Neural networks offer a promising tool for the analysis of nonlinear economies. In this paper, we derive conditions for the global stability of nonlinear rational expectations equilibria under neural network learning. We demonstrate the applicability of the conditions in analytical and numerical...

Threshold models have been widely used to analyze interdependent behavior, yet empirical research identifying people's thresholds is nonexistent. We introduce an incentivized method for eliciting thresholds and use it to study support for affirmative action in a large, stratified sample of the...

"This informative book reveals the pervasive nature of large inaccuracies in economic statistics. Drawing on numerous real-world examples including case studies from the COVID-19 pandemic, Peter van Bergeijk presents profound insights into how downplaying these errors undermines the scientific...

This paper explores the realities of disclosure risks in the current big data landscape, examining implications for individuals, society, and the evolving ethical landscape. One these realities is pervasive use of dark patterns in data collection. Dark patterns are user interfaces crafted to...