column (3) despite the fact that the variation is now within country across regions instead of within country across time. But we also find that the country-level conflict debt is strongly associated with regional poverty in columns (4) and (5). When we run a horserace between both in columns (6) and (7) we get stronger results from the country-level debt, but it is hard to rule out local effects.<sup>6</sup> This suggests both regional and country conflict debt play a role for poverty but that there are important regional spill-overs at work which affect the regional result. One obvious channel through which this will be the case is internal displacement which is affecting a large number of people.<sup>7</sup> Displacement will lead the regional conflict debt and poverty measures to diverge if the channel is the loss of individual human capital which is displaced at the same time at which it is harmed. Another possible channel is that risk perceptions change for an entire country if a region experiences violence. Outside investors will then not invest in any region of a country. This might also explain why subnational studies sometimes find less strong effects of violence on the economy when compared to macro studies.

_Table 3: Poverty and Conflict Debt: Sub-country Level (Weighted Regressions)_

||(1)<br>Poverty|(2)<br>Poverty|(3)<br>Poverty|(4)<br>Poverty|(5)<br>Poverty|(6)<br>Poverty|(7)<br>Poverty|
|---|---|---|---|---|---|---|---|
||rate|rate|rate|rate|rate|rate|rate|
|Conflict debt|11.27<sup>***</sup>|4.672<sup>**</sup>|2.279|||7.005<sup>**</sup>|2.581|
||(3.252)|(1.880)|(1.484)|||(3.557)|(2.121)|
|Country conflict debt||||16.01<sup>***</sup>|7.785<sup>***</sup>|12.03<sup>***</sup>|6.374<sup>**</sup>|
|||||(3.225)|(2.240)|(3.469)|(2.519)|
|Country fixed effects|No|No|Yes|No|No|No|No|
|Continent fixed effects|No|Yes|No|No|Yes|No|Yes|
|Adjusted R-squared|0.0279|0.527|0.737|0.0352|0.530|0.0435|0.531|
|Observations|1885|1885|1885|1885|1885|1885|1885|

Notes: Robust standard errors in parentheses. * p<0.1, ** p<0.05, *** p<0.01. The dependent variable is poverty rate (in percent). Conflict debt is the discounted history of conflict years where a conflict year is defined as by more than 0.08 fatalities per 1,000 population. Country conflict debt is computed in the same manner at the country level. The regressions weighted by population are on the cross-sectional data of sub-country regions between 1992-2018 whenever sub-regional poverty rates are available.

In Table 4 we use both the UCDP and the ACLED data to look into the relationship between conflict history and the poverty rate at the regional level but within the continent of Africa. As before we use population weights to reduce measurement error. Columns (1) and (2) show results for UCDP and columns (3) and (4) show results for ACLED. All results are for the African continent only and are remarkably robust between the two conflict data sets. Most importantly, the results are now robust to country fixed effects in columns (2) and (4), i.e. they are significant within countries. This provides some evidence for a local mechanism being at play. It is again remarkable how the coefficient on conflict debt is robust across tables with magnitudes being very similar in Tables 1, 3 and 4.

> 6 In Appendix Table A5 we show that this is also robust to dropping countries for which we have only aggregate country observations.

> 7 According to the UNHCR, some 41.3 million people were internally displaced due to armed conflict at the end of 2018.

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