In the left side of Table 8, panel A, we compare the 57 OCF-increasing changer sample to itself over time-before and after the reclassification for variables similar to those in the cross-sectional regression. For variables created as averages over the sample period, averages are based on the periods before and after the reclassification. The significantly positive differences in the means and medians of the difference in OCF (reported minus pro forma) and interest paid reported in financing are a function of the criteria for inclusion as an OCF-increasing changer. In addition, we find that equity issues and analysts’ forecast coverage are higher in the period after the change. The mean and median profitability of changers is significantly lower after the change.
On the right side of Table 8, panel A, we compare the 57 OCF-increasing changers to the control sample. We find significant differences in the means, medians or both of the difference in OCF (reported minus pro forma), interest paid reported in financing, equity issues, analysts’ forecast coverage, cross-listed in the US, and industry.
Table 8, panel B, presents results of a logistic regression with the dependent variable OCF-Increasing Classification Change equal to one if the firm increased OCF by making a classification change and zero otherwise. Results indicate that firms with greater equity issuance are more likely to make OCF-increasing choices. Any valuation enhancement related to higher reported OCF would increase equity issuance proceeds, but the relation is not direct, particularly as equity issuance is measured historically. We find that analyst forecast coverage is negatively associated with changing, consistent with analysts’ cash flow forecasts serving some deterrent role. Similarly, those firms that have greater industry homogeneity and are cross-listed in the US are less likely to make an OCF-increasing classification change. These firms appear to be responding to external forces to maintain current OCF reporting choices.
Additional analyses and variables
Data on auditors indicate that 88% of our full sample of 798 firms are audited by a Big Four auditor (Deloitte, Ernst & Young, KPMG, or PricewaterhouseCoopers). To consider the possibility that classification choice is driven by the auditor, we re-estimate our regressions including an indicator variable for each of these auditors. Results show that none of the indicator variables are significant (not tabulated). Thus we do not find evidence that classification choice is associated with auditor choice.
We also examine the effect of including the following other variables, but none are significant: credit risk, average market-to-book ratio, average returns, an indicator variable for earnings that are just positive, variability of OCF (computed as the standard deviation of the firm’s OCF over the sample period), and capital intensity, which captures structure of operations and potential financing needs.
When we include only observations with interest paid located on the face of or in the footnotes to the financial statements (about 70% of the sample), regression results resemble the overall reported results.
We also reviewed the classification choices of a larger set of cross-listed firms to determine whether the results on the cross-listing variable are generalizable to a broader set of cross-listing firms. We collected data on 83 European Union cross-listed firms in 2006 (including some of the 40 cross-listed firms in our sample), and we find the classification choice for interest paid resembles our overall sample: 78% reporting in operating and 22% in financing.
Market pricing of the persistence of cash flows
Results of the analysis comparing the persistence parameters for accruals and cash flow components of earnings are presented in Table 9. For both groups, accruals are significantly less persistent than operating cash flows, similar to findings of Sloan (1996) and ). The lower persistence of accruals is indicated by the FLEX group’s persistence parameter (i.e., forecasting coefficient) for accruals of 0.4302, compared to 0.6788 for operating https://paydayloanstennessee.com/cities/gainesboro/ cash flow (panel A). For the non-FLEX group, persistence parameters are 0.4339 and 0.6851 for accruals and operating cash flow, respectively (panel B).