Strategic Interaction and Empirical Models: An Application of Statistical Backward Induction to the U.S. Special 301 Report

While conventional statistical methods usually assume that the error
term in the models are independent and identically distributed (i.i.d.),
this assumption is usually violated when observations are interdependent
due to the strategic interactions among players. The violation of the i.i.d
assumption results in the inefficient estimation of standard errors that can
further invalidate the hypothesis testing. This paper discusses the method
of statistical backward induction (SBI) developed by Curtis S. Signorino

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