small effect on Chile’s multilateral resistance, which falls by only a little, and hence has a relatively small mitigating effect on the impact of the FTA on Chile-Peru trade. If the country is the United States, trade cost changes have a big downward impact on Chile’s multilateral resistance, which reduces the extent to which the absolute reduction in Chile-Peru costs ( _Z12_ ) is a relative reduction ( _Z12/P1P2_ ) and hence has a relatively big mitigating effect on the impact of the FTA on Chile-Peru trade.

Multilateral resistance by definition refers to trade costs that are not confined to the bilateral barriers between two countries. It is thus concerned with “third country” effects. If Chile and Peru sign an agreement but nothing happens with Uruguay, the cost of trading with Uruguay goes up in relative terms, so trade with Uruguay falls. By predicting reduced trade with third parties, accounting for multilateral resistance has many points of contact with the concept of trade diversion. In fact, the algebra offers a specific prediction of what would happen to bilateral trade involving all country pairs. By differentiating equation 4 with respect to the MR terms but keeping the FTA term constant, it can be established that trade with third parties falls.<sup>10</sup> While it is a specific prediction, it is not necessarily accurate or correct. It is based on a Taylor Approximation of third country effects and ignores a number of potentially relevant issues in trade diversion. Further, moving beyond bilateral flows and computing the full extent of trade diversion and hence a net effect on a country’s exports would require a calculation for all third countries (e.g. changes in _Mi2_ for all _i_ importers) and would make us stray from this paper’s objective. Leaving this question to future research, our concern remains with bilateral trade; MR is only relevant for our efforts to calculate the bilateral comparative static effects correctly.

# **4. Data and estimation**

We use the same data as Baier & Bergstrand (2007),<sup>11</sup> which come from various sources: nominal bilateral trade flows for 96 trading partners and at 5 year intervals from 1960 till 2000 come from the International Monetary Fund's Direction of Trade Statistics; nominal GDPs are from the World Bank's World Development Indicators (2003); bilateral distances, language and adjacency dummy variables were compiled from the CIA Factbook; and the FTA dummy variable was calculated using appendices in Lawrence (1996) and Frankel (1997) as well as various websites detailed in the Data Appendix. It includes full FTAs and customs unions but not partial agreements. 10% of them are between Northern countries, 31% between Northern and Southern countries and 49% between countries from the South. A list of the trade agreements analyzed, including a classification of them into North-North, North-South and SouthSouth FTAs is detailed in the Data Appendix together with a table containing the 96 potential trading partners.<sup>12</sup> Our estimation approach draws on that of Baier & Bergstrand (2007) but instead of having only one dummy for the FTA, we split agreements into those between two Northern countries, between two Southern countries and between a Northern country and a Southern country. The criteria to classify

> 10 For example, countries 1 and 2 can be Chile and Peru respectively such that the equation is for exports from Peru to Chile. Changes in exports from Uruguay to Chile can be found by assigning Uruguay the subscript 3. In general, .

> 11 We thank Scott Baier and Jeff Bergstrand for facilitating our use of the data.

> 12The analyses covers the period from 1960 till 2000 and a total of 119 new agreements have been implemented since 2000, with about 50% of them being S-S and 40% being N-S agreements.

10