Products of random matrices associated to one-dimensional random media
satisfy a central limit theorem assuring convergence to a gaussian centered at
the Lyapunov exponent. The hypothesis of single parameter scaling states that
its variance is equal to the Lyapunov exponent. We settle discussions about its
validity for a wide class of models by proving that, away from anomalies,
single parameter scaling holds to lowest order perturbation theory in the
disorder strength. However, it is generically violated at higher order. This is
explicitely exhibited for the Anderson model.Comment: minor corrections to previous version, to appear in Annales H.
Poincar