Working Papers

Consumers’ Privacy Sensitivity in Digital Markets: Evidence from the Mobile App Industry

Abstract: I investigate the privacy sensitivity of consumers in the mobile app market, taking into account the benefits of sharing personal information. The findings indicate that users are more privacy sensitive than suggested by the literature. Additionally, the sensitivity to the collection of data related to identity is shown to increase over time, but with persistent heterogeneity across countries. In fact, French and German consumers exhibit greater privacy concerns than their US and Canadian counterparts. The heightened sensitivity to privacy raises questions about the need to enforce privacy regulations, especially in competitive markets where consumers can choose products that prioritize privacy over those that do not.

Consumer Data, Product Quality and Privacy Discrimination in Competitive Markets

Abstract: This paper studies the firms’ inability to set different data collection policies across countries on surpluses and privacy in the mobile app industry. By developing and estimating a structural dynamic game model, the findings reveal that US consumers are less privacy-sensitive than their European counterparts. Empirical evidences also suggest that the US market is more profitable for developers than the European market. As a result, when developers cannot adjust their data collection policies across countries, they tend to prioritize collecting consumer data, as the profit gains in the US outweigh the losses in Europe. Through counterfactual analysis, I demonstrate that a regulation enforcing privacy discrimination in data collection across countries would increase consumer surplus and privacy in European countries. However, this regulation would have the opposite effect in the US. This paper aims to inform policymakers about the implications of non-discriminatory data collection policies, particularly in markets with privacy-sensitive consumers.

Deliver Us from Crime? Online Platforms, Gig Jobs, and Offending
with Grazia Cecere (Institut Mines-Telecom), José De Sousa (Univsersité Paris Panthéon-Assas), Olivier Marie (Erasmus University Rotterdam) and Inès Picard (CREST)

Abstract: We investigate the impact of the rise of on-demand food delivery platforms on local employment and crime rates, leveraging the temporal and geographic disparities in their introduction in France. Our staggered difference-in-differences approach reveals that the arrival of a delivery platform in an employment area increases job opportunities for unqualified jobs, as evidenced by a rise in registered riders. This increase in employment opportunities concurrently leads to a large reduction in drug-related crimes, inactivity and social welfare for the unemployed. These results indicate that the gig economy fosters employment opportunities for low-skilled workers, youth, and migrants, facilitating their engagement in lawful economic activities.

Work in Progress

Reallocation of Carpooling Supply
with Xaver Lambin (ESSEC Business School)

Abstract: Many online platforms create value by intermediating different type of users. In the case of one-to-one matching, congestion may arise, causing matching inefficiencies. To alleviate these inefficiencies and increase the number of successful matches, platforms may employ algorithms that involve setting or recommending prices. They may also choose not to disclose certain products to certain consumers. In this paper, we argue that the strategic display of products can enhance efficiency, user surplus and profits in ways that price adjustments alone, even dynamic, cannot achieve. In particular, capacity-constrained goods should be selectively shown to picky consumers while being hidden from consumers with weaker preferences, sometimes even when the picky consumers have lower willingness to pay.

Formation of Social Interaction Preferences in the Sharing Economy
with Xaver Lambin (ESSEC Business School) and Pinar Yildirim (Wharton School)

Abstract: This paper examines the evolution of individual preferences regarding social interaction and diversity based on past interactions with others. By leveraging a unique dataset on carpooling, we take advantage of exogenous variations in the number of passengers, their characteristics, as well as exogenous variations in the distribution of individuals’ characteristics in the market to analyze individual preferences in future carpooling choices. The results are particularly relevant for understanding the formation of preferences and promoting public transportation.

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