| Scope and method of study. This study examines whether geographic information disclosed at an increasingly disaggregated level (specifically, consolidated vs. continent vs. country) results in increased predictive ability of company operations (specifically, sales, gross profit, and earnings). Multinational corporations are formed by combining the annual operating results of six individual firms, one from each of six countries. This approach makes it possible to compare the forecasting accuracy of data disclosed at the country, continent, and consolidated levels, not possible using current geographic segment disclosures. Furthermore, this approach makes it possible to examine the predictive ability of information, such as gross profit, that is currently being considered for segment disclosure by national and international regulatory authorities. The study uses both year-ahead forecast models as in prior geographic segment studies and regression forecast models. For each of these forecast models, forecasting accuracy using perfect foresight measures and forecasts of exchange rate changes, inflation, and real GNP growth are examined.;Findings and conclusions. The results for sales and gross profit demonstrate that the accuracy of forecasts increase as sales and gross profit are disclosed at a more disaggregated geographic level. The hypothesized relationship between consolidated, continent, and country levels, while holding strongly under perfect foresight, holds to a lesser extent using forecasts of exchange rates, inflation, and real GNP. The results for earnings using year-ahead forecast models also indicates that the accuracy of earnings forecasts significantly improve with greater geographic disaggregation. However, the results for earnings should be interpreted with caution since the coefficient estimates using regression forecast models provide evidence that the three forecasting factors (i.e., exchange rate changes, inflation, and real GNP) are not significantly related to forecasts of annual earnings. |
