With grouping, a sample is sorted by an observable variable and the mean values of the dependent variable in the extreme-ranked groups are compared. We show that test power is maximized when the two extreme groups each contain 27% of the sample, a much larger percentage than that typically used in the literature. This result is not sensitive to the distribution of the dependent variable. We also show that regression is unambiguously more powerful than grouping, even when the independent variable is measured with error.

This paper examines the extent to which aggregate stock return variation is explained by variables chosen to reflect revisions in expectations of future dividends. In effect, we decompose realized dividend growth into expected and unexpected components using information in aggregate investment, dividend yield, and future returns. A parsimonious specification accounts for over 70% of annual return variation. We also conduct a cross-sectional experiment using portfolios formed on the basis of annual return performance. This analysis shows that nearly 90% of the portfolio return variation is explained by dividend and expected return variables.

We examine post-acquisition performance for the 50 largest U.S. mergers between 1979 and mid-1984. Merged firms show significant improvements in asset productivity relative to their industries, leading to higher operating cash flow returns. This performance improvement is particularly strong for firms with highly overlapping businesses. Mergers do not lead to cuts in long-term capital and R&D investments. There is a strong positive relation between postmerger increases in operating cash flows and abnormal stock returns at merger announcements, indicating that expectations of economic improvements underlie the equity revaluations of the merging firms.