the yearly stock of refugees. More formally, we run the following regression for country _i_ in year _t_ : _refugeesit_ = _incidenceit_ + _phaseit_ + _δi_ + _δt_ + _εit_ Our outcome of interest is _refugeesit_ , which is the stock of refugees. The variable _incidenceit_ is conflict incidence. In one specification of the model we use the definition from the PRIO dataset of at least 25 battle related deaths caused by an internal conflict. In the other specifications we use a more stringent definition of internal conflict which requires at least 1000 battle related fatalities.<sup>24</sup> Variable _phaseit_ is a vector of dummies we use to show the dynamics in the stock of refugees in different phases of the conflict. In one specification we control for the _year before the conflict starts_ and _first year of conflict_ . Then, we include in succession dummies for the _last year of conflict_ and _recovery years_ up to the tenth year of recovery.

Finally, _δi_ and _δt_ are respectively country and year fixed effects: the former control for time invariant country-specific impact on the change of the number of refugees, while year fixed effects capture the average state-invariant influence of each year _t_ on _refugeesit_ .

Table 6 reports the results. In column (1) conflict incidence coincides with the PRIO definition of at least 25 battle related deaths, i.e variable _25+ battle deaths_ . The estimated coefficient indicates that during conflicts more than 144,000 people leave their home country on average. This average rises markedly when we use the more stringent definition of at least 1000 battle related fatalities as conflict incidence variable. In fact, in column (2) the estimated effect of conflict incidence on _refugeesit_ more than doubles. Note that in this specification we include the dummy _25-1000 battle deaths_<sup>25</sup> in order to check whether people have an incentive to leave their country when some violence occurred, but the situation has not escalated into a conflict with more than 1000 deaths in a given year. We notice that during these years a significant number of people leave the country, but this average is very low if compared with the average stock of refugees during the violent years with more than 1000 deaths. We therefore focus on dynamics in war period, using as “conflict incidence” the tighter definition of at least 1000 battle related deaths.

Column (3) of table 6 adds to the previous model the controls for the initial phase of the conflict, namely _year before the war_ and _first year of the war_ . Compared to column (2), the estimated coefficient of the variable _1000+ battle related deaths_ increases. On average, the stock of refugees during conflict is more than 487,000 people. But in the first year of conflict the average stock is by 384,851 lower, i.e. only 20 percent of the almost 500,000 refugees leave their country during the first year of conflict.<sup>26</sup> Column (3) also tells us that there is there is no significant departure during the year before the conflict. This suggests that forced displacement of people takes off with the start of violence but not before.

> 24Note, that we now switched to counts of fatalities as our outcome variable is also in absolutes. Weighting both sides by population would not change the results.

> 25This dummy takes value one if in country _i_ during year _y_ the registered battle related deaths are between 25 and 1000.

> 26 The number of 20 percent is obtained by computing (487,968-384,851)/487,968 _._

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