This paper presents an algorithm to identify a state-space model of a linear system using a backward-time approach. The procedure consists of three basic steps. First, the Markov parameters of a backward-time observer are computed from experimental input-output data. Second, the backward-time observer Markov parameters are decomposed to obtain the hackward-time system Markov parameters (backwar...

Backward induction is the most widely accepted principle for predicting behavior in dynamic games. In experiments, however, players frequently violate this principle. An alternative is a 2-parameter “dynamic level-k” model, where players choose a rule from a rule hierarchy. The rule hierarchy is iteratively defined such that the level-k rule is a best-response to the level-(k− 1) rule and the l...

The paper investigates the stability properties of markets with backward bending supply curves. Parameters are chosen so that the two classic models of price dynamics, the Walrasian model and the Marshallian model, give opposite predictions. The results are: (1) market instability can be observed; (2) in the backward bending case stability is captured by the Walrasian model and the Marshallian ...