Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP,...

How damaging are uncertainty shocks during extreme events such as the great recession and the Covid-19 outbreak? Can monetary policy limit output losses in such situations? We use a nonlinear VAR framework to document the large response of real activity to a financial uncertainty shock during...

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

A standard result in contests is that a higher-ability player has a higher probability of winning the prize than a lower-ability player. Put differently, a stronger player has an advantage over a weaker player in a contest. There are very few exceptions to this standard result. I consider a...

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...

This paper assesses the impact of US policy responses to the Covid-19 pandemic on various cryptocurrencies and also technology stocks using fractional integration techniques. More precisely, it analyses the behaviour of the percentage returns in the case of nine major coins (Bitcoin - BITC,...

This paper presents novel evidence for the prevalence of deviations from rational behavior in human decision making – and for the corresponding causes and consequences. The analysis is based on move-by-move data from chess tournaments and an identification strategy that compares behavior of...

Economic theory provides ambiguous and conflicting predictions about the association between algorithmic pricing and competition. In this paper we provide the first empirical analysis of this relationship. We study Germany’s retail gasoline market where algorithmic-pricing software became...

Algorithms play an increasingly important role in economic situations. These situations are often strategic, where the artificial intelligence may or may not be cooperative. We study the deter-minants and forms of algorithmic cooperation in the infinitely repeated prisoner’s dilemma. We run a...