Simulation New 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: –

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