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Simulation New Media in International Relations, WWU- Münster, 6 -7 July 2001

Simulation New Media in International Relations, WWU- Münster, 6 -7 July 2001. Detlef Sprinz PIK - Potsdam Institute for Climate Impact Research & University of Potsdam. Overview. Goals The BDM Policy Forecaster: An Introduction An Example (or two) Experience in the Classroom Conclusions.

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Simulation New Media in International Relations, WWU- Münster, 6 -7 July 2001

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  1. SimulationNew Media in International Relations, WWU- Münster, 6 -7 July 2001 Detlef Sprinz PIK - Potsdam Institute for Climate Impact Research & University of Potsdam

  2. Overview • Goals • The BDM Policy Forecaster: An Introduction • An Example (or two) • Experience in the Classroom • Conclusions

  3. Goals • Augment Traditional Forms of Education: • broaden methodological horizon • simulate policy (ex post and ex ante) • application to a specific policy domain • strengthen generic abilities of students • organization of group processes and common results • presentation of group results • short paper formats

  4. Goals • Format of the Course: • general introduction into the policy domain (climate policy) • 3 sequences (each for national, European, and global policy issues) of • student simulation input papers and external, specialized lectures • student group simulations & presentations

  5. The BDM Policy Forecaster • Assumption • Rationality of Actors • competing actors • maximize expected utility under limited time horizon • “voting” on issues • Ability to Provide Input Data • underlying unidimensional policy space

  6. The BDM Policy Forecaster • Goal: Decision-Making • offers and counteroffers • “produce” winning coalitions (if possible) or “fabricate” majorities • Outcome of Vote • determined by • median voter theorem • veto player • fall back: status quo

  7. The BDM Policy Forecaster • Inputs by Actor • general power or influence (resources) of each actor • stated policy position • salience (priority) of each actors

  8. The BDM Policy Forecaster • Simulation Terminates When • expected benefits of further negotiations < expected benefits of further negotiations • costs of bargaining rise with successive bargaining rounds (discounting) • Model Sequences Suggest • likely offers and their credibility • conflict, compromise, acquiescence, or stalemate

  9. Perceptual Analysis Source: Bueno de Mesquita (2000)

  10. Use in My Course • Replication of Decisions or Predictions • context of climate change • three rounds of simulations • Germany • European Union • global • replications of some decisions where we know the outcome • predictions about some decisions where we do not yet know the outcome

  11. An Example • German Simulation: • emission reductions: national political process (Germany) • Global Simulation: • emission reductions prior to Kyoto negotiations • Access: • http://bdm.cqpress.com

  12. Experience in the Classroom • Context • time-constraints for preparation, weekly assignments • students invested considerable time & enthusiasm • development of scale for positions is a crucial first step • research mostly based on Internet-based research; useful >= 1998/1999

  13. Experience in the Classroom • The Student Experience (based on questionnaire and discussions) • cons • wish longer introduction into the substantive matter • prefer more time for preparation (fewer simulations) • prefer more guidance on data inputs • found that the wording of the assignment (simulation exercise) is crucial

  14. Experience in the Classroom • Pros • had no problems with the technical requirements (PC, private Internet access) • used actor papers as preparation for simulations • appreciate highly the deviation from the long term-paper assignment • mostly liked group simulations • appreciate the presentations of the simulation results

  15. Experience in the Classroom • Options for Revising the Syllabus • fewer simulations • more demonstration examples • recap of model philosophy • longer presentations

  16. Conclusions • The BdM Policy Forecaster combines • structured expert inputs with • a decision-making algorithm to • predict policy outcomes which are • analogous to voting decisions • Simulations Take Considerable Time to Prepare and Continuous Mentoring • Experimental/Prototype Course

  17. Conclusions • Students Are Oriented Towards Perfect Science, not Short Homework Assignments • Traditional Forms of Learning Shape Expectations on What is Scientific • Simulations Enrich the Pedagogical Compendium, But Students Should be Aware not to Expect “the magic (academic) bullet” from Simulation Models

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