Privacy and Platform Competition


Dimakopoulos, Philipp (Humboldt University Berlin)
Sudaric, Slobodan (Humboldt University Berlin)


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.


ad targeting; platform competition; privacy; user data


D43; L13; L40; L86


Open PDF file

Privacy and Platform Competition
Tagged on: