In this paper, we provide a ${cal H}_{infty}$--norm lower bound on the worst--case identification error of least--squares estimation when using FIR model structures. This bound increases as a logarithmic function of model complexity and is valid for a wide class of inputs characterized as being quasi--stationary with covariance function falling off sufficiently quickly.