Remarks on a Political Modeling Strategy for Social Systems

Detlef SprinzPIK - Potsdam Institute for Climate Impact Research

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Overview

• Goals

• Options

• Conclusions

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Goals

• Provide a (Set of) Tool(s) to– provide a framework for the analysis of non-

trivial decisions– among multiple actors– on various levels of analysis or aggregation– to replicate past decisions and– explore the likely outcomes of major decisions

for the future

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Options

• Basic Options– case study– statistical analysis– (cooperative and non-cooperative) game theory– optimization tools (incl. CBA)– simulation

• form of quasi-experimentation

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Options

• Example: Political Simulation Model of Bueno de Mesquita

• Assumptions– Rationality of Actors

• competing actors

• maximize expected utility under limited time horizon

• “voting” on issues

• no level of analysis problem

– Ability to Provide Input Data

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Options

• 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

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Options

• Inputs by Player– general power or influence (resources) of each actor– stated policy position– salience (priority) of each actors

• Simulation Terminates When– expected benefits of further negotiations

< expected benefits of further negotiations– discounting the outcomes over time

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Options

• Advantage of BdM Policy Forecaster– utilizes case experience similar to case study

analyst in a fully structured way– provides forecasts and simple dynamic of

decision-Making– rigorous tool rather than guesstimate

• accuracy is imperfect (ca. 90% correct predictions)

– permits sensitivity analyses

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Options

• Some Challenges & Limitations– lack of simultaneously including related agenda

items (problem of uni-dimensional political space)

– high-quality data inputs• not easily available even for many European

countries

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Options

• How to Use it for Social Systems I– 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 (e.g., post-Kyoto)

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Options

• How to Use it for Social Systems II– beyond climate change– in context of European Climate Forum

• with select target groups (self-selected)

• replication

• short-term forecasting (easy “verification”) & learning

• longer-term forecasts

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Conclusions

• A Proposed Sequence of Activities– build a backbone at PIK incl. endowment– review other options in the family of simulation

models– outreach to a limited set of relevant inter/national

institutions– engage a small set of internationally renowned

scholars• Bueno de Mesquita, Jacobson et al.

• Underdal, CICERO et al.