Description:
We analyze how the adoption of the California Consumer Protection Act (CCPA), which limits buying or selling consumer data, heterogeneously affects firms with and without previously gathered data on consumers. Exploiting a novel and hand-collected data set of 11,436 conversational-AI firms with rich personal data on identifiable U.S. consumers, we find that the CCPA gives a strong protection and advantage to firms with in-house data on consumers. First, products of these firms experience significant appreciations in customer ratings and are able to collect more customer data relative to their competitors after the adoption of the CCPA. Second, publicly traded firms with in-house data exhibit higher valuations, profitability, asset utilization, and they invest more after the adoption of the CCPA. Third, earnings of such firms can be more accurately predicted by analysts. To rationalize these empirical findings, we build a general equilibrium model where firms produce final goods using labor and data in the form of intangible capital, which can be traded with other firms subject to an iceberg transportation cost. When the introduction of the CCPA increases the transportation cost, firms without in-house data suffer the most because they cannot adequately substitute the previously externally purchased data, while firms with in-house data expand their market share