decisions on "the extent to which other major developed countries are undertaking a comparable effort," i.e., extending GSP preferences of their own to the country in question (USTR [1999]). Thus, different GSP programs are correlated"<sup>5</sup> and the measurement of GSP status here, while technically representing the US program only, offers a reasonable approximation of all developed country preferences for developing countries.

# 4.1 Key Variables

_GSP Status._ The dummy variable _GSP,,t_ is 1 if country i was a United States GSP beneficiary in year t; 0 otherwise"<sup>6</sup> . This information was collected from USTR [1991] and Federal Register _[various]._ The _GSP_ dummy admittedly glosses over important distinctions between countries with widely-varying amounts of actual US GSP benefits. In order to capture that variation, we also construct the variable _GSP Fraction,,t,_ defined as country _i's_ GSP exports to the US (USITC [2002]) as a percent of its total exports in year t (World Bank [2001b]). Unfortunately, this variable is available only for the last decade,<sup>17</sup> so we use _GSP Practzon_ for sensitivity testing only.

_Trade Polzcy Measures._ Available data on aggregate national trade protection are notoriously imperfect. Our strategy is redundancy: if we obtain similar findings with each of the several most frequently used measures of trade policy, our inferences will be more robust. The most common method of measuring protectionism is to examine trade flows, not policy, in the form of trade volume divided by GDP, mainly because of data availability. Accordingly, our variable _Closure,,t_ is country i's total imports as a percent of GDP in year t. This is subtracted from zero to make higher values represent greater import restrictiveness, yielding a sample mean of -46. It has the virtue of capturing the effect of non-tariff as well as tariff barriers. However, as many have argued (e.g., Dollar and Kraay [2001] and Rodrfguez and Rodrik [2001]), trade openness reflects not just _polzcy_ but also geography and market size (though we control on the right hand side for these factors). Among the measures which reflect policy more directly, we adopt _Dutiesq,t_ (duties as a percent of total trade, from World Bank [2001b]) and _Tariff,t_ (the unweighted average nominal tariff, from World Bank [2001a]). These variables average 9.4 and 20.6, respectively, in our dataset. Rodrfguez and Rodrik [2001] make a strong case for _Duties_ as the best of an imperfect lot, since _Tariff_ weights policies on small-volume products like golf putters the same as tariffs on automobiles. However, because highly protected industries have fewer imports (and thus fewer duties), _Duttes_ understates protection levels. Below we estimate models using these

> I<sup>5</sup> For instance, the US announced the withdrawal of Malaysia from its GSP program in October 1996, and the European Union followed suit in 1997 by slashing eligibility for all of Malaysia's chief exports (palm oil, plastics, rubber, wood, clothing, consumer electronics, and all agricultural products), if not cutting it from the program formally.

> 16 The GSP eligibility of Pakistan and Argentina was halved in the late 1990s; we code this as withdrawal of GSP. 1<sup>7</sup> Earlier data on GSP imports by country are disaggregated by 10-digit product code, by customs entry point, by month, and available only in microfiche form.

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