We analyze platform competition where user data is collected to improve adtargeting. Considering that users incur privacy costs, we show that the equilibrium level of data provision is distorted and can be inefficiently high or low: if overall competition is weak or if targeting benefits are low, too much private data is collected, and vice-versa. Further, we find that softer competition on either market side leads to more data collection, which implies substitutability between competition policy measures on both market sides. Moreover, if platforms engage in two-sided pricing, data provision is efficient.

We study the allocation of German lawyers to regional courts for legal trainee-ships. Because of excess demand in some regions lawyers often have to wait before being allocated. The currently used "Berlin" mechanism is not weakly Pareto efficient, does not eliminate justified envy and does not respect improvements. We introduce a mechanism based on the matching with contracts literature, using waiting time as the contractual term. The resulting mechanism is strategy-proof, weakly Pareto efficient, eliminates justified envy and respects improvements. We extend our proposed mechanism to allow for a more flexible allocation of positions over time.

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