Data utilized for the analyses

In this paper we utilize as a starting point the data and methods utilized by Martin et al. (2008) in their paper, which they make available through their website. The dataset include data on conflicts, total bilateral and multilateral trade, distance between countries, geographic areas of countries, history of country’s UN voting over security issues, the existence of free trade agreements, membership to GATT (before 1995) / WTO organization (after 1995), the presence of common languages and colonial ties between country pairs.

The data utilized by Martin et al. (2008) are not directed in the country pair, for example data on bilateral trade between country i and country j include both export from i to j as well as export from j to i. As mentioned, in this paper we replicate this method and analyses, but we also distinguish the direction of trade flows between country pairs, by treating differently import from export operations.

141

See Allan, J. A. (2003), Virtual water - the water, food and trade nexus: Useful concept or misleading metaphor? Water International 28(1): 106-113.

142 _{Hoekstra, A. Y. and P. Q. Hung (2002), Virtual Water Trade, A Quantification of Virtual Water Flows Between Nations in}

Relation to International Crop Trade, Value of Water Research Report Series No. 11, Delft, Netherlands, UNESCO-IHE Institute for Water Education.

143_{Professor Tony Allan was inspired by Israeli concerns not to „over-export‟ water intensive agricultural products in view of emerging}

local water scarcity. “Virtual water” refers to the volume of water consumed during the entire life-cycle of products. In the following of this paper, we will refer to virtual water trade as the trade in (water-intensive) agricultural and food products – please refer to the following section on data utilized.

The data on conflicts used in this paper come from the COW project (at http://cow2.la.psu.edu/) that makes available a wide-ranging and precise description of interstate armed conflicts. The main dependent variable is the occurrence of a conflict (MID) between a pair of countries. This data set is available for the years 1816–2001, but we only use the years 1986–2000 because this is the period for which one of our principal explanatory variable, virtual water trade, is available.

In the COW data set, MID is coded with a hostility level ranging from 1 to 5 (1 = No militarized action, 2 = Threat to use force, 3 = Display of force, 4 = Use of force, and 5 = War), and War is defined as a conflict with at least 1000 deaths of military personnel. By this standard, fewer than 100 interstate wars have been fought since 1815. At the country pair level of analysis, the number of pairs of states at war is naturally larger, since in multi-state wars, each state on one side would be paired with every state on the other. Even so, the small number of warring country pairs inhibits the creation of truly robust estimates of war determinants. Consequently, in line with Martin et al. (2008), all those events occurred between country pairs defined in the dataset with an hostility level equal to 3 or above144 _{are defined as a conflict}

(MID); the MID variable thus assumes value equal to 1 in correspondence of the country pairs and years for which an even classified in the dataset with an hostility level of 3, 4 or 5, and it assumes the value 0 otherwise. Our sample consists, for each year of the 1986–2000 period, of all existing country pair combinations (‚dyads‛); of this sample of dyads, few are engaged in an MID, even with our enlarged definition.

We will also use a different specification of the principal dependent variable MID, which we call MID_NEW, taken from the COW dataset (COW 2.0 dyadic dataset), which distinguishes the direction of conflict by providing information on which country within the dyad has originated the conflict. If country i has initiated the conflict, the variable MID_NEW assumes value equal to 1, and it assumes value equal to 0 in all other cases (when the dyad in that year did not enter into a conflict, or whether there was a conflict but initiated from country j).

Our final cleaned bilateral dataset, which is a panel of 15 years representing all directed country pairs, contains 281,744 observations. In all, as expected, the number of observations where a conflict is held is really small, and it stands to 917, corresponding to the 0.325 % of the total sample. This number is consistent with the one in Martin et al. (2008) which reports a conflict ratio which is 0.511% of the total sample.

Data on total bilateral and multilateral total trade, trade in oil and gas, and trade in footwear, are taken from the NBER-UN Trade Data set (http://cid.econ.ucdavis.edu/data/undata/undata.html), providing data on both total and sectorial trade between country pairs for the period 1962-2000. Data on oil and gas trade are extracted based on the SITC4 codes of the commodities traded145_{. Data on virtual}

water trade are reconstructed on the basis of data from Food and Agricultural Organization of the United Nations, Statistics Division (Faostat), forthe international trade of 309 agricultural commodities exchanged from country of origin i to country of destination j. These data refer to the ‘blue’ and the ‘green’ components of the water-footprint of the products traded146_.

Data on individual countries’ GDP are taken from the World Bank dataset; these data are utilized for calculating bilateral and multilateral trade openness. Variables accounting for bilateral trade impediments or facilitating factors (distance, contiguity, and colonial links) and for geographic areas come from the CEPII bilateral distance database (www.cepii.fr/anglaisgraph/bdd/distances.htm) utilized in standard gravity models.

144 _{Examples of display of force (level 3 of an MID) include a decision of mobilization, a troop or ship movement, a border violation, or a}

border fortification. These are government-approved and unaccidental decisions. Examples of use of force (level 4 of a MID) include a blockade, an occupation of territory, or an attack.

145_{Data utilized for the category “trade in oil and gas” are those extracted under the SITC4 code Division: 33 (“Petroleum, petroleum}

products and related materials”) and Division: 34 (“Gas, natural and manufactured”).

146_{The water footprint of a product is the volume of water needed to produce the product. The „blue‟ water footprint refers to the}

volume of surface and groundwater consumed (evaporated) as a result of the production of a good; the „green‟ water footprint refers to the rain-water consumed. The „grey‟ water footprint of a product refers to the volume of freshwater that is required to assimilate the load of pollutants based on existing ambient water quality standards – please refer to Mekonnen and Hoekstra (2011).

Finally, information on democratic status of individual countries derive from the Polity IV database, which provides the composite index that ranks countries on a −10 to +10 scale in terms of democratic institutions utilized in the paper.