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We study dynamic task allocation when providers' expertise evolves endogenously through training. We characterize optimal assignment protocols and compare them to discretionary procedures, where it is the clients who select their service providers. Our results indicate that welfare gains from centralization are greater when tasks arrive more rapidly, and when training technologies improve. Monitoring seniors' backlog of clients always increases welfare but may decrease training. Methodologically, we explore a matching setting with endogenous types, and illustrate useful adaptations of queueing theory techniques for such environments.

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Auctioneers of patents are observed to allow joint bidding by coalitions of buyers. These auctions are distinguished by the good for sale being non-rivalrous, but still excludable, in consumption{that is, they auctions of club goods. This affects how coalitional bidding impacts auction performance. We study the implications of coalitions of bidders on second-price (or equivalently, ascending-price) auctions. Although the formation of coalitions can benefit the seller, we show that stable coalition profiles tend to consist of excessively large coalitions, to the detriment of both auction revenue and social welfare. Limiting the permitted coalition size increases efficiency and confers benefits on the seller. Lastly, we compare the revenues generated by patent auctions and multi-license auctions, and we find that the latter are superior in a large class of environments.