In discretely observed diffusion models, inference about unknown param
eters in a smooth drift function has attracted much interest of late.
This paper deals with a diffusion-type change-point model where the dr
ift has a discontinuity across the point of change, analysed in detail
in continuous time by Ibragimov and Hasminskii. We consider discrete
versions of this model with integrated or blurred observations at a re
gular lattice. Asymptotic convergence rates and limiting distributions
are given for the maximum likelihood change-point estimator when the
observation noise and the lattice spacing simultaneously decrease. In
particular, it is shown that the continuous and discrete model converg
ence rates are generally equal only up to a constant; under specific c
onditions on the blurring function this constant equals unity, and the
normalized difference between the estimators tends to zero in the lim
it.