|ECA||0.218<sup>**</sup>|0.077|0.473<sup>*</sup>|-0.003|
|---|---|---|---|---|---|
|||(0.035)|(0.532)|(0.054)|(0.983)|
|LAC||0.129|-0.154|0.083|0.026|
|||(0.188)|(0.306)|(0.489)|(0.817)|
|MENA||-0.069|-0.306<sup>***</sup>|-0.060|-0.145<sup>*</sup>|
|||(0.306)|(0.002)|(0.671)|(0.052)|
|SA||-0.289<sup>***</sup>|-0.299<sup>**</sup>|-0.473<sup>***</sup>|-0.195|
|||(0.004)|(0.016)|(0.010)|(0.127)|
|Observations|237|237|127|111|78|
|Countries|85|85|49|59|42|
|R-squared|0.061|0.135|0.153|0.216|0.180|

_Notes:_ * p < 0.10, ** p < 0.05, *** p < 0.01. p-values in parentheses. Estimated via OLS. Standard errors are clustered at the country level. The omitted categories for income group and region are LMIC and SSA. _Source:_ Authors’ analysis based on the variables and data sources described in Section III, Table 1.

Of course, the negative relationship between levels of WBG engagement and median DEA scores observed in Figure 10 only represents a simple association which is unconditional of other factors. To test whether this relationship also holds when controlling for other factors, Table 4 reports the results of regressing WBG engagement on the DEA efficiency scores and other potentially relevant variables. Colum (1) reports the results when technological readiness, natural resources, and control of corruption are included as regressors along with the DEA scores. In column (2), countries’ income group and geographical region are added. Columns (3) to (5) further include tax policy, informal sector activity, and social trust. According to the results in Table 4, WBG engagement elated to DRM indeed tends to be stronger in countries that feature lower DRM efficiency (the coefficient is statistically significant in most specifications in Table 4).<sup>22</sup> This finding is consistent with the result in Figure 10 that the median DEA scores tend to decrease with higher levels of WBG engagement (as well as with the result that there are nevertheless many countries with large untapped revenue potential that feature only little WBG engagement).

In addition, Table 4 shows that WBG engagement in DRM tends to be stronger in countries that feature lower levels of technological readiness and better control of corruption. Moreover, there is some evidence that WBG engagement in DRM plays a smaller role in UMICs than in LICs and LMICs (column 2). For regions, the results indicate that WBG engagement tends to be stronger in SSA than in EAP and SA, but not as strong as in ECA (note that SSA is the omitted category for region). Finally, there is no evidence of a significant relationship between WBG engagement in DRM and countries’ natural resource endowments, tax policy, informal sector activity, and measures of social trust.<sup>23</sup>

> 22 The insignificant coefficient of “DEA score” in column (5) of Table 4 may be due to the smaller number of observations included in this regression (due to the limited availability of data on the variable “Trust”).

> 23 These results are robust to using an alternative measure of WBG engagement defined relative to recipient countries’ government revenues (rather than GDP). Specifically, when we repeat the regressions specified in Table 4 using as dependent variable ‘WBG engagement as a share of client countries’ total government revenues (excluding grants)’, then the coefficients of _DEA score_ and _Technology_ remain negative and statistically significant across most specifications, the coefficient of _Control of corruption_ remains positive and significant, and the coefficients of _Natural resources_ , _Tax policy_ , _Informal sector_ , and _Trust_ are always insignificant.

22