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 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 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 analyze the coverage of U.S. political scandals by U.S. newspapers during the past decade. Using automatic keyword-based searches we collected data on 35 scandals and approximately 200 newspapers. We find that Democratic-leaning newspapers -- i.e., those with a higher propensity to endorse...