performance on some of the criteria in the question, but without providing any indication of the current level of performance.

Average write-up grade differs by question: they tend to be highest for question 16 and lowest for question 14. Note that, unlike the case with write-up length, these differences cannot be attributed to the number of sub-ratings or criteria contained in the questions. Relatively low grades for question 15 can be attributed at least in part to major revisions in the question prior to the 2011 CPIA exercise. Many question 15 write-ups for 2011 still addressed the old criteria better than they did the new criteria. There is no obvious explanation for the low grades for question 14, on revenue mobilization. Fewer than 1 in 13 write-ups for question 14 received a grade of “A”, compared to more than 1 in 4 for question 16.

Regional variations portrayed in Figure 6 are even larger than variations across questions. Only about 1 in 10 grades in EAP countries are “C” or lower, compared to more than one half in LCR. No EAP write-ups were graded “D”, compared to 1 in 8 of LCR’s write-ups. More than half of EAP write-ups received an “A” grade, compared to only 5.4% in LCR.

Table 2 presents multivariate tests of the association of write-up grades with word count and other variables. Equation 2.1 reports results from an ordered probit regression, while equation 2.2 reports an OLS regression for the same model specification. The dependent variable is an ordinal scale with only four categories, so ordered probit is the preferred method. We run OLS as well, however, because its coefficients (unlike the case with probit) are directly interpretable as marginal effects. Those coefficients could be misleading if the two methods generate very different results. However, the t-statistics are remarkably similar in equations 2.1 (ordered probit) and 2.2 (OLS), and the same set of variables are statistically significant in both tests. Moreover, marginal effects computed from binary probit regressions on sub-samples of observations with adjacent grades<sup>8</sup> indicate that little information is lost by assuming linearity and using OLS. For simplicity, the remainder of this section will therefore focus on results from OLS tests.

Lengthier write-ups receive significantly higher grades, but quantitatively the average effect is rather modest. A 1.5-unit increase in the log of word count (more than three standard deviations, or an increase from the mean of 735 words to about 3000 words) is required to produce an increase of one grade level, e.g. from “C” to “B”.

Grades are not significantly different for IDA or benchmark countries, or for proposed ratings increases or decreases from the previous year. Grades are significantly higher in larger countries and in those with more press freedoms. In-country CMUs are associated with lower average grades. Grades are lower for LCR than for other regions, and differences between LCR and three regions (EAP, ECA and MNA) are statistically significant. Other things equal, grades are nearly a full level higher on average for EAP than for LCR countries. The mean grade (calculated by assigning scores of 4, 3, 2 and 1 respectively to grades A, B, C and D) is 3.41 for EAP and 2.40 for LCR, for a difference of 1.01. The EAP regression coefficient of .835 in

> 8 Specifically, three probit regressions were run on observations with “A” and “B”, “B and “C”, and “C” and “D” grades respectively.  Marginal effects for most variables (calculated at the mean values of all other regressors) are very similar across the three sub-samples.

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