A compromise between contemporaneous and inter-temporal analyses is the so-called window analysis where DEA is applied successively on overlapping time periods of constant width (called a window). Once the window width has been specified all observations within it are viewed and examined in an inter-temporal manner referred to as locally inter-temporal analysis . The method was initially proposed by Charnes et al.  in order to measure efficiency in cross sectional and time varying data. Furthermore, when window-DEA is applied, the number of observations taken into account is multiplied essentially by a factor equal to window’s width, which is quite useful when dealing with small sample sizes as it increases the discrimination capability of the method . Therefore, two factors should be reconciled when choosing window width. The window should be wide enough to incorporate the minimum number of DMUs for the required discrimination but it should also be narrow enough to ensure that technological change within it is negligible and therefore it will not allow misleading or unfair comparisons between DMUs belonging to distant apart time periods .