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,...

We study the interplay between scientific progress and culture through text analysis on a corpus of about eight million books, with the use of techniques and algorithms from machine learning. We focus on a specific scientific breakthrough, the theory of evolution through natural selection by...

Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised...

The energy transition increases the demand for minerals from ethnically diverse, conflict-prone developing countries. We study whether and where mining is possible in such countries without raising the risk of civil conflict. We proceed in three steps: First, we propose a theoretical model to...

The European higher education landscape has become increasingly integrated causing competition among universities that is no longer bound to national borders. In view of this development, the present paper investigates the relative efficiency of 450 European universities between 2011 and 2014....

This article analyzes how the General Data Protection Regulation (GDPR) has affected the privacy practices of FinTech firms. We study the content of 308 privacy statements respectively before and after the GDPR became binding. Using textual analysis methods, we find that the readability of the...

We develop a novel firm-level measure of cybersecurity risk using textual analysis of cybersecurity-risk disclosures in corporate filings. The measure successfully identifies firms extensively discussing cybersecurity risk in their 10-K, displays intuitive relations with quantitative measures of...

This paper retraces how financial stability considerations interacted with U.S. monetary policy before and during the Great Recession. Using text-mining techniques, we construct indicators for financial stability sentiment expressed during testimonies of four Federal Reserve Chairs at...

We examine the profitability of personalized pricing policies that are derived using different specifications of demand in a typical retail setting with consumer-level panel data. We generate pricing policies from a variety of models, including Bayesian hierarchical choice models, regularized...