**Table 4.** Continued

|**Country**|**Exports**|**Wild boot. SE**|**GDP/capita**|**Wild boot. SE**|
|---|---|---|---|---|
|~~16~~<br>Slovenia|0.00|0.03|0.06|0.02|
|Spain|0.12|0.02|0.06|0.02|
|Switzerland|0.12|0.02|0.06|0.02|
|Tanzania|0.04|0.02|0.06|0.01|
|Trinidad and Tobago|0.07|0.03|0.07|0.01|
|Turkey|0.18|0.04|0.07|0.02|
|United Kingdom|0.04|0.02|0.06|0.01|
|Uruguay|0.02|0.03|0.06|0.02|
|Vietnam|−0.01|0.03|0.06|0.02|
|West Bank and Gaza|0.13|0.03|0.06|0.02|
|Yemen|0.13|0.03|0.06|0.02|
|Zambia|0.06|0.02|0.06|0.01|
|Average|0.10|0.03|0.06|0.02|

_Source_ : Authors’ calculation. _Note_ : Wild Boot. SE are wild bootstrapped standard errors.

This is done for _X_ being population size and EPA characteristics, and _Y_ being Exports or GDP per capita, respectively. Note that for each bootstrap sample the exogenous variables are kept unchanged from the original data. That is we generate _B_ = 500 bootstrap samples ∗ �� and re-estimate the TT,cctt ∗ parameter of interest, say _β_ . From the original sample we have , and the ��YYcc,tt, XXcc,tt tt,cc=1� can now be used to BB estimate the standard errors.<sup>18</sup> ββ̂ �ββ̂bb bb=1 Note that all returns are positive and statistically significant at least at the 95 percent level with a few exceptions. There is a strong and positive correlation between export and GDP per capita returns as illustrated in fig. 4. Thus, the larger are returns in terms of exports, the larger are returns in terms of GDP per capita as well. Note that this does not imply that export and GDP per capita returns are similar within countries. Average export returns are twice as large as returns in terms of GDP per capita as can be seen at the bottom of table 4. Indeed, for the large majority of countries export returns are larger than GDP per capita returns (to the right of the line in fig. 4). However, there is a smaller set of countries for which exports returns tend to be smaller than GDP per capita returns (observations to the left of the line in fig. 4).<sup>19</sup> These differences in exports and GDP per capita returns across countries are explained by differences in EPA’s characteristics in each country. Some of these characteristics may have a stronger impact on exports than on GDP per capita and vice-versa. This matters because if the ultimate objective of export promotion is GDP per capita growth, benchmarking policies, institutional setups, or interventions against export growth could be misleading. For example while Malawi and Nicaragua

> 18 Note that this would be significantly more complex if the standard errors were to be calculated over the two stages. In this case one would need to create bootstrap replicates simultaneously not only for Exports and GDP but also for log-budget, substituting the bootstrap log-budget for the original when generating _Y_<sup>*</sup> , and replicating the dependence structure between _ξ_ and the ɛ<sup>_u_</sup> . You would then need to repeat the two-step estimation procedure for each bootstrap sample. Given that the control functions are not statistically significant, this is not needed.

> 19 Note that larger returns in terms of GDP per capita can be explained if, for example, the export-promotion intervention allows domestic firms to better coordinate in the supply chain in order to capture foreign markets. Assume that thanks to an intervention exports double. GDP may more than double if inputs used in the production of exports were previously imported and are now domestically produced. The impact of certain export-promotion activities may be larger on nonexporting firms as well. This may be the case, for example, of export-promotion activities that focused on improving small firms’ managerial skills or productivity. Many of these small firms may not be able to circumvent the fixed cost of exporting in spite of the program having a positive impact on their productivity leading to a larger impact on GDP than on exports.