We analyze the partisanship of Securities and Exchange Commissioners (SEC) and members of the Federal Reserve Board of Governors (Fed) using the language-based approach of Gentzkow, Shapiro, and Taddy (Econometrica, 2019). The level of partisanship among these regulators is greater than that of...

We derive a general expression for the value of information to a price-taking investor in a dynamic environment and provide a framework for its estimation. We study the value of both private and public information and break it down into its instrumental and psychic parts. To illustrate, we...

Text data is ultra-high dimensional, which makes machine learning techniques indispensable for textual analysis. Text is often selected—journalists, speechwriters, and others craft messages to target their audiences' limited attention. We develop an economically motivated high dimensional...

Text data is ultra-high dimensional, which makes machine learning techniques indispensable for textual analysis. Text is often selected—journalists, speechwriters, and others craft messages to target their audiences' limited attention. We develop an economically motivated high dimensional...

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...

Text data is ultra-high dimensional, which makes machine learning techniques indispensable for textual analysis. Text is often selected--journalists, speechwriters, and others craft messages to target their audiences' limited attention. We develop an economically motivated high dimensional...

How does the speed by which information diffuses affect its value to a stock market investor? In a structural model solved in closed-form, this speed has two opposing effects on the empirically dominant term of the value of information. Faster-diffusing information means quicker and less noisy...