# **5.2** Endogeneity **of** GSP

The second set of regressions addresses the potential for endogeneity of GSP status.<sup>2 9</sup> This is a critical issue, though indeterminate as to direction. Granting and removing GSP eligibility is, after all, a political decision. In particular, endogeneity may arise if a recipient's import policy affects the United States removal decision. On one hand, if US exporters (rather than primarily US import-competing producers) influence the decision, then beneficiary countries with high trade barriers of their own would be prime targets for removal. This suggests GSP recipients may be _more,_ not less, open to imports than ex-beneficiaries. If so, the estimates from the first set of regressions may be conservative. On the other hand, the US may be _most_ likely to maintain GSP eligibility for precisely those countries that have failed to overcome the legacy of import substitution, because they have prospered the least and are in greatest apparent need of foreign aid. This implies GSP should be associated with worse policies (e.g., high trade barriers), just as we have proposed - but for a different reason. If true, the results from our OLS regressions may overstate GSP's effect. Either way, we must explicitly address potential endogeneity bias in order to have greater confidence in our findings. However, we emphasize that this paper _makes no_ claim about the direction of the reverse causality. Rather, the point is simply to see whether GSP still independently affects import policies even in a model that acknowledges its endogeneity.

We use an instrumental variables (IV) approach to isolate the "treatment effect" of GSP on trade policy when the treatment itself is endogenous. That is, imagine a prior equation, _GSPt_ = **'x%t-1** + **_Uz,t_** (3) where _GSP,,t_ = 1 if _GSP*t_ > 0 but 0 otherwise, and x is a vector of instruments thought to be uncorrelated with E in equation (2). Because of the discrete nature of _GSP,_ the usual 2SLS instrumental variables method may overstate the coefficient estimates. Instead, we use the well-known "treatment effects" instrumental variables (IV) approach, much like a Heckman selection model but with observed trade policy outcomes even for those countries not receiving the "treatment" (GSP). This model assumes E,,t in (2) and _u,,t_ in (3) are correlated, and we estimate it using maximum likelihood (Greene [2000, 933-934]). We thus use values of _GSPt,t (not GSP,,t-.,_ since we are correcting for simultaneous causation here) fitted from a first-stage probit regression as the optimal instrument for _GSP,,t_ in equation (2). Models 4, 5, and 6 separately apply this method to _Dut%es, Tarff,_ and _Closure,_ paralleling models 1, 2, and 3, reporting traditional heteroscedastic-consistent standard errors.

The decisive issue is exogeneity of the instruments. Fortunately, as Ozden and Reinhardt [2002] demonstrate, there are a number of good predictors of US GSP eligibility; many of these have no conceivable direct link to the developing country's own trade policy. These include (a) a dummy denoting the presence of other foreign policy sanctions imposed by the US on country **230;** (b) capitol-to-capitol distance from country i to the United States, in

> 29We thank Caroline Freund for suggesting these additional tests.

> 3 0Institute for International Economics [2000]; Office of Foreign Assets Control [2002])

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