We investigate the role played by the media in the expectations formation process of households. Using a novel news-topic-based approach we show that news types the media choose to report on, e.g., fiscal policy, health, and politics, are good predictors of households' stated inflation...

This paper presents a review of empirical methods used to assess the behavioral, economic, and political outcomes of Internet and social media usage. Instead of merely surveying the various impacts of the Internet, we examine the methods adopted to identify these impacts. We describe two main...

We consider the effect of adaptive model selection and regularization by agents on price volatility and market stability in a simple agent-based model of a financial market. The agents base their trading behavior on forecasts of future returns, which they update adaptively and asynchronously...

Attention is a pivotal resource in the modern economy and plays an increasingly prominent role in economic analysis. We summarize research on attention from both psychology and economics, placing a particular emphasis on its capacity to explain numerous documented violations of classical...

Effective financial reporting requires efficient information processing. This paper studies factors that determine efficient information processing. I exploit a unique small business lending setting where I am able to observe the entire codified demographic and accounting information set that...

Can algorithms help people predict behavior in high-stakes prisoner’s dilemmas? Participants watching the pre-play communication of contestants in the TV show Golden Balls display a limited ability to predict contestants’ behavior, while algorithms do significantly better. We provide...

We are interested in forecasting bankruptcies in a probabilistic way. Specifically, we compare the classification performance of several statistical and machine-learning techniques, namely discriminant analysis (Altman's Z-score), logistic regression, least-squares support vector machines and...

We are interested in forecasting bankruptcies in a probabilistic way. Specifically, we compare the classification performance of several statistical and machine-learning techniques, namely discriminant analysis (Altman's Z-score), logistic regression, least-squares support vector machines and...

We are interested in forecasting bankruptcies in a probabilistic way. Specifcally, we compare the classifcation performance of several statistical and machine-learning techniques, namely discriminant analysis (Altman's Z-score), logistic regression, least-squares support vector machines and...

The pervasive strengths of Artificial Intelligence have simplified analysis and execution of virtually all Financial businesses and the ensuing digital transformation in progress requires a cogent state of the art examination of technologies and models in use to operationalize this...