not imply causation. In the multivariate correlation analysis, high market share was associated with high profits, but high profits could have been associated with high market share, or a third factor common to both could have caused the correlation. Many analysts believe that it is possible to use a statistical causality test to determine causation, but if the whole problem is that correlation is insufficient to determine causation in the first place, then how can using another correlation, which is what is used in the tests, determine causation. → In connection with the market share, already indicated and frequent allegations that correlations are used in the PIMS investigations to draw conclusions about causal relationships, i.e. correlation is equated with causality. However, this problem is too obvious not to have been examined in detail during the development of the PIMS program. Backhaus et al. formulate this aptly: "The primary field of application of regression analysis is the investigation of causal relationships (cause-effect relationships), which we can also refer to as "The more the" relationships". Backhaus et al. (2006), p. 46 (Emphasis in the original.) These authors then add the following: "It should be emphasized here that neither regression analysis nor other statistical methods can prove causalities beyond doubt. Rather, regression analysis can only prove correlations between variables. This is a necessary but not yet sufficient condition for causality." Backhaus et al. (2006), p.48 f. Within the framework of the PIMS studies, it was thus possible to determine causalities with the help of time series analyses due to the availability of data over longer periods. See, for example, Barylite (1994), p. 61. Correlations in this sense, including in the PIMS program, initially give nothing other than a reason to investigate possible causalities substantiated and intensively.'' Causation cannot be investigated by statistical methods. Granger causality utilizes time series methods to examine statistical causation. However, both regression analysis and granger causality rely on correlations between variables. Correlation is not sufficient to determine causation. Another important criticism of PIMS is that it does not take into account heterogeneity in the data set. The presumption of PIMS analysis is that the same "laws of the marketplace" apply to all industries. However, the statistical assumptions employed in the econometric analysis make the assumption that all cross-sectional observations come from one statistical distribution that is the same for all cross-sectional observations. This tends to be the Achilles heel