We study the problem of how to share the cost of a backbone network among its customers. A variety of empirical cost-sharing policies are used in practice by backbone network operators but very little ever reaches the research literature about their properties. Motivated by this, we present a systematic study of such policies focusing on the discrepancies between their cost allocations. We aim at quantifying how the selection of a particular policy biases an operator's understanding of cost generation. We identify F-discrepancies due to the specific function used to map traffic into cost (e.g., volume vs. peak rate vs. 95-percentile) and M-discrepancies, which have to do with where traffic is metered (per device vs. ingress metering). We also identify L-discrepancies relating to the liability of individual customers for triggered upgrades and consequent costs (full vs. proportional), and finally, TCO-discrepancies emanating from the fact that the cost of carrying a bit is not uniform across the network (old vs. new equipment, high vs. low energy or real estate costs, etc.). Using extensive traffic, routing, and cost data from a tier-1 network we show that F-discrepancies are large when looking at individual links but cancel out when considering network-wide cost-sharing. Metering at ingress points is convenient but leads to large M-discrepancies, while TCO-discrepancies are huge. Finally, L-discrepancies are intriguing and esoteric but understanding them is central to determining the cost a customer inflicts on the network.