estimated. Therefore, restricting the weight to be identical over time should also not affect the results substantially. Another implication of the small changes over time in the weights is that they did not contribute signi fi cantly to the EU’s tariff reduction in the UR.<sup>62</sup> To conclude, the assumption of constant weights is reasonable in this sample and does not appear to affect our main results signi fi cantly. This is further supported by noting that the sign and signi fi cance of the main parameters in table 6 are identical to those we found in table 2. The main predictions of the model are still con fi rmed and the only difference is a small change in the magnitude of the point estimate of the growth effect, but even that is not signi fi cantly different from table 2.<sup>63</sup> Nonetheless we did fi nd evidence of signi fi cant determinants that generate different political economy weights across industries. This suggests that in general the variation in these weights should be modeled empirically and theoretically.<sup>64</sup>

# 5 Conclusion

We analyze the effects of preferential trade agreements on multilateral trade liberalization—a controversial issue where the evidence has been scarce. The model we develop captures key features of the current trading system and provides a rich set of predictions regarding the impact of PTAs on MTL. We derive and estimate the structural equations of protection using detailed tariff data for the EU during the last two multilateral rounds and fi nd evidence that its PTAs slowed down MTL. As the model predicts, this occurred only in products with a zero preferential tariff and was not present in agreements with a common external tariff and transfers. Our model also incorporates domestic political economy motives for setting trade policy and we fi nd a negative relation between import penetration and tariff levels working through the extra weight that governments place on producer surplus. We estimate that these industry weights are increasing in regional concentration and employment shares. We also fi nd evidence of reciprocity in the EU’s MTL.

In the absence of its PTAs the EU would have lowered its MFN tariff on PTA products by an additional 1.6 percentage points. Since the average reduction for non-PTA products was almost twice

> 62 Even though the individual industry weights we estimate do not differ from the mean, we do fi nd some differences in the weights across industries at the extremes. In particular, bilateral comparisons of each of 353, 354 (petroleum and coal) and 314 (tobacco) with the remaining industries reveal that the lower bound of the 95% con fi dence intervals of these 3 industries exceed the upper bound of the rest a total of 12 times in 1992 and 51 in 1978.

> 63 To compare the speci fi cations across tables 2 and 6 we also calculated a different version that includes an intercept in the weight equation and thus nests our initial speci fi cation. In those speci fi cations (not shown) the estimated intercept of the weight equation was zero indicating, as we expected, that the extra weight placed on an industry is zero if its share of employment is zero and it has average concentration.

> 64 Such improvements in modeling could potentially help to explain the puzzlingly low political economy weights thus far found, when estimating structural political economy models of trade protection.

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