Do households facing an interval of prices rather than a simple price alter the results of poverty analyses? To address this question, we exploit a unique dataset from Niger in which agropastoral households provide the minimum and maximum prices they paid for each consumed product in each season. We estimate poverty measures based on this price information using several absolute poverty line methodologies. Prices are used for valuing household consumption bundles, estimating household-specific price indices, valuing minimal calorie requirements, and extrapolating the link between food poverty and consumption. The results for Niger show statistically significant differences in the estimated chronic and dynamic poverties for these approaches, especially for international poverty comparisons and seasonal transient poverty monitoring. Specifically, using minimum and maximum prices generates gaps in the estimated poverty rates for Nigerien agropastoral households that exceed regional poverty disparities, which implies that regional targeting priorities in poverty alleviation policies would be reversed if these alternative prices are utilized. This result suggests that typically estimated poverty statistics, which assume that each household, or even cluster, faces a unique price for each product in a given period, may be less accurate for policy monitoring than generally believed.