Identifiability of parameters is a fundamental prerequisite for model identification. It concerns uniqueness of the model parameters determined from experimental or simulated observations. This dissertation specifically deals with structural or a priori identifiability: whether or not parameters can be identified from a given model structure and experimental measurements. We briefly present the identifiability problem in linear and non linear dynamical model. We compare DSGE and Agent Based model (ABM) in terms of identifiability of the structural parameters and we finally discuss limits and perspective of numerical protocols to test global identifiability in case of ergodic and markovian economical systems.
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