We began by comparing earnings with operating cash flows for the five countries in that sample and then repeated the process for earnings and dividends for the seven countries in the dividend sample. Our final set of results describes the performance of multiple valuations based on earnings forecasts for all 10 countries.

We used the interquartile (IQ) range of the dispersion of price-deflated valuation errors as a measure of the performance of various value drivers. We did so because the IQ range is less sensitive to outliers than are other dispersion measures, such as standard deviation or root mean squared errors. When using alternative ranges (10–90 percent and 5–95 percent), however, we obtained results that are qualitatively similar to those reported here. We also confirmed that these IQ ranges for the different pricing-error distributions straddle a median that is approximately zero. When comparing two value drivers—say, 1 and 2—we report the interquartile range for the distributions of pricing errors for both variables (IQ1 and IQ2). We measured the relative improvement (%IMP) in performance of variable 2 over variable 1 by calculating the percentage decrease in the interquartile range [%IMP = 100 percent × (IQ1 − IQ2)/IQ1]. We also computed a t-statistic for %IMP, derived from a bootstrap approach (see Liu et al. 2002 for details).

Operating Cash Flows vs. Earnings

Columns 1–4 in Table 19.2 contain the results of comparing earnings forecasts with ...

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