Due to this finding the analysis shifted to identifying specific risks that are

Due to this finding the analysis shifted to

This preview shows page 221 - 223 out of 311 pages.

Due to this finding, the analysis shifted to identifying specific risks that are the best red flags for high overall risk. A ‘high’ overall risk assessment is defined with a clear action orientation. It means the analyst and their supervisor agree that, all things considered, the application of some kind of audit product is justified. Being placed in the high overall risk category is still a rare event. This characterised only thirty-three HWIs (14%). There were six HWIs who were not assessed as being in either a high, medium or low risk category. They were treated as not a high risk and included with medium and low risk HWIs for the purpose of the following analysis. Table 10.3 shows the summary from a logistic regression analysis predicting high overall risk. The independent variables in the model are the 207 issues coded as 1 for a high risk (that is a rating greater than 7) and zero (that is a rating of 1 to 7). Issues coded like this are referred to as flags to differentiate them from rated issues. Because of the interest in choosing a minimum set of ‘flags’ we chose a stepwise algorithm, which selects the best predictor of likelihood from amongst the 207 flags, then the second-best after the first-best has been included, and so on. The stopping criterion is when the addition of further flags does not sufficiently increase predictability of membership into the correct risk group to warrant the added complexity. A scree slope test based on the percentage correctly predicted was used to define this stopping point. Thus we attempted to balance statistical and practical significance. The first predictor of high overall risk is being rated over 7 in the ‘other miscellaneous items – other’ category (Issue 9, Table 10.1): The potential meaning of this finding is discussed in the next section. 6 The issue rated over 7 with the next most predictive value in this model is ‘use of an offshore entity in an unlisted country’ (Issue 2, Table 10.1). We might assume that ratings over 7 will mostly be incurred when there is concern that the unlisted country is a tax haven. The third most useful predictor is ‘trust distributions – capital distributions in cash (to the HWI)’ 7 (Issue 13, Table 10.1). Various other analyses were undertaken to confirm the stability of these results, and this flag also turned out to be important in these supplementary analysis. For example, ‘trust distributions – capital distributions in cash (to the HWI)’ is the top predictor in a model predicting the sum of all risk
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212 Taxing Democracy ratings (0-10) across all 207 issues. Indeed all three flags in Table 10.3 are recurrently useful and statistically significant predictors across different types of analyses. Column two in Table 10.3 shows the Likelihood Chi-square statistic for the inclusion of the flag at each step of the model building process. Beyond this set of flags, the increase in correctly predicted high risk HWIs was small (even though other flags subsequently entered into the model were statistically significant).
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  • Fall '16
  • tax authority, Australian Taxation Office, Tax Office, Compliance Model

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