Olarreaga, Sperlich, and Trachsel 2 (Canada); others only focus on new or non-exporters. Some only focus on small and medium-size firms (Uruguay); others spend more than 75 percent of their budget on large firms (Honduras). Some promote exports across all sectors (Philippines) while others focus on a more limited range of sectors (France). The objective of this project is to find out which of these EPAs’ characteristics are associated with more exports and higher GDP per capita growth.

Merging data from three rounds of EPAs’ surveys conducted between 2005 and 2014, the study obtains an unbalanced panel across developing and developed countries with information on EPAs’ budget, funding sources, and activities. To better understand why some EPAs may be more efficient than others, the study explicitly models with the help of a semi-parametric varying coefficient model (see Park et al. 2015 for a recent review) the heterogeneity in returns to export-promotion budgets as a function of EPAs’s characteristics. The study finds that the returns in terms of export growth associated with a 1 percent increase in export-promotion budgets varies from 0 percent in Cyprus and Vietnam to 0.22 percent in Portugal. The returns in terms of GDP per capita vary from 0.05 in Malawi to 0.10 percent in Portugal and Nicaragua. These differences at the country level are explained by differences in agencies’ characteristics. The study finds that EPAs that have a larger share of their budget coming from fees for services provided, or spend a larger share of their budget on marketing activities as well as nonmatching grants, or have a strategic mandate to target export promotion of a few sectors or destinations have larger returns in terms of exports. Of all these characteristics only the share of expenditure on marketing activities matters for GDP per capita returns.<sup>1</sup> These results are important for at least three reasons. First, they help identify the export-promotion strategies and EPAs’ characteristics that are associated with higher returns. They are therefore a valuable guide to EPAs that want to help exporters, and can help define best practices in export promotion. Second, to the authors’ knowledge, this is the first study to quantify returns in terms of GDP per capita. This is important because export growth cannot be the ultimate goal of export-promotion policies, but rather an instrument to achieve broader social and economic welfare, which is here proxied by GDP per capita. Interestingly, the results highlight that what may be good for export growth may not necessarily be good for GDP per capita growth. This is crucial and suggests that the exclusive focus on exports in the evaluation of EPAs may be misleading. Some interventions, such as expenditure in nonmatching grants, may generate export growth, but they do not lead to GDP per capita growth. Third, by explicitly modeling the heterogeneity in returns this study’s identification strategy addresses the problem of causality in a statistically more satisfying manner than existing studies that simply focus on average returns.<sup>2</sup> To see this, note that in most studies measuring average returns causality is established through the use of an instrumental-variable estimator, which assumes that returns to export promotion are homogeneous across countries (see, for example, Lederman, Olarreaga, and Payton 2010). As any export-promotion expert would argue, this is unlikely given that export promotion agencies differ significantly in their institutional set-up and programs. The use of instrumental variables will then identify the average returns associated with variations in export-promotion budgets that are caused by variations in the instrumental variables (or IVs). Clearly, the larger the unexplained heterogeneity in the returns to EPA budgets, the larger the difference between the returns identified by altering IVs (the so-called local average treatment effects, or LATE, which vary with the choice and values of IVs), and the larger their difference with respect to the average returns over the entire population (the so-called average treatment effect, or ATE). In other words, the returns to export promotion that are identified are a function of the choice and value of the instruments that are used.<sup>3</sup>

> 1 In the survey, the study explicitly defines marketing activities as including trade fairs, trade missions, follow-up services offered by representatives abroad, and importer missions.

> 2 As usual, there is no free lunch, and the authors discuss limitations to their methodology in the conclusion.

> 3 This and its consequences have been thoroughly discussed by Heckman, Urzua, and Vytlacil (2006) among others.