Lauren H. Cohen
Professor of Business Administration
Lauren Cohen is a Professor in the Finance area at Harvard Business School, an Editor of Management Science, and a Faculty Research Fellow at the National Bureau of Economic Research. He has also served on the editorial boards of the Review of Financial Studies and the Review of Asset Pricing Studies. Prior to joining HBS, he was an Assistant Professor of Finance at Yale University, in the School of Management, where he was on the faculty from 2005-2007.
His award-winning research has been published in the top journals in Finance and Economics. It is also frequently described in various media outlets including The Wall Street Journal, The New York Times, The Washington Post, Fortune, and Forbes. He is the recipient of a National Science Foundation (NSF) Early Career Development Award for his research agenda on Relationships in Finance. Dr. Cohen received a PhD in finance and an MBA from the University of Chicago in 2005. He earned dual undergraduate degrees from the University of Pennsylvania - a BSE from the Wharton School and a BA in economics from the College of Arts & Sciences in 2001. He serves on the advisory board of Quadriserv, Inc.
We provide theoretical and empirical evidence on the evolution and impact of non-practicing entities (NPEs) in the intellectual property space. Heterogeneity in innovation, given a cost of commercialization, results in NPEs that choose to act as "patent trolls" that chase operating firms' innovations even if those innovations are not clearly infringing on the NPEs' patents. We support these predictions using a novel, large dataset of patents targeted by NPEs. We show that NPEs on average target firms that are flush with cash (or have just had large positive cash shocks). Furthermore, NPEs target firm profits arising from exogenous cash shocks unrelated to the allegedly infringing patents. We next show that NPEs target firms irrespective of the closeness of those firms' patents to the NPEs', and that NPEs typically target firms that are busy with other (non-IP related) lawsuits or are likely to settle. Lastly, we show that NPE litigation has a negative real impact on the future innovative activity of targeted firms.
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.