Second, World Bank investment projects may potentially have higher quality in comparison with national investment projects. However, as the same approach is applied to all countries in the sample, our measures are internally consistent and comparable over time and across countries, unless there is a systematic bias in the evaluation of investment projects in some countries relative to others.

# **2.2. Characteristics of the public investment quality index**

Using the procedure described in the previous section, we obtain PIQ-F scores for 120 countries (PIQ-F is a cross-sectional index spanning 2000-2021), PIQ-D scores for an unbalanced panel covering up to 107 countries over 2010-2021 (for a total of 898 observations), and PIQ-Q scores for an unbalanced panel of up to 91 countries over 2004-2021 (for a total of 894 observations). The three indexes have similar distributions and are highly correlated with each other (Table 2.2 and Annex Figure A2).

PIQ-F is positively correlated with a set of standard measures of institutional quality and infrastructure development, as well as with the PIMI index (Figure 2.1). The index is significantly correlated with institutional quality measures that reflect regulatory quality and public sector management. The correlation with PIMI is also positive but weaker. This could be attributed to a time mismatch (PIMI primarily relies on data from the 2007-2010 period) and to the fact that, unlike PIQ, PIMI does not control for income per capita and GDP growth.<sup>16</sup> Figure 2.2 shows the evolution of the correlation between PIQ-D and different measures of institutional quality and public investment management. The solid line shows the slope coefficient of 10-year rolling-window regressions of PIQ-D on different institutional quality and public investment management measures, and the dashed line indicates the corresponding 90-percent confidence intervals. We find that PIQ-D is positively and statistically significantly correlated with PIMI up to 2013. After that the correlation goes to zero and becomes insignificant, which supports the conjecture that PIMI may not be an accurate measure of the quality of public investment management in more recent years. By contrast, PIQ-D index remains positively and significantly correlated with the time-variant measures of institutional quality.

We find that LICs have low investment quality and lag other EMDEs (Figure 2.3).<sup>17</sup> This is consistent with what has been found for other indicators of public sector efficiency (IMF 2015; Dabla-Norris et al. 2012). There is also a large gap between commodity-exporting EMDEs and other EMDEs. In line with the “paradox of plenty,” we find that commodity exporters have low PIQ scores.<sup>18</sup> There is also evidence that the gap between rich and poor EMDEs, as well as that between commodity exporters and commodity importers has widened over time (Figure 2.4). Comparing across regions, we find that countries in Sub-Saharan Africa (SSA) and in the Middle

> 16 The correlation between PIQ and PIMI is much higher when the number of control variables in the computation of PIQ is minimized and the period spans only the years over which the underlying PIMI data were collected. 17 This is even though the PIQ indexes are derived while controlling for real per capita GDP. PIQ values obtained without controlling for GDP per capita show even larger differences across income groups.

> 18 This is also consistent with the findings in Dabla-Norris et al. (2012).

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