  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.
