We investigate whether institutional investors “vote with their feet” when dissatisfied with a firm's management by examining changes in equity ownership around forced CEO turnover. We find that aggregate institutional ownership and the number of institutional investors decline in the year prior to forced CEO turnover. However, selling by institutions is far from universal. Overall, there is an increase in shareholdings of individual investors and a decrease in holdings of institutional investors who are more concerned with holding prudent securities, are better informed, or are engaged in momentum trading. Measures of institutional ownership changes are negatively related to the likelihoods of forced CEO turnover and that an executive from outside the firm is appointed CEO.

Universities are a key institution in the U.S. innovation system, and an important aspect of their involvement is the role they play in public-private partnerships. This note offers insights into the performance of industry-university research partnerships, using a survey of precommercial research projects funded by the Advanced Technology Program. Although results must be interpreted cautiously because of the small size of the sample, the study finds that projects with university involvement tend to be in areas involving new science and therefore experience more difficulty and delay, yet are more likely not to be aborted prematurely. Our interpretation is that universities are contributing to basic research awareness and insight among the partners in ATP-funded projects.

Collusive Practices in Repeated English Auctions: Experimental Evidence on Bidding Rings by Owen R. Phillips, Dale J. Menkhaus and Kalyn T. Coatney. Published in volume 93, issue 3, pages 965-979 of American Economic Review, June 2003

Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of Yule (1926) and Granger and Newbold (1974) . Data mining for predictor variables interacts with spurious regression bias. The two effects reinforce each other, because more highly persistent series are more likely to be found significant in the search for predictor variables. Our simulations suggest that many of the regressions in the literature, based on individual predictor variables, may be spurious.