Lauren H. Cohen
L.E. Simmons Professor of Business Administration
Lauren Cohen is the L.E. Simmons Professor in the Finance area at Harvard Business School, an Editor of Management Science, and a Research Associate 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, The Economist, and Forbes. It has been recognized by numerous National Science Foundation (NSF) Awards, including a National Science Foundation 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.
The Growing Problem of Patent Trolling • SCIENCE • VIDEO
The last decade has seen a sharp rise in patent litigation in the U.S., with 2015 having one of the highest patent lawsuit counts on record. In theory, this could be a consequence of growth in the commercialization of technology and innovation – patent lawsuits increase as more firms turn to intellectual property (IP) protection to safeguard their competitive advantages. However, the majority of recent patent litigation is driven by nonpracticing entities (NPEs), firms that generate no products, but instead amass patent portfolios for the sake of enforcing IP rights afforded therein. We discuss new, large-sample evidence adding to a growing literature suggesting that NPEs – in particular, large patent aggregators – on average act as “patent trolls”, suing cash‐rich firms seemingly irrespective of actual patent infringement. This has a negative impact on future innovation activity at targeted firms. These results suggest a need to check the power of NPEs through changes in U.S. IP policy, in particular to screen out trolling early in the litigation process.
We develop a theoretical model of, and provide the first large-sample evidence on, the behavior and impact of non-practicing entities (NPEs) in the intellectual property space. Our model shows that NPE litigation can reduce infringement and support small inventors. However, the model also shows that as NPEs become effective at bringing frivolous lawsuits, the resulting defense costs inefficiently crowd out some firms that, absent NPEs, would produce welfare-enhancing innovations without engaging in infringement. Our empirical analysis shows that on average, NPEs appear to behave as opportunistic patent trolls. NPEs sue cash-rich firms ― a one standard deviation increase in cash holdings roughly doubles a firm's chance of being targeted by NPE litigation. We find moreover that NPEs target cash unrelated to the alleged infringement at essentially the same frequency as they target cash related to the alleged infringement. By contrast, cash is neither a key driver of intellectual property lawsuits by practicing entities (e.g., IBM and Intel), nor of any other type of litigation against firms. We find further suggestive evidence of NPE opportunism, such as forum shopping and targeting of firms that may have reduced ability to defend themselves against litigation. We find that NPE litigation has a real negative impact on innovation at targeted firms: firms substantially reduce their innovative activity after settling with NPEs (or losing to them in court). Moreover, we neither find any markers of significant NPE pass-through to end innovators, nor of a positive impact of NPEs on innovation in the industries in which they are most prevalent.
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.