Table 3. Accounting for Selective In-migration

|Trimming using the|All-Time In-m|igration Rate|1980 In-m|igration Rate|1985 In-mig|ration Rate|
|---|---|---|---|---|---|---|
||Wealth Index|Wealth Index|Wealth Index|Years of Education|Years of Education|Years of Education|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Guerrilla control|-0.101***|-0.260**|-0.121***|-0.277**|-0.121***|-0.274**|
||(0.0353)|(0.107)|(0.0358)|(0.109)|(0.0358)|(0.109)|
|Observations|3,630|3,637|3,630|3,637|3,630|3,637|
|Bandwidth (Km)|2.266|2.266|2.266|2.266|2.266|2.266|
|Dependent mean|-0.0330|6.538|-0.0280|6.570|-0.0280|6.565|

_Notes:_ The results follow the specification of equation 1 for the Wealth Index and Years of Education outcomes. However, we trim the dependent variables by using different in-migration rates. In Columns 1 and 2, we use the all-time in-migration rate to trim the 10.4 percent most educated and wealthy people and the 3.3 percent least educated and wealthy from the treated and control groups’ respective distributions. In Columns 3 and 4, we use the in-migration rate from 1975 to 1980 to trim the 0.4 percent most educated and wealthy people and the 0.6 percent least educated and wealthy from the control group’s respective distributions. In Columns 3 and 4, we use the in-migration rate from 1979 to 1985 to trim the 0.7 percent most educated and wealthy people and the 0.8 percent least educated and wealthy from the control group’s respective distributions. The unit of observation in all columns is the census tract. Information from all columns was obtained from the Population Census of 2007. 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 guerrilla-controlled boundary. The estimates use triangular kernel weights. Robust standard errors in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.

# **V.C External validity**

In Appendix D, we conducted two analyses to rule out that the results are specific to our RD sample. First, we show that at baseline the RD sample is similar in characteristics to the rest of the country (see Table D.11). Second, we show how the main results change once we move outside the two km bandwidth. Figure D.11 shows that results are pretty homogeneous across space.

# **VI EXPLORING POTENTIAL MECHANISMS**

Why would the FMLN’s influence endure so many years after its territorial control ended? As discussed above, one explanation concerns the reshaping of economic structures and local governance that led to the demise of the former commercial agriculture system and disengagement with the state.<sup>25</sup> In particular, reliance on plot-based agriculture and lack of public engagement with the state could have created a negative feedback loop that depressed living standards in the long run. We hypothesize that many of these changes continued through the present day due to lasting distrust of the state and elites. We find that even though former guerrilla areas today have

> 25While most agricultural elites from the 1950s lost prominence after the conflict, distrust of the state and new elites or landowners could persist due to historical factors even if the new entrants provided better labor conditions.

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