▁So ▁it ▁is ▁vital ▁to ▁be ▁clear ▁that ▁to ▁give ▁apt ▁expression ▁to ▁the ▁ ▁sever ity ▁of ▁the ▁uncertainty , ▁in ▁the ▁Info - G ap ▁framework ▁these ▁three ▁construct s ▁ ▁are ▁given ▁specific ▁meaning . ▁Working ▁Ass um ptions ▁ ▁The ▁region ▁of ▁uncertainty ▁ ▁is ▁relatively ▁large . ▁In ▁fact , ▁Ben - Ha im ▁( 2 0 0 6 , ▁p .   2 1 0 ) ▁indicates ▁that ▁in ▁the ▁context ▁of ▁info - g ap ▁decision ▁theory ▁most ▁of ▁the ▁commonly ▁encountered ▁regions ▁of ▁uncertainty ▁are ▁un bounded . ▁ ▁The ▁estimate ▁ ▁is ▁a ▁poor ▁approximation ▁of ▁the ▁true ▁value ▁of ▁. ▁That ▁is , ▁the ▁estimate ▁is ▁a ▁poor ▁indic ation ▁of ▁the ▁true ▁value ▁of ▁ ▁( Ben - Ha im , ▁ 2 0 0 6 , ▁p .   2 8 0 ) ▁and ▁is ▁likely ▁to ▁be ▁substantial ly ▁wrong ▁( Ben - Ha im , ▁ 2 0 0 6 , ▁p .   2 8 1 ). ▁ ▁In ▁the ▁picture ▁ ▁represents ▁the ▁true ▁( unknown ) ▁value ▁of ▁. ▁ ▁The ▁point ▁to ▁note ▁here ▁is ▁that ▁conditions ▁of ▁severe ▁uncertainty ▁ent ail ▁that ▁the ▁estimate ▁▁ ▁can — rel atively ▁speaking — be ▁very ▁distant ▁from ▁the ▁true ▁value ▁. ▁This ▁is ▁particularly ▁pert inent ▁for ▁method ologies , ▁like ▁info - g ap , ▁ ▁that ▁seek ▁robust ness ▁to ▁uncertainty . ▁Indeed , ▁assuming ▁otherwise ▁ ▁would — method olog ically ▁speaking —