framework developed in Hausmann and Rodrik (2003) and Hausmann, Hwang and Rodrik (2006) (HHR). They define the “productivity frontier” of a country as the optimal composite of exports that would maximize prospective future growth. Countries that fall short of the productivity frontier have two basic channels through which they can grow. First, countries can grow by producing more of the same goods they have already been producing. Second, and more interestingly, countries can improve their growth prospects by developing new products that shift them closer to their productivity frontier. The analysis of HHR reveals that, if new products have a high productivity (i.e. they tend to be produced by countries with higher levels of income per capita) then the GDP of the country producing and exporting the new product eventually converges to that of the high income countries. Econometric analysis presented in this paper and in HHR show that productivity of exports is a statistically significant explanatory variable of GDP per capita growth, after controlling for initial GDP per capita, the human capital endowment and period-specific and country-specific dummies<sup>1</sup> .

Market forces alone may not be sufficient to shift the structure of exports towards goods of higher productivity and thereby enhance growth prospects. Here, we mention some of the reasons why market forces alone may be insufficient and cite their main advocates. One reason is that the production of new goods would in many cases require product-specific public goods that are not always available. Even worse, the main provider of those goods, be it the public or the private sector may be unaware of the need for them. Examples of such goods are product or sector specific infrastructure as well as complex non-tangibles such as product-specific legislation. Failures of coordination may also prevent a new high-income product from developing (Morris and Shin 2000). Product-specific services and labor or managerial skills may never develop if there is no demand for them in the economy. At the same time a lack of those same product-specific services, labor and managerial skills may forestall the development of new products that depend upon them. The need for industry-specific learning (Arrow 1962, Bradhan 1970) may make it difficult to become a producer of new goods. Industry externalities (Jaffe, Trajtenberg and Henderson 1993) can make the introduction of new products path-dependent, possibly causing other failures of coordination. In other cases, a country may be “stuck” in a low-value-added equilibrium (Murphy, Schleiffer and Vishny 1989). Some analysts have cited the so-called o-ring effect whereby a small failure in the complex succession of processes needed to produce and export a new good successfully, might cause the whole process to fail (Kremer 1993 and Kremer and Maskin 1994). “Cost discovery” -- the learning process by which an entrepreneur discovers from experience the true cost of producing a new product -- may deter private sector investment in the development of new products (Hausmann and Rodrik 2003). Moreover, static comparative advantages might not necessarily bring about the best results in terms of growth performance. For example, spillovers in learning can make international trade of a less-developed country to be detrimental to growth (Young 1991). Furthermore, low-growth traps can result from static comparative advantages in sectors subject to lower endogenous growth rates (Matsuyama 1991).

In the present paper, we quantify several indicators proposed in HHR to measure the level of income or productivity embedded in Argentine exports and then we compare them with actual GDP per capita. According to the HHR empirical analysis, countries with a high level of export productivity relative to their actual GDP tend to have higher growth rates. In other words, the income content of exports tends to be a good predictor of future growth. If the structure of Argentine exports is changing towards goods of higher productivity (either by exporting more of the

> 1 The results are robust to various estimation techniques and the inclusion of other variables as discussed in the last section of the paper.

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