Lauren H. Cohen
Associate Professor of Business Administration, Marvin Bower Fellow
Lauren Cohen is an Associate Professor in the Finance area and Marvin Bower Fellow at Harvard Business School, an Associate Editor of the Review of Financial Studies, Management Science, and the Review of Asset Pricing Studies, and a Faculty Research Fellow at the National Bureau of Economic Research. Prior to joining HBS, Professor Cohen was an Assistant Professor of Finance at Yale University, in the School of Management, where he was on faculty from 2005-2007.
Professor Cohen’s research focuses on empirical asset pricing, behavioral finance, and portfolio choice. He has investigated the effect of limited attention on price evolution and studied the information in shorting for future returns. His recent work examines the role of social networks in information transmission in equity markets and government. His research has been published in the Journal of Political Economy, Journal of Finance, Journal of Financial Economics, and the Review of Financial Studies. It has also been covered in media outlets including The Wall Street Journal, The New York Times, The Washington Post, The Financial Times, The Economist, Business Week, Fortune, and Forbes. He has been awarded a National Science Foundation Early Career Development (CAREER) Award for his research agenda on Relationships in Finance.
Professor Cohen received a Ph.D. in finance and an MBA from the University of Chicago in 2005. He earned dual undergraduate degrees from the University of Pennsylvania - a B.S.E. from the Wharton School and a B.A. in economics from the College of Arts & Sciences in 2001. He serves on the advisory board of Quadriserv, Inc.
We exploit a novel setting in which the same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into prices. We document substantial return predictability from the set of easy-to-analyze firms to their more complicated peers. Specifically, a simple portfolio strategy that takes advantage of this straightforward vs. complicated information processing classification yields returns of 118 basis points per month. Consistent with processing complexity driving the return relation, we further show that the more complicated the firm, the more pronounced the return predictability. In addition, we find that sell-side analysts are subject to these same information processing constraints, as their forecast revisions of easy-to-analyze firms predict their future revisions of more complicated firms.
Do Powerful Politicians Cause Corporate Downsizing?
This paper employs a new empirical approach for identifying the impact of government spending on the private sector. Our key innovation is to use changes in congressional committee chairmanship as a source of exogenous variation in state-level federal expenditures. In doing so, we show that fiscal spending shocks appear to significantly dampen corporate sector investment and employment activity. This retrenchment follows both Senate and House committee chair changes, occurs in large and small firms and within large and small states, and is most pronounced among geographically-concentrated firms. The effects are economically meaningful and the mechanism - entirely distinct from the more traditional interest rate and tax channels - suggests new considerations in assessing the impact of government spending on private sector economic activity.