shows that the subnational allocation of World Bank project funding is not oriented toward poorer areas within countries in terms of the share of the bottom 40 in the population of the areas because these areas receive, on average, less funding from the World Bank.

The estimates in column (3) add three more control variables: a dummy variable equal to 1 if the capital city is located in the respective area, the estimated travel time from the other administrative areas to the capital, and the number of conflict-related deaths. The only significant one among these is the dummy variable for the capital city. The finding shows that areas with a capital city tend to receive a higher share of World Bank funding independently of the size of the population or the number of the bottom 40.

In column (4), the insignificant variables—travel time and conflict-related deaths—are excluded. The significance level of the capital area increases from 10 percent in column (3) to 1 percent in column (4).<sup>26</sup> In quantitative terms, the fact that an area encompasses the capital city raises the share of World Bank funding the area receives by an average 0.018 (33.7 percent of the mean). This substantial effect indicates that donors are inclined to work in capital cities. Efficiency or visibility considerations may play a role (see section 2).

Table 4 shows the results across world regions.<sup>27</sup> In columns (1)–(5), only the bottom 40 variable is included, whereas the estimates in columns (6)–(10) add population and the capital area as control variables. The estimates with only the bottom 40 variable show that the coefficient on the bottom 40 is, although positive and significant at the 5 percent level, substantially smaller in the case of SubSaharan Africa than in other regions.<sup>28</sup> The inclusion of the two control variables renders the difference even more striking. While the coefficient on the bottom 40 is not significant in the other regions, it is significant at the 1 percent level and negative in Sub-Saharan Africa. Hence, the negative and significant coefficient in columns (3) and (4) of table 3 appear to be solely driven by the subnational allocation of World Bank project funding in Sub-Saharan Africa. There, poorer subnational areas appear to receive less project funding, whereas this is apparently not the case in the other world regions.<sup>29</sup>

**Table 4: Zero-Inflated Beta Regressions, by World Region**

||_(1)_<br>_SSA_|_(2)_<br>_EAP_|_(3)_<br>_ECA_|_(4)_<br>_LAC_|_(5)_<br>_SAR_|_(6)_<br>_SSA_|_(7)_<br>_EAP_|_(8)_<br>_ECA_|_(9)_<br>_LAC_|_(10)_<br>_SAR_|
|---|---|---|---|---|---|---|---|---|---|---|
|Ln bottom 40|0.095**|0.332***|0.516***|0.376***|0.334***|−0.214***|0.207|0.024|0.256|−0.097|
||(0.040)|(0.067)|(0.109)|(0.062)|(0.046)|(0.058)|(0.185)|(0.275)|(0.166)|(0.126)|
|Ln population||||||0.628***|0.187|0.563*|0.096|0.625***|
|||||||(0.078)|(0.217)|(0.300)|(0.210)|(0.180)|
|Capital||||||0.588***|0.663|−0.231|0.356|0.395**|
|||||||(0.143)|(0.569)|(0.274)|(0.367)|(0.189)|
|Number of countries|27|5|8|10|6|27|5|8|10|6|
|Observations,number|436|144|148|193|121|436|144|148|193|121|

_Note:_ The dependent variable is the share of World Bank funding a region receives. Country fixed effects are included in all estimations. Robust standard errors are shown in parentheses. EAP = East Asia and Pacific. ECA = Eastern Europe and Central Asia. LAC = Latin American and the Caribbean. SAR = South Asia. SSA = SubSaharan Africa.

***p < .01 **p < .05 *p < .1

26 Apart from efficiency gains because of fewer explanatory variables, the number of observations (areas) rose relative to column (3) because the data on estimated travel times to the capital are not available for all areas. 27 Standard errors are not clustered in these regressions because of the relatively small number of clusters (countries). Robust standard errors are estimated, however.

28 The significance level of the coefficient is 1 percent in all other world regions. The estimates on the Middle East and North Africa are not included because only two countries (with 39 subnational areas) in that region are included in the sample.

29 An additional result is that the coefficient on the capital area is only significant in South Asia and Sub-Saharan Africa.

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