Using a large hand-collected data set from 2001 to 2006, we find that activist hedge funds in the United States propose strategic, operational, and financial remedies and attain success or partial success in two-thirds of the cases. Hedge funds seldom seek control and in most cases are nonconfrontational. The abnormal return around the announcement of activism is approximately 7%, with no reversal during the subsequent year. Target firms experience increases in payout, operating performance, and higher CEO turnover after activism. Our analysis provides important new evidence on the mechanisms and effects of informed shareholder monitoring.ALTHOUGH HEDGE FUND ACTIVISM IS WIDELY discussed and fundamentally important, it remains poorly understood. Much of the commentary on hedge fund activism is based on supposition or anecdotal evidence. Critics and regulators question whether hedge fund activism benefits shareholders, while numerous commentators claim that hedge fund activists destroy value by distracting managers from long-term projects. However, there is a dearth of large-sample evidence about hedge fund activism, and existing samples are plagued by various biases. * We thank the Acting Editor who handled our submission. Brav is with Duke University, Jiang is with Columbia University, Partnoy is with University of San Diego, and Thomas is with Vanderbilt University. The authors have benefited from discussions with Patrick Bolton, Bill Bratton, Martijn Cremers, Gregory Dyra, Alex Edmans, Allen Ferrell, Gur Huberman, Joe Mason, Edward Rock, Mark Roe, Roberta Romano, Tano Santos, William Spitz, Robert Thompson, and Gregory van Inwegen and comments from seminar and conference participants at the American Law and Economics Association, Arizona State University, Association of American Law Schools, BNP Paribas Hedge Fund Centre Symposium, Chicago Quantitative Alliance, Columbia University, The Conference Board, Drexel University, Duke University, FDIC, University of Florida, Goldman Sachs Asset Management, Hong Kong University of Science and Technology, Interdisciplinary Center (Herzlyia, Israel), Inquire (UK), University of Kansas, London Business School, Nanyang Technological University, National University of Singapore, Singapore Management University, Society of Quantitative Analysts, University of Amsterdam, U.S. Securities and Exchange Commission, University of Texas at Austin, University of Virginia, University of Washington, Washington University in St. Louis, Wharton, the European Financial Management Association annual meeting in Vienna, and the Vanderbilt Investor Activism Conference. We owe special thanks to a large number of research assistants for their help in data collection and, in particular, to Jennifer Blessing, Amod Gautam, Greg Klochkoff, and Samantha Prouty. We also thank George Murillo for excellent research assistance. Brav and Jiang acknowledge the financial support from the FDIC, the Q-Group, and the Yale/Oxford Shareholders and Corporate Governance Research Agenda. Jiang is also th...

Cotton plants were grown in CO2‐controlled growth chambers in atmospheres of either 35 or 65 Pa CO2. A widely accepted model of C3 leaf photosynthesis was parameterized for leaves from both CO2 treatments using non‐linear least squares regression techniques, but in order to achieve reasonable fits, it was necessary to include a phosphate limitation resulting from inadequate triose phosphate utilization. Despite the accumulation of large amounts of starch (>50 g m−2) in the high CO2 plants, the photosynthetic characteristics of leaves in both treatments were similar, although the maximum rate of Rubisco activity (Vcmax), estimated from A versus Ci response curves measured at 29°C, was ∼10% lower in leaves from plants grown in high CO2. The relationship between key model parameters and total leaf N was linear, the only difference between CO2 treatments being a slight reduction in the slope of the line relating Vcmax to leaf N in plants grown at high CO2. Stomatal conductance of leaves of plants grown and measured at 65 Pa CO2 was approximately 32% lower than that of plants grown and measured at 35 Pa. Because photosynthetic capacity of leaves grown in high CO2 was only slightly less than that of leaves grown in 35 Pa CO2, net photosynthesis measured at the growth CO2, light and temperature conditions was approximately 25% greater in leaves of plants grown in high CO2, despite the reduction in leaf conductance. Greater assimilation rate was one factor allowing plants grown in high CO2 to incorporate 30% more biomass during the first 36 d of growth.

Carbon-use efficiency (CUE), the ratio of net primary production (NPP) to gross primary production (GPP), describes the capacity of forests to transfer carbon (C) from the atmosphere to terrestrial biomass. It is widely assumed in many landscape-scale carbon-cycling models that CUE for forests is a constant value of $ 0.5. To achieve a constant CUE, tree respiration must be a constant fraction of canopy photosynthesis. We conducted a literature survey to test the hypothesis that CUE is constant and universal among forest ecosystems. Of the 60 data points obtained from 26 papers published since 1975, more than half reported values of GPP that were not estimated independently from NPP; values of CUE calculated from independent estimates of GPP were greater than those calculated from estimates of GPP derived from NPP. The slope of the relationship between NPP and GPP for all forests was 0.53, but values of CUE varied from 0.23 to 0.83 for different forest types. CUE decreased with increasing age, and a substantial portion of the variation among forest types was caused by differences in stand age. When corrected for age the mean value of CUE was greatest for temperate deciduous forests and lowest for boreal forests. CUE also increased as the ratio of leaf mass-to-total mass increased. Contrary to the assumption of constancy, substantial variation in CUE has been reported in the literature. It may be inappropriate to assume that respiration is a constant fraction of GPP as adhering to this assumption may contribute to incorrect estimates of C cycles. A 20% error in current estimates of CUE used in landscape models (i.e. ranging from 0.4 to 0.6) could misrepresent an amount of C equal to total anthropogenic emissions of CO 2 when scaled to the terrestrial biosphere.