# **3  Empirical analysis**

## **3.1  Research design and data**

We are interested in the decision of potential donor countries (i.e. every country that has not been directly affected by a disaster) to provide post-disaster assistance and the channel and type the actual donors choose. In order to examine the effect of humanitarian needs of a recipient country and strategic interests of a donor country, we construct a basic dyadic data set for each major natural disaster (that is included in the EM-DAT data set) in a given country between 2000 and 2007. For any given disaster in a country, all remaining countries are considered as potential donor nations. Including only those cases where one potential donor actually provided aid in our regression would truncate the data. All potential donors that did not provide post-disaster assistance are coded zero and this information is used in the first stage selection estimates. The combination of 228 disasters, where information on both the channel and type of disaster aid is available, and 187 potential donor nations, results in a basic dataset of 42,636 observations. However, this number is reduced to between 20,077 and 25,836 (depending on the specification) due to missing data. Of the aforementioned observations, between 2,603 and 3,123 (depending on the specification) observations are actual aid contribution (dependent variable=1).

The dependent variables are dummies that switch to 1 if a donor has contributed post-disaster assistance (in the selection equation), switch to 1 if the if the contribution was bilateral (in the channel equation) or switch to 1 if the type of contribution was cash (in the type equation). In figures 1 and 2 we show the breakdown of total aid in bilateral vs. multilateral and cash vs. inkind by major recipients. Pakistan received 602 contributions. Among these 602 contributions, 463 (77%) were made via a multilateral agency and 139 (23%) were made bilaterally. Peru on the other end of the list, received 99 contributions where 54 (55%) where made multilaterally and 45 (45%) bilaterally. The differences between recipient countries in the type of disaster aid received is even bigger. Out of 100 contributions to Haiti only 1 (1%) was bilateral cash, while Mozambique received 53 (16%) bilateral aid contributions out of 335 disaster assistance flows. The main explanatory variables include indicators for humanitarian needs by the recipient and variables accounting for strategic interests of the donor. The former group includes the number of fatalities in a disaster (in thousand) and the level of gross domestic product per capita (GDP p.c.). The latter group contains information on the donor's trade volume with the recipient and the percentage of fuel exports of total merchandise exports by the recipient. These two variables are widely used as empirical proxies for strategic interests in the existing aid allocation literature (e.g. Fink & Redaelli 2009, Berthelemy 2004). In addition we include dummies for the type of natural disaster.

In choosing other relevant covariates, we follow the existing empirical literature (e.g. Fink & Redaelli 2009, Alesina & Dollar 2000): Size of the recipient country (population), distance between donor and recipient, oneness for trade, colonial history between the donor and the recipient as well as an updated version of Gartzke's affinity index that is constructed using voting patterns in the United Nations General Assembly. The index ranges between 1 (recipient and donor always voted the same way) and -1 (recipient and donor never voted the same way). In addition we include two dummy variables that account for common religious beliefs and common language in the donor and recipient countries. The donor nation’s level of development measured via the GDP p.c. is also included. Table 15 gives an overview of the data sources used.

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