A popular identification strategy in non-experimental panel data uses instrumental variables constructed by interacting exogenous but potentially spurious time series or spatial variables with endogenous exposure variables to generate identifying variation through assumptions like those of differences-in-differences estimators. Revisiting a celebrated study linking food aid and conflict shows that this strategy is susceptible to bias arising from spurious trends. Re-randomization and Monte Carlo simulations show that the strategy identifies a spurious relationship even when the true effect could be non-causal or causal in the opposite direction, invalidating the claim that aid causes conflict and providing a caution for similar strategies.