The Dynamics of Reciprocity, Accountability, and Credibility

Do public opinion dynamics play an important role in understanding conflict trajectories between democratic governments and other rival groups? The authors interpret several theories of opinion dynamics as competing clusters of contemporaneous causal links connoting reciprocity, accountability, and...

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Bibliographic Details
Published in:The Journal of conflict resolution 2008-06, Vol.52 (3), p.343-374
Main Authors: Brandt, Patrick T., Colaresi, Michael, Freeman, John R.
Format: Article
Language:English
Subjects:
Accountability
Arab Israeli Relations
Arab-Israeli conflict
Bayesian analysis
Bayesian method
Coefficients
Conflict
Conflict resolution
Conflict theory
Credibility
Feedback
Forecasting
Forecasting models
Hostility
International cooperation
International politics
Israel
Jews
Judaism
Military Intervention
Modeling
Parametric models
Peace
Political conflict
Prospects
Public Opinion
Reciprocity
Time series
Time series forecasting
U.S.A
War
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Summary:Do public opinion dynamics play an important role in understanding conflict trajectories between democratic governments and other rival groups? The authors interpret several theories of opinion dynamics as competing clusters of contemporaneous causal links connoting reciprocity, accountability, and credibility. They translate these clusters into four distinct Bayesian structural time series models fit to events data from the Israeli-Palestinian conflict with variables for U.S. Intervention and Jewish public opinion about prospects for peace. A credibility model, allowing Jewish public opinion to influence U.S., Palestinian, and Israeli behavior within a given month, fits best. More pacific Israeli opinion leads to more immediate Palestinian hostility toward Israelis. This response's direction suggests a negative feedback mechanism in which low-level conflict is maintained and momentum toward either all-out war or dramatic peace is slowed. In addition, a forecasting model including Jewish public opinion is shown to forecast ex ante better than a model without this variable.
ISSN:0022-0027
1552-8766
DOI:10.1177/0022002708314221