Prior research, primarily based on lab experiments, suggests that females might be more averse to competition than males and could be more inclined towards collaboration, instead. Were these findings to generalize to adults across the workforce, there could be profound implications for...

We document strikingly similar gender differences in financial literacy across countries. When asked to answer questions that measure knowledge of basic financial concepts, women are less likely than men to answer correctly and more likely to indicate that they do not know the answer. In...

Local daily newspapers historically played an important role in U.S. democracy by providing citizens with information about local policy issues. In recent decades, local newspapers have struggled to compete with new online platforms. In the first study of private equity (PE) in a struggling...

This paper shows how to remove attenuation bias in regression analyses due to measurement error in historical data for a given variable of interest by using a secondary measure which can be easily generated from digitized newspapers. We provide three methods for using this secondary variable to...

We examine next-day newspaper accounts of large daily jumps in 16 national stock markets to assess their proximate cause, clarity as to cause, and the geographic source of the market-moving news. Our sample of 6,200 market jumps yields several findings. First, policy news - mainly associated...

We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 Wall Street Journal articles for 1984-2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of...

We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text content of 800,000 Wall Street Journal articles for 1984{2017, we estimate a topic model that summarizes business news as easily interpretable topical themes and quantifies the...

We create a newspaper-based Equity Market Volatility (EMV) tracker that moves with the VIX and with the realized volatility of returns on the S&P 500. Parsing the underlying text, we find that 72 percent of EMV articles discuss the Macroeconomic Outlook, and 44 percent discuss Commodity Markets....

We introduce a new text-mining methodology that extracts sentiment information from news articles to predict asset returns. Unlike more common sentiment scores used for stock return prediction (e.g., those sold by commercial vendors or built with dictionary-based methods), our supervised...

We use new data on entries and exits of US daily newspapers from 1869 to 2004 to estimate effects on political participation, party vote shares, and electoral competitiveness. Our identification strategy exploits the precise timing of these events and allows for the possibility of confounding...