The findings present two main points. First, the resource dependency indicator by itself does not significantly affect MPI, indicating that resource-dependent countries, on average, do not differ in their level of poverty from other countries. Second, the interaction between economic growth and resource dependency is significant and positive. This suggests that economic growth has a less substantial impact on reducing poverty in resource-dependent countries compared to those that are not resource dependent.

This result reveals an additional concern for policy makers: the already slow economic growth in resource-dependent countries further translates into less effective poverty reduction, amplifying the urgency of addressing the unique obstacles presented by natural resources.

Table 5: MPI and GDP by income groups and resource dependency

|VARIABLES<br>Dummy|(1)<br>MPI<br>low income|(2)<br>MPI<br>lower-<br>middle|(3)<br>MPI<br>upper-<br>middle|(4)<br>MPI<br>Resource<br>dependent|
|---|---|---|---|---|
|Change in GDP (current + lagged)|-1.261***|-1.171***|-1.003***|-1.504***|
||(0.251)|(0.341)|(0.210)|(0.283)|
|Dummy|0.026**|-0.036**|0.005|-0.013|
||(0.013)|(0.015)|(0.026)|(0.014)|
|Dummy x change in GDP|0.727**|0.172|-0.479|1.003***|
||(0.339)|(0.410)|(0.481)|(0.379)|
|Constant|-0.049***|-0.024**|-0.040***|-0.031**|
||(0.012)|(0.012)|(0.006)|(0.012)|
|Observations|126|126|126|125|
|R-squared|0.251|0.204|0.151|0.163|

**Note:** Robust standard errors are presented in parentheses. ***p < 0.01, **p < 0.05, *p < 0.1.

Wu et al. (2024) identified a different poverty-growth elasticity for Sub-Saharan Africa using income poverty, prompting us to examine the relationship between economic growth and its impact on the MPI across different world regions. To address the issue of small sample sizes, we employ the same approach as for the income groups (see above) by interacting individual region dummies with changes in GDP.

Table 6 presents the results by region for the MPI and highlights three regions: Latin America and the Caribbean, South Asia, and Sub-Saharan Africa. In the case of Sub-Saharan Africa, our findings align with Wu et al. (2024) in that, the growth-poverty relationship is smaller for non-monetary poverty, similar to their findings for monetary poverty. However, we also observe that this reduced relationship holds for Latin America and the Caribbean. Conversely, the opposite is true for South Asia. This region appears to leverage economic growth more effectively in reducing poverty than the rest of the sample.

When examining the subcomponents of the MPI, as detailed in Table A 5, we observe additional nuances. The Arab states, for example, exhibit poor performance in reducing child mortality. However, they excel in providing all living standard components of the MPI compared to the rest of the sample. The East Asia and Pacific region shows superior performance only regarding assets. The negative MPI result for Latin America and the Caribbean, shown in Table 6, is driven by poor performance in the subcomponents of years of schooling, housing, and assets. South Asia, on the other hand, outperforms the sample in the subcomponents of nutrition, years of schooling, and 16