countries by level of income is based on the World Bank Atlas Method, which classifies every world economy as low income, middle income and high income depending on their gross national income. We have used the official WB thresholds for 1987 and divided the countries in our sample between North (with more than $6,000 per capita annually), which include high-income countries and South (less than $6,000 per capita annually), which include low- and middle-income countries.

The trade agreement dummies we create are effectively an interaction between a general FTA dummy and a dummy for whether the signatories are Southern, Northern or a combination. These dummies capture all kinds of observable and unobservable country characteristics. With reference to the theoretical discussion in Section 2, these include those features that make countries more natural traders and that influence the nature of the trade agreement struck. While our need to distinguish between types of FTAs is in part motivated by the theoretical discussion, this specification is not intended to test any claim directly.

We include time-and-country ( _it_ & _jt_ ) as well as bilateral ( _ij_ ) dummies. The time-and-country dummies are primarily included to control for multilateral resistance. An alternative would be to construct MR terms from observables usually included in gravity models (as in Adam & Cobham, 2008), but dummies offer a number of advantages. Construction of MR terms is subject to measurement error, particularly the internal distance measure (Baier & Bergstrand, 2009). In most cases, for example distance, the variation over time is due only to variation in the GDP share terms, which leads to multicolinearity. Furthermore, dummies also capture any other time-varying exporter- and importer-specific effects like GDP and unobserved characteristics. For this reason, we use the time-and-country dummies.<sup>13</sup> Identification of the FTAs as a causal effect must be mindful of unobserved characteristics that affect both trade and FTAs, some of which were noted in Section 2. Further, Baier & Bergstrand (2007) provide evidence that FTAs are expected to be signed by countries anticipating further additional trade facilitation, for example reduced red tape or eased visa processing, because the benefits are greater when the other restrictions are higher. Such unobservables are in the error term and are negatively correlated with trade but positively correlated with FTAs. It follows (Wooldridge, 2002) that failing to control for this source of endogeneity leads to an underestimate of the FTAs coefficients.<sup>14</sup> Furthermore, Baier & Bergstrand (2007) appeal to the literature and empirical evidence to argue that these characteristics are related to potential trade levels, not any fluctuations in potential trade over time. Unobservables affecting potential trade and FTAs are therefore well captured by bilateral fixed effects.<sup>15</sup> These fixed effects will also capture any other time-invariant country-pair characteristics (e.g. distance, adjacency, common language) that are common in gravity models but not of direct interest. Remaining endogeneity concerns are investigated by running specifications that estimate the effect of future FTAs on current trade flows (Wooldridge, 2002).

> 13 Constructing the terms may be an attractive option if the variable of interest is monadic because such country specific variables, for example business environment variables, cannot be identified when using time-and-country dummies (Behar, Manners & Nelson, 2009).

> 14 It can appear inconsistent to be using this argument to argue this causes downward bias while at the same time ignoring arguments that closer countries trade more. However, this second cause of (upward) bias is always controlled for with observable variables, like distance, so standard gravity specifications do not experience upward bias from this source.

> 15 Random effects methods cannot adequately deal with this source of endogeneity. Furthermore, Egger (2000) uses Monte Carlo evidence to record the superiority of bilateral fixed effects methods over a random effects specification.

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