This paper derives a preference for data privacy from consumers' temptation utility. This approach facilitates a welfare analysis of different data privacy regulations, such as the GDPR enacted by the European Union and the CCPA enacted by the state of California, when a fraction of the...

This paper examines how data-driven personalized decisions can be made while preserving consumer privacy. Our setting is one in which the firm chooses a personalized price based on each new customer's vector of individual features; the true set of individual demand-generating parameters is...

There are materials in literature about how privacy on stigmatizing features like alcoholism, history of tax-evasion, or testing positive in AIDS-related testing may be partially protected by a proper application of randomized response techniques (RRT). The paper demonstrates what amendments are...

In this paper, we quantify hateful content in online civic discussions of politics and estimate the causal link between hateful content and writer anonymity. To measure hate, we first develop a supervised machine-learning model that predicts hate against foreign residents and hate against women...

Society is becoming increasingly dependent on data-rich, "Big Tech" platforms and social networks, such as Facebook and Google. But what happens to our data when these companies close or fail? Despite the high stakes involved, this topic has received only limited attention to date. In this...