**<u>TABLE 8: INFLUENTIAL POINTS FOR AGGREGATE REVENUE DEVIATIONS</u>**

||**Outliers 1/**|**Influential Points 2/**|
|---|---|---|
|_PCT_INT_|Afghanistan 2004/05 and 2006/07, Jamaica 2003/04<br>and 2005/06,Sierra Leone 2004|Jamaica 2005/06|
|_H02 DRY_|None|None|
|_H06 Rp ∙ Z(SYSTEM)_|Solomon Island 2004, Tonga 2008/09, Yemen 2005<br>and2006|None|
|_H10 Rp ∙ Z(GNIPC)_|Afghanistan 2004/05, Ghana 2006, Maldives 2005,<br>Yemen 2005 and2006|None|

1. Observations outside of the mean plus or minus 2 standard deviations or, for highly skewed distributions, the most extreme observations.

2. Single observations that, when excluded, make a coefficient insignificant at the 10 percent level.

Before concluding that equation 9b is suitable, three more diagnostic tests are made. The JarqueBera test fails to reject the null hypothesis of a normally distributed error term. The null hypothesis of no heteroskedasticity is rejected by White’s test. In order to facilitate hypothesis testing, White’s heteroskedasticity-consistent standard errors & covariance are employed. The Ramsey RESET test can detect mis-specification from incorrect functional form, simultaneity, and omitted variables. It fails to reject the null of no mis-specification using squared fitted values of the dependent variable. The adjusted r-squared is 0.707 with the dummies and 0.503 without them. Even though these results are very encouraging, some caution must be maintained since it is already known from the discussion in Section IV above that there could be some missing explanatory variables such as unexpected shocks to relative prices. The bottom line, however, is that equation 9b holds up well on its econometric merits.

While many of the proposed correlates for aggregate revenue deviations were rejected, those that were not tell an interesting story. The constant is highly significant and positive, creating a bias of 15 percentage points towards revenue surplus – consistent with Figure 2, Section III. As expected, revenue deviations are highly correlated with the degree of ambition in revenue policy: unanticipated surpluses are most common when revenue targets are not ambitious. The two interactive terms modify this tendency: governments are more likely to hit their revenue targets when they have presidential systems and when PFM capacity, measured by _ln_ (GNIPC), is high. As expected, debt service takes a negative sign: under-performing revenue is one of the causes of indebtedness.

The results indicate a high youth dependency ratio pushes revenue deviations in a negative direction, contrary to H02. It may be, as conjectured in Section IV, that _DRY_ is instead an indicator of the size of the talent pool a government may draw upon.<sup>43</sup> Populations with a large volume of youth below age 15 will hold fewer educated, experienced adults who can serve productively as civil servants. In other words, _DRY_ might better serve as an indicator of capacity for PFM.

# _B. Aggregate Expenditure Deviations_

The results of the analysis for aggregate expenditure deviations are shown in Table 9. Column 1 shows the hypothesized signs for each independent variable in equation 10. Columns 2 and 3 show the results for an encompassing equation 10a that includes all 26 hypothesized variables. Columns 4 and 5 show the results of the Bayesian averaging after removing the 7 least significant variables. Columns 6 and 7 show the author’s preliminary results (equation 10b), based on the Bayesian

> 43 This could be difficult to test more deeply:  educational attainment is highly correlated not only with dependency ratios (young and old) but also with income per capita and PEFA scores, with a high probability of two-way causality between some or all of these variables.

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