Table 8. Effects of Guerrilla Control on Migration Outcomes

||||Interna|tional Migrants||Always Lived in|Same Location|People who Arrived|Years since|
|---|---|---|---|---|---|---|---|---|---|
||During Control|At any Time|Years since|Households that Received|Received Remittance from|Same Location|as the Mother|During Control|Arrival|
||(Share)|(Share)|Departure|Remittances (Share)|War Migrant (Share)|(Share)|(Share)|(Share)||
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|Guerrilla control|-0.00219|-0.00221|-0.341|-0.00674|-0.00194|0.00788|0.00648|-0.00452|-0.218|
||(0.00171)|(0.00498)|(0.27700)|(0.00427)|(0.00126)|(0.00956)|(0.00978)|(0.00321)|(0.41100)|
|Observations|3,637|3,637|3,396|3,637|3,637|3,637|3,637|3,637|3,524|
|Bandwidth (Km)|2.266|2.266|2.266|2.266|2.266|2.266|2.266|2.266|2.266|
|Dependent mean|0.0230|0.112|7.416|0.103|0.0140|0.766|0.730|0.0620|16.470|

_Note:_ The table presents the results of equation 1 for our outcomes related to migration. Columns 1–5 focus on outcomes for international migrants. Columns 6–9 focus on internal in-migration flows. All information was obtained from the Population Census of 2007. The unit of observation in all columns is the census tract. Controls not shown include a linear polynomial of the distance to the boundary of guerrilla territory, its interaction with whether the tract was under guerrilla control or not, and up to 400 fixed effects representing the closest evenly spaced break in the guerrillacontrolled boundary. The algorithm of Calonico, Cattaneo and Titiunik (2014) was used to set the bandwidth and the estimates use triangular kernel weights. Robust standard errors in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.

Finally, we also looked at temporal migration for work by analyzing whether individuals work in a different census tract or municipality from where they live across the boundaries (Table D.22). We do not find that residents of former guerrilla areas are more likely to work outside their community, providing further evidence that out-migration may not drive the results.

It is puzzling that these people do not migrate today given better economic opportunities nearby. It is possible that they prefer not to leave their village due to strong social ties, more “rootedness,” and because they do not trust outsiders. This idea aligns with our results in Table 4 (Column 5), where we show that individuals in former guerrilla areas are more likely to trust members of their community than they trust residents of nearby areas.

Evidence has shown individuals can remain attached to their land when property rights are not defined or depend on land use, and plots are isolated from large markets (Albertus, Espinoza and Fort, 2020; De Janvry et al., 2015). Two elements suggest this was not the case in El Salvador. As we noted earlier, after the 1992 peace agreements, the state recognized property rights in guerrilla territory. Consequently, occupants of those lands could sell their plots and migrate if they wished. We also show that our results do not vary according to the distance of each individual to the road network or a main city (see Table D.23).

# **VI.D Ruling out conflict and violence persistence**

This section explores whether the negative effects of guerrilla control stemmed mainly from higher conflict or the persistence of violence, which may have been more intense in areas close to the 39