comparing diversification performances among countries with similar natural resource endowments, similar levels of economic development, and similar size.

For these purposes, and using data for 171 countries over the period 2000-2011 and following Lederman and Maloney (2012, Chapter 7), we estimate a model linking diversification indicators (the Herfindahl Index, the count of export products, and the share of the top 5 products in total export revenue)<sup>5</sup> with an indicator of resource abundance (net exports of natural resources per capita, as defined above), the level of economic development as measured by the log of GDP per capita, and the size of the labor force, as in equation (1)<sup>6</sup> :

# Di = β 0 + β 1N _XR_ i + β 2l _ogGDPpc_ i + β 3l _ogLabForce_ i +ε i   (1)

where Di is the diversification indicator (for the Herfindahl we consider the average of the square root of the Herfindahl Index of export concentration for country ‘i’ over the period 2000-2011, for the count of products we use the logarithm of the average count of products exported by country ‘i’ over the period 2000-2011, and for the share of the top 5 products we take its average over the period 2000-2011), NXR is the average of net exports of minerals and natural resources of country ‘i’ over the period 2000-2011, logGDPpc is the average of the logarithm of per capita GDP in constant dollars of 2000 over the period 2000-2011, and logLabForce is the average of the logarithm of the size of the labor force of country ‘i’ over the period 2000-2011.

Results are reported in Table 1 (Appendix). As expected, the estimation of equation (1) for each of the diversification indicators suggests unambiguously that while resource abundance is associated with more concentrated export structures, the level of development and the size of the labor force are associated with more diversified ones. The three coefficients on the explanatory variables are very well determined at 5 percent significance, and the models fit the data at all conventional levels of significance (in fact, the models explain 31.7, 42.7 and 81 percent of the variance of the root of the Herfindahl index, the share of the top 5 products, and the log count of exported products, respectively).

The estimated models allow us to benchmark ECA countries’ performances with respect to the conditional means of the sample. Within ECA, resource rich countries are less diversified than resource poor countries, and they are also less diversified than predicted, given their size, their resource endowments and their level of development. Figures 4, 5 and 6 plot the actual concentration indices (root of Herfindahl Index, share of the top 5 products in total exports, and log of count of exported products) against the predicted concentration indices that emerge from the models (results are in Table 1). The 45-degree lines in each figure plot the locus along which the actual level of diversification of a given country matches the predicted one based on the model. For example, both for the Herfindahl and the share of the top 5 products, Azerbaijan, Turkmenistan, Kazakhstan and Russia are well above the 45degree line, suggesting that their export structures are substantially more concentrated than predicted

> 5 The Herfindahl Index measures the concentration of export shares held by a particular product (destination) in a given export profile, and varies from zero (no concentration) to one (full concentration). The count of export products is the count of different HS-6 categories that contain exports of at least 100,000 USD, and the share of the top 5 export products measures the sum of export revenue obtained from the largest 5 export products as a portion of total export value in a given year.

> 6 Alternative non-linear specifications could also be considered, given the findings in the literature on diversification and the level of development mentioned above (Imbs & Wacziarg, 2003).

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