irrespective of the targeting feature of the terrorist event. Put differently, the prior regressions are unable to discriminate between the multilateral component effect of a terrorist action located in _i_ or _j_ ( _T_<sup>_i_</sup> or _T_<sup>_j_</sup> ) and the bilateral cost of terror ( _Tij_<sup>_k_).</sup> One study which starts indeed to differentiate between source countries and target countries in cross-national studies of terrorism, _albeit_ without relating terrorism to trade, is Krueger and Laitin (2003). They use a different dataset than ITERATE, the dataset issued by the US State Department on _Patterns of Global Terrorism._ from 1997 to 2002. Though coding differently terrorist events, the two datasets correlate reasonably well<sup>8</sup> . Looking at the characteristics of the ”source” and the ”target” countries, Krueger and Laitin find that GDP per capita is significantly related to terrorism for the ”target” country but not for the ”source country”. This confirms previous micro studies (Krueger and Maleckova 2003) that terrorism does not recruit because of poverty or low income. Another interesting result is that lack of civil liberties seems to affect positively and significatively terrorism at the source country level while, interestingly countries with a high level of civil liberties seem to be more vulnerable to terrorism and appear more likely a target during the period. The disparate findings based on country of origin and target country illustrate the importance of investigating separately the determinants of terrorism by origin and target.

In the same vein, another dimension also neglected in previous studies is the fact that terrorist events can occur as well in a third ”host” country (ie. different from the country where the terrorist organization is resident and from the country whose interests are mainly hurt). To illustrate the importance of this phenomenon, figure 3 sketches the distribution of the incidents extracted from the ITERATE database across 3 possible locations (origin, target country and third country). As before, the country is coded as target when it is that of the main nationality of the victims. It is important to note here that victims, in ITERATE, are defined as ”those who are directly affected by the terrorist incident by the loss of property, lives, or liberty”. Thus, when a French embassy is hit without casualties in say, an African country, France is then coded as the target country. Besides, the third country represents the country where the action begins _albeit_ different from the origin and target states. From figure 3, we can see that only a small and relatively stable proportion over time (10 to 20%) takes place in the target countries. Attacks like those of New York (2001), Madrid (2003) and more recently London (2005) are not representative of most of the incidents. In the earlier period, around 30 to 50% of the incidents took place in third countries but that share declined steadily over the period to reach around 20% of the incidents. This reduction seems to be concomitant with the rise of the share of incidents located in origin countries (i.e. where they have been planned and prepared) has been growing steadily. Hence, at the end of the period, 60 to 80% of the incidents became local. These findings are quite similar to those of Krueger and Laitin (2003) who use the Department of State dataset to assert that, in recent years, perpetrators preferred setting-up actions against ”targets from

> 8Excluding India which involves problems of definition of what is a transnational terrorist incident between India and Pakistan, the two datasets correlate at 0,9 at the level of the place of attack and 0,89 at the country of origin.

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