results discussed above it appears at least plausible that forward looking multinationals develop a notion of the risk of reversal to conflict and react to it.

Table 9: Fragility and Investment Flows

||(1)<br>investment fows|(2)<br>investment fows|(3)<br>investment fows|(4)<br>investment fows|
|---|---|---|---|---|
|peace|-0.693**|0.565**|0.741***|0.803***|
||(0.292)|(0.270)|(0.178)|(0.166)|
|peace * persistence of peace|1.485***<br>(0.358)||||
|peace * persistence of confict||0.138<br>(0.432)|||
|frst 5 years of peace|||-0.148|-0.0616|
||||(0.246)|(0.264)|
|fragile peace||||-0.437***<br>(0.125)|
|Observations|5,849|5,849|5,849|5,849|
|Number of Countries|211|211|211|211|

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, *p<0.1.Table 9 presents results of a poisson regression with an exposure variable capturing global positive net investment flows in the OECD sample. “Peace” is a dummy that takes a value of 1 in country _i_ during year _t_ there is no civil war, defined as violence above an intensity of 0.008 battle-related deaths per 1000 inhabitants. “Persistence of peace” is the likelihood, calculated at the country level that a year of peace is followed by another year of peace. “Persistence of conflict” is the likelihood that a year of conflict is followed by another year of conflict. “First five years of peace” is a dummy that indicates if the end of the most recent conflict has been less than five years ago. “Fragile peace” is a dummy that takes a value of 1 if a year is peaceful, within five years of the last conflict and reverts back to conflict within the next five years.

We illustrate this channel by estimating an actual risk model for the critical period of the first five years after conflict and bringing this model to the FDI data. The technique we deploy is akin to a two stage least squares IV estimation. We first estimate a risk model and then use the fitted values of this model to explain investment. However, the aim here is not to provide identification but to illustrate the plausibility of the idea that multinationals build expectations based on observables and are influenced by these in their decision to invest. The model we use is based on two variables highlighted in this report: “political exclusion” and “refugees”. In Table 10 column (1) we use the share of the population that is excluded from political power, the share of the population that is discriminated, the number of refugees per capita and a dummy that indicates the absence of refugees to predict fragility. In this regression we focus on all years that were five years after conflict and use our explanatory variables to distinguish the years that are followed by a relapse to conflict from those that do not. All variables have the expected sign and are significantly correlated with conflict relapse. The fitted values from this risk model vary between 0.12 and 0.88 and have a mean of 0.25.

In columns (2) to (5) of Table 10 we bring these numbers to the various foreign investment data. We use the fitted values instead of the actual fragility dummy and set all years outside of the first five years after conflict equal to zero. Expected fragility, estimated with refugees and political exclusion, explains foreign direct investment extremely well. An increase by 10 percentage points in the estimated fragility is associated with a reduction of flows by about 50 percentage points. In Table 11 we use FDI data from OECD dataset. We show that this result is robust to adding a large set of controls like democracy scores, log-GDP and growth of GDP. What is more, we can even add 55