - The complexity of turnout

  10. Rules of behaviour based on causal stories Initial party preference inherited – party preference can be linked to learning from parents. People vote out of habit – going to the polls in one election will lead to a greater likelihood of returning to the polls in a subsequent election. People vote because they care about who wins - voters are more likely to turnout if they have a stronger preference for one party or another. Voting is a social norm – civic duty is an important rationale for individual-level turnout. People share the political views of their greater networks – probability of agreement within a network depends on the distribution of political opinion within one’s network (autoregressive networks). Electors can be mobilised to vote by family, friends and political parties – household members, friends and political parties will ask people to vote on election day. There are large amounts of homophily in social networks – individuals have more contact with similar people. Education increases the level of political interest – the level of exposure to (political) information one is exposed to increases when pursuing higher education. Political experts are more influential within political discussion networks – People will tend to listen to people they believe are political experts (those who have higher levels of political interest and involvement). Satisfaction with the outcome of an election increases future turnout – positive reinforcement from voting will lead to further voting. Voting can be hindered by personal shocks – the birth of a child disturbs habit. Voting varies with age – declining health, mobility, and energy levels impede voting 11/09/2013 - The complexity of turnout

  11. Voting: intention vs. decision • Agents have a vote intention • Civic duty • Habit • Instrumental reasons • Agents vote for the party they are supporting (colour) • Acquired/changed via discussion • Intention to vote may be fulfilled come Election Day • Theory of planned behaviour • Factors disturbing positive intention • Those without the intention to vote can be mobilised to do so by family/friends/parties 11/09/2013 - The complexity of turnout

  12. Political discussion networks • Key networks in the voter model • Influence on vote & party choice • Content of political discussions • Duty • Colour • Intention • Characteristics of discussions • Strength of message • Location • Occurrence • Content can be passed along discussants • Ability to pass information along dependent on the level of political interest of discussants • Network influence is auto-regressive 11/09/2013 - The complexity of turnout

  13. Campaigns and cascades • Campaigns: tools of persuasion (long campaign) and mobilisation (short campaign) for parties • Long campaign: 16 ticks before election, every fourth election • Increase in the level of favourable discussion on the part of involved agents with any other receptive agent • Short campaign: 4 ticks before election, every election • Increase the vote intention of similarly coloured agents • Dependent on level of intention of receiver • Following campaigns, influenced agents have the opportunity to convince other agents in their networks • Peer-to-peer mobilisation • Cascade 11/09/2013 - The complexity of turnout

  14. 20-year cycles Averaged over 10 runs (with same conditions) Three campaign scenarios: No short campaign Short campaign at election tick 4-week short campaign Different probabilities of adult agents being contacted in a repeated campaign cycle (0%, 25%, 50%, 75%, 100%) Results 11/09/2013 - The complexity of turnout

  15. Average turnout according to length of SC in various contact scenarios 11/09/2013 - The complexity of turnout

  16. Macro-level treatment effect 11/09/2013 - The complexity of turnout

  17. Average number of agents influenced 11/09/2013 - The complexity of turnout

  18. Reasons for voting 11/09/2013 - The complexity of turnout

  19. Thank you! scid@manchester.ac.uk http://www.scid-project.org

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