  In this paper, we consider an estimation problem of the regression
coefficients in multiple regression models with several unknown change-points.
Under some realistic assumptions, we propose a class of estimators which
includes as a special cases shrinkage estimators (SEs) as well as the
unrestricted estimator (UE) and the restricted estimator (RE). We also derive a
more general condition for the SEs to dominate the UE. To this end, we
generalize some identities for the evaluation of the bias and risk functions of
shrinkage-type estimators. As illustrative example, our method is applied to
the "gross domestic product" data set of 10 countries whose USA, Canada, UK,
France and Germany. The simulation results corroborate our theoretical
findings.
