This paper addresses implicit opinions expressed via inference over explicit sentiments and events that positively/negatively affect entities (goodFor/badFor, gfbf events). We incorporate the inferences developed by implicature rules into an optimization framework, to jointly improve sentiment detection toward entities and disambiguate components of gfbf events. The framework simultaneously beats the baselines by more than 10 points in F-measure on sentiment detection and more than 7 points in accuracy on gfbf polarity disambiguation.