▁uncertainty ▁often ▁leads ▁to ▁the ▁selection ▁of ▁highly ▁conserv ative ▁alternatives . ▁ ▁This ▁is ▁precisely ▁the ▁reason ▁that ▁this ▁parad ig m ▁is ▁not ▁always ▁a ▁satisf actory ▁method ology ▁for ▁decision - making ▁under ▁severe ▁uncertainty ▁( T int ner ▁ 1 9 5 2 ). ▁ ▁As ▁indicated ▁in ▁the ▁over view , ▁info - g ap ' s ▁robust ness ▁model ▁is ▁a ▁Max imin ▁model ▁in ▁dis gu ise . ▁More ▁specifically , ▁it ▁is ▁a ▁simple ▁instance ▁of ▁Wald ' s ▁Max imin ▁model ▁where : ▁ ▁The ▁region ▁of ▁uncertainty ▁associated ▁with ▁an ▁alternative ▁decision ▁is ▁an ▁immediate ▁neighborhood ▁of ▁the ▁estimate ▁. ▁ ▁The ▁uncertain ▁out comes ▁of ▁an ▁alternative ▁are ▁determined ▁by ▁a ▁characteristic ▁function ▁of ▁the ▁performance ▁requirement ▁under ▁consideration . ▁ ▁Thus , ▁aside ▁from ▁the ▁conserv at ism ▁issue , ▁a ▁far ▁more ▁serious ▁issue ▁must ▁be ▁addressed . ▁ ▁This ▁is ▁the ▁valid ity ▁issue ▁ar ising ▁from ▁ ▁the ▁local ▁ ▁nature ▁of ▁info - g ap ' s ▁robust ness ▁analysis . ▁ ▁Local ▁vs ▁global ▁robust ness ▁▁ ▁The ▁valid ity ▁of ▁the ▁results ▁generated ▁by ▁info - g ap ' s ▁robust ness ▁analysis ▁are ▁cont ing ent ▁on ▁the ▁quality ▁of ▁the ▁estimate ▁. ▁According ▁to ▁info - g ap ' s ▁own ▁working ▁assumptions , ▁this ▁estimate ▁is ▁poor ▁and ▁likely ▁to ▁be ▁substantial ly ▁wrong ▁( Ben - Ha im , ▁ 2 0 0 6 , ▁p .   2 8 0