In this paper, the authors develop a new estimation method that is suitable for censored models with two high-dimensional fixed effects and that is based on a sequence of least squares regressions, yielding significant savings in computing time and hence making it applicable to frameworks in...

The idea behind the methodology proposed in this paper is to show the utilities that it can offer, a software tool to make recommendations to the banking users when making a claim against a bad practice from their banks or wish to make an inquiry in order to ascertain the chances of a favorable...

This explorative study examines how Facebook's News Feed, fear of missing out (FOMO), news literacy, experience of fake news, disappointment at local election results, trust in the News Feed, and perceptions of algorithms affect users' attitude toward Facebook as a political news source and fake...

The rise of digital platforms requires a deeper understanding of the structural role of algorithmic management in work environments. In this interdisciplinary study, we examine how digital platforms, which offer food delivery service, use a mobile application for management of their workforce....

We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question....

We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question....