Cooperative localization has emerged as an appealing technology since it can improve the localization performance without any infrastructure change compared with non-cooperative localization. However, some well-localized agents may not be willing to sacrifice additional power to improve the others' localization accuracy. This paper proposes an incentive mechanism from an economic perspective for cooperative localization, whereby a pricing scheme is designed to lead each agent to the optimal state. A game-theoretic algorithm is proposed where each player (agent) can obtain the optimal budget strategy to minimize its individual utility. To make profits in the game, the relationship between the agent's network condition and its budget strategy is derived. Furthermore, a fairness-aware price allocation rule (PAR) is developed to distribute the budget among the reference agents proportional to each node's contribution. Analytical and numerical results show that agents with better network conditions are more likely to join the cooperation under the proposed incentive mechanism, leading to an improved localization performance.