The expenditure elasticity pattern in section 5.2 is the more easily anticipated of the two principal results; the price responsiveness pattern is the more consequential one. Every estimated own-price elasticity in the Nigerian system is negative under both the Marshallian and the Hicksian definition, so the law of demand and compensated negativity hold for every food group estimated. Within the set of goods with statistically confirmed negative compensated own-price responses, cereals (−0.51) are the least price-responsive, consistent with their role as a dietary staple for which households have limited substitution opportunities even when compensated for the income loss. Cereals are simultaneously the largest single budget share in the Nigerian food basket, at 24.9 percent. A food group that is both large in the budget and inelastic in demand is precisely the combination that produces large welfare losses when its price rises, because households cannot reduce their cereal purchases proportionately to a price increase without a correspondingly large reduction in food intake, and the budget share affected is large to begin with. The welfare estimates in section 4.5 quantify this mechanism under the assumption of full price transmission from global to domestic cereal markets, and using long-run elasticities that likely understate the short-run response to a sudden price spike; both qualifications are discussed in section 5.6. A cereal price increase of the magnitude associated with the 2022 disruption of Ukrainian and Russian grain exports, seventy percent, generates a second-order compensating variation equal to 11.4 percent of food expenditure and 7.1 percent of total household expenditure for the average household in this sample. The fifty percent increase comparable to the 2010-11 price spike costs 9.1 percent of food expenditure and 5.6 percent of total expenditure, and the thirty percent increase comparable to the 2008 crisis costs 6.1 percent of food expenditure and 3.8 percent of total expenditure. These figures are computed after allowing for the compensated substitution toward vegetables, fruit, and other food groups documented in section 4.4. The central argument that follows from placing the expenditure and price results side by side is that Nigerian households have substitution opportunities available to them, the positive compensated cross-price elasticities in the Hicksian matrix are direct evidence of this, but those opportunities are not large enough to prevent a major cereal price shock from imposing a substantial welfare cost, because the good in question is both budget-dominant and demand-inelastic. This finding sits within a long empirical literature on staple food prices and household welfare in developing economies. Deaton (1989) uses household survey data from Thailand to show that rice price changes have sharply different welfare consequences for net rice buyers and net rice sellers, a distributional point that this study's aggregate compensating variation estimates do not separately identify but that is a natural next step once a structural demand system of the kind estimated here for Nigeria is in hand. Ivanic and Martin (2008) find that the staple food price increases of the 2008 world food crisis raised poverty among net food-buying households across a sample of low-income countries, and Headey (2011) traces the role of trade policy responses, particularly export restrictions, in amplifying the price shocks that drove those welfare losses. Bellemare (2015) extends the welfare consequences of food price movements beyond household budgets directly, linking food price volatility, as distinct from the price level, to social unrest, which suggests that the welfare costs quantified in section 4.5 may understate the full social cost of cereal price instability if that instability has consequences beyond the household budget constraint modelled here. Gibson (2013) makes the closely related point that household surveys in developing countries generally prioritise collecting living-standards data over the price data needed to measure welfare impacts properly, and that studies ignoring households' coping responses, particularly downgrading food quality to maintain quantity, tend to overstate the welfare harm of rising prices; the Nigerian estimates in this study rely on unit-value-based prices precisely because no separate price survey was available, a limitation discussed further in section 5.6. Hertel and colleagues (2001) take a complementary, general-equilibrium approach, using a global trade model to assess how staple food price variability translates into poverty vulnerability for low-income households across several countries simultaneously, a cross-country perspective this study's single-country structural design does not attempt to replicate.